FTIR

Applied Spectroscopy Reviews

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Advances in Fourier transform infrared (FTIR) spectroscopy of biological tissues Abdullah Chandra Sekhar Talari, Marcela A. Garcia Martinez, Zanyar Movasaghi, Shazza Rehman & Ihtesham Ur Rehman To cite this article: Abdullah Chandra Sekhar Talari, Marcela A. Garcia Martinez, Zanyar Movasaghi, Shazza Rehman & Ihtesham Ur Rehman (2017) Advances in Fourier transform infrared (FTIR) spectroscopy of biological tissues, Applied Spectroscopy Reviews, 52:5, 456-506, DOI: 10.1080/05704928.2016.1230863 To link to this article: https://doi.org/10.1080/05704928.2016.1230863

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APPLIED SPECTROSCOPY REVIEWS 2017, VOL. 52, NO. 5, 456–506 http://dx.doi.org/10.1080/05704928.2016.1230863

Advances in Fourier transform infrared (FTIR) spectroscopy of biological tissues Abdullah Chandra Sekhar Talaria, Marcela A. Garcia Martineza, Zanyar Movasaghib, Shazza Rehmanc, and Ihtesham Ur Rehmana a

Department of Materials Science and Engineering, The Kroto Research Institute, University of Sheffield, Sheffield, UK; bBarts Health NHS Trust, Community Health Service Division, St. Leonard’s Hospital, London, UK; c Department of Medical Oncology, Airedale NHS Foundation Trust, Airedale General Hospital, Steeton, West Yorkshire, UK

ABSTRACT

KEYWORDS

This article reviews some of the recent advances on FTIR spectroscopy in areas related to natural tissues and cell biology. It is an update on our previously published review on the applications of spectroscopic methods employed for the analysis of biological molecules, and summarizes some of the most widely used peak frequencies and their assignments. The aim of this review is to update and consolidate our previously published spectral database, which will help researchers in defining the chemical structure of the biological tissues introducing most of the important peaks present in the natural tissues more precisely and accurately. In spite of applying different methods, there seems to be a considerable similarity in defining the peaks of identical areas of the FTIR spectra. As a result, it is believed that preparing a unique collection of the frequencies encountered in FTIR spectroscopic studies can provide substantial help for future studies. In this article, we have included recent studies that have been reported since previous publication that will be of considerable assistance and added value to those who are focusing their research on defining chemical pathway to the progression of different diseases.

FTIR spectroscopy; biological tissues; cancer research; spectral peak assignments

Aim of this study The vibrational spectroscopic techniques, including FTIR spectroscopy, are potential tools for non-invasive optical tissue diagnosis. In recent years, applications of spectroscopic techniques in biological studies have increased a great deal, and particularly clinical investigations related to malignancy and cancer detection by spectroscopic means have attracted attention both by the clinical and non-clinical researchers. Several papers have been published on the diagnostic importance of different spectroscopic and imaging techniques in the area of cancer detection (1–14). However, there is still a gap, as it appears that the details of characteristic peak frequencies and their definitions, which can be attributed to specific functional groups present in the biological tissues, have

CONTACT Ihtesham Ur Rehman i.u.rehman@sheffield.ac.uk Department of Materials Science and Engineering, The Kroto Research Institute, The University of Sheffield, North Campus, Broad Lane, Sheffield S3 7HQ, UK. © 2017 Taylor & Francis Group, LLC

APPLIED SPECTROSCOPY REVIEWS

457

not been fully investigated. Furthermore, there is no paper to date that addresses the FTIR spectroscopic investigations of biological tissues, as researchers have to rely on a number of research papers and the majority of the times the interpretation of the spectral data differs significantly. In this paper, significant amount of spectroscopic investigation reported on biological tissues has been reviewed and it reveals that there are striking similarities in defining different peak frequencies. As a result, a unique database has been created containing a detailed study of the existent data; different chemical bands and their assignments of spectral bands could provide significant assistance to research groups focusing on spectroscopy. This, in turn, can lead to considerable improvements in the quality and quantity of the research done. This article aims to present a wide and detailed collection of interpretation of FTIR spectral frequencies. It is envisaged that this paper will be of significant assistance to research groups working on FTIR spectroscopy of biological tissues.

Introduction Recently, spectroscopy has emerged as one of the major tools for biomedical applications and has made significant progress in the field of clinical evaluation. Research has been carried out on a number of natural tissues using spectroscopic techniques, including FTIR spectroscopy. These vibrational spectroscopic techniques are relatively simple, reproducible, non-destructive to the tissue and only small amounts of material (micrograms to nanograms) with a minimum sample preparation are required. In addition, these techniques also provide molecular-level information allowing investigation of functional groups, bonding types, and molecular conformations. Spectral bands in vibrational spectra are molecule specific and provide direct information about the biochemical composition. These bands are relatively narrow, easy to resolve and sensitive to molecular structure, conformation, and environment. A considerably wide field of medical and biological studies has been covered by spectroscopic methods in recent years. It is strongly believed that in studies related to spectroscopic techniques, both the reliable experimental procedure and characterization of spectral peak positions and their assignment along with accurate peak detection and definition are of crucial importance. Although a number of scientists have used different techniques, it seems that there is a marked similarity in their spectral interpretation of comparable areas in their collected spectra. These spectral interpretation investigations reported to date have been tabulated in Table 1 and provide a detailed account of spectral frequencies of the biological tissues.

FTIR spectroscopy FTIR spectroscopy is a vibrational spectroscopic technique that can be used to optically probe the molecular changes associated with diseased tissues (15–17). The method is employed to find more conservative ways of analysis to measure characteristics within tumor tissue and cells that would allow accurate and precise assignment of the functional groups, bonding types, and molecular conformations. Spectral bands in vibrational spectra are molecule specific and provide direct information about the biochemical composition. FTIR peaks

458

A. C. S. TALARI ET AL.

Table 1. Spectral interpretations. FTIR peak 472/5 cm¡1 521 cm¡1 600–900 cm¡1 606 cm¡1 608 cm¡1 635 cm¡1 700–1000 cm¡1 724 cm¡1 793 cm¡1 802–5 cm¡1 805 cm¡1 813 cm¡1 829 cm¡1 831/3 cm¡1 835 cm¡1 835–40 cm¡1 860 cm¡1 868 cm¡1 878 cm¡1 889 cm¡1 890 cm¡1 892 cm¡1 900–1300 cm¡1 900–1350 cm¡1 915 cm¡1 925–9 cm¡1 933 cm¡1 938 cm¡1 940 cm¡1 960 cm¡1 961 cm¡1 963 cm¡1 963/4 cm¡1 964 cm¡1 965 cm¡1 966 cm¡1 968 cm¡1 970 cm¡1

971 cm¡1 972 cm¡1 985 cm¡1 988/93 cm¡1 994 cm¡1 995 cm¡1 996 cm¡1

Assignment

Ref. no.

Ca H Ca’ torsion and C–OH3 torsion of methoxy group(4) Ca H Ca’ torsion and ring torsion of phenyl(1) CH out-of-plane bending vibrations Ring deformation of phenyl(1) Ring deformation of phenyl(1) OH out-of-plane bend (associated) Out-of-plane bending vibrations C H deformation Guanine in a C3’endo/syn conformation in the Z conformation of DNA Left-handed helix DNA (Z-form) C30 endo/anti (A-form helix) conformation Ring CH deformation C2’ endo conformation of sugar C2’ endo conformation of sugar C20 endo/anti (B-form helix) conformation Left-handed helix DNA (Z form) C30 endo/anti (A-form helix) conformation Left-handed helix DNA (Z form) C30 endo/anti (A-form helix) conformation C C, C O deoxyribose C30 endo/anti (A-form helix) conformation C20 endo/anti (B-form helix) conformation C C, C O deoxyribose Fatty acid, saccharide (b) Phosphodiester region Phosphodiester stretching bands region (for absorbances due to collagen and glycogen) Ribose ring vibrations: RNA/DNA Left-handed helix DNA (Z form) Z type DNA Unassigned Carotenoid Symmetric stretching vibration of n1PO43¡ (phosphate of HA) C O deoxyribose, C C d(C H O) (polysaccharides, pectin) C C, C O deoxyribose C C and C O in deoxyribose of DNA of tumor cells C O deoxyribose, C C C O stretching of the phosphodiester and the ribose C O deoxyribose, C C DNA PO4¡ stretch, C C stretch C N& C stretch: nucleic acids, C N& C stretch: nucleic acids Ribose-phosphate main chain vibrations of RNA–DNA Symmetric stretching mode of dianionic phosphate monoesters of phosphorylated proteins or cellular nucleic acids DNA Choline nPO4 D of nucleic acids and proteins Symmetric stretching mode of dianionic phosphate monoester in phosphorylated proteins, such as phosvitin OCH3 (polysaccharides, pectin) OCH3 (polysaccharides–cellulose) RNA stretching, ring bending of uracil C O ribose, C C Ring breathing C O ribose, C C RNA

(124) (124) (125) (124) (124) (126) (124) (79) (108) (108) (108) (124) (108) (108) (108) (108) (108) (108) (108) (127) (108) (108) (108) (28) (88) (53) (108) (53) (28) (128) (124) (73) (129) (108) (108) (73) (27) (73) (33), (62) (48) (53) (130) (95) (79) (33) (130) (33) (129) (129) (64) (73) (124) (73) (62) (Continued on next page)


459

Table 1. (Continued). FTIR peak 1000–50 cm¡1 1000–140 cm¡1 1000–150 cm¡1 1000–200 cm¡1 1000–300 cm¡1 1000–350 cm¡1 1000–650 cm¡1 1008 cm¡1 1009/10/1 cm¡1 1011 cm¡1 1017 cm¡1 1018 cm¡1 1020 cm¡1 1020–50 cm¡1 1021 cm¡1 1022 cm¡1 1024 cm¡1 1025 cm¡1

1028 cm¡1 ¡1

1029/30 cm 1030 cm¡1

1030 cm¡1 1030 cm¡1 1031 cm¡1

1032 cm¡1 1033 cm¡1 1034 cm¡1 1035 cm¡1

1036 cm¡1 1037 cm¡1 1039

Assignment

Ref. no.

Ring stretching vibrations mixed strongly with CH in-plane bending Protein amide I absorption A reasonably specific area for nucleic acids in the absence of glycogen C OH bonds in oligosaccharides such as mannose & galactose Mainly from phosphate or oligosaccharide groups C O stretching (carbohydrates) CH in-plane bending vibrations The aromatic CH bending and rocking vibrations Region of the phosphate vibration Carbohydrate residues attached to collagen and amide III vibration (in collagen) Porphyrin ring of heme proteins CHa,a’ out-of-plane bending and Ca D Ca’ torsion Stretching C O deoxyribose CHa,a’ out-of-plane bending and Ca D Ca’ torsion C O H vibrations of the sugar moiety n(CO), n(CC), d(OCH), ring (polysaccharides, pectin) DNA Glycogen Ribose ring vibrations: RNA Glycogen Glycogen (C O stretch associated with glycogen) C O stretch, C O bend Carbohydrates peak for solutions Vibrational frequency of –CH2OH groups of carbohydrates (including glucose, fructose, glycogen, etc.) Glycogen –CH2OH groups and the C O stretching vibration coupled with C O bending of the C OH groups of carbohydrates (including glucose, fructose, glycogen, etc.) Glycogen absorption due to C O and C C stretching and C O H deformation motions O CH3 stretching of methoxy groups Glycogen vibration CH2OH vibration ns C O Collagen and phosphodiester groups of nucleic acids Stretching C O ribose Collagen Glycogen n(CC) skeletal cis conformation, n(CH2OH), n(CO) stretching coupled with C O bending Collagen One of the triad peaks of nucleic acids (along with 1060 and 1081) O CH3 stretching of methoxy groups n(CC) skeletal cis conformation, n(CH2OH), n(CO) stretching coupled with C O bending Collagen Skeletal trans conformation (CC) of DNA n(CC) skeletal cis conformation, n(CH2OH), n(CO) stretching coupled with C O bending Glycogen n(CO), n(CC), n(CCO), (polysaccharides–cellulose) C C skeletal stretching n(CC) skeletal cis conformation, n(CH2OH), n(CO) stretching coupled with C O bending n(C O)

(125) (89) (27) (74) (74) (23) (125) (124) (73) (23) (25) (124) (73) (124) (79) (129) (88), (62) (28) (53) (28), (130) (28), (130) (48) (3) (105) (3), (88) (85) (105) (124) (42), (89) (42) (90) (85) (73) (65) (38) (65), (98) (33), (88) (27) (124) (59), (65) (23) (105) (65) (130) (129) (39) (65) (56) (Continued on next page)

460


Table 1. (Continued). FTIR peak 1039/40 cm¡1 1040–100 cm¡1 1042 cm¡1 1045 cm¡1

1045/545 cm¡1 1050 cm¡1

1050–70 cm¡1 1050–80 cm¡1 1050–100 cm¡1

1051 cm¡1 1052 cm¡1 1053 cm¡1 1055 cm¡1

¡1

1056/7 cm 1059 cm¡1 1060 cm¡1

1064 cm¡1 1065 cm¡1 1066 cm¡1 1068 cm¡1 1070 cm¡1 1070–80 cm¡1 1071 cm¡1 1075 cm¡1

Assignment

Ref. no.

Stretching C O ribose Symmetric PO2¡ stretching in RNA and DNA C O H vibrations of the sugar moiety Glycogen band (due to OH stretching coupled with bending) C O stretching frequencies coupled with C O bending frequencies of the C OH groups of carbohydrates(including glucose, fructose, glycogen, etc. –CH2OH groups and the C O stretching vibration coupled with C O bending of the C OH groups of carbohydrates (including glucose, fructose, glycogen, etc.) Gives an estimate carbohydrate concentrations (lower in malignant cells) ns CO O C C O stretching coupled with C O bending of the C OH of carbohydrates Glycogen C O C stretching (nucleic acids and phospholipids) Indicates a degree of oxidative damage to DNA Phosphate and oligosaccharides PO2¡ stretching modes, P O C antisymmetric stretching mode of phosphate ester, and C OH stretching of oligosaccharides C O C stretching of DNA and RNA C O stretch, C O bend Phosphate I band for 2 different C O vibrations of deoxyribose in DNA in A and B forms of helix or ordering structure nC O & dC O of carbohydrates Shoulder of 1121 cm¡1 band due to DNA Oligosaccharide C O bond in hydroxyl group that might interact with some other membrane components Mainly from phospholipid phosphate and partly from oligosaccharide C OH bonds Phosphate ester PO2¡ stretching and C OH stretching of oligosaccharides Phosphate residues Membrane-bound oligosaccharide C OH bond (a part of it may originate from the hydroxyl group of the sugar residue) n(CO), n(CC), d(OCH) (polysaccharides, pectin) C H Stretching C O deoxyribose 2-methylmannoside Oligosaccharide C OH stretching band Mannose and mannose-6-phosphate Stretching C O deoxyribose One of the triad peaks of nucleic acids (along with 1031 and 1081 cm¡1) n(CO), n(CC), d(OCH) (polysaccharides–cellulose) Stretching C O ribose C O stretching of the phosphodiester and the ribose Nucleic acids, in the absence of glycogen PO2¡ symmetric stretching of nucleic acids Stretching C O ribose Mannose and mannose-6-phosphate Symmetric phosphate [PO2¡ (sym)] stretching Nucleic acid band Phosphate I band for 2 different C O vibrations of deoxyribose in DNA in disordering structure Symmetric phosphate stretching modes or n( PO2¡) sym. (phosphate stretching modes originate from the

(73) (23) (79) (43), (67) (105) (85) (105) (85) (90) (42) (28) (23) (88) (74) (74) (23) (48) (108), (64) (33) (84) (74) (74) (74) (74) (74) (74) (129) (79) (73), (64) (74) (74) (74) (73) (44) (129) (73) (27) (27) (81) (73) (74) (39) (131) (108) (65) (Continued on next page)


461

Table 1. (Continued). FTIR peak

1076 cm¡1 1076 cm¡1 1078 cm¡1

1079 cm¡1 1080 cm¡1

1081 cm¡1

1082 cm¡1

1083 cm¡1 1084 cm¡1

1084–6 cm¡1 1085 cm¡1

1086 cm¡1

1087 cm¡1

Assignment phosphodiester groups in nucleic acids and suggest an increase in the nucleic acids in the malignant tissues) n(PO2¡) symmetric stretching of phosphodiester Skeletal cis conformation (CC) of DNA Symmetric phosphate [PO2¡ (sym)] stretching ns PO2¡ Phosphate I in RNA Symmetric phosphate Glycogen absorption due to C O and C C stretching and C O H deformation motions DNA in healthy samples, in the absence of glycogen Indicating the role of phosphates during diseases C OH stretching band of oligosaccharide residue ns PO2¡ n PO2¡ Phosphate vibration Symmetric phosphate [PO2¡ (sym)] stretching Collagen and phosphodiester groups of nucleic acids Symmetric phosphate stretching modes or n(PO2¡) sym. (phosphate stretching modes originate from the phosphodiester groups in nucleic acids and suggest an increase in the nucleic acids in the malignant tissues) n(PO2¡) symmetric stretching of phosphodiesters Phosphate I in RNA One of the triad peaks of nucleic acids (along with 1031 and 1060) PO2¡ symmetric Phosphate band Collagen Symmetric phosphate stretching band of the normal cells Symmetric phosphate [PO2¡ (sym)] stretching PO2¡ symmetric DNA (band due to PO2¡ vibrations) Symmetric phosphate [PO2¡ (sym)] stretching PO2¡ symmetric Stretching PO2¡ symmetric Absorbance by the phosphodiester bonds of the phosphate/ sugar backbone of nucleic acids Nucleic acid region Nucleic acid–Phosphate band ns(PO2¡) of nucleic acids PO2¡ symmetric (Phosphate II) PO2¡ symmetric Mainly from absorption bands of the phosphodiester group of nucleic acids and membrane phospholipids, and partially protein (amide III). The band originating from sugar chains (C OH band) overlaps. Mainly from phospholipid phosphate and partly from oligosaccharide C OH bonds Phosphate ester Symmetric phosphate stretching modes or n(PO2¡) sym. (phosphate stretching modes originate from the phosphodiester groups in nucleic acids and suggest an increase in the nucleic acids in the malignant tissues) PO2¡ symmetric n(PO2¡) symmetric stretching of phosphodiester C O H vibrations of the sugar moiety PO2¡ symmetric (Phosphate II) Symmetric stretching of phosphate groups of phosphodiester linkages in DNA and RNA

Ref. no.

