Abstract
A potential role of optical technologies in medicine including micro-Raman spectroscopy is diagnosis of bacteria, cells and tissues which is covered in this chapter. The main advantage of Raman-based methods to complement and augment diagnostic tools is that unsurpassed molecular specificity is achieved without labels and in a nondestructive way. Principles and applications of micro-Raman spectroscopy in the context of medicine will be described. First, Raman spectra of biomolecules representing proteins, nucleic acids, lipids and carbohydrates are introduced. Second, microbial applications are summarized with the focus on typing on species and strain level, detection of infections, antibiotic resistance and biofilms. Third, cytological applications are presented to classify single cells and study cell metabolism and drug–cell interaction. Fourth, applications to tissue characterization start with discussion of lateral resolution for Raman imaging followed by Raman-based detection of pathologies and combination with other modalities. Finally, an outlook is given to translate micro-Raman spectroscopy as a clinical tool to solve unmet needs in point-of-care applications and personalized treatment of diseases.
References
[1] Krafft C, von Eggeling F, Guntinas-Lichius O, Hartmann A, Waldner MJ, Neurath MF, et al. Ex-vivo and in vivo optical molecular pathology. J Biophotonics. 2018;11:e201700236.10.1002/jbio.201700236Suche in Google Scholar
[2] De Gelder J, De Gussem K, Vandenabeele P, Moens L. Reference database of Raman spectra of biological molecules. J Raman Spectrosc. 2007;38:1133–47.10.1002/jrs.1734Suche in Google Scholar
[3] Maquelin K, Kirschner C, Choo-Smith LP, van den Braak N, Endtz HP, Naumann D, et al. Identification of medically relevant microorganisms by vibrational spectroscopy. J Microbiol Meth. 2002;51:255–71.10.1016/S0167-7012(02)00127-6Suche in Google Scholar
[4] Pahlow S, Meisel S, Cialla-May D, Weber K, Rösch P, Popp J. Isolation and identification of bacteria by means of Raman spectroscopy. Adv Drug Del Rev. 2015;89:105–20.10.1016/j.addr.2015.04.006Suche in Google Scholar PubMed
[5] Ramoji A, Galler K, Glaser U, Henkel T, Mayer G, Dellith J, et al. Characterization of different substrates for Raman spectroscopic imaging of eukaryotic cells. J Raman Spectrosc. 2016;47:773–86.10.1002/jrs.4899Suche in Google Scholar
[6] Pahlow S, Kloß S, Blättel V, Kirsch K, Hübner U, Cialla D, et al. Isolation and enrichment of pathogens with a surface‐modified aluminium chip for Raman spectroscopic applications. Chem Phys Chem. 2013;14:3600–5.10.1002/cphc.201300543Suche in Google Scholar PubMed
[7] Maquelin K, Choo-Smith L-P, Endtz HP, Bruining H, Puppels G. Rapid identification of Candida species by confocal Raman microspectroscopy. J Clin Microbiol. 2002;40:594–600.10.1128/JCM.40.2.594-600.2002Suche in Google Scholar PubMed PubMed Central
[8] Buijtels PC, Willemse-Erix H, Petit P, Endtz HP, Puppels GJ, Verbrugh HA, et al. Rapid identification of mycobacteria by Raman spectroscopy. J Clin Microbiol. 2008;46:961–5.10.1128/JCM.01763-07Suche in Google Scholar PubMed PubMed Central
[9] Rebrošová K, Šiler M, Samek O, Ruzicka F, Bernatova S, Hola V., et al. Rapid identification of staphylococci by Raman spectroscopy. Sci Rep. 2017;7:14846.10.1038/s41598-017-13940-wSuche in Google Scholar PubMed PubMed Central
