Clinical Spectroscopy最新文献

{"title":"Validated differentiation of Listeria monocytogenes serogroups by FTIR spectroscopy using an Artificial Neural Network based classifier in an accredited official food control laboratory","authors":"Helene Oberreuter,&nbsp;Martin Dyk,&nbsp;Jörg Rau","doi":"10.1016/j.clispe.2023.100030","DOIUrl":"https://doi.org/10.1016/j.clispe.2023.100030","url":null,"abstract":"<div><p><em>Listeria monocytogenes</em> is a well-known human pathogen, and especially the young, the elderly, otherwise immunocompromised individuals or pregnant women might suffer severe health consequences from listeriosis. Up to date, Fourier-Transform Infrared (FTIR) spectroscopical methods have been established for decades as a valuable means to differentiate between microbiological specimens at different taxonomical levels. In recent years, machine-based learning methods using Artificial Neural Networks (ANN) have highly advanced the discriminatory power of distinguishing spectrally closely related units such as serogroups of a given species. The present report describes the classification performance evaluation of a manufacturer (Bruker Daltonics, Bremen, Germany) - provided <em>L. monocytogenes</em> serogroup classifier by means of a formalized external validation carried out in a single laboratory. <em>N =</em> 630 absorption spectra from <em>n =</em> 94 food <em>L. monocytogenes</em> isolates pertaining to <em>n =</em> 11 serotypes / <em>n =</em> 3 serogroups were recorded on the IR Biotyper (Bruker Daltonics) and subsequently typed by the given classifier. The quantitative evaluation of inclusivity and exclusivity was performed following the principles of the Guidelines for Validating Species Identifications Using MALDI-TOF-MS issued by the German Federal Office of Consumer Protection (BVL) for a targeted identification. The FTIR classifier allocated all <em>n =</em> 486 spectra from <em>n =</em> 71 serogroup 1/2 and 4 isolates correctly to their respective serogroups, resulting in a true-positive rate of 100%. All remaining <em>n =</em> 144 spectra from <em>n =</em> 23 isolates of serogroup 3 were correctly allocated to an arbitrarily combined class entity of serogroups 3 and 7, likewise yielding both inclusivity and exclusivity rates of 100%. Consequently, in our official food control laboratory, this validated IR Biotyper method has been integrated into the accredited workflow for <em>L. monocytogenes</em> analysis in food samples according to ISO 11290, followed by MALDI-TOF MS confirmation on the species level to subsequent serogrouping and pre-selection by FTIR spectroscopy for Whole Genome Sequencing (WGS). This study confirmed that FTIR spectroscopy in combination with Artificial Neural Networks proves to be a reliable and thus valuable tool for the differentiation of the most common serogroups from <em>Listeria monocytogenes</em>. The application of FTIR spectroscopy saves valuable resources with respect to labor and time and thus facilitates outbreak analyses of the clinically relevant severe food-borne disease listeriosis where potentially a high number of isolates are involved.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"5 ","pages":"Article 100030"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666054723000078/pdfft?md5=880a67e7273b952c56bd632dcf904a21&pid=1-s2.0-S2666054723000078-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91992742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid detection of heart failure using a spectroscopic liquid biopsy","authors":"Loren Christie ,&nbsp;Alexandra Sala ,&nbsp;James M. Cameron ,&nbsp;Justin J.A. Conn ,&nbsp;David S. Palmer ,&nbsp;William J. McGeown ,&nbsp;Jane A. Cannon ,&nbsp;John Sharp ,&nbsp;Matthew J. Baker","doi":"10.1016/j.clispe.2023.100029","DOIUrl":"https://doi.org/10.1016/j.clispe.2023.100029","url":null,"abstract":"<div><p>Heart disease is growing annually across the globe with numbers expected to rise to 46% of the population by 2030. Early detection is vital for several reasons, firstly it improves the long-term prognosis of the patient by admitting them through the appropriate pathway faster, secondly it reduces healthcare costs by streamlining diagnosis and finally, in combination with management or treatment, it can prevent the progression of the disease which in turn improves the patient’s quality of life. Therefore, there lies an increasing need to develop assays which can rapidly detect heart disease at an early stage. The Dxcover® liquid biopsy platform employs infrared spectroscopy and artificial intelligence, to quickly analyse minute amounts of patient serum. In this study, discrimination between healthy controls and diseased patients was obtained with an area under the receiver operating characteristic curve (AUC) of 0.89. When assessing the heart failure vs all patients, which is most akin to what would be observed in a triage setting, the model when tuned to a minimum of 45% specificity yielded a sensitivity of 89% and an NPV of 0.996, conversely when sensitivity was set at a 45% minimum, the specificity was 96%, giving an NPV of 0.991 when using a 1.5% prevalence. Other models were assessed in parallel, but the performance of the ORFPLS model was overall superior to the other models tested. In this large scale (n = 404) proof-of-concept study, we have shown that the Dxcover liquid biopsy platform has the potential to be a viable triage tool in emergency and routine situations for the diagnosis of heart failure.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"5 ","pages":"Article