(65) (105) (105) (90) (108) (28), (130) (27) (27) (95) (82) (28), (130) (28), (44), (96) (89) (42) (85) (65)

(44) (108) (27) (82) (97) (88) (33) (39) (82) (43) (42), (88) (82) (108) (88) (88) (84) (33) (73) (82) (82), (40)

(74) (74) (65)

(82) (44), (132) (79) (73) (23) (Continued on next page)

462



1088–90 cm¡1 1089 cm¡1 1090 cm¡1 1090–100 cm¡1 1094 cm¡1 1095 cm¡1 1099/100 cm¡1 1101 cm¡1 1104 cm¡1 1105 cm¡1 1107 cm¡1 1110 cm¡1 1112 cm¡1 1113/5 cm¡1 1117 cm¡1 1119 cm¡1 1119 cm¡1 1120 cm¡1

1121 cm¡1 1122 cm¡1 1125 cm¡1 1126 cm¡1 1137 cm¡1 1145 cm¡1

1150 cm¡1

1150–200 cm¡1 1151 cm¡1 1152 cm¡1 1153 cm¡1 1155 cm¡1 1159–74 cm¡1 1160 cm¡1 1161 cm¡1 1161/2 cm¡1

Assignment

Ref. no.

Symmetric PO2¡ stretching in RNA and DNA Symmetric stretching of phosphate groups in phospholipids DNA Phosphate I (stretching PO2¡ symmetric vibration) in B-form DNA PO2¡ symmetric vibration, nucleic acid Stretching PO2¡ symmetric in RNA Mannose and mannose-6-phosphate Phosphate ester (C O P) band Phosphate II (stretching PO2¡ asymmetric vibration) in A-form RNA Stretching PO2¡ symmetric(Phosphate II) nasym(C O C) (polysaccharides–cellulose) Stretching PO2¡ symmetric Stretching PO2¡ symmetric(Phosphate II) Methyl-carbon stretching (polypeptides) Symmetric stretching P O C Carbohydrates n(CO), n(CC), ring (polysaccharides, pectin) n(CO) n(CC) ring (polysaccharides, cellulose) Phosphate groups in RNA Symmetric stretching P O C C O stretching vibration of C OH group of ribose (RNA) Symmetric stretching P O C C O stretching mode Mannose-6-phosphate Phosphorylated saccharide residue C O stretching d C–O, d C O H, d C O C (carbohydrate related) Symmetric phosphodiester stretching band RNA Shoulder of 1121 cm¡1 band due to RNA nC O of carbohydrates RNA CH2,6 in-plane bend and C1–Ca–Ha bend n(CO) n(CC) ring (polysaccharides, cellulose) n(C–O), disaccharides, sucrose n(C–O)C n(C C), disaccharides, sucrose Oligosaccharide C OH stretching band 2-methylmannoside Phosphate and oligosaccharides Oligosaccharide C O bond in hydroxyl group that might interact with some other membrane components Membrane-bound oligosaccharide C OH bond C O stretching vibration C O stretching mode of the carbohydrates CH8, CH”8 deformations n(C O C), ring (polysaccharides, pectin) Phosphodiester stretching bands (sym. and asym.) Glycogen absorption due to C O and C C stretching and C O H deformation motions CH8, CH”8 deformations Stretching vibrations of hydrogen-bonding C OH groups C O stretching vibration n (C C)-diagnostic for the presence of a TR Lappin structure, most likely a cellular pigment. nC O of proteins and carbohydrates CO stretching Stretching vibrations of hydrogen-bonding C OH groups Mainly from the C O stretching mode of C OH groups of serine, threonine and tyrosine of proteins)

(23) (23) (56) (108) (45) (108) (74) (74) (108) (73) (129) (27) (73) (64) (73) (84) (129) (129) (64) (73) (23) (73) (130) (74) (74) (39) (40) (88) (62), (88) (84) (33) (56) (120) (129) (129) (129) (74) (74) (74)

(130) (33) (124) (129) (88) (27) (124) (42) (28) (107) (33) (42) (42) (65) (Continued on next page)


463

Table 1. (Continued). FTIR peak 1162 cm¡1 1163 cm¡1 1163/4 cm¡1 1164 cm¡1

1165 cm¡1 1168 cm¡1 1170 cm¡1 1171 cm¡1 1172 cm¡1

1172/3 cm¡1 1173 cm¡1 1173 cm¡1 1179 cm¡1 1180–300 cm¡1 1185/1/2 cm¡1 1188 cm¡1 1191 cm¡1 1200 cm¡1 1201 cm¡1 1204 cm¡1

1205 cm¡1 1206 cm¡1 ¡1

1207 cm

1209 cm¡1 1212 cm¡1 1217 cm¡1 1220 cm¡1 1220–4 cm¡1 1220–40 cm¡1 1220–50 cm¡1 1220–350 cm¡1 1222 cm¡1

Assignment

Ref. no.

n(CC), d(COH), n(CO) stretching Stretching modes of the C OH groups of serine, threonine, and tyrosine residues of cellular proteins d(C O C), ring (polysaccharides, cellulose) CH’9, CH7, CH’7 deformations C O stretching band of collagen (type I) Mainly from the C O stretching mode of C OH groups of serine, threonine and tyrosine of proteins) n(CC), d(COH), n(CO) stretching C O stretching(in normal tissue) Hydrogen-bonded stretching mode of C OH groups d C–H, d C O H, d C O C (carbohydrate related) C–O(H) stretching (Ser, Thr, and Tyr) nas CO O C C O bands from glycomaterials and proteins CO OC asymmetric stretching CO O C asymmetric stretching: ester bonds in cholesteryl esters Stretching vibrations of non-hydrogen-bonding C OH groups CO stretching CO stretching of collagen (type I) Stretching modes of the C OH groups of serine, threonine, and tyrosine residues of cellular proteins CO stretching of the C OH groups of serine, threonine and tyrosine in the cell proteins as well as carbohydrates C O stretching(in malignant tissues) Non-hydrogen-bonded stretching mode of C OH groups Cholesterol ester Amide III band region CH2 Deoxyribose Phospholipids Collagen Phosphate (P D O) band PO2¡ asymmetric (Phosphate I) Vibrational modes of collagen proteins-amide III C O C, C O dominated by the ring vibrations of polysaccharides C O P, P O P Collagen C O C, C O dominated by the ring vibrations of polysaccharides C O P, P O P Amide III Collagen PO2¡ asymmetric (Phosphate I) Collagen PO2¡ asymmetric (Phosphate I) PO2¡ asymmetric (Phosphate I) PO2¡ asymmetric (Phosphate I) PO2¡ asymmetric vibrations of nucleic acids when it is highly hydrogen bonded Asymmetric hydrogen-bonded phosphate stretching mode Phosphate II (stretching PO2¡ asymmetric vibration) in B-form DNA Asymmetric PO2¡ stretching in RNA and DNA n PO2¡ Amide III (C N stretching and N H in plane bending, often with significant contributions from CH2 wagging vibrations) Phosphate stretching bands from phosphodiester groups of cellular nucleic acids CH6,20 ,a,a’ rock

(44), (58) (33) (129) (124) (82) (44) (44), (58) (97) (33) (40) (81) (90) (82) (56) (53) (42) (42) (82) (33) (42) (97) (33) (79) (49) (73) (73) (64) (65) (74) (73) (49) (44), (60) (30), (88) (44), (65) (27) (33) (27) (23) (73) (73) (73) (42) (33) (108) (23) (96) (23) (33) (120) (Continued on next page)

464


Table 1. (Continued). FTIR peak 1222/3 cm¡1 1224 cm¡1

1226 cm¡1 1230 cm¡1

1232 cm¡1 1234 cm¡1 1235 cm¡1

¡1

1236 cm

1236–42 cm¡1 1236/7 cm¡1 1237 cm¡1 1238 cm¡1

1238/9 cm¡1 1240 cm¡1

1240–45 cm¡1

Assignment

Ref. no.

PO2¡ asymmetric (Phosphate I) Collagen Asymmetric stretching of phosphate groups of phosphodiester linkages in DNA and RNA Asymmetric PO2¡ stretching in RNA and DNA Symmetric stretching of phosphate groups in phospholipids PO2¡ asymmetric (Phosphate I) Stretching PO2¡ asymmetric Overlapping of the protein amide III and the nucleic acid phosphate vibration DNA nPO2¡ asymmetric PO2¡ asymmetric (Nucleic acid) Composed of amide III as well as phosphate vibration of nucleic acids CH6,20 ,a,a’ rock Antisymmetric PO2¡ stretching, nucleic acid Amide III and asymmetric phosphodiester stretching mode (nasPO2¡), mainly from the nucleic acids nasPO2¡ of nucleic acids Relatively specific for collagen and nucleic acids Stretching PO2¡ asymmetric (phosphate I) PO2¡ asymmetric (Phosphate I) PO2¡ asymmetric Stretching PO2¡ asymmetric(phosphate I) Asymmetric phosphate [PO2¡ (asym.)] stretching modes Stretching PO2¡ asymmetric Amide III PO2¡ asymmetric stretching, fully hydrogen bonded: mainly nucleic acids with the little contribution from phospholipids NHQHN bending vibration Asymmetric PO2¡ stretching nas PO2¡ Collagen Asymmetric non-hydrogen-bonded phosphate stretching mode (phosphate stretching modes originate from the phosphodiester groups of nucleic acids and suggest an increase in the nucleic acids in the malignant tissues) Mainly from absorption bands of the phosphodiester group of nucleic acids and membrane phospholipids, and partially protein (amide III) Amide III PO2¡ asymmetric vibrations of nucleic acids when it is nonhydrogen-bonded nas PO2¡ Collagen Asymmetric phosphodiester stretching band Amide III PO2¡ ionized asymmetric stretching n(PO2¡) asymmetric stretching of phosphodiesters Composed of amide III mode of collagen protein and the asymmetric stretching mode of the phosphodiester groups of nucleic acids Asymmetric stretching mode of phosphodiester groups of nucleic acids Asymmetric PO2¡ stretching in RNA Amide III, Asymmetric PO2¡ stretch mode nas PO2¡ (nucleic acid related) Phosphate I (stretching PO2¡ symmetric vibration) in A-form RNA

(73), (133) (23) (23) (23) (23) (73) (27), (108) (25) (62) (56) (81) (27) (124) (45) (49) (33) (88) (73) (73) (61) (73) (42), (102) (108) (27) (53) (54) (82) (28), (65) (23), (33) (33) (65) (82) (82) (42) (90) (88) (88) (65) (44), (105) (28), (65), (67), (98) (33) (33) (23) (56) (40)

(108) (Continued on next page)


465

Table 1. (Continued). FTIR peak 1240–65 cm¡1 1240–310 cm¡1 1241 cm¡1

¡1

1242 cm

1243 cm¡1

1243/4 cm¡1 1244 cm¡1 1244/5 cm¡1 1245 cm¡1 1246 cm¡1 1247 cm¡1 1248 cm¡1 1250 cm¡1 1250–400 cm¡1 1252/55 cm¡1 1256 cm¡1 1262 cm¡1 1264 cm¡1 1265 cm¡1 1272/3 cm¡1 1276 cm¡1 1278 cm¡1 1278/9 cm¡1 1280 cm¡1 1282 cm¡1 1283 cm¡1 1283–1339 cm¡1 1284 cm¡1 1287 cm¡1 1288 cm¡1 1291/2 cm¡1 1294/5/6 cm¡1

Assignment

Ref. no.

Amide III(C N stretching mode of proteins, indicating mainly a-helix conformation) nC–N, amide III PO2¡ asymmetric (Phosphate I) Phosphate band (phosphate stretching modes originate from the phosphodiester groups of nucleic acids and suggest an increase in the nucleic acids in the malignant tissues) (Generally, the PO2¡ groups of phospholipids do not contribute to these bands) Phosphate stretching bands from phosphodiester groups of cellular nucleic acids nas phosphate Amide III (protein), nPHO (lipid, nucleic acid) PO2¡ asymmetric Collagen I and IV Amide III Amide III collagen n(PO2¡) asymmetric stretching of phosphodiesters Asymmetric phosphate [PO2¡ (asym.)] stretching modes (phosphate stretching modes originate from the phosphodiester groups of nucleic acids and suggest an increase the in nucleic acids in the malignant tissues) (Generally, the PO2¡ groups of phospholipids do not contribute to these bands) Phosphate in RNA Collagen (type I) Collagen I and IV Asymmetric phosphate stretching (nasPO2¡) RNA PO2¡ asymmetric (Phosphate I) PO2¡ asymmetric PO2¡ asymmetric PO2¡ asymmetric (Phosphate I) PO2¡ asymmetric C N stretching Amide III CH2 wagging vibration of the acyl chains (phospholipids) Amide III PO2¡ asymmetric (Phosphate I PO2¡ asymmetric (Phosphate I) Amide III PO2¡ asymmetric (Phosphate I) CHa’ rocking CHa’ rocking N H thymine Vibrational modes of collagen proteins-amide III Deformation N–H Collagen Amide III Amide III band components of proteins Collagen Collagen Amide III (protein), nPHO (lipid, nucleic acid) Collagen Amide III band components of proteins Collagen Deformation N–H N H thymine N H thymine Deformation N H cytosine

(49), (134) (96) (73) (97) (42)

(33) (44) (71) (82) (82) (27), (88) (23) (44), (132) (42)

(108) (82) (82) (28), (108), (130) (62) (73) (82), (130) (28), (82) (73) (82) (54) (107) (23) (27), (64) (73) (73) (64) (73) (124) (124) (73) (49) (73) (65) (27) (44), (65) (23), (88) (33) (71) (33) (58) (23) (73) (73) (73) (73) (Continued on next page)

466



Assignment

Ref. no.

1301 cm¡1 1303 cm¡1 1306 cm¡1 1307 cm¡1 1309 cm¡1 1310 cm¡1

C OH bending vibration d C–H, d C O H (undetermined) Unassigned band Amide III Amide III Amide III CH2 stretching Amide III band components of proteins Amide III (protein), nPHO (lipid, nucleic acid) CH2 stretching Amide III band components of proteins Collagen Stretching C N thymine, adenine Benzene ring mixed with the CH in-plane bending from the phenyl ring and the ethylene bridge CH2 wagging d(CH), ring (polysaccharides, pectin) d(CH), ring (polysaccharides, pectin) d(CH), ring (polysaccharides, cellulose) Collagen CH2 wagging Collagen In-plane C O stretching vibration combined with the ring stretch of phenyl CH2 wagging Collagen CH2 wagging: phospholipid, fatty acid, triglyceride, amino acid side chain Stretching C–O, deformation C–H, deformation N–H Stretching C–O, deformation C–H, deformation N–H CH3 symmetric bending: lipids d(CH2), n(CC) (polysaccharides, pectin) Stretching C N cytosine, guanine Stretching C–O, deformation C–H, deformation N–H Deformation N–H, C–H Stretching C N cytosine, guanine C H deformation dCH3 Stretching C–O, deformation C–H, deformation N–H Carbon particle CH2 asymmetric bending, COO¡ stretch (proteins and fatty acids) Less characteristic, due to aliphatic side groups of the amino acid residues Symmetric CH3 bending of the methyl groups of proteins CH3 CH3 symmetric deformation Extremely weak peaks of DNA and RNA arise mainly from the vibrational modes of methyl and methylene groups of proteins and lipids and amide groups Symmetric CH3 bending modes of the methyl groups of proteins d[(CH3)] sym. D[C(CH3)2) symmetric Symmetric stretching vibration of COO¡ group of fatty acids and amino acids dsCH3 of proteins Symmetric bending modes of methyl groups in skeletal proteins

(81) (40) (130) (27) (56) (96) (39) (44), (65) (71) (39) (44), (65) (33) (73) (124)

1312 cm¡1 1314 cm¡1 1316 cm¡1 1317 cm¡1 1327/8 cm¡1 1328 cm¡1 1330 cm¡1 1335 cm¡1 1335 cm¡1 1336 cm¡1 1337 cm¡1 1337/8 cm¡1 1339 cm¡1 1340 cm¡1 ¡1

1343 cm

1358 cm¡1 1367 cm¡1 1368 cm¡1 1369/70 cm¡1 1370/1 cm¡1 1370/1/3 cm¡1 1373 cm¡1 1378 cm¡1 1380 cm¡1 1390 cm¡1 1392 cm¡1 1395 cm¡1 1396 cm¡1 1397 cm¡1 1398 cm¡1 1399 cm¡1

1400 cm¡1

(44), (60) (129) (129) (129) (88) (44), (59), (67) (33) (124) (44), (65) (23), (65) (53) (73) (73) (53) (129) (73) (73) (108) (73) (79) (90), (96) (73) (27) (81) (27) (42) (56) (135) (42) (65) (61), (131) (44) (130) (33) (33) (Continued on next page)


467


1400–500 cm¡1 1400 cm¡1 1400/1 cm¡1 1400/1/2 cm¡1 1401 cm¡1 1401/2 cm¡1

1402 cm¡1 1403 cm¡1

1404/5 cm¡1 1412/4 cm¡1 1416 cm¡1 1417 cm¡1 1418/9 cm¡1 1419 cm¡1 1430 cm¡1 1444 cm¡1 1449 cm¡1 1450 cm¡1 1451 cm¡1 1453 cm¡1 1454 cm¡1 ¡1

1455 cm

¡1

1455/6 cm

1456 cm¡1 1457 cm¡1

Assignment

Ref. no.