[10] Wulf M, Willemse-Erix D, Verduin C, Puppels G, van Belkum A, Maquelin K. The use of Raman spectroscopy in the epidemiology of methicillin-resistant Staphylococcus aureus of human-and animal-related clonal lineages. Clin Microbiol Infect. 2012;18:147–52.10.1111/j.1469-0691.2011.03517.xSuche in Google Scholar PubMed
[11] Te Witt R, Vaessen N, Melles D, Lekkerkerk WS, van der Zwaan EA, Zandijk WH, et al. Good performance of the SpectraCellRA system for typing of methicillin-resistant staphylococcus aureus isolates. J Clin Microbiol. 2013;51:1434–8.10.1128/JCM.02101-12Suche in Google Scholar PubMed PubMed Central
[12] Kloss S, Kampe B, Sachse S, Rösch P, Straube E, Pfister W, Kiehntopf M, Popp J. Culture independent Raman spectroscopic identification of urinary tract infection pathogens: a proof of principle study. Anal Chem. 2013;85:9610–6.10.1021/ac401806fSuche in Google Scholar PubMed
[13] Schröder U-C, Ramoji A, Glaser U, Sachse S, Leiterer C, Csaki A, et al. Combined dielectrophoresis-Raman setup for the classification of pathogens recovered from the urinary tract. Anal Chem. 2013;85:10717–24.10.1021/ac4021616Suche in Google Scholar PubMed
[14] Harz M, Kiehntopf M, Stöckel S, Rösch P, Straube E, Deufel T, et al. Direct analysis of clinical relevant single bacterial cells from cerebrospinal fluid during bacterial meningitis by means of micro‐Raman spectroscopy. J Biophotonics. 2009;2:70–80.10.1002/jbio.200810068Suche in Google Scholar PubMed
[15] Willemse-Erix DF, Scholtes-Timmerman MJ, Jachtenberg J-W, van Leeuwen WB, Horst–Kreft D, Bakker Schut TC, et al. Optical fingerprinting in bacterial epidemiology: Raman spectroscopy as a real-time typing method. J Clin Microbiol. 2009;47:652–9.10.1128/JCM.01900-08Suche in Google Scholar PubMed PubMed Central
[16] Kirschner C, Maquelin K, Pina P, Ngo Thi NA, Choo-Smith LP, Sockalingum GD, et al. Classification and identification of enterococci: a comparative phenotypic, genotypic, and vibrational spectroscopic study. J Clin Microbiol. 2001;39:1763–70.10.1128/JCM.39.5.1763-1770.2001Suche in Google Scholar PubMed PubMed Central
[17] Große C, Bergner N, Dellith J, Heller R, Bauer M, Mellmann A, et al. Label-free imaging and spectroscopic analysis of intracellular bacterial infections. Anal Chem. 2015;87:2137–42.10.1021/ac503316sSuche in Google Scholar PubMed
[18] Voor in ‘T Holt AF, Severin JA, Goessens WH, Te Witt R, Vos MC. Instant typing is essential to detect transmission of extended-spectrum beta-lactamase-producing Klebsiella species. PLoS One. 2015;10:e0136135.10.1371/journal.pone.0136135Suche in Google Scholar PubMed PubMed Central
[19] Assmann C, Kirchhoff J, Beleites C, Hey J, Kostudis S, Pfister W, et al. Identification of vancomycin interaction with Enterococcus faecalis within 30 min of interaction time using Raman spectroscopy. Anal Bioanal Chem. 2015;407:8343–52.10.1007/s00216-015-8912-ySuche in Google Scholar PubMed
[20] Dekter H, Orelio C, Morsink M, Tektas S, Vis B, Te Witt R, et al. Antimicrobial susceptibility testing of Gram-positive and-negative bacterial isolates directly from spiked blood culture media with Raman spectroscopy. Euro J Clin Microbiol Infectious Diseas. 2017;36:81–9.10.1007/s10096-016-2773-ySuche in Google Scholar PubMed
[21] Athamneh A, Alajlouni R, Wallace R, Seleem M, Senger R. Phenotypic profiling of antibiotic response signatures in Escherichia coli using Raman spectroscopy. Antimicrob Agents Chemother. 2014;58:1302–14.10.1128/AAC.02098-13Suche in Google Scholar PubMed