Specific absorption of proteins Symmetric stretch of methyl groups in proteins Ring stretching vibrations mixed strongly with CH in-plane bending nsCH3 vibrations COO¡& symmetric stretching: fatty acids d C–H, d C O H (lipids) COO¡ symmetric stretching of acidic amino acids aspartate and glutamate CH3 symmetric deformation Symmetric CH3 bending modes of the methyl groups of proteins d[(CH3)] sym. COO¡ symmetric stretching of fatty acids Symmetric CH3 bending modes of the methyl groups of proteins d[(CH3)] sym. Stretching C–N, deformation N–H, deformation C–H d[C(CH3)2) symmetric d C–H, d C O H Symmetric CH3 bending modes of the methyl groups of proteins d[(CH3)] sym. DsCH3 of collagen d[C(CH3)2) symmetric CH3 asymmetric deformation Stretching C–N, deformation N–H, deformation C–H Deformation C–H, N–H, stretching C–N Stretching C–N, deformation N–H, deformation C–H Deformation C–H ns(COO¡) (polysaccharides, pectin) d (CH2) (polysaccharides, cellulose) d(CH2), lipids, fatty acids d(CH) (polysaccharides, pectin) Asymmetric CH3 bending of the methyl groups of proteins Methylene deformation in biomolecules Polyethylene methylene deformation modes CH3 symmetric deformations Asymmetric CH3 bending modes of the methyl groups of proteins d[(CH3)] asymmetric Das CH and das CH2 CH2 bending: mainly lipids, with the little contribution from proteins Asymmetric methyl deformation d[(CH3)] asymmetric C O H Less characteristic due to aliphatic side groups of the amino acid residues dasCH3 of proteins Symmetric bending modes of methyl groups in skeletal proteins Asymmetric CH3 bending modes of the methyl groups of proteins d[(CH3)] asymmetric CH3 bending vibration (lipids and proteins) Extremely weak peaks of DNA and RNA arise mainly from the vibrational modes of methyl and methylene groups of proteins and lipids and amide groups Asymmetric CH3 bending modes of the methyl groups of proteins

(95) (28) (124) (45) (53) (40) (23) (135), (39) (45) (61), (131) (23) (65) (41), (65), (98) (73) (44) (71) (65) (59) (33) (44) (135) (73) (73) (73), (48) (108) (129) (129) (129) (129) (42) (130) (27) (39) (65) (44), (61) (45) (53) (28) (56), (81) (73) (27) (33) (33) (65) (44), (59), (65) (132) (23) (42) (65) (Continued on next page)

468



1458 cm¡1 1460 cm¡1 1462 cm¡1 1465 cm¡1 1467 cm¡1 1468 cm¡1

1469 cm¡1 1470 cm¡1 1480 cm¡1 1480–543 cm¡1 1480–600 cm¡1

1482 cm¡1 1482/3/5 cm¡1 1486 cm¡1 1487/8 cm¡1 1488/9 cm¡1 1489 cm¡1 1490 cm¡1 1494 cm¡1 1495/6 cm¡1 1500 cm¡1 1500–60 cm¡1 1504 cm¡1 1510 cm¡1 1514 cm¡1 1517 cm¡1 1519 cm¡1 1524 cm¡1 1526 cm¡1 1527 cm¡1 1528 cm¡1 152829/30 cm¡1 1530 cm¡1 1531 cm¡1 1532 cm¡1 1534 cm¡1 1535/7 cm¡1 1536 cm¡1 1539 cm¡1 1540 cm¡1 1540–650 cm¡1

Assignment

Ref. no.

d[(CH3)] asymmetric dC–H dasCH3 of collagen d[(C–H] lipid related Paraffin CH2 scissoring mode of the acyl chain of lipid Cholesterol-methyl band dCH2 dCH2 of lipids CH2 bending vibration (lipids and proteins) CH2 scissoring: lipids CH2 bending of the acyl chains of lipids CH2 scissoring vibration of the acyl chains (phospholipids) CH2 bending of the methylene chains in lipids Polyethylene methylene deformation modes Amide II The region of the amide II band in tissue proteins. Amide II mainly stems from the C N stretching and C N H bending vibrations weakly coupled to the CHO stretching mode Benzene C8–H coupled with a ring vibration of guanine Deformation C–H C D C, deformation C–H Deformation C–H In-plane CH bending vibration CHC stretching vibration of benzenoid rings C D C, deformation C–H In-plane CH bending vibration In-plane CH bending vibration C D C, deformation C–H In-plane CH bending vibration from the phenyl rings CH in-plane bending Amide II (an N H bending vibration coupled to C N stretching) In-plane CH bending vibration from the phenyl rings In-plane CH bending vibration from the phenyl rings CH in-plane bend n(C D C) – diagnostic for the presence of a TR Lappin structure, most likely a cellular pigment Amide II Amide II Stretching C D N, C D C CHN guanine Stretching C D N, C D C CHN guanine CHN adenine, cytosine Stretching C D N, C D C Modified guanine? Stretching C D N, C D C Modified guanine Amide II Stretching C D N, C D C Cytosine Amide II Protein amide II absorption—predominately b-sheet of amide II Amide II Amide II

(44), (59), (65) (132) (71) (33) (40) (3) (82) (43) (96) (33) (23) (53) (42) (23) (136) (27) (129) (49)

(65) (73) (108) (73) (108) (124) (54) (73) (124) (124) (73) (124) (124) (23) (124) (124) (124) (107) (90) (140) (73) (73) (73) (73) (108) (73) (73) (73) (73) (44) (73) (62) (45), (81) (49) (44) (89) (Continued on next page)


469


Assignment

Ref. no.

1541 cm¡1

Amide II absorption (primarily an N H bending coupled to a C N stretching vibrational mode) Amide II Amide II Amide II bands (arises from C N stretching and CHN bending vibrations) Protein band Amide II (dN–H, nC–N) Peptide amide II Amide II: (protein N H bending, C N stretching), a-helical structure Amide II Amide II Amide II of proteins Amide II Amide II of proteins N H bending and C N stretching C N stretching and CHN bending of amide II Ring stretching vibrations with little interaction with CH in-plane bending Region of the base vibrations Amide II Ring base CO stretching Predominately a-sheet of amide II (amide II band mainly stems from the C N stretching and C N H bending vibrations weakly coupled to the CHO stretching mode) Ring base Ring base Ring base Amide II CHN adenine CHN adenine CHN adenine Thymine Ring C C stretch of phenyl Amide II Ring C C stretch of phenyl CHC stretching of quinoid rings Ring C C stretch of phenyl C D N, NH2 adenine Ring C C stretch of phenyl (2) Methylated nucleotides C D N, NH2 adenine The region of the amide I band of tissue proteins (highly sensitive to the conformational changes in the secondary structure) (amide I band is due to in-plane stretching of the CHO bond, weakly coupled to stretching of the C N and in-plane bending of the N H bond) CHO stretching (lipids) CHN cytosine, N H adenine C D N, NH2 adenine Adenine vibration in DNA nas (COO¡) (polysaccharides, pectin) Adenine vibration in DNA Adenine vibration in DNA Ring C C stretch of phenyl Peak of nucleic acids due to the base carbonyl stretching and ring breathing mode Uracil

(28), (130)

1543 cm¡1 1544 cm¡1 1545 cm¡1 1546 cm¡1 1549 cm¡1 1550 cm¡1

1550–650 cm¡1 1550–800 cm¡1 1551 cm¡1 1552 cm¡1 1553 cm¡1

1555 cm¡1 1559 cm¡1 1567 cm¡1 1570 cm¡1 1571/3 cm¡1 1574/5 cm¡1 1576 cm¡1 1577 cm¡1 1581 cm¡1 1588 cm¡1 1589 cm¡1 1592 cm¡1 1594 cm¡1 1596 cm¡1 1597 cm¡1 1600–720 cm¡1

1600–800 cm¡1 1601/2 cm¡1 1603/4 cm¡1 1604 cm¡1 1605 cm¡1 1606 cm¡1 1609 cm¡1 1618 cm¡1 1620 cm¡1 1622 cm¡1

(27) (56), (96) (105), (130) (43) (90) (57), (95) (53) (40), (78) (44), (46) (33) (131) (82) (41), (68) (39) (125) (73) (71) (73) (42) (49) (73) (73) (73) (137) (73) (73) (73) (62) (124) (48) (124) (54) (124) (73) (73) (73) (73) (49)

(23) (73) (73) (108) (129) (108) (108) (124) (27) (62) (Continued on next page)

470


Table 1. (Continued). FTIR peak 1624 cm¡1 1630–700 cm¡1 1631 cm¡1 1632 cm¡1 1633 cm¡1 1632/4 cm¡1 1635 cm¡1 1636 cm¡1 1637 cm¡1 1638/9 cm¡1 1639 cm¡1 1640 cm¡1 1641 cm¡1 1642 cm¡1 1643 cm¡1 1644 cm¡1 1646 cm¡1

1647/8 cm¡1 1649 cm¡1

1650 cm¡1

1651 cm¡1 1652 cm¡1 1652/3 cm¡1 1653/4 cm¡1 1654 cm¡1 1655 cm¡1

1656 cm¡1 1657 cm¡1 1658 cm¡1 1659 cm¡1 1660 cm¡1 1664/5 cm¡1

Assignment

Ref. no.

Amide I Amide I region Amide I: b-sheet Ring C C stretch of phenyl Guanine CHC uracil, C D O b-sheet structure of amide I Proportion of b-sheet secondary structures (shoulder) CHO stretching of carbonyl group, typical saccharide absorption CHC uracil, C D O Triple helix O H deformation CHC thymine, adenine, N H guanine Amide I Amide I band of protein and H O H deformation of water Amide I vCDO C5 methylated cytosine? Amide I band (arises from CHO stretching vibrations) Amide I Amide I C5 methylated cytosine? C D O, stretching CHC uracil, NH2 guanine Amide I (protein), d H O H Amide I in normal tissues-for cancer is in lower frequencies Unordered random coils and turns of amide I C D O, C D N, N H of adenine, thymine, guanine, cytosine O H bending (water) Amide I Amide I absorption (predominantly the CHO stretching vibration of the amide C D O) Protein amide I absorption C D O, stretching CHC uracil, NH2 guanine Peptide amide I CHO stretching of amide I Amide I (protein) Amide I a-helix Amide I: (mainly protein CHO stretching), a-helical structure Amide I C2 D O cytosine C D O, C D N, N H of adenine, thymine, guanine, cytosine Amide I Amide I (of proteins in a-helix conformation) Amide I (n C D O, d C–N, d N–H) CHO cytosine C D O, C D N, N H of adenine, thymine, guanine, cytosine Peak of nucleic acids due to the base carbonyl stretching and ring breathing mode Amide I has some Tr lapping with the carbonyl stretching modes of nucleic acid Amide I (a-helix) Amide I C2 D O cytosine a-helical structure of amide I C D O, stretching CHC uracil, NH2 guanine Amide I Amide I Amide I band n(C D C) cis, lipids, fatty acids CHO Cytosine, uracil

(140) (28) (53) (124) (62) (73) (49) (23) (54) (73) (75) (79) (73) (44) (68) (40) (56) (73) (105) (44), (45) (131) (73) (73) (71) (131), (46), (81) (49) (108) (23) (46) (28), (130) (73) (57), (84) (39) (38), (41) (63) (53), (56) (31) (73) (108) (78) (74), (90) (73) (108) (73) (27) (33) (129) (96), (138), (48) (73) (49), (75) (73) (27) (44) (107) (129) (73) (Continued on next page)


471


Assignment

Ref. no.

1665 cm¡1 1666 cm¡1 1667 cm¡1 1670 cm¡1

Amide I (disordered structure solvated) CHO stretching vibration of pyrimidine base Amide I b-turns of proteins Amide I (anti-parallel b-sheet) n(C D C) trans, lipids, fatty acids Stretching CHO vibrations which are H-bonded(changes in the CHO stretching vibrations could be connected with destruction of old H-bonds and creation of the new ones) CHO guanine deformation N H in plane Unordered random coils and turns of amide I CHO guanine deformation N H in plane Adenine CHO guanine deformation N H in plane Amide I (disordered structure-non-hydrogen bonded) Amide I b-turns of proteins Peak of nucleic acids due to the base carbonyl stretching and ring breathing mode A high frequency vibration of an antiparallel b-sheet of amide I (the amide I band is due to in-plane stretching of the CHO band weakly coupled to stretching of the C N and in-plane bending of the N H bond) Amide I b-turns of proteins C2 D O guanine N H thymine The region of the bases Fatty acid esters CHO guanine CHO thymine Stretching CHO vibrations which are H-bonded (changes in the CHO stretching vibrations could be connected with destruction of old H-bonds and creation of the new ones) CHO thymine CHO guanine CHO thymine CDO CHO thymine CHO thymine Amide I (arises from CHO stretching vibration) CHO stretching vibration of DNA and RNA CHO stretching vibration of purine base CDO CHO stretching band mode of the fatty acid ester CHO band Absorption band of fatty acid ester Fatty acid ester band CHO stretching (lipids) CHO stretching (lipids) n(C D O), phospholipids, CE n(C D O) (polysaccharides, hemicellulose) CHO stretching CDO CHO stretching (lipids) Ester CHO stretching vibration (phospholipids) vCDO

(129) (23) (63) (129) (129) (73)

1679 cm¡1

1680 cm¡1 1681/4 cm¡1 1682 cm¡1 1684 cm¡1 1685 cm¡1 1690 cm¡1 1694 cm¡1

1695 cm¡1 1698/9 cm¡1 1700–15 cm¡1 1700–800 cm¡1 1700/2 cm¡1 1702 cm¡1

1706/7 cm¡1 1707 cm¡1 1708 cm¡1 1712/9 cm¡1 1713/4/6 cm¡1 1717 cm¡1

1719 cm¡1 1725–45 cm¡1 1728/9 cm¡1 1730 cm¡1 1736 cm¡1 1737 cm¡1 1738/40 cm¡1 1739 cm¡1 1740 cm¡1

1741 cm¡1 1743 cm¡1 1744 cm¡1

v CHO (fat, lipid) CHO stretching mode of lipids v CHO (lipids) Lipids Ester CHO stretch: triglycerides, cholesterol esters

(73) (49) (73) (62) (73) (129) (63) (27) (49)

(63) (73) (73) (108) (74) (73) (73) (73) (73) (73) (73) (73) (73) (73) (23) (23) (23) (73) (74) (74) (74) (74) (23) (81) (79) (139) (45) (88) (102) (131) (23) (23) (56) (71) (57) (40) (140) (53) (Continued on next page)

472


Table 1. (Continued). FTIR peak 1745 cm¡1 1750 cm¡1 1997/2040/53/ 58 cm¡1 2100 cm¡1 2600 cm¡1 2633/678 cm¡1 2727/731 cm¡1 2761 cm¡1 2765/66/69/99 cm¡1 2800 cm¡1 2800–3000 cm¡1 2800–3100 cm¡1 2800–3500 cm¡1 2802/12/20/21/4/ 34 cm¡1 2834 cm¡1 2836 cm¡1 2838 cm¡1 2846 cm¡1 2848 cm¡1 2849 cm¡1 2850 cm¡1

2851 cm¡1

2852 cm¡1 2853 cm¡1

2854 cm¡1 2855 cm¡1 2860 cm¡1 2862 2865 cm¡1 2869 cm¡1 2870 cm¡1 2871 cm¡1 2874 cm¡1 2875 cm¡1 2884/85 cm¡1 2886/7/8/9/90 cm¡1

Assignment Ester group (C D O) vibration of triglycerides n(C D O) (polysaccharides, pectin) n(C D C) lipids, fatty acids The band of second order

Ref. no. (131) (129) (129) (73)

A combination of hindered rotation and O H bending (water) H-bonded NH vibration band Stretching N H (NH3C) Stretching N H (NH3C) CH3 modes Stretching N H (NH3C) Stretching N H (NH3C) C–H Lipid region CH3, CH2-lipid and protein C H stretching vibrations of methyl (CH3) and methylene (CH2) groups and olefins Cholesterol, phospholipids and creatine (higher in normal tissues) Stretching vibrations of CH2 and CH3 of phospholipids, cholesterol and creatine Stretching N H (NH3C)

(23) (108) (73) (73) (25) (73) (73) (90) (23), (88) (74) (131)

Symmetric stretching of methoxy (1) Stretching N H (NH3C) Stretching C–H Symmetric stretching of methoxy (3) Symmetric stretching of methoxy (4) Cholesterol, phospholipids and creatine (higher in normal tissues) Stretching vibrations of CH2 and CH3 of phospholipids, cholesterol and creatine Stretching C–H C H stretching bands Stretching C–H ns CH2, lipids, fatty acids CH2 symmetric Symmetric CH2 stretch CH2 symmetric stretching: mainly lipids, with the little contribution from proteins, carbohydrates, nucleic acids Fatty acids ns CH2 Symmetric stretching vibration of CH2 of acyl chains (lipids) ns CH2 of lipids Asymmetric CH2 stretching mode of the methylene chains in membrane lipids nC–H CH2 symmetric stretching ns CH2 of lipids Stretching C–H Fatty acids Aliphatic C H stretching Antisymmetric and symmetric stretching of CH3 CH3 symmetric stretching: protein side chains, lipids, with some contribution from carbohydrates and nucleic acids CH3 symmetric stretching ns CH3 Stretching C–H, N–H Symmetric stretching vibration of CH3 of acyl chains (lipids) CH3 symmetric stretching Stretching C–H Stretching C–H

(124) (73) (73) (124) (124) (105) (105)

(105) (105) (73)

(73) (131) (73) (129) (81) (73) (53) (56) (90) (23) (33) (33) (71) (39) (40) (73) (56) (54) (45) (53) (81) (90) (124) (23) (39) (124) (124) (Continued on next page)


473

Table 1. (Continued). FTIR peak 2893/4/6 cm¡1 2916 cm¡1 2917/8/9 cm¡1 2917 cm¡1 2921 cm¡1 2922 cm¡1 2923–33 cm¡1 2923/5 cm¡1 2924 2925 cm¡1 2926 cm¡1 2928 cm¡1 2930 cm¡1 2931 cm¡1 2947/8 cm¡1 2951 cm¡1 2952 cm¡1 2951/3/5/6 cm¡1 2954 cm¡1 2956 cm¡1 2958 cm¡1 2959 cm¡1

2960 cm¡1 2962 cm¡1 2963 cm¡1 2965 cm¡1 2970 cm¡1 2975 cm¡1 2984 cm¡1 2993/4 cm¡1 2994 cm¡1 2998/9 cm¡1 3000 cm¡1 3000–600 cm¡1 3000–700 cm¡1 3007 cm¡1 3007–10 cm¡1 3008 cm¡1

3012 cm¡1 3015 cm¡1 3015/17/20 cm¡1

Assignment

Ref. no.