[22] Schröder UC, Kirchhoff J, Hübner U, Mayer G, Glaser U, Henkel T, et al. On‐chip spectroscopic assessment of microbial susceptibility to antibiotics within 3.5 hours. J Biophotonics. 2017;10:1547–57.10.1002/jbio.201600316Suche in Google Scholar PubMed
[23] Beier BD, Quivey RG, Berger AJ. Identification of different bacterial species in biofilms using confocal Raman microscopy. J Biomed Opt. 2010;15:066001.10.1117/1.3505010Suche in Google Scholar PubMed
[24] Muhamadali H, Chisanga M, Subaihi A, Goodacre R. Combining Raman and FT-IR spectroscopy with quantitative isotopic labeling for differentiation of E. coli cells at community and single cell levels. Anal Chem. 2015;87:4578–86.10.1021/acs.analchem.5b00892Suche in Google Scholar PubMed
[25] Hildebrandt ER, Cozzarelli NR. Comparison of recombination in vitro and in E. coli cells: measure of the effective concentration of DNA in vivo. Cell. 1995;81:331–40.10.1016/0092-8674(95)90386-0Suche in Google Scholar
[26] Schie IW, Kiselev R, Krafft C, Popp J. Rapid acquisition of mean Raman spectra of eukaryotic cells for a robust single cell classification. Analyst. 2016;141:6387–95.10.1039/C6AN01018KSuche in Google Scholar PubMed
[27] Puppels GJ, Olminkhof JH, Segers-Nolten GM, Otto C, De Mul FF, Greve J. Laser irradiation and Raman spectroscopy of single living cells and chromosomes: sample degradation occurs with 514.5 nm but not with 660 nm laser light. Exp Cell Res. 1991;195:361–7.10.1016/0014-4827(91)90385-8Suche in Google Scholar PubMed
[28] Notingher I, Verrier S, Romanska H, Bishop AE, Polak JM, Hench LL. In situ characterisation of living cells by Raman spectroscopy. Spectros (Amsterdam, Netherlands). 2002;15:43.Suche in Google Scholar
[29] Pavillon N, Hobro AJ, Smith NI. Cell optical density and molecular composition revealed by simultaneous multimodal label-free imaging. Biophys J. 2013;105:1123–32.10.1016/j.bpj.2013.07.031Suche in Google Scholar PubMed PubMed Central
[30] Pavillon N, Smith NI. Implementation of simultaneous quantitative phase with Raman imaging. EPJ Tech Instrum. 2015;2:5.10.1140/epjti/s40485-015-0015-9Suche in Google Scholar
[31] Butler HJ, Ashton L, Bird B, Cinque G, Curtis K, Dorney J, et al. Using Raman spectroscopy to characterize biological materials. Nat Protoc. 2016;11:664.10.1038/nprot.2016.036Suche in Google Scholar PubMed
[32] Neugebauer U, Clement JH, Bocklitz T, Krafft C, Popp J. Identification and differentiation of single cells from peripheral blood by Raman spectroscopic imaging. J Biophotonics. 2010;3:579–87.10.1002/jbio.201000020Suche in Google Scholar PubMed
[33] Neugebauer U, Bocklitz T, Clement JH, Krafft C, Popp J. Towards detection and identification of circulating tumour cells using Raman spectroscopy. Analyst. 2010;135:3178–82.10.1039/c0an00608dSuche in Google Scholar PubMed
[34] Dochow S, Krafft C, Neugebauer U, Bocklitz T, Henkel T, Mayer G, et al. Tumour cell identification by means of Raman spectroscopy in combination with optical traps and microfluidic environments. Lab Chip. 2011;11:1484–90.10.1039/c0lc00612bSuche in Google Scholar PubMed
[35] Dochow S, Beleites C, Henkel T, Mayer G, Albert G, Clement J, et al. Quartz microfluidic chip for tumour cell identification by Raman spectroscopy in combination with optical traps. Anal Bioanal Chem. 2013;405:2743–6.10.1007/s00216-013-6726-3Suche in Google Scholar PubMed