CH3 symmetric stretch Cholesterol, phospholipids and creatine (higher in normal tissues) Stretching vibrations of CH2 and CH3 of phospholipids, cholesterol and creatine Stretching C–H Cholesterol ester CH2 asymmetric stretching: mainly lipids, with the little contribution from proteins, carbohydrates, nucleic acids nas CH2 Asymmetric stretching vibration of CH2 of acyl chains (lipids) C H stretching bands in malignant tissues Stretching C–H Fatty acids CH2 asymmetric C H stretching bands in normal tissues nas CH2 lipids nas CH3 lipids Aromatic C H stretching nC–H Stretching C–H C H stretching bands nas CH2 Stretching C–H Stretching C–H Stretching C–H CH3 asymmetric stretch Stretching C–H Antisymmetric and symmetric stretching of CH3 Asymmetric stretching vibration of CH3 of acyl chains (lipids) CH3 asymmetric stretching: lipids, protein side chains, with some contribution from carbohydrates and nucleic acids C H stretching nas CH3 of lipids, DNA and proteins Asymmetric stretching mode of the methyl groups from cellular proteins, nucleic acids and lipids nas CH3 CH3 asymmetric stretching CH3 modes Stretching C–H nas CH3, lipids, fatty acids Stretching N–H, stretching C–H CHa,a’ stretch C H ring CHa,a’ stretch C H ring C H ring CH stretching vibrations (remain unaltered by the methoxy and hydroxyl substitution) N H stretching O H stretching (water) C–H D C H groups that are related to olefins bands or unsaturated fatty acids (absent in cancer samples) C H ring nas ( D C–H), lipids, fatty acids Olefinic D CH stretching vibration: unsaturated lipids, cholesterol esters n D CH n D CH of lipids CH2, aromatic stretch

(135) (105) (105) (73) (79) (53), (81) (76) (23) (131) (73) (56) (38) (131) (33) (40) (54) (71) (73) (131) (44) (79) (73) (73) (135) (73) (45) (23), (81) (53) (131) (33), (76) (33) (90) (39) (25) (73) (129) (73) (124) (73) (124) (73) (73) (124) (49) (23) (131) (131) (73) (129) (53) (76) (33) (124) (Continued on next page)

474


Table 1. (Continued). FTIR peak 3021/2 cm¡1 3023 cm¡1 3050 cm¡1 3059 cm¡1 3064 cm¡1 3070 cm¡1 3072/4 cm¡1 3074 cm¡1 3075 cm¡1 3078 cm¡1 3110–3532 cm¡1 3111/4/6 cm¡1 3163/82 cm¡1 3190 cm¡1 3194/5/7/9/ 200 cm¡1 3200–550 cm¡1 3201 cm¡1 3216/17/26 cm¡1 3273/87/89 cm¡1 3280 cm¡1 3283 cm¡1 3292 cm¡1 3293 cm¡1 3295 cm¡1 3300 cm¡1 3301 cm¡1 3313 cm¡1 3320 cm¡1 3327 cm¡1 3328 cm¡1 3330/5/7/9/43 cm¡1 3350 cm¡1 3353 cm¡1 3354 cm¡1 3359 cm¡1 3362 cm¡1 3396 cm¡1 3401 cm¡1 3410/16/20/22 cm¡1 3430 cm¡1 3435/442 cm¡1 3500–600 cm¡1 3506 cm¡1 3524/28/42 cm¡1 3561 cm¡1 3570/77/78/82/90/ 9 cm¡1 3611 cm¡1

Assignment

Ref. no.

C H ring Aromatic CH stretching Amid B (N H stretching) N H stretching of amide B C2C–H2 aromatic stretching Fermi-enhanced overtone of the amide II band (at 1550 cm¡1) C H ring v CH3 symmetric CH stretching band of the phenyl rings C2C–H2 aromatic stretching Amide B bands stemming from N H stretching modes in proteins and nucleic acids C H ring free O H stretching and N H stretching with hydrogen bonded secondary amino groups C H ring Stretching N H symmetric N H stretching bands of mainly cis-ordered substructures Stretching N H symmetric

(73) (54) (90) (45) (124) (49) (73) (56) (124) (124) (73)

Symmetric and asymmetric vibrations attributed to water. So, it would be better not to consider this region for detailed analysis Stretching N H symmetric Stretching O H symmetric Stretching O H symmetric v O–H(water), vN H (protein) N H stretching of amide A and O H stretching of carbohydrates N H stretching (amide A) OH stretching (associated) Amid A (N H stretching) Amide A bands stemming from N H stretching modes in proteins and nucleic acids N H stretching (amide A) Amide A band Amide A band NH band Stretching N H asymmetric Amide A band Stretching N H asymmetric O–H, N–H, C–H Stretching N H asymmetric O–H, N–H, C–H Stretching N H asymmetric O–H, N–H, C–H O–H, N–H, C–H Stretching O H asymmetric O H and N H stretching vibrations (hydrogen bonding network may vary in the malignant tissues) Stretching O H asymmetric N H stretching bands of mainly trans-ordered substructures Stretching O H asymmetric OH bonds OH stretching (free) Stretching O–H OH stretching (free) Stretching O–H

(105)

O

H and N H stretching vibrations (hydrogen-bonding network may vary in the malignant tissues)

(73) (54) (73) (73) (49) (73)

(73) (73) (73) (40) (45) (39) (124) (90) (49) (39) (44) (44) (108) (73) (44) (73) (108) (73) (108) (73) (108) (108) (73) (131) (73) (49) (73) (108) (120) (73) (124) (73) (131)


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are relatively narrow, and in many cases can be associated with the vibration of a particular chemical bond (or a single functional group) in the molecule (18, 19). A detailed definition of Raman spectroscopy and its application in biological studies has been presented (20). Although Raman spectroscopy and FTIR are relevant techniques, with their respective spectra complementary to one another, there are some differences between them. Probably the most important difference is the type of samples, which can be investigated by each of these methods. FTIR mainly deals with non-aqueous samples, while Raman is as effective with aqueous samples as it is with non-aqueous ones. This is because of the problem mostly taken place with FTIR spectroscopy, which is due to strong absorption bands of water (21–23). In Raman, however, fluorescence and strong effect of glass (mostly as containers) are the most significant problems being faced during analysis. Raman requires minimal sample preparation and can do confocal imaging, whereas, FTIR requires comparatively more sample preparation and does not have the ability of confocal imaging. Furthermore, the physical effect of infrared is created by absorption, and mainly influences the dipole and ionic bands such as O–H, N–H, and CHO. Raman effect originates from scattering (emission of scattered light) and changing of the polarizability of covalent bands like CHC, C S, S S, and aromatics. In other words, FTIR spectroscopy is due to changes in dipole moment during molecular vibration, whereas Raman spectroscopy involves a change in polarizability (24). Another difference existing between these 2 techniques is their resolution. While Raman has lateral resolution of 1–2 mm and confocal resolution of 2.5 mm, FTIR does not provide the possibility of confocal resolution, and its lateral resolution is 10– 20 mm (25). FTIR spectroscopy and biological research A wide range of biological studies has been covered by FTIR analysis. These studies include Cervix [26–41], lung [42–48], breast [23, 49–56], skin [57–64], gastro-intestinal tissue [65– 71], brain [72–81], oral tissue [82, 83], lymphoid tissue [84], lymphocytes (Childhood Leukemia) [85–87], non-Hodgkin’s lymphoma [88], prostate [89–94], colon [95–103], bladder [104] fibroblasts [105], bacteria [106, 107], tumor cells [108, 109], DNA [110], anticancer drug [111, 112], tissue processing [113], cancer detection [114], tissue preservation [115], cytotoxicity and heating [116], plant tissue [117], gallstones [118], glucose measurement [119], bone [120, 121], DNA [122], and myocardial infarction [123]. This part of this article presents a brief summary of experimental procedure that has been applied by different research groups. It is believed that knowing what has been considered in Materials and Methods of different studies can lead to a better understanding of peak definitions obtained. Wood et al. have reported on FTIR spectroscopy as a biodiagnostic tool for cervical cancer. The spectra of normal epithelial cells illustrated intense glycogen bands at 1022 cm¡1 and 1150 cm¡1, and a pronounced symmetric phosphate stretch at 1078 cm¡1. The spectral features suggestive of dysplastic or malignant transformations were mainly indicating symmetric and asymmetric phosphate modes and a reduction in the glycogen band intensity. This study demonstrated the potential of the automated FTIR cervical screening technology in the clinical environment (26). Chiriboga et al. reported on the differentiation and maturation of the epithelial cells in the human cervix using infrared spectroscopy. Different layers of human cervical squamous tissue, representing different cellular maturation stages, exhibited quite dissimilar spectral

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patterns. Thus, it was concluded that this technique represents a powerful tool to monitor cell maturation and differentiation. In addition, a proper interpretation of the state of health of cells exfoliated from such tissues would be obtained through a detailed understanding of the spectra of the individual layers (27). Wood et al. carried out a FTIR microspectroscopic investigation of cell types and potential confounding variables in screening for cervical malignancies. The aim of the study was to determine the effectiveness of infrared spectroscopy in the diagnosis of cervical cancer and dysplasia. It was found that leukocytes, and in particular lymphocytes, have spectral features in the phosphodiester region (1300–900 cm¡1), suggestive of changes indicative of malignancy. The use of ethanol as a fixative and dehydrating agent resulted in retention of glycogen and thus minimizing the spectral changes in the glycogen region due to sampling technique. Erythrocyte spectra exhibited a reduction in glycogen band intensity, but could be discerned by a relatively low intensity ns PO2¡ band. Endocervical mucin spectra exhibited a reduction of glycogen band and a very pronounced ns PO2¡ band, which was similar in intensity to the corresponding band in HeLa ns PO2¡ cells (28). Sindhuphak et al. screened cervical cell samples of Thai women by using FTIR spectroscopy. Data collected was related to the histological diagnosis. Two hundred and seventy-five cervical cell specimens were received from patients undergoing hysterectomy. Histological examinations showed 108 normal cases and 167 abnormal cases. When compared to the histology data, FTIR results showed a sensitivity of 96.3% and specificity of 96.4%. False negative and false positive rates were 3.7% and 3.6%, respectively (29). Mordechai et al. conducted a study on formalin-fixed melanoma and cervical cancer by FTIR microspectroscopy (FTIR-MSP). The aim of this study was to detect common biomarkers, which occur in both types of cancer, distinguishing them from the respective nonmalignant tissues. The spectra were analyzed for changes in levels of biomolecules such as RNA, DNA, phosphates, and carbohydrates. Whereas, carbohydrate levels showed a good diagnostic potential for detection of cervical cancer, this was not the case for melanoma. However, variation of the RNA/DNA ratio as measured at 1121/1020 cm¡1 showed similar trends between non-malignant and malignant tissues. The ratio was higher for malignant tissues in both types of cancer (30). Chiriboga et al. carried out a comparative study between the spectra collected from biopsies of exfoliated cervical cells and cervical squamous epithelium using infrared spectroscopy. A comparison of infrared absorption spectra obtained from the different layers of squamous epithelium from the human cervix, and infrared spectra obtained from exfoliated cervical cells was done. It was shown that the technique is a sensitive tool to monitor maturation and differentiation of human cervical cells. Therefore, it was concluded that this spectroscopic method provides new insights into the composition and state of health of exfoliated cells (31). Wong carried out a research on exfoliated cells and tissues from human endocervix and ectocervix by FTIR and ATR/FTIR spectroscopy. They measured the transmission infrared spectra of exfoliated endocervical mucin-producing columnar epithelial cells and the attenuated total reflectance (ATR) infrared spectra of the single-columnar cell layer on the endocervical tissues. All the data collected was compared with the corresponding infrared spectra of ectocervical squamous cells and squamous epithelium. The effects of the contaminated connective tissue on the infrared spectra of the endocervical columnar epithelial tissue demonstrated that ATR/FTIR is a more desirable method in order to obtain meaningful and


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good-quality infrared spectra of tissue samples. This specially applies for samples consisting of thin layers of different types of tissues. Substantial differences in the infrared spectra between the columnar cells and squamous cells on the endocervical and ectocervical tissues, respectively, were evident. The strong glycogen bands in the infrared spectrum of the ectocervical squamous cells were absent in the spectrum of endocervical columnar cells. These spectral changes were similar to those observed in malignant squamous cells. Therefore, if the decrease in the intensity of the glycogen bands were used as the only criterion for determining cellular abnormalities in the cervix, the presence of a large number of normal endocervical columnar cells in the cervical specimen would lead to a false result. Consequently, it was concluded that in addition to the glycogen bands, other features in the infrared spectra should be considered for evaluation of abnormalities in exfoliated cervical epithelial cells (32). A pressure-tuning FTIR spectroscopic study of carcinogenesis in human endometrium was reported by Fung et al. The spectra of normal tissues differed from those obtained from grade I and grade III adenocarcinoma. Changes in the spectra of malignant samples were observed in the symmetric and asymmetric stretching bands of the phosphodiester backbones of nucleic acids, the CH stretching region, the C–O stretching bands reflecting the C– OH groups of carbohydrates and cellular protein residuals, and last but not least, the pressure dependence of the CH2 stretching mode. All these spectral changes in the endometrium were reproducible. It was also found for the first time that the epithelium in the normal endometrium exhibits unique structural properties compared with the epithelium of other normal human tissues (33). Wong et al. has reported for the first time that FTIR could be used to differentiate between normal and malignant tissue of the cervix. The aim of this study was mass screening and few other groups have demonstrated that FTIR could be used for diagnosis as well as exemplifying molecular abnormalities during disease progression. Fung et al. found that FTIR has provided better results than standard Pap smear in terms of false negative rate and negative predicted value (34). Chang et al. demonstrated that precancerous tissues could be differentiated from normal tissue of the uterine based on 2 spectral regions between 1130– 1180 cm¡1 and 1180–1260 cm¡1(35). Mordechai et al. reported that glycogen levels could be used as prospective biomarkers in cervical cancer detection. This study has been used formalin-fixed cervical tissues and it has been a matter of debate (36). Walsh et al. recorded that ATR-FTIR associated with PCA and LDA has identified phosphate and glycogen as potential markers in the spectral region of 950–1200 cm¡1 (37). Ostrowska et al. reported that FTIR could be used in cervical cancer detection based on human papillomavirus (HPV) copy number and its dependent biomarker protein p16INK4A expression. This study has used 4 cervical cell lines starting with negative to positive number of HPV copies per cell. The nuclear and cytoplasmic regions have similar FTIR bands for all cell lines. However, spectral signatures have revealed that relative intensities of peaks related to vibrations of cellular components have varied among cell lines. Nucleic acid levels were increased with the increasing number of HPV copies, contrary to this, lipid levels were decreased as the number of HPV copies increased and no changes in the protein levels with irrespective of HPV copy number were reported. This study has shown that lipids and RNA levels signatures can be used to differentiate between normal and cancer cell lines. In addition, PCA analysis demonstrated that spectral analysis clearly differentiate the nuclear and cytoplasmic characteristic signals, and additionally discriminate the cell lines (38).

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Liu et al. demonstrated that FTIR could be used to differentiate between thyroid cancer and benign thyroid lesions. This aim was achieved by using cervical metastatic and non-metastatic tissues and using ATR probe to get spectra in the range of 1000 to 4000 cm¡1 scanned freshly removed metastatic lymph nodes. Spectral signatures have shown considerable differences between metastatic and non-metastatic nodes. The lipids at 1400 cm¡1, nucleic acids at 1240 cm¡1, and nitrogen-containing molecules at 3280 cm¡1, 1640 cm¡1, and 1546 cm¡1 have significantly increased in metastatic groups. On the other side, the lipids at 2925 cm¡1, 2855 cm¡1, and 1743 cm¡1 and carbohydrates at 1165 cm¡1 have decreased profoundly. In addition, the metastatic and non-metastatic nodes were differentiated by peak position and FWHM (39). Schubert et al. used Spectral Cytopathology (SCP) and infrared microspectroscopy, combined with a multivariate method of analysis (PCA), to identify molecular alterations in the nucleus and the cytoplasm of cervical samples. The advantage of this study is to identify chemical changes that were not observed by the cytopathologists because these alterations have not caused any morphological changes. Spectral analysis has been achieved in between 3100–2800 cm¡1 and 1700–1200 cm¡1. The aim behind to choose range from 1700– 1200 cm¡1 is completely devoid of glycogen distribution. The 2 prominent peaks of proteins were observed at 1650 cm¡1 (amide I, C D O stretching) and 1550 cm¡1 (amide II, C–N stretching, and N–H deformation). Nucleic acids (DNA and RNA), phosphates, and phospholipids were absorbed at the band region between 1480 and 1200 cm¡1. Additionally to this, C–H stretching vibrations were found at 3100–2800 cm¡1 mainly caused by lipids and phospholipids. PCA-based scores have blindly discriminated between cells from normal samples and morphologically normal looking cells from abnormal samples. This technique has differentiated several indistinguishable cervical samples with high specificity and sensitivity (40). Wang et al. focused on the microscopic FTIR studies of lung cancer cells in pleural fluid. The results demonstrated significant spectral differences between normal, lung cancer, and tuberculosis cells. The most considerable differences were in the ratio of peak intensities of 1030 and 1080 cm¡1 bands (originated mainly in glycogen and phosphodiester groups of nucleic acids). One of the important advantages of this method was the possibility of obtaining quick and reliable results (41). The research of Yano et al. was about direct measurements of human lung cancerous and non-cancerous tissues by FTIR microscopy. The aim of this study was to answer the question of whether this technique can be used as a clinical tool or not. The corrected peak heights (H1045 and H1467) obtained from the bands at 1045 cm¡1 and 1465 cm¡1, which are due to glycogen and cholesterol were chosen for a quantitative evaluation of the malignancy. It was concluded that these peaks are an exceptionally useful factor for discrimination of the cancerous tissues from the non-cancerous ones. If the H1045/ H1467 ratio from measured spectrum is larger than 1.4, it could be said with confidence that the tissue contains squamous cell carcinoma (SCC) or adenocarcinoma at least partially. Furthermore, they carried out the microscopic mapping of the tissues containing both cancerous and non-cancerous sections, demonstrating that the color map reflects small changes in the spatial distribution of cancer cells in the tissues (42). Yang et al. reported on tumor cell invasion by FTIR microspectroscopy. In this study, a 3D artificial membrane using collagen type I–one of the main components of basal membranes of the lung tissue–was established in order to investigate tumor cell


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invasion of lung cancer. The mapping images obtained with FTIR microspectroscopy were validated with standard histological section analysis. The FTIR image produced using a single wavenumber at 1080 cm¡1, corresponding to PO2¡ groups in DNA from cells, correlated well with the histological section, which clearly revealed a cell layer and invading cells within the membrane. Furthermore, peaks corresponding to amide I and amide II in the spectra of invading cells shifted comparably to the noninvading cells, which may relate to the changes in conformation and/or heterogeneity in the phenotype of the cells. The data presented in this study demonstrate that FTIR microspectroscopy can be a fast and reliable technique to assess tumor invasion in vitro (43). Wang et al. reported that FTIR microscope equipped with focal plane array (FPA) was used to detect chemical changes between nucleus and endoplasmic reticulum (ER) of single human gastric adenocarcinoma BGC823 cell line. The most intense absorption observed in the ER, around 1738 cm¡1, is due to C D O stretching of lipid esters. In nucleus, the most intense absorptions were identified at 1644 cm¡1 due to amide I, 1539 cm¡1 due to amide II, and 1088 cm¡1 due to symmetric stretching of PO2 group of nucleic acids. The peaks’ shifts were clearly noticed in the average spectra of nucleus and ER. The band at 1232 cm¡1 in the ER is shifted to 1244 cm¡1 in nucleus and this is due to changes of hydrogen bonds in DNA molecules. The ratio of H2954/H2922 has suggested that lipids in the nucleus were more CH3 relative than CH2 when compared to ER (44). Lee et al. demonstrated that ATR-FTIR technology could be useful in detecting structural and intracellular alterations in normal and lung cancer cells. In this study, NCI-H358 lung cancer cells and NHBE normal lung cells were analyzed under FITR and the spectra were acquired at a 4 cm¡1 resolution, 128 scans, and in the 1000–3500 cm¡1 spectral range. The most intense band was at amide I (1650 cm¡1) in normal cells, which corresponds to the C D O stretching vibration of the peptide backbone. The next intense band was amide II, centered at 1550 cm¡1, and corresponding to C–N stretching and N–H group in-plane bending. The other dominant absorption modes were CH3 in-plane bending vibrations (1460 and 1400 cm¡1), PO2¡ group stretching modes (1235 and 1085 cm¡1), and PO32¡ group vibration (970 cm¡1). The spectra of lung cancer cell line was dominated by 2 bands (970 and 1085 cm¡1), assigned to the vs (PO32¡) and vs (PO2¡) vibrations as compared to normal cells. This may be credited to structural modifications in DNA especially greater phosphorylation of the cancerous cells. These 2 bands could be considered as useful markers for discrimination of lung cancer cells from normal cells. Furthermore, the intensity ratios of vs (PO32¡)/amide I or vs (PO2¡)/amide I could be used as successful spectral markers in lung cancer discrimination (45). Pijanka et al. reported that synchrotron (S)-based infrared technology could be applied on diagnosis of lung disease using stained epithelial cells. This study has used H&E and pap staining cells and their effect on FTIR spectra. S-FTIR technology was applied on both preand post-staining cells. H&E and pap staining procedures have produced decreased intensity alterations in the lipids region and fingerprint region of normal and cancerous cell lines. The usage ethanol step in the staining procedure has diminished the intensity of CH2 stretching vibrations at 2920 and 2850 cm¡1 of the methylene groups in the membrane lipids and C D O stretching vibration at 1740 cm¡1 mode of phospholipids. In addition to this, stained cells have shown amide III peak shifts from 1530 cm¡1 to 1513 cm¡1. PCA was performed on

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stained cell spectral data and different clustering was clearer in Pap staining compared to H&E staining (46). Lewis et al. demonstrated that FTIR mid-infrared spectroscopy could be useful in lung cancer detection using sputum. FTIR spectra were collected from 25 lung cancerous and healthy controls. Spectral bands in the region of 1800 to 950 cm¡1 reflected a vibration from the following groups: PO4¡ stretch and C–C stretch (964 cm¡1), C–O stretch and C–O bend (1024 cm¡1 and 1049 cm¡1), COO– stretch and C–H bend (1411 cm¡1), and last but not least amide I (1656 cm¡1) and amide II (1577 cm¡1). These bands have significantly shifted in normal to cancerous cells. In addition to these peak shifts, glycogen peaks such as 1024¡1 and 1049 cm¡1 were more effectively differed from normal to cancerous samples than the rest. Furthermore, a combination of hierarchical cluster analysis (HCA) and PCA discriminated from normal to cancerous samples and HCA dendrogram has suggested that Raman peak numbers could play vital role in high diagnostic accuracy of disease (47). Eckel et al. analyzed the IR spectra of normal, hyperplasia, fibroadenoma, and carcinoma tissues of human breast. They worked on characteristic spectroscopic patterns in the proteins bands of the tissue. Some of the results of their experiments are as follows: (A) In carcinomatous tissues the bands in the region of 3000–3600 cm¡1 shifted to lower frequencies. (B) The 3300 cm¡1/3075 cm¡1 absorbance ratio was significantly higher for the fibroadenoma. (C) For the malignant tissues, the frequency of a-helix amide I band decreased, while the corresponding b-sheet amide I band frequency increased. (D) The 1657 cm¡1/ 1635 cm¡1 and 1553 cm¡1/1540 cm¡1 absorbance ratios were the highest for fibroadenoma and carcinoma. (E) The 1680 cm¡1/1657 cm¡1 absorbance ratio decreased significantly in the order of normal, hyperplasia, fibroadenoma, and carcinoma. (F) The 1651 cm¡1/ 1545 cm¡1 absorbance ratio increased slightly for fibroadenoma and carcinoma. (G) The bands at 1204 cm¡1 and 1278 cm¡1, assigned to the vibrational modes of the collagen, did not appear in the original spectra as the resolved peaks and were distinctly stronger for the carcinoma tissues. (H) The 1657 cm¡1/1204 cm¡1 and 1657 cm¡1/1278 cm¡1 absorbance ratios, both yielding information on the relative content of collagen increased in the order of normal, hyperplasia, carcinoma, and fibroadenoma (48). Verdonck et al. used FTIR imaging to characterize different types of breast tumor cells and hence be able to discriminate them from normal breast cells. Nineteen breast cancer tissue samples were analyzed in this experiment and mainly 6 different types of cells were distinguished according to the spectral features. To obtain a spectral profile for each cell type, cells were first identified in the H&E staining sample and then used as a reference to localize them in the unstained sample used in FTIR. Once all data was collected, it was analyzed with PCA aiming to discriminate one group from the other. Results showed that In PC1, the highest variance (62.8%) was seen in the protein region (1700–1500 cm¡1) mainly reflecting a difference in the secondary structure of proteins. This variance leads to the separation of the spectral data of both the connective tissue and vascular tissue from the rest of the spectra. PC2, in the other hand, reflected a variance in the nucleic acid region leading to the significant discrimination of the erythrocyte spectra. As indicated by the score plot, the 3 main principal components were able to clearly separate each group of cells according to the variables found in the spectral data (49). The main focus area of the comparative infrared spectroscopic study of Fabian et al. was on human breast tumors, human breast tumor cell lines, and xenografted human tumor cells. The results indicated that substantial differences exist on a macroscopic


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level between the tumors, tumor cell lines, and xenografted tumor cells, which are related to the presence of a significant connective tissue matrix in the tumors. On a macroscopic level, tumor cell xenografts appear—in spectroscopic terms—to be relatively homogenous with a relatively weak signature characteristic of connective tissue. Differences on a microscopic level between adjacent small areas (30 mm2) of the same xenografted tumor could be detected, which were due to local variations in collagen content. In addition to variations in collagen content, variations in the deposition of microscopic fat droplets throughout both human and xenografted tumors could be detected. The results indicated the care with which infrared spectroscopic studies of tissues must be carried out to avoid incorrect interpretation of results due to an incomplete understanding of tissue pathology (23). Ozek et al. demonstrated that ATR-FTIR could be used to illustrate a tumor suppressor in MCF breast cancer cells. The miR-125b precursor was cloned and transfected into MCF cells. Both MCF7-125b cells and MCF-EV cells (empty vector) were analyzed by ATR-FTIR spectroscopy. The decrease in lipid content (3050–2800 cm¡1) in MCF-125b is indicating reduction in the concentration of saturated and unsaturated bonds in lipid structures due to lipid peroxidation. This result was supported by CH2 scissoring mode of lipids (1468 cm¡1) and COO¡ symmetric stretching of fatty acids (1400 cm¡1). FTIR results revealed a decrease in protein content as well as RNA content in MCF-125b cells. Substantial increase in glycogen (1045 cm¡1)/phosphate (1084 cm¡1) ratio was observed in mir-125b cells due to low metabolic activity whereas this ratio was decreased in MCF-EV cells. The ratio of RNA (1121cm¡1)/DNA (1020cm¡1) was significantly decreased in mir-125b cells due to decrease in the transcriptional activity of transfected cells, hence less proliferation. Furthermore, cluster analysis has clearly differentiated the MCF-EV and mir-125b cells based on ATR-FTIR spectral signatures (50). Tiwari et al. reported that FTIR coupled with electrochemical biosensor could be used for breast cancer detection. In this study, biosensor was made up of chitosan–co-polyaniline (CHIT–co-PANI) and it is coated in indium-tin-oxide (ITO). This sensor was immobilized with 40 bases length of complementary DNA (cDNA), which is associated with breast cancer susceptible gene BRCA1. Breast cancer tissues, which were stored in liquid nitrogen has been used for mRNA extractions. Additionally, cDNA was prepared and hybridized on to CHIT– co-PANI/ITO electrode. The FTIR spectrum of this biosensor has shown O–H stretching and N–H stretching at 3100–3532 cm¡1, C–N stretching at 1248 cm¡1, C D C stretching of quinoid rings at 1588 cm¡1, C D C stretching vibrations of benzoid rings at 1489 cm¡1, C D O stretching of carbonyl group at 1636 cm¡1, aromatic C–H stretching at 3023 cm¡1, and aliphatic C–H stretching at 2926 and 2865 cm¡1. FTIR results have matched the cDNA composition of the biosensor and the band at 1226 cm¡1 has confirmed phosphate vibration. Finally, the band at region 3105–3364 cm¡1 is due to N–H stretching vibration and the band at region 2922–2863 cm¡1 and 1632–1668 cm¡1 is due to attachment of cDNA with the biosensor (51). Rehman et al. reported that FTIR-ATR microspectroscopy could be used in differentiating between low nuclear grade (LNG), intermediate nuclear grade (ING), and high nuclear grade (HNG) of ductal carcinoma in situ (DCIS) and grade I, II, and III of invasive ductal carcinoma (IDC). The intensity of C–H and N–H bands in the region of 3500–3200 cm¡1 decreases when increasing the grade of LNG to HNG. The absolute intensity has increased in the region of 3000–2800 cm¡1 as it increased in the concentrations of proteins, nucleic

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acids, and lipids. The relative intensities of vs CH3 of lipids, DNA, proteins, and stretching vibrations of CH2 and CH3 of phospholipids (2960–2922 cm¡1) have observed highest in HNG and lowest in LNG. Spectral signatures have revealed that HNG, ING, and LNG were predominated by lipid/acylglyceride, lipid/acylglyceride/protein, and protein, respectively. The significant differences were observed in the IDC grades (I, II, and III) at 1080– 1030 cm¡1. This is due to v1CO32¡, v3 PO43¡, v(C–C) skeletal of acyl backbone of lipids, vPO2¡) symmetric stretching of phosphodiester in nucleic acids, and d (C–H) and phenylalanine of collagen. The band centered at 1029 cm¡1 increases in absorbance with the increasing grade I to III and new bands has emerged at 1055 cm¡1 with the increasing grade I to III as well. The new group of peaks has appeared at 997, 890, and 765 cm¡1 and constantly increased as the cancer advances from grade I to III (52). Mostaco-Guidolin et al. demonstrated that FTIR could be used to differentiate breast cancer cells based on oestrogen receptor expression. MCF-7 (oestrogen receptor positive ER C) and SKBr3 (estrogen receptor negative ER ¡) were analyzed in this study. The spectral data of both cell lines have shown predominant bands at 1640 cm¡1 (amide I) and 1540 cm¡1 (amide II). Based on the second derivative spectra of the both cell lines, peak shifts were observed in the area of 1122 cm¡1 (RNA), 1397 cm¡1 (CH3 from proteins and lipids), 1651 cm¡1 (amide I), 2851 cm¡1 (fatty acids), and 2962 cm¡1 (stretching of fatty acids). The key differences were observed in the intensity of C–OH stretching (1087 cm¡1), CH3 stretching (1397cm¡1), amide II stretching (1543 cm¡1), amide I-b sheet (1651 cm¡1), and fatty acid stretching (2924 cm¡1). According to Pollock theory, binding of estrogen to its receptor stimulates proliferation of mammary cells, thus enhancing cell division and replication. This was proved by the FTIR spectral data. MCF-7 cells have shown twice absorbance intensity in the region of DNA (1085 cm¡1), amide II (1542 cm¡1), and amide I (1650 cm¡1) compared to SKBr3 cells. SKBr3 cells have shown larger band area (2924 and 2962 cm¡1) of lipids compared to MCF-7 cells due to increased choK (phosphocholine) expression. Significant statistical differences (p < 0.05) were observed in average of amide I/amide II, RNA/DNA, amide I/DNA, and amide I/ lipids (53). The study of Sukuta and Bruch was on factor analysis of cancer FTIR Evanescent Wave Fiberoptical (FTIR-FEW) spectra. The purpose of the research was to isolate pure biochemical compounds and spectra and to classify skin cancer tumors. Apart from fulfilling the primary goals, it was demonstrated that the combination of FTIR-FEW technique and chemical factor analysis has the potential of a clinical diagnostic tool (54). Wong et al. applied infrared spectroscopy combined with high pressure (pressure-tuning infrared spectroscopy) for studying the paired sections of basal cell carcinomas (BCC) and normal skin from ten patients. In this study, atmospheric pressure IR spectra from BCC were dramatically different from those from the corresponding normal skin. Compared to their normal controls, BCCs displayed increased hydrogen bonding of the phosphodiester group of nucleic acids, decreased hydrogen bonding of the C–OH groups of proteins, increased intensity of the band at 972 cm¡1, a decreased intensity ratio between the CH3 stretching and CH2 stretching bands, and accumulation of unidentified carbohydrates (55). Lucassen et al. used ATR-FTIR spectroscopy to measure hydration of the stratum corneum. It was believed that the determination of the hydration state of the skin is necessary to obtain basic knowledge about the penetration and loss of water in the skin stratum corneum. In this study, direct band fitting of the water bending combination, and OH stretch bands over the 4000–650 cm¡1 wavenumber range were applied. Separate band fits of water,


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normal stratum corneum, and occluded hydrated stratum corneum spectra were obtained yielding band parameters of the individual water contributions in the bending mode at 1640 cm¡1, the combination band at 2125 cm¡1, and the OH stretches in the hydrated skin stratum corneum spectra. They concluded that band fit analysis of hydrated skin stratum corneum ATR-FTIR spectra offers the possibility for quantitative determination of individual water band parameters (56). McIntosh et al. used infrared spectroscopy to examine BCC to explore distinctive characteristics of BCC versus normal skin samples and other skin neoplasms. Spectra of epidermis, tumor, follicle sheath, and dermis were acquired from unstained frozen sections and analyzed qualitatively by t-tests and by linear discriminant analyses. Dermal spectra were significantly different from the other skin components mainly due to absorptions from collagen in dermis. Spectra of normal epidermis and BCC were significantly different by virtue of subtle differences in protein structure and nucleic acid content. Linear discriminant analysis (LDA) characterized spectra as arising from BCC, epidermis, or follicle sheath with 98.7% accuracy. Use of LDA accurately classified spectra as arising from epidermis overlying BCC versus epidermis overlying non-tumor-bearing skin in 98% of cases. Spectra of BCC, SCC, nevi, and malignant melanoma were qualitatively similar. Distinction of BCC, SCC, and melanocytic lesions by linear discriminant analyses, however, was 93.5% accurate. Therefore, spectral separation of abnormal versus normal tissue was achieved with high sensitivity and specificity (57). Barry et al. recorded Fourier transform (FT) Raman and infrared spectra of the outermost layer of human skin, the stratum corneum. Assignments consistent with the FT Raman vibrations were made for the first time and compared with assignments from the FTIR spectrum. The results demonstrated that FT Raman spectroscopy holds several advantages over FTIR in studies of human skin. The molecular and conformational nature of human skin, and modifications induced by drug or chemical treatments, may be assessed by FT Raman spectroscopy (58). Hammody et al. employed FTIR microscopy to discriminate between malignant melanoma and normal epidermis. Chemometric approaches such as 2-population t-test, Gaussian distribution, and discriminant classification function (DCF) analysis were used to develop diagnostic algorithm. FTIR spectra were collected from patient biopsies and significant peak shifts were observed in malignant skin compared to normal epidermis. Amide I and PO2 stretching bands were shifted due to biochemical changes in proteins and nucleic acid, respectively. This study has shown sensitivity of 86% and specificity of 83% in disease diagnosis and it is better than current clinical diagnostic accuracy (59). Tosi et al. reported that FTIR microspectroscopy could be applied in distinguishing normal, benign, and malignant melanomas using metabolic analysis of skin tissues. This study has used paraffin-embedded tissue biopsies of different disease grade melanocytes and disease discrimination was based on melanin production. A combination of HCA and PCA was performed on spectral data and a good separation was achieved among discrete clusters of different skin lesions. Biochemical changes in protein a-helix and b-sheet structures were obtained; phosphate groups of nucleic acid conformations have contributed toward disease classification. In addition, chemometric results were in adequate agreement with histopathological conclusion (60). Ly et al. applied a combination of FTIR microimaging and multivariate approach to characterize various melanoma types and to investigate IR signatures in primary cutaneous