[36] Schie IW, Rüger J, Mondol AS, Ramoji A, Neugebauer U, Krafft C, et al. High-throughput screening Raman spectroscopy platform for label-free cellomics. Anal Chem. 2018;90:2023–30.10.1021/acs.analchem.7b04127Suche in Google Scholar PubMed
[37] Duraipandian S, Traynor D, Kearney P, Martin C, O’Leary JJ, Lyng FM. Raman spectroscopic detection of high-grade cervical cytology: using morphologically normal appearing cells. Sci Rep. 2018;8:15048.10.1038/s41598-018-33417-8Suche in Google Scholar PubMed PubMed Central
[38] Yosef HK, Krauß SD, Lechtonen T, Jütte H, Tannapfel A, Käfferlein HU, et al. Noninvasive diagnosis of high-grade urothelial carcinoma in urine by Raman spectral imaging. Anal Chem. 2017;89:6893–9.10.1021/acs.analchem.7b01403Suche in Google Scholar PubMed
[39] Tolstik T, Marquardt C, Matthäus C, Bergner N, Bielecki C, Krafft C, et al. Discrimination and classification of liver cancer cells and proliferation states by Raman spectroscopic imaging. Analyst. 2014;139:6036–43.10.1039/C4AN00211CSuche in Google Scholar PubMed
[40] Hedegaard M, Krafft C, Ditzel HJ, Johansen LE, Hassing S, Popp J. Discriminating isogenic cancer cells and identifying altered unsaturated fatty acid content as associated with metastasis status, using k-means clustering and partial least squares-discriminant analysis of Raman maps. Anal Chem. 2010;82:2797–802.10.1021/ac902717dSuche in Google Scholar PubMed
[41] Vanna R, Ronchi P, Lenferink AT, Tresoldi C, Morasso C, Mehn D, et al. Label-free imaging and identification of typical cells of acute myeloid leukaemia and myelodysplastic syndrome by Raman microspectroscopy. Analyst. 2015;140:1054–64.10.1039/C4AN02127DSuche in Google Scholar PubMed
[42] Talari AC, Evans CA, Holen I, Coleman RE, Rehman IU. Raman spectroscopic analysis differentiates between breast cancer cell lines. J Raman Spectrosc. 2015;46:421–7.10.1002/jrs.4676Suche in Google Scholar
[43] Klossa J, Daliphard S, Troussard X, Vielh P, Manfait M, Angulo J, et al. Using biophotonics techniques to retrieve prognostic intracellular signatures. Irbm. 2011;32:72–5.10.1016/j.irbm.2011.01.039Suche in Google Scholar
[44] Krafft C, Knetschke T, Funk RH, Salzer R. Studies on stress-induced changes at the subcellular level by Raman microspectroscopic mapping. Anal Chem. 2006;78:4424–9.10.1021/ac060205bSuche in Google Scholar PubMed
[45] Hobro AJ, Pavillon N, Fujita K, Ozkan M, Coban C, Smith NI. Label-free Raman imaging of the macrophage response to the malaria pigment hemozoin. Analyst. 2015;140:2350–9.10.1039/C4AN01850HSuche in Google Scholar PubMed
[46] Konorov SO, Schulze HG, Piret JM, Blades MW, Turner RF. Label-free determination of the cell cycle phase in human embryonic stem cells by Raman microspectroscopy. Anal Chem. 2013;85:8996–9002.10.1021/ac400310bSuche in Google Scholar PubMed
[47] Hsu J-F, Hsieh P-Y, Hsu H-Y, Shigeto S. When cells divide: label-free multimodal spectral imaging for exploratory molecular investigation of living cells during cytokinesis. Sci Rep. 2015;5:17541.10.1038/srep17541Suche in Google Scholar PubMed PubMed Central
[48] Stiebing C, Matthaeus C, Krafft C, Keller AA, Weber K, Lorkowski S, et al. Complexity of fatty acid distribution inside human macrophages on single cell level using Raman micro-spectroscopy. Anal Bioanal Chem. 2014;406:7037–46.10.1007/s00216-014-7927-0Suche in Google Scholar PubMed
[49] Matthaus C, Krafft C, Dietzek B, Brehm BR, Lorkowski S, Popp J. Noninvasive imaging of intracellular lipid metabolism in macrophages by Raman microscopy in combination with stable isotopic labeling. Anal Chem. 2012;84:8549–56.10.1021/ac3012347Suche in Google Scholar PubMed
[50] Naemat A, Elsheikha HM, Boitor RA, Notingher I. Tracing amino acid exchange during host-pathogen interaction by combined stable-isotope time-resolved Raman spectral imaging. Sci Rep. 2016;6:20811.10.1038/srep20811Suche in Google Scholar PubMed PubMed Central
[51] El-Mashtoly SF, Yosef HK, Petersen D, Mavarani L, Maghnouj A, Hahn S, et al. Label-free Raman spectroscopic imaging monitors the integral physiologically relevant drug responses in cancer cells. Anal Chem. 2015;87:7297–304.10.1021/acs.analchem.5b01431Suche in Google Scholar PubMed
[52] Braeutigam K, Bocklitz T, Schmitt M, Roesch P, Popp J. Raman spectroscopic imaging for the real-time detection of chemical changes associated with docetaxel exposure. Chem Phys Chem. 2013;14:550–3.10.1002/cphc.201200800Suche in Google Scholar PubMed
[53] Salehi H, Derely L, Vegh AG, Durand JC, Gergely C, Larroque C, et al. Label-free detection of anticancer drug paclitaxel in living cells by confocal Raman microscopy. Appl Phys Lett. 2013;102:113701.10.1063/1.4794871Suche in Google Scholar
[54] Salehi H, Middendorp E, Panayotov I, Dutilleul PY, Vegh AG, Ramakrishnan SK, et al. Confocal Raman data analysis enables identifying apoptosis of MCF-7 cells caused by anticancer drug paclitaxel. J Biomed Opt. 2013;18:056010.10.1117/1.JBO.18.5.056010Suche in Google Scholar PubMed
[55] Schie IW, Alber L, Gryshuk AL, Chan JW. Investigating drug induced changes in single, living lymphocytes based on Raman micro-spectroscopy. Analyst. 2014;139:2726–33.10.1039/C4AN00250DSuche in Google Scholar PubMed
[56] Draux F, Gobinet C, Sule-Suso J, Manfait M, Jeannesson P, Sockalingum GD. Raman imaging of single living cells: probing effects of non-cytotoxic doses of an anti-cancer drug. Analyst. 2011;136:2718–25.10.1039/c0an00998aSuche in Google Scholar PubMed
[57] Huang H, Shi H, Feng SY, Chen W, Yu Y, Lin D, et al. Confocal Raman spectroscopic analysis of the cytotoxic response to cisplatin in nasopharyngeal carcinoma cells. Anal Meth. 2013;5:260–6.10.1039/C2AY25684CSuche in Google Scholar
[58] El-Mashtoly SF, Petersen D, Yosef HK, Mosig A, Reinacher-Schick A, Kötting C, et al. Label-free imaging of drug distribution and metabolism in colon cancer cells by Raman microscopy. Analyst. 2014;139:1155–61.10.1039/c3an01993dSuche in Google Scholar PubMed
[59] Cheng JX, Xie XS. Coherent Raman scattering. Boca Raton, FL, USA: CRC Press, 2012.Suche in Google Scholar
[60] Wei D, Chen S, Liu Q. Review of fluorescence suppression techniques in Raman spectroscopy. Appl Spectrosc Rev. 2015;50:387–406.10.1080/05704928.2014.999936Suche in Google Scholar
[61] Diem M, Mazur A, Lenau K, Schubert J, Bird B, Miljkovic M, et al. Molecular pathology via IR and Raman spectral imaging. J Biophotonics. 2013;6:855–86.10.1002/jbio.201300131Suche in Google Scholar PubMed
[62] Krafft C, Codrich D, Pelizzo G, Sergo V. Raman and FTIR microscopic imaging of colon tissue: a comparative study. J Biophoton. 2008;1:154–69.10.1002/jbio.200710005Suche in Google Scholar PubMed
[63] Krafft C, Belay B, Bergner N, Bergner N, Romeike BF, Reichart R, et al. Advances in optical biopsy–correlation of malignancy and cell density of primary brain tumors using Raman microspectroscopic imaging. Analyst. 2012;137:5533–7.10.1039/c2an36083gSuche in Google Scholar PubMed