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melanoma and its correlation with dermatopathological parameters. This study has used set of paraffin-embedded thin sections, which represents different histological types. It has also emphasized that FTIR imaging may be able to identify spectral markers for clear separation of melanoma cells from epidermis and benign adjacent nevus. Furthermore, this study has found tumor heterogeneity based on stromal reactions of different types of melanoma. Finally, it has suggested that spectral staining will give more focus on tissue architecturerelated melanoma invasion (61). Lima et al. studied the biochemical differences between normal skin and SCC tissue. They induced carcinogenesis process on the skin of 13 mice through application of a carcinogenic substance, TPA (12-O-tetradecanoyl-phorbol-13acetate). Topical acetone was applied to other 13 mice to keep them as a control group (normal skin tissue). Both normal and neoplastic tissue were analyzed with ATR-FTIR spectroscopy using a spectral resolution of 4 cm¡1 and collecting a spectra within the range of 4000 to 400 cm¡1. The absorption intensity of 970, 1517, 1638, and 1655 cm¡1 bands showed an increase in spectra from neoplastic tissue. Band at 970 cm¡1 represents the phosphorylation process of pRB retinoblastoma protein, which promotes cell replication. Increase of 1517 cm¡1 band, related to amide II, indicated an increase in protein content related to cell proliferation caused by phosphorylation processes. Peaks in the amide I region at 1655 and 1638 cm¡1 showed an increase of absorption. The 1638 cm¡1 band, related to b-sheet structure of protein, exhibited a shift to a lower wavenumber whereas the 1655 band, related to a-helix structure of protein, showed a shift to a higher wavenumber. These features suggested biochemical changes in the hydrogen bond toward peptide groups changing the organization of atoms and hence the symmetry of proteins, leading to a mutation or deformation of protein folding. All data collected was classified by HCA method. This statistical method was able to distinguish between normal and neoplastic tissue effectively. The accuracy of the analysis was of 86.4%. This study showed that important signaling markers, characteristic of neoplastic tissue (SCC), are highly detectable by ATR-FTIR spectroscopy (62). Wald et al. used FTIR imaging to identify melanoma cells and lymphocyte populations from lymph nodes with metastasis. Six main cell types were identified, each with a characteristic spectral database. Since a significant amount of spectra were collected for each cell type, all data was analyzed with multivariate statistical analyses, being PCA and K-means clustering the primary ones. Results, based on the mean IR spectra of the main cell types, showed significant differences between the erythrocyte spectrum and the rest of the main cells spectra. These differences were highly noted in the1400–1000 cm¡1 region, the amide II band, and the lipid region (3000–28000 cm¡1). Also, by using PCA, melanoma cells were identified with 87.1% sensitivity and 85.7% specificity. These rates are highly similar to the ones presented by histochemistry methods. Furthermore, FTIR was able to detect subtle differences between B and T cells, particularly in the regions of 1240 and 1080 cm¡1 mainly due to the symmetric and asymmetric stretching of PO2¡¡ groups. Additionally to this, significant spectral differences were shown between lymphocytes in non-invaded and invaded lymph nodes. These significant differences are due to the contribution of nucleic acid (63). Fujioka et al. reported on discrimination between normal and malignant human gastric tissues by FTIR spectroscopy. Their aim was to determine whether malignant and normal human gastric tissues could be distinguished by the technique. As a result, 22 out of 23 gastric tissue samples and 9 out of 12 gastric normal samples were correctly segregated, yielding


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88.6% accuracy. Subsequently, they concluded that FTIR spectroscopy can be a useful tool for screening gastric cancer (64). Junhom et al. used FTIR microspectroscopy to identify the biochemical differences between parental HepG2 and cisplatin-resistant HepG2 cells. All data was analyzed with PCA in order to distinguish the main variables or biomarkers between these 2 groups. Three main loading plots identified the biochemical differences within the lipid, protein, carbohydrate, and nucleic acid regions. The most notorious differences were quantitatively detected in the protein region within the spectral range of 1700–1600 cm¡1 for amide I and 1600– 1500 cm¡1 for amide II. These changes reflected a modification of the secondary structure between cells that are sensitive to the anticancer drug and cells resistant to the drug. In particular, in the cisplatin-resistant HepG2 cells, there was a high-absorbance noted on the 1657 cm¡1 peak when compared to the parental HepG2 cells. Several changes were detected on the remained regions (1300–900 cm¡1). All these variables lead to the cluster separation between the parental and drug-resistant data sets. These notorious clusters were indicated by a score plot with 96.5% accuracy (65). Ukkonen et al. used FTIR imaging to analyze the biochemical features in tumor microenvironment (TME) surrounding melanoma and oral squamous carcinoma cells (OSCC). Using transmission mode and a spectral resolution of 8 cm¡1, spectra were collected from 3 different areas of TME: (i) near-cancer cells, (ii) TME from the middle of the tissue, and (iii) far-cancer cells. When compared to the spectra collected from far-tumor section, spectra collected from near-tumor section showed a shift to a lower wavenumber within the 3600 to 3200 cm¡1 region due to the stretching vibration of O–H. This indicates an increase in water molecule due to the high dense population of cancer cells within that area. Furthermore, when compared to far-tumor section spectra, spectra taken from near-tumor section also exhibited significant markers within the 1700 to 1600 cm¡1 region indicating an increase in collagen degradation due to the invasion of cancer cells. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) were performed as complementary methods to analyze the data provided by FTIR. The statistical methods classified the data into 3 different clusters where there was a significant difference between the cluster labeled as near-tumor section and the cluster named as far-tumor section. This study showed that the data provided by FTIR imaging working in collaboration with appropriate statistical methods provided an accurate discrimination between near, middle, and far TME regions due to the different signaling biomarkers presented in each group (66). Weng et al. studied tumors from stomach, small intestine, colon, rectum, liver, and other parts of the digestive system with FTIR fiber optics and FT-Raman spectroscopic techniques. The spectra of samples were recorded on a Magna750 FTIR spectrometer with a mercury cadmium telluride detector (MCD) and mid-infrared optical fiber. In this occasion, measurements were taken by touching the samples with an ATR probe. FT-Raman spectra of the samples were recorded on a 950 FT-Raman spectrometer. The results indicate that (i) the CHO stretching band of adipose can be observed in some normal tissues but is rarely found in malignant tissues and (ii) the relative intensities I1460/I1400 are high for normal tissue but low for malignant tissue. For most normal tissues, the intensities for the 1250 cm¡1 band are stronger than for band around 1310 cm¡1, while the 1310 cm¡1 band in malignant tissues is often stronger than the 1250 cm¡1 bands (67). In a study reported by Mordechai et al., adenocarcinoma and normal colonic tissues were studied. FTIR microspectroscopy was employed to analyze thin tissue specimens and a direct

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comparison with normal histopathological analysis, which served as a gold reference. Several unique differences between normal and cancerous intestinal specimens were observed. The cancerous intestine showed weaker absorption strength over a wide region. In addition, IR absorption spectra from intestinal tissues (normal and cancerous) with other biological tissue samples were also effectively compared (68). A diagnostic research was carried out by Li et al., which aimed at classifying endoscopic gastric biopsies into healthy, gastritis, and malignancy through the use of FTIR spectroscopy. A total of 103 endoscopic samples, including 19 cases of cancer, 35 cases of chronic atrophic gastritis, 29 cases of chronic superficial gastritis, and 20 healthy samples, were investigated by ATR-FTIR. Significant differences were observed in FTIR spectra of these 4 types of gastric biopsies. It was demonstrated that the sensitivity of the method for healthy, superficial gastritis, atrophic gastritis, and gastric cancer was 90%, 90%, 66%, and 74%, respectively. It was concluded that FTIR spectroscopy can be a useful technique for monitoring disease processes in gastric endoscopic biopsies (69). Thumanu et al. applied FTIR microspectroscopy and chemometrics to identify liver cirrhosis and hepatocellular carcinoma (HCC) using patient blood serum samples. This study has identified biochemical fingerprint of HCC, cirrhosis, and healthy controls using FTIR bands. HCC samples have shown higher b-sheet content of protein and lower lipid content compared to cirrhosis and healthy controls. This will give opportunity to establish new spectral markers for identification of liver disease. Furthermore, PLS-DA classified HCC, cirrhosis, and healthy controls with high sensitivity, specificity, and 100% prediction accuracy (70). Colagar et al. reported that FTIR microspectroscopy could be used to differentiate between normal and cancerous gastric tissues. Spectral data were obtained from both tissues in the region of 900–1800 cm¡1 and amide I peak has used for normalization in both normal and cancerous ones. The ratio of 1045/1545 cm¡1 has provided a carbohydrate concentration. Carbohydrate levels were decreased in the cancerous tissues as compared to normal tissues. Normal tissues have higher intensity of PO2 symmetrical and asymmetrical stretching vibrations than that of cancerous ones. The profound variations in the region 1185– 1350 cm¡1 have denoted distinct chemical differences between normal and cancerous ones. The glucose/phosphate ratio (1030/1080 cm¡1) was observed very high in normal tissues than compared to cancerous tissues. Variations in tyrosine/phosphate ratio (1512/ 1080 cm¡1), RNA/DNA ratio (996/966 cm¡1), and amide I/amide II ratio (1643/1544 cm¡1) have become excellent markers to find out chemical changes during disease progression. The intensity ratios of RNA/DNA and amide I/amide II were higher in normal when compared to cancerous ones. The intensity ratios of stretching vibrations CH2 (2925 cm¡1) and CH3 (2958 cm¡1) were declined from normal to cancerous due to changes in distribution of proteins and lipids (71). Yizhuang et al. demonstrated that ATR-FTIR associated with optic fibers could be used to discriminate between normal and malignant gastric tissues both in vivo and in vitro. Normal tissues have shown characteristic CHO band (fat) and C H stretching band (lipid, fat, and protein). These peaks were absent in cancerous ones and peaks like 2923 and 2853 cm¡1 appeared less frequently in cancerous tissues as compared to normal tissue. Consumption of fat due to enhanced nutritional and energy requirement is a predominant feature of malignant tissues. The intensity of purine base pairs (1313 cm¡1) is stronger in malignant tissues due to presence of nucleic acids and specific surface proteins. The intensity of C O and C O H vibrations of carbohydrates (1160 cm¡1) is stronger in normal when compare


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with cancerous ones. Additionally, normal mucosa is enriched with glycoproteins and these results are in agreement with the staining results. The presence of C O vibration (1120 cm¡1) is stronger in malignant tissues due to the presence of glycogen in different cellular components such as tissue surface, intercellular substance, and plasma. Subtraction spectral results have further confirmed the differences between normal and cancerous tissues. Also, O H and N H vibrations (3374, 3251 cm¡1) were stronger in cancerous due to variations in hydrogen bond network, whereas C–H stretching vibrations (2945 cm¡1) and C H O stretching (1744 cm¡1) were stronger in normal tissues. The amide I peak (1650 cm¡1) is stronger in normal tissues due to high amount of protein with a-helical secondary structure. Furthermore, statistical analysis results have confirmed that amide I band and the intensity ratio of amide I/amide II are useful markers to distinguish normal and malignant gastric tissues (72). Choo et al. applied infrared spectra of human central nervous system tissue for diagnosis of Alzheimer’s disease (AD). In addition, they presented a means of classifying the spectroscopic data non-subjectively using several multivariate methods. The results demonstrated that IR spectroscopy could potentially be used in the diagnosis of AD from autopsy tissue. It was shown that correct classification of white and grey matter from brains identified by standard pathological methods as heavily, moderately, and minimally involved can be achieved with success rates of greater than 90% using appropriate methods. Classification of tissue as either control or AD was achieved with a success rate of 100% (73). FTIR spectra of RNA isolated from tumor brain (glioma) and DNA isolated from lowdose gamma-irradiated epididymis cells of rats from the Chernobyl accident zone were investigated by Dovbeshko et al. The aim of the study was to study nucleic acid damage and reported on the existence of damage in the primary, secondary, and tertiary structure of nucleic acid, which seem to be connected with modification of bases and sugars, and redistribution of the H-bond network. It has also been reported that a great amount of statistical data and good mathematical approaches are needed for the use of these data as diagnostic criteria (74). Yoshida et al. measured the FTIR spectra of brain microsomal membranes prepared from rats fed under 2 dietary oil conditions with and without brightness-discrimination learning tasks: one group fed-linolenate deficient oil (safflower oil) and the other group fed the sufficient oil (perilla oil) from mothers to offspring. The infrared spectra of microsomes under the 2 dietary conditions without the learning task showed no significant difference in the range 1000–3000 cm¡1. Only after the learning task the infrared spectral differences were noted between the microsomal membranes from both groups. Spectral differences were observed mainly in the absorption bands of fatty acid ester at around 1730 cm¡1 (sn-2 position), those of phosphate and oligosaccharides in the range of 1050–1100 cm¡1, and a band at around 1145 cm¡1. These results suggest changes in hydration of membrane surface and modification in oligosaccharide environment (removal or modification) of microsomes, which may be correlated in part with dietary oil-induced changes in learning performance (75). Noreen et al. has used FTIR imaging to discriminate between normal healthy brain tissues and xenografted glioma tumors based on collagen content. FTIR imaging was used to potentially differentiate connective tissue components based on secondary structures of the collagen types. Pure product spectra for type I, III, IV, V, and VI collagens were used as references for analyzing collagen contents in both tissues. FTIR spectra of both tissues were

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collected from FTIR images and curve fitting of amide I region. Eight selected amide I bands with different spectral interval (a-helix – 1658 cm¡1, b-sheets – 1691, 1679, and 1626 cm¡1, b-turns – 1669 and 1610 cm¡1, triple helix – 1637 cm¡1, and unordered structures – 1647 cm¡1) were chosen to perform secondary structure calculations. Curve-fitting method was established and this method was used for all the other samples. Multivariate correspondence factorial analysis (CFA) was used to distinguish between normal and tumor tissues based on their secondary structure profiles (76). Wehbe et al. reported that FTIR imaging could be used as a powerful analytical tool to distinguish between normal blood vessels (NBVs) and tumor blood vessels (TBVs) of glioma. FTIR images of blood capillaries were collected from normal xenografted tissue sections, intracranial xenografted tumors, and human brain tumor samples. All visible images were obtained in the 4000 to 720 cm¡1 range using 8 scans per pixel with spectral solution of 4 cm¡1. Spectral intervals such as amide I and II (1712–1500 cm¡1), fatty acyl chains (3020–2800 cm¡1), lipid esters (1776–1720 cm¡1), and osidic residues (1180–950 cm¡1) were used to differentiate between NBVs and TBVs. A classification method was established by using 2 spectral intervals (3020–2800 and 1180–950 cm¡1), belonging to IR absorptions of fatty acyl chains and osidic residues, respectively. Curve- fitting method was used at fatty acyl intervals (3050–2800 cm¡1) to highlight the spectral differences. Fatty acyl chain unsaturation and its length was calculated by using these ratios ((CH)/nas(CH3) and nas(CH2)/ nas(CH3)). Unsaturation has increased in the tumor with respect to NBV, while its length was decreased in the tumor with respect to normal. These results have indicated that tumor vascular endothelial cells have more unsaturated phospholipids due to hypoxic condition and the total reduction of lipids is due to increase in malignancy. Second derivative spectra emphasize on absorption band at »1068 4 cm¡1 (osidic residues), which was used to differentiate between NBVs and TBVs. This peak was not found in the TBVs but it appeared with less intensity in the NBVs. Finally, this study has also developed a classification method that can be applied on human glioma tissues to test its transferability with small percentage of misclassification (77). Noreen et al. reported that FTIR imaging could be used as functional histology probe for investigating both the molecular contents of brain tissues as well as angiogenic properties of solid and diffuse tumors. The aim of this study is using barium sulfate (BaSO4) and bare gold (Au) nanoparticles (NP) as contrast agents to explore brain blood vasculature. BaSO4 was selected as highly absorption IR agent of NP to reveal morphological deformities of tumor capillaries, while Au-NP was chosen as low absorption IR agent of NP to reveal diffusion properties of leaky blood vessels. The FTIR images were collected from tumor sections in the 4000–900 cm¡1 ranges with a spectral resolution of 8 cm¡1, and 128 scan per pixel. FTIR images have revealed chemical fingerprint of blood vasculature such as deformities of capillary structures via distribution studies of contrast agents and NP. This study has proven that advancement of FTIR imaging approach will be a valuable tool to understand tumor vascular biology in near future (78). Beljebbar et al. reported that FTIR imaging could be used in the monitoring and interpretation of biochemical changes associated with C6 glioma growth and invasion. Micro-FTIR maps were collected from both normal and malignant tissues from day 7 to day 21 after implantation of C6 glioma cell suspension in brain parenchyma. The prominent FTIR bands observed in normal and tumor tissue spectra were 1654 cm¡1 (amide I), 1546 cm¡1 (amide II), 1740 cm¡1 (C H O of lipids), 1396 cm¡1 (COO¡ of fatty acids and amino acids),