[64] Bergner N, Krafft C, Geiger KD, Kirsch M, Schackert G, Popp J. Unsupervised unmixing of Raman microspectroscopic images for morphological analysis of non-dried brain tumor specimens. Anal Bioanal Chem. 2012;403:719–25.10.1007/s00216-012-5858-1Suche in Google Scholar PubMed
[65] Bergner N, Medyukhina A, Geiger KD, Kirsch M, Schackert G, Krafft C, et al. Hyperspectral unmixing of Raman micro-images for assessment of morphological and chemical parameters in non-dried brain tumor specimens. Anal Bioanal Chem. 2013;405:8719–28.10.1007/s00216-013-7257-7Suche in Google Scholar PubMed
[66] Bergner N, Bocklitz T, Romeike BF, Reichart R, Kalff R, Krafft C, et al. Identification of primary tumors of brain metastases by Raman imaging and support vector machines. Chemom Intell Lab Syst. 2012;117:224–32.10.1016/j.chemolab.2012.02.008Suche in Google Scholar
[67] Gajjar K, Heppenstall LD, Pang W, Ashton KM, Trevisan J, Patel II, et al. Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis. Anal Meth. 2013;5:89–102.10.1039/C2AY25544HSuche in Google Scholar PubMed PubMed Central
[68] Abramczyk H, Brozek-Pluska B, Surmacki J, Jablonska-Gajewicz J, Kordek R. Raman ‘optical biopsy’ of human breast cancer. Prog Biophys Mol Biol. 2012;108:74–81.10.1016/j.pbiomolbio.2011.10.004Suche in Google Scholar PubMed
[69] Mavarani L, Petersen D, El-Mashtoly SF, Mosig A, Tannapfel A, Kötting C, et al. Spectral histopathology of colon cancer tissue sections by Raman imaging with 532 nm excitation provides label free annotation of lymphocytes, erythrocytes and proliferating nuclei of cancer cells. Analyst. 2013;138:4035–9.10.1039/c3an00370aSuche in Google Scholar PubMed
[70] Horsnell JD, Smith JA, Sattlecker M, Sammon A, Christie-Brown J, Kendall C, Stone N. Raman spectroscopy - A potential new method for the intra-operative assessment of axillary lymph nodes. Surgeon-J Royal Colleges Surgeons Edinburgh Ireland. 2012;10:123–7.10.1016/j.surge.2011.02.004Suche in Google Scholar PubMed
[71] Bielecki C, Bocklitz TW, Schmitt M, Krafft C, Marquardt C, Gharbi A, et al. Classification of inflammatory bowel diseases by means of Raman spectroscopic imaging of epithelium cells. J Biomed Opt. 2012;17:076030.10.1117/1.JBO.17.7.076030Suche in Google Scholar PubMed
[72] Minamikawa T, Harada Y, Koizumi N, Okihara K, Kamoi K, Yanagisawa A, et al. Label-free detection of peripheral nerve tissues against adjacent tissues by spontaneous Raman microspectroscopy. Histochem Cell Biol. 2013;139:181–93.10.1007/s00418-012-1015-3Suche in Google Scholar PubMed
[73] Cals FL, Schut TC, Hardillo JA, de Jong RJ, Koljenovic S, Puppels GJ. Investigation of the potential of Raman spectroscopy for oral cancer detection in surgical margins. Lab Invest. 2015;95:1186–96.10.1038/labinvest.2015.85Suche in Google Scholar PubMed
[74] Stewart S, Kirschner H, Treado PJ, Priore R, Tretiakova M, Cohen JK. Distinguishing between renal oncocytoma and chromophobe renal cell carcinoma using Raman molecular imaging. J Raman Spectrosc. 2014;45:274–80.10.1002/jrs.4460Suche in Google Scholar
[75] Marzec KM, Wrobel TP, Rygula A, Maslak E, Jasztal A, Fedorowicz A, et al. Visualization of the biochemical markers of atherosclerotic plaque with the use of Raman, IR and AFM. J Biophotonics. 2014;7:744–56.10.1002/jbio.201400014Suche in Google Scholar PubMed
[76] Lattermann A, Matthäus C, Bergner N, Beleites C, Romeike BF, Krafft C, et al. Characterization of atherosclerotic plaque depositions by Raman and FTIR imaging. J Biophotonics. 2013;6:110–21.10.1002/jbio.201200146Suche in Google Scholar PubMed
[77] Pilarczyk M, Mateuszuk L, Rygula A, Kepczynski M, Chlopicki S, Baranska M, et al. Endothelium in spots - high-content imaging of lipid rafts clusters in db/db mice. PLoS One. 2014;9:e106065.10.1371/journal.pone.0106065Suche in Google Scholar PubMed PubMed Central
[78] Kong K, Rowlands CJ, Varma S, Perkins W, Leach IH, Koloydenko AA, et al. Diagnosis of tumors during tissue-conserving surgery with integrated autofluorescence and Raman scattering microscopy. Proc Natl Acad Sci USA. 2013;110:15189–94.10.1073/pnas.1311289110Suche in Google Scholar PubMed PubMed Central
[79] Kong K, Zaabar F, Rakha E, Ellis I, Koloydenko A, Notingher I. Towards intra-operative diagnosis of tumours during breast conserving surgery by selective-sampling Raman micro-spectroscopy. Phys Med Biol. 2014;59:6141–52.10.1088/0031-9155/59/20/6141Suche in Google Scholar PubMed
[80] Patil CA, Kirshnamoorthi H, Ellis DL, van Leeuwen TG, Mahadevan-Jansen A. A clinical instrument for combined Raman spectroscopy-optical coherence tomography of skin cancers. Lasers Surg Med. 2011;43:143–51.10.1002/lsm.21041Suche in Google Scholar PubMed PubMed Central
[81] Ashok PC, Praveen BB, Bellini N, Riches A, Dholakia K, Herrington CS. Multi-modal approach using Raman spectroscopy and optical coherence tomography for the discrimination of colonic adenocarcinoma from normal colon. Biomed Opt Express. 2013;4:2179–86.10.1364/BOE.4.002179Suche in Google Scholar PubMed PubMed Central
[82] Bocklitz T, Braeutigam K, Urbanek A, Hoffman F, von Eggeling F, Ernst G, et al. Novel workflow for combining Raman spectroscopy and MALDI-MSI for tissue based studies. Anal Bioanal Chem. 2015;407:7865–73.10.1007/s00216-015-8987-5Suche in Google Scholar PubMed
© 2019 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Micro-Raman spectroscopy in medicine
- Computational prediction of toxicity of small organic molecules: state-of-the-art
- Phthalocyanines core-modified by P and S and their complexes with fullerene C60: DFT study
- From beams to glass: determining compositions to study provenance and production techniques
- Computational methods for NMR and MS for structure elucidation I: software for basic NMR
- Conformations and interactions comparison between R- and S-methadone in wild type CYP2B6, 2D6 and 3A4
- Applications of magnetic resonance imaging in chemical engineering
- Combined approach of homology modeling, molecular dynamics, and docking: computer-aided drug discovery
Artikel in diesem Heft
- Micro-Raman spectroscopy in medicine
- Computational prediction of toxicity of small organic molecules: state-of-the-art
- Phthalocyanines core-modified by P and S and their complexes with fullerene C60: DFT study
- From beams to glass: determining compositions to study provenance and production techniques
- Computational methods for NMR and MS for structure elucidation I: software for basic NMR
- Conformations and interactions comparison between R- and S-methadone in wild type CYP2B6, 2D6 and 3A4
- Applications of magnetic resonance imaging in chemical engineering
- Combined approach of homology modeling, molecular dynamics, and docking: computer-aided drug discovery