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1238 cm¡1 (PO2¡ of nucleic acids), and 1082 cm¡1 (PO2¡ of phospholipids). White matter has high intensity of CH2 scissoring (1466 cm¡1) than CH3 asymmetric bending (1454 cm¡1) due to its high lipid content. Tumor tissues have shown decreased and even disappearance bands at 1466 cm¡1 (lipids) and 1740 cm¡1 (phospholipids) compared to normal tissues. Malignant tissue has shown the band at 1070 cm¡1 (C C stretching) and reduced intensity of the band at 1082 cm¡1 (phospholipids diminution) compared to normal tissues. Multivariate statistical analyses such as cluster analysis (CA) and non-negative leastsquares algorithm (NNLS) have successfully identified as well as quantified the chemical changes associated with development of the glioma tumor (79). Ali et al. used FTIR to study the biochemical changes occurring in the white matter of a rat’s brain after 9 weeks of having a stroke. Samples were analyzed and spectra were collected from different areas of each sample. Both, normal and stroke-affected white matter data was analyzed with PCA along with some more analysis modalities. The loading spectrum of PC1 had a variance of 42.9% mainly in the amide I region (around 1695 to 1637 cm¡1) and amide II (1543 cm¡1). Additionally to this, the PC2 loading spectrum had a variance of 21.4% in the protein and ester region (around 1730 cm¡1). From PC3 to PC6, small variations were located in these same regions as well. Overall, the data analysis of the spectral data indicated a decrease in intensity of the lipid region and other changes in the ester and protein range particularly when compared to healthy brain tissue (80). Dreissig et al. reported that FTIR spectroscopy could be useful in quantitative study of lipid composition in relation to porcine brain tumor development. The objective of this study was to establish correlation between normal and tumor lipid content using quantitative approaches such as thin-layer chromatography and statistical approaches such as PLS. Major lipid contents concentrated in this study were cholesterol (CH), phosphatidylethanolamine (PE), and phosphatidylcholine (PC). An expected CH content was not detected by both approaches but PE content was successfully quantified by PLS approach. Both methods have identified lower PC content in grey matter of brain composition. A combination of other spectroscopic methods and FTIR will improve better diagnosis of brain cancer in the near future (81). Caine et al. reported in their review article that FTIR microspectroscopy could be used to detect protein secondary structural changes in AD, Parkinson’s disease (PD), meningioma, transmissible spongiform encephalopathies, and multiple sclerosis. In AD, FTIR was used to assess the spatial relationship between the dense-core plaques, phospholipid distribution, and creatine deposits. FTIR spectra of mice AD tissue has shown doublet peak between 1410 and 1384 cm¡1 (creatine deposits) and 1623 cm¡1 (b-sheet secondary structure of densecore plaques). In PD, the spectra of both normal and PD-affected neuron bodies have shown peaks associated with lipids at 1740 cm¡1, 2930 cm¡1, and 2850 cm¡1. These higher intensity peaks likely confirmed the presence of phospholipid myelin. The spectra of PD-affected nerve cell bodies has shown increased intensities in the lipid functional groups (2930 and 2850 cm¡1) and CO O C stretching (1173 cm¡1 ) as well as a decreased intensity in the nucleic acids (anti-symmetric at 1236 cm¡1, symmetric at 1086 cm¡1 of PO2¡ stretching bands). This review article had explored different central nervous diseases and their spectral markers that will be beneficial in the future therapeutic approaches (82). Ke et al. reported that ATR-FTIR spectroscopy could be used to find out biochemical changes at different time intervals of post-mortem rat brain. The aim of this study is to assess post-mortem interval (PMI), which will be useful in forensic analysis. Linear

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regression analysis was applied on ATR-FTIR data, and the correlation was established between the relative absorption intensity and the PMI. Different peak ratios were examined and major changes were noticed as PMI increases. Lipid corresponding FTIR bands at 1737 (C H O stretching) and 2871 (CH3 symmetric stretching) became weak and even disappeared as PMI increased. This is a very rare study and the results of this study has suggested that FTIR may be useful as a forensic tool (83). Fukuyama et al. used FTIR microscopy for studying the differences between oral SCC and normal mucosa (normal gingival epithelium or normal subgingival tissue). The tissue spectra were compared with the purified human collagen and keratin. One half of every tissue specimen was measured with FTIR and the other half was investigated histologically. The obtained data suggested that this technique is applicable to clinical diagnostics (84). Menzies et al. reported that combination of FTIR spectroscopy and multivariate approach could be used to diagnose head and neck cancers. In previous study, this group has detected lung cancer from patient sputum samples with high sensitivity and specificity. In this study, IR spectra were collected from sputum cell pellets and fingerprint region was probed to detection of oral, pharyngeal, and laryngeal cancers. Band absorption differences were observed throughout spectra between normal and cancer spectra particularly within the carbohydrate and nucleic acid regions. Amide I, II, and carbohydrate regions were used to develop potential models to discriminate disease from normal control. Protein and glycoprotein structural changes might contribute toward spectral cancer detection and this preliminary study will be useful to evaluate FTIR as diagnostic tool for early detection of head and neck cancers (85). Andrus collected the spectra of various grades of malignant non-Hodgkin’s lymphoma. Structural changes to lipids and proteins in the wavenumber region of 2800–300cm¡1, seen as increasing CH3/CH2 ratio and decreasing symmetric CH2/asymmetric CH2 ratio, were found to occur with increasing lymphoma grade. Rising ribose content (1121 cm¡1) was seen to correlate with rising 996/966 cm¡1 ratio (an index of RNA/DNA) with increasing malignancy grade as well. It was concluded that this method can potentially be applied to clinical cancer grading, or in vitro cancer treatment sensitivity testing (86). Mordechai et al. applied FTIR microspectroscopy for the follow-up of childhood leukemia chemotherapy. A case study was presented where lymphocytes isolated from 2 children before and after the treatment were characterized using FTIR microspectroscopy. Significant changes in the spectral pattern in between 800 and 1800cm¡1 region were found after the treatment. Preliminary analysis of the spectra revealed that the protein content decreased in the T-type Acute Lymphoblastic Leukemia (ALL) patient before the treatment in comparison to the aged-matched controls. It was shown that the chemotherapy treatment results in decreased nucleic acids, total carbohydrates, and cholesterol contents to a remarkable extent in both B and T-type ALL patients (87). Zelig et al. applied FTIR spectroscopy to pre-screen leukemia by examining blood samples of leukemia patients, healthy individuals, and patients having leukemia like symptoms. FTIR spectra were collected from peripheral blood mononuclear cells (PBMC) in the range of 700–4000 cm¡1 with 128 co-added scans. This study has identified several consistent spectral markers for leukemia detection in high-wavenumber region. Lipid markers have played a very important role in diagnosing leukemia from diseases having leukemia-like symptoms (88).


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Prabhakaran et al. reported that FTIR could be employed to investigate biochemical composition of whole human blood. In this study, blood samples were collected and air-dried, and FTIR spectra were recorded in the wave number region of 2000–400 cm¡1 at a resolution of 4 cm¡1. FTIR spectra have revealed prominent peaks at 1020 cm¡1 (glycogen), 1082 cm¡1 (phosphate stretching band), 1300–1000 cm¡1 (phosphodiester), 1369 cm¡1 (C N of cytosine and guanine), 1800–1600 cm¡1 (C H phenyl ring), 1659 cm¡1 (amide I), and last but not least 1544 cm¡1 (amide II). Peak fitting has revealed new peaks in the spectra such as 1690 (base carbonyl stretching of nucleic acid), 1167 (C O stretch), 1244 (asymmetric PO2¡ stretch), and 1731 (fatty acid esters). This study has also quantified total phosphate content, RNA/DNA level, glycogen/phosphate ratio, carbohydrates level, and amide I/amide I. These peak ratios will be useful in understanding biological information of blood components in near future (89). Andrus and Strickland used FTIR spectroscopy for cancer grading. Freeze-dried tissue samples from lymphoid tumors were studied. The absorbance ratio of 1121 cm¡1/ 1020 cm¡1 increased, along with the emergence of an absorbance pulse at 1121 cm¡1, with increasing clinic pathological grade of malignant lymphoma. This study proposed the above ratio as an index of the cellular RNA/DNA ratio after subtraction of the overlapping absorbances, if present, due to collagen or glycogen. Absorbance attributable to collagen increased lymphoma grade and was greater in benign inflammatory tumors than in low-grade lymphomas. It was also suggested that the ratio trend may form the basis of a universal cancergrading parameter to assist with cancer treatment decisions and may also be useful in the analysis of cellular growth perturbation induced by drugs or other therapies (90). In another study, Gazi et al. applied FTIR microspectroscopy to separate the paraffinembedded tissues samples of benign and cancerous prostate. They could also separate the FTIR spectra of prostate cancer cell lines derived from different metastatic sites. It was found that the ratio of peak areas of 1030 and 1080 cm¡1 (corresponding to glycogen and phosphate vibrations, respectively) suggests a potential method for the differentiation of benign from malignant cells. It should be mentioned that the tissues were analyzed after mounting onto a BaF2 plate and subsequent removal wax using CitroclearTM followed by acetone (91). Paluszkiewicz reported on human cancer prostate tissues using FTIR microspectroscopy and SRIXE techniques. The tissue samples were also analyzed by a histopathologist. In this research, differences between cancerous and non-cancerous parts of the analyzed tissues were observed for both methods (92). Gazi et al. reported that FTIR microspectroscopy could be used to study fatty acid metabolism through COX pathway in prostate cancer cell lines under different environmental conditions. Cancer cells were cultured in different concentrations of D31-PA (deuterated palmitic acid) and D8-AA (deuterated arachidonic acid) at different incubation periods. FTIR spectra were collected at 4 cm¡1 resolution with 256 scans, whereas HD FTIR maps were collected at 6.25 mm pixel resolution. FTIR results of this study have established that media has influenced uptake of D31-PA by cancer cells during incubation and it was confirmed in the spectral region of 2250–2050 cm¡1. FTIR mapping of nuclei has revealed that most intense phosphate diester peaks were observed at the range of 1274–1181 cm¡1, which reflects a high concentration of nucleic acids. On the other hand, FTIR maps of cellular organelles have shown high intensity of symmetric and asymmetric CH2 and CH3 vibrations at 3004–2837 cm¡1 due to lipid hydrocarbons. The most intense lipid hydrocarbon signals of different cytoplasmic regions were due to the presence of D31-PA and its metabolites.

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Furthermore, molecular structures of deuterates have exhibited different number of Raman peaks because of D8-AA and D-31PA (93). Baker et al. demonstrated that combination of multivariate approach with synchrotron microspectroscopy could be used to study RWPE prostate cancer cell lines. FTIR spectra were acquired from both non-tumorigenic and tumorigenic cell lines in the range of 700–6000 cm¡1 with spectral resolution of 4 cm¡1. Genetic algorithm, PCA, and support vector machines were used to analyze the spectral data. The first principal component (PC1) has separated tumorigenic and less invasive cell lines from slow and fast invasive cell lines, whereas second principal component (PC2) separates nontumorigenic from tumorigenic cell lines. This study has shown high degree of classification accuracy and will be useful to establish as biochemical models to study cancer invasion in near future (94). Pezzei et al. reported that FTIR spectroscopic imaging could be applied in detection of prostate cancer using frozen tissue biopsies. This study has used benign and malignant stromal tissues and exceptional IR spectra were collected from snap frozen cancerous tissue. High-quality IR spectra were collected in the range from 4000 to 750 cm¡1 with a spectral resolution of 4 cm¡1. The spectral data reveals that both cancer and stromal tissues have expressed major peaks around »3300 (Amide A), »3010 (lipids, cholesterols, esters), »1620–1695 (Amide I), »1550 (Amide II), »1360–1260 (Amide III), »1350–1260 (vPO2¡), »1310–1240 (Amide III), »1250–1220 (PO2¡ groups of phospholipids), »1225 (v PO2¡ asymmetric of nucleic acids and phospholipids), »1185–1120 (C–O ring vibrations), and »1084 (PO2¡ groups nucleic acids). Spectra of cancer tissue have expressed »3100 (Amide B) and »1400 (COO¡ group), and these bands are not expressed in stromal tissue. Chemometric approaches such as K-means clustering, fuzzy c-means clustering (FCM), and HCA were explored new spectral markers, which will be helpful in understanding the correlation between molecular fingerprint and its histopathological behavior (95). Brown et al. reported that both FTIR microspectroscopy and time-lapse microspectroscopy could be used to understand the prostate cancer (CaP) invasion in metastasis. This study has used paraformaldehyde fixed PC-3 cells to understand the Arachidonic Acid (AA) effects in CaP invasion. ATR images were obtained at 6.25 mm pixel resolution and background scan was recorded at 8 or 4 cm¡1 with 75 scans and whereas sample was recorded at 8 or 4 cm¡1 with 64 scans. FTIR spectra have provided metabolic pathway of D8-AA and its deuterated metabolites. Spectral signatures not only identify D8-AA location, but also identified the D8-AA uptake. The band at 2150 cm¡1 indicates y(C-D) signal and it represents D8-AA. Background spectra were obtained in the spectral range where the peak 2150 cm¡1 was absent. The results of this study clearly indicate that D8-AA and its metabolites were specifically present in intra-cellular components of adipocytes and CaP cells, but absent in stromal cells (96). Argov et al. reported on FTIR microspectroscopic study of Inflammatory Bowel Disease (IBD) as an intermediate stage between normal and cancer. In this work, FTIR microspectroscopy was used to evaluate IBD cases and to study the IR spectral characteristic with respect to cancer and normal tissues from formalin-fixed colonic biopsies from patients. IBD tissues could be segregated from cancer or normal ones using certain parameters such as phosphate content and RNA/DNA ratios. The results exhibited that FTIR microspectroscopy can detect biochemical changes in morphologically identical IBD and cancer tissues and suggest which cases of IBD may require further evaluation for carcinogenesis (97).


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Richter et al. used FTIR spectroscopy in combination with positron emission tomography to identify the tumor tissues. Thin tissue sections of human squamous carcinoma from hypopharynx and human colon adenocarcinoma grown in nude mice were investigated. Tumor tissues could successfully be identified by FTIR spectroscopy, while it was not possible to accomplish this with PET alone. On the other hand, PET permitted the non-invasive screening for suspicious tissues inside the body, which could not be achieved by FTIR (98). Rigas et al. applied FTIR spectroscopy to study the tissue sections of human colorectal cancer. Pairs of tissue samples from colorectal cancer and histologically normal mucosa, 5– 10 cm away from the tumor, were obtained from 11 patients who underwent partial colectomy. All cancer specimens displayed abnormal spectra compared with the corresponding normal tissues. These changes involved the phosphate and C–O stretching bands, the CH stretch region, and the pressure dependence of the CH2 bending and C D O stretching modes. It was indicated that in colonic malignant tissue, there are changes in the degree of hydrogen-bonding of (i) oxygen atoms of the backbone of nucleic acids (increased); (ii) OH groups of serine, tyrosine, and threonine residues (any or all of them) of cell proteins (decreased); and (iii) the C H O groups of the acyl chains of membrane lipids (increased). In addition, changes in the structure of proteins and membrane lipids were shown (as judged by the changes in their ratio of methyl to methylene groups), as well as in the packing and the conformational structure of the methylene chains of membrane lipids (99). Rigas and Wong studied 7 human colon cell lines by infrared spectroscopy including the study of several spectral parameters under high pressure (pressure-tuning spectroscopy). The 7 adenocarcinoma cell lines displayed almost all of the important spectroscopic features of colon cancer tissues: (a) increased hydrogen-bonding of the phosphodiester groups of nucleic acids; (b) decreased hydrogen-bonding of the C OH groups of carbohydrates and proteins; (c) a prominent band at 972 cm¡1; and (d) a shift of the band normally appearing at 1082 cm¡1 to 1086 cm¡1. These cell lines differed spectroscopically from the colon cancer tissues in that: (a) they displayed a band at 991 cm¡1, which is weak in colon tissues; and (b) the packing and degree of disorder of membrane lipids were close to those observed in normal colonic tissues. They concluded that these findings (i) establish IR spectroscopy, used in combination with pressure tuning, as a useful method to address problems of tumor biology in cell culture systems; (ii) indicate that these cell lines offer a useful experimental model to explore the origin of the spectroscopic changes that we observed in colon cancer tissues, and (iii) support the idea that the malignant colonocyte is the likely source of all or most spectroscopic abnormalities of human colon cancer (100). Walsh et al. demonstrated that FTIR spectroscopic imaging could be useful in chemical characterization of gastrointestinal disorders such as colon cancer, ulcerative colitis, and Crohn’s disease. This study has compared H&E stained images with spectroscopic images like ATR and HD FTIR images. ATR images have pixel size of 1.56 £ 1.56 mm, with 4 scans per pixel at a spectral resolution of 8 cm¡1, whereas HD FTIR images have a pixel size of 1.1 £ 1.1 mm, with 32 scans per pixel at a spectral resolution of 8 cm¡1. The advantage of ATR image over transmission mode has allowed the revelation of lymphocytes and intracellular mucin. The spatial localization of lymphocytes and epithelial cells has allowed regions of interest (ROIs) to be drawn that related to these components. The spectra of ROIs have established that lymphocytes and mucin have unique spectral signatures as compared to the neighboring tissue. Intracellular mucin ROIs has shown a band at 1030 cm¡1 due to glycogen absorbance of glycosylated glycoproteins (101).

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Madhavi et al. reported that FTIR could be used to investigate properties of colon cancerrelated drug, curcumin, and its drug–polymer interaction. FTIR studies have confirmed that there was no interaction between the drug and the polymer, plus the crystallinity of the drug has not changed while fabrication. This result boosted the usage of this polymer in the development of curcumin microspheres. Carbonyl band stretching in the FTIR spectra were used to interpret the physical state of the drug. Drug and drug-coated polymer exhibited some chemical differences that were observed in the region of 1800–1500 cm¡1. Crystalline curcumin have shown 2 specific bands in the region of 1653 and 1590 cm¡1 due to C H O stretching of aliphatic and aromatic carbonyl groups (102). Li et al. applied FTIR spectroscopy and chemometrics to distinguish colon cancer from colitis among colon biopsies. FTIR spectra were collected from colon patient biopsies using ATR-FTIR in the range of 1000–4000 cm¡1 at a resolution of 4 cm¡1. Spectral data have revealed major fat-related IR peaks at 1743 cm¡1, 2858 cm¡1, 2927 cm¡1, and 2966 cm¡1. The intensity of these bands has become less in as disease progress, and completely absent in malignant tissues. This is due to additional nutritional requirements for cancer growth. Moreover, the relative intensity of amide II to amide I peak has decreased in colon cancer compared to colitis biopsies. Chemometric approaches such as PCA and naive bayes classification (NBC) were able to diagnosed disease with a sensitivity of 97.6%, specificity of 70.2%, and total accuracy of 82.8%. This approach has shown great promise for in vivo diagnosis with the development of endoscopic FTIR miniprobes for instant diagnosis at endoscopy level. (103). Sade et al. reported that ATR-FTIR spectroscopy and spin label ESR (SL-ESR) could be used to study the effects of celecoxib—a selective COX-2 (cyclo-oxygenase-2)—in the COX2 expressing and non-expressing cells. In this study, ATR-FTIR was used to study lipid dynamics and SL-ESR was used to study lipid fluidity. The peak at 2850 cm¡1 has represented CH2 symmetric stretch of fatty acyl chains. Bandwidth of CH2 stretching mode has increased as increase in the dynamics of the membrane system. FTIR spectral data has revealed that bandwidth of CH2 symmetric stretching has decreased in celecoxib-treated COX-2 expressing cells and this suggested reduction in lipid dynamics. (104). Khanmohammadi et al. demonstrated in their review article that IR spectroscopy could be used as a green analytical chemistry tool to explore biochemical fingerprint in clinical oncology. This article has covered different types of cancers and IR evolution in their research. In colon cancer, the spectral range of 1150–1000 cm¡1 has shown potential molecular markers such as phosphate stretch for early detection of malignancy. Cellular components such as total carbohydrates, phosphate, and creatine contents have decreased absorption in malignant colon epithelial cell when compared to the normal ones. Atmospheric or tuned pressure has shown great implications in IR parameters especially in amide I structure and it was useful standard in diagnosis of malignancy. Second derivative analysis curve-fitted data has revealed that there is an increase in a-helices and a decrease in b-sheet composition. This is also a discriminant feature between normal and cancerous samples. Malignant colon tissues have shown prominent peaks at 1160 cm¡1 (v(C O), v(C O H), and v(C C)), 1080 cm¡1 (v(PO2¡)), and 1040 cm¡1 (v(CH2OH), v(C O), and C O bending). Combination of silver halide optic fiber approach and double binary algorithm has differentiated cancerous from normal ones. Combination feature extraction approach and support vector machine has achieved 95% accuracy in cancer detection. Combination of wavelet features


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with artificial neural network has revealed new FTIR markers such as RNA/DNA ratio and phosphate content (105). Al-Muslet et al. reported that FTIR spectroscopy could be useful in detecting bladder cancer from patient biopsies. Spectra were recorded from normal and pre-treated malignant bladder tissue biopsies and clear spectral changes were observed between normal and cancerous samples. Clear spectral differences were observed in lipid bands at high-wave number region, and protein and nucleic acid bands at fingerprint region. Malignant tissues have shown greater absorption in N–H, amide I, and amide II peaks compared to normal tissues. The C H stretching vibration at lipid region and C H O vibration at amide I region have become weaker and even disappear. This study has shown a promising approach for FTIR technology to be used as a diagnostic tool for bladder malignancies (106). In vitro viral carcinogenesis was studied by Huleihel. In this study, FTIR microscopy was used to investigate spectral differences between normal and malignant fibroblasts transformed by retrovirus infection. Significant differences were observed between cancerous and normal cells. It was concluded that the contents of vital cellular metabolites were significantly lower in the transformed cells than in the normal cells. In addition, as an attempt to identify cellular components responsible for the spectral dissimilarities, they found considerable differences between DNA of normal and cancerous cells (107). In a proof-of-concept study, Mossoba et al. made an investigation on printing microarrays of bacteria for identification by infrared microscopy. They used the technique as a tool for rapid bacteria identification and could demonstrate its effectiveness (108). According to a published paper by Naumann, FTIR and FT-NIR Raman spectra of intact microbial cells are highly specific, fingerprint-like signatures which can be used to (i) discriminate between diverse microbial species and strains, (ii) detect in situ intracellular components or structures such as inclusion bodies, storage materials, or endospores, (iii) detect and quantify metabolically released CO2 in response to various different substances, and (iv) characterize growth-dependent phenomena and cell drug interactions. Particularly interesting applications arise by means of a light microscope coupled to the spectrometer. FT-IR spectra of micro-colonies containing less than 103 cells can be obtained from colony replica by a stamping technique that transfers micro-colonies growing on culture plates to a special IR sample holder. FTIR and FT-NIR Raman spectroscopy can also be used in tandem to characterize medically important microorganisms (109). Dovbeshko et al. carried out a FTIR reflectance study on surface-enhanced IR absorption of nucleic acids from tumor cells. The application of this method to nucleic acids isolated from tumor cells revealed some possible peculiarities of their structural organization, namely, the appearance of unusual sugar and base conformations, modification of the phosphate backbone, and redistribution of the H-bond net. The spectra of the RNA from the tumor cells showed more sensitivity to the grade of malignancy than the spectra of the DNA. After application of the anticancer drug doxorubicin to sensitive and resistant strains, the DNA isolated from these strains had different spectral features, especially in the region of the phosphate I and II bands (110). Derenne et al. employed a combination of FTIR spectroscopy and statistical approach to identify total amount of lipids in cancer cell extracts. In this study, initially PLS models were applied on pure lipids, and established models were further applied on cell lipid extracts, and then on lipid extracts of drug-treated cells. Six major lipids were quantified using PLS

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models and this will be useful to study lipid changes in near future. This study could not detect major spectral differences between treated and untreated cancer cell lipid extracts. However, the models established in this study were consistent and could be employed on high-throughput measurements (111). Jalkanen et al. used vibrational spectroscopy to study protein and DNA structure, hydration and binding of biomolecules, as a combined theoretical and experimental approach. The systems studied systematically were the amino acids, peptides, and a variety of small molecules. The goal was to interpret the experimentally measured vibrational spectra for these molecules to the greatest extent possible, and to understand the structure, function, and electronic properties of these molecules in their various environments. It was also believed that the application of different spectroscopic methods to biophysical and environmental assays is expanding, and therefore a true understanding of the phenomenon from a rigorous theoretical basis is required (112). Binoy et al. studied FTIR and NIR-FT Raman spectral features of the anticancer drug combretastatin-A4. The vibrational analysis showed that the molecule exhibits similar geometric behavior as cis-stilbene, and has undergone steric repulsion resulting in phenyl ring twisting with respect to the ethylenic plane (113). Bellisola et al. used FTIR microspectroscopy along with unsupervised multivariate analysis to identify infrared spectral markers for drug targeting in leukemia cells. Spectra were collected from drug-treated human K562 cells especially in the range of 4000–800 cm¡1 using single channel mercury-cadmium-telluride detector. The aim of this study is to detect and monitor transmembrane signaling steps corresponding to drugs reactions and effects of apoptosis. Spectral markers were identified in single cells related to oncogenic proteins and its associated enzymes. Chemometric approaches have classified living and apoptotic cells successfully. This approach may be useful to examine structural and biochemical effects of various drug compounds in ex vivo cell models in near future (114). Faolin et al. carried out a study on examining the effects of tissue processing on human tissue sections using vibrational spectroscopy. This study investigated the effect of freezing, formalin fixation, wax embedding, and de-waxing. Spectra were recorded from tissue sections to examine biochemical changes before, during, and after processing with both Raman and FTIR spectroscopy. New peaks due to freezing and formalin fixation as well as shifts in the amide bands resulting from changes in protein conformation and possible cross-links were found. Residual wax peaks were observed clearly in the Raman spectra. In the FTIR spectra, a single wax contribution was seen which may contaminate the characteristic CH3 deformation band in biological tissue. This study confirmed that formalin-fixed paraffin processed (FFPP) sections have diagnostic potential (115). Sahu and Mordechai studied FTIR spectroscopy in cancer detection. The areas of focus were the distinction of premalignant and malignant cells and tissues from their normal state using specific parameters obtained from the spectra. It was concluded that while the method still requires pilot studies and designed clinical trials to ensure the applicability of such systems for cancer diagnosis, substantial progress has been made so far. This has been expressed by incorporating advances in computational into the system to increase the sensitivity of the entire setup, making it an objective and sensitive technique suitable for automation to suit the demands of the medical community (116). Kobrina et al. employed combination of multivariate approach and FTIR spectroscopy to explore histological regions in intact articular cartilage. The main goal of this study is to


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investigate spatial dependent structural and molecular compositional changes of collagen and proteoglycan (PG) in articular cartilage. Both rabbit and bovine intact patellae samples were used to obtain spectral measurements in the range of 4000–720 cm¡1 with spectral resolution of 4 cm¡1. Total amide range consisting of 1200–1720 cm¡1, amide I range of 1585– 1720 cm¡1, amide II range of 1510–1584 cm¡1, and PG range of 1300–1490 cm¡1 were analyzed in this study. FCM was applied on normalized spectral data to reveal spatial biochemical differences between 2 species. Rabbit samples have shown more distinct clusters whereas bovine samples shown more complex layered structures. Differences in clustering might be caused by gradual decrease of PG/collagen ratio from top to bottom layers of cartilage (117). Whelan et al. applied FTIR spectroscopy to detect in situ DNA conformational transition. The aim of this investigation is to identify DNA transitional changes especially from B-DNA to A-DNA in eukaryotic cells. This approach has not only identified clear DNA transitions during rehydration but also provided spectral markers for this transition. Spectral data have revealed that both single- and double-stranded DNA and single-stranded RNA have shown B-DNA in hydration step. FTIR bands at 936 § 1 cm¡1 (paired AT base vibration), 1087 § 1 cm¡1 (vsym(PO2¡ )), 1051§1 cm¡1 n(C–O), and 969 § 1 cm¡1 ( C–C stretch of the DNA backbone, v(C–C)) were identified. Additionally to this, FTIR has identified the transition of B to A DNA shift of the vasym(PO2¡ ) from 1225 § 2 cm¡1 to 1238 § 1 cm¡1. Furthermore, both the second derivative spectra and principal component have shown strong absorption at shoulders (1100 and 1063 cm¡1) in all dehydrated samples. These changes in the DNA bands reflect the transition from the native B-like DNA found in live, hydrated cells to an A-like structure in a non-homogenous environment. This approach has shown great promise to FTIR spectroscopy as an analytical tool in the examination of DNA in cells so that it can be implicated in the study of disease, cell survival, and chromatin theory (118). Yang et al. applied FTIR spectroscopic mapping to analyze biochemical parameters in myocardial infarction (MI) lesions. This study has also analyzed MI in cardiac cross-sections. FTIR spectra were acquired from human tissue in the range of 4000–400 cm¡1 with spectral resolution of 8 cm¡1. FTIR mapping and FTIR original spectra based on integrated absorbance have revealed peaks at 1638 cm¡1 (collagen triple helix), 1081 cm¡1(PO2¡ symmetric stretch of nucleic acids and C–O stretch of phospholipids), 2837 cm¡1 (CH3 symmetric stretch of proteins), and 3290 cm¡1 (N–H stretch of amide A). FTIR mapping results were correlated with histopathological analysis, such as N–H stretching of red mapping area were consistent with H&E staining results and it further interpret that N–H stretching of secondary amine was involved in fibrosis after an MI. FTIR mapping has also revealed that CH3 symmetric stretch was not associated in the fibrosis process. Moreover, triple-helix structure of fibrocollagenous tissues were expansively involved in the infarction process. Furthermore, spectral data of nucleic acids revealed that nucleic acids are prevalent in normal myocardium but damaged in the infracted myocardium. This was observed in both recent and old myocardial infarction. This approach has established a link between morphologic and molecular information and assist histopathologists in better diagnosis regarding myocardial infarction (119). Theophilou et al. used ATR-FTIR spectroscopy to analyze the biochemical differences between normal, borderline, and malignant ovarian cancer tissue. Ovarian cancers involve a very complex and heterogeneity group of subtype tumors. Apart from histopathological evidence, current diagnostic tools present some limitations when it comes to discriminating

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between all these types of tumors. Hence, ATR-FTIR spectroscopy analyzed 35 benign samples, 20 borderline tumor samples, and 106 ovarian carcinoma samples. Spectral data was collected within 4000 cm¡1 to 600 cm¡1 ranges using a spectral resolution of 8 cm¡1. Spectra of malignant tissue showed an increase in lipid to protein ratio, which was calculated by analyzing the band intensities in the lipid region (1750–1730 cm¡1) in relation to the protein region (1410 cm–1390 cm¡1). In addition, the phosphate to carbohydrate ratio was slightly increased in malignant tissue when compared with benign and borderline tissue. This ratio was established by measuring the bands intensities of the phosphate region (1055– 1045 cm¡1) in relation to the carbohydrate region (1555–1535 cm¡1). PCA and LDA are 2 of the statistical methods used in this experiment. The alterations in lipid-to-protein ratio and phosphate-to-carbohydrate ratio are biomarkers that led to the discrimination between benign, baseline, and malignant tissue when performing the statistical analysis. Furthermore, the statistical methods were able to classify the data collected from the ovarian carcinoma samples into different carcinoma subtypes based on the spectral differences within this group of samples (120). The characteristic peak frequencies It is believed that accurate peak definitions can have significant influence on reliability of the results provided through different spectroscopic techniques. Studies reported to date in the literature indicate that most of the scientists have mainly used the previously published articles in order to define the data acquired from the spectra collected. However, without having a reliable and detailed database which can cover most of the required peaks in the spectral range, it would be a time-consuming task to find the meanings of different unknown peak intensities. In biological studies, for instance, where a wide range of chemical bands and functional groups can be attributed to every single peak, finding appropriate meanings, which can demonstrate the clinical importance of the technique and achieved results, can be one of the most important steps in finalizing a spectroscopic research work. As a result, and with the aim of putting these shortages aside, a wide range of most frequently seen peaks in FTIR studies are presented in Table 1.

Summary FTIR spectroscopy has become a well-accepted and widely used method to characterize biological tissues. The technique of FTIR spectroscopy has become a technique of choice for scientists interested to find the chemical structural properties of natural and synthetic tissues. Not surprisingly, increasing number of research groups are showing interest in applying FTIR spectroscopy for different objectives and methodologies, and considerable amount of time and financial resources are being allocated to this area. The information presented in this review can result in significant savings, particularly in terms of time that scientists, especially the non-spectroscopists, have to spend for defining spectral data. The literature compiled in this review will help in precise and speedy interpretation of the spectral data. The tabulated part, which is the main and comprehensive part of this article, is presented in a way that will surely make it easy to follow for researchers and will help in understanding the important characteristic peaks that are present in FTIR spectra of biological tissues. It is envisaged that considering the type of samples being investigated and the chemical bands


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and functional groups that can possibly exist in the samples, the peak frequencies can be located in the table, and the appropriate interpretations could be made with confidence. Furthermore, having a detailed knowledge of the list of peaks that can be assigned to different biochemical compounds (such as lipids, proteins, or nucleic acids) would lead to a better correlation between the chemical structural and the medical aspects of spectroscopy. The lipid contents and the chemical structure of these compounds can be evaluated using peaks frequencies at 2956 cm¡1 (asymmetric stretching vibration of CH3 of acyl chains), 2922 cm¡1 (asymmetric stretching vibration of CH2 of acyl chains), 2874 cm¡1 (symmetric stretching vibration of CH3 of acyl chains), 2852 cm¡1 (symmetric stretching vibration of CH2 of acyl chains), and 1600–1800 cm¡1 (C H O stretching). The specifications of protein contents of biological samples can also be understood from 1717 cm¡1 (Amide I, arising from CHO stretching vibration), 1500–600 cm¡1 (Amide II, N H bending vibration coupled to C N stretching), and 1220–1350 cm¡1 (Amide III, C N stretching and N H in plane bending, often with significant contributions from CH2 wagging vibrations). The peaks related to nucleic acids are as follow: 1717 cm¡1 (C H O stretching vibration of purine base), 1666 cm¡1 (C H O stretching vibration of pyrimidine base), 1220–1240 cm¡1 (asymmetric PO2¡ stretching), 1117 cm¡1 (C O stretching vibration of C OH group of ribose), 1040– 100 cm¡1 (symmetric stretching of phosphate groups of phosphodiester linkages), and 1050–70 cm¡1 (C O C stretching) (23). However, it would be more useful to have further and continuous review of this field to improve this work on regular basis (every 5 years) and to keep it updated to prepare a unique database that can be used for different methodologies. In addition, the different research topics being covered on a regular basis, this review may provide significant assistance not only to spectroscopists, but to other clinical and non-clinical researchers, who are working in research disciplines related to biomaterials, dental materials, chemistry, biophysics, cell biology, tissue engineering, medicine and dentistry, and cancer research, aiming to understand the chemical pathways to the progression of disease through spectroscopic means (121–137).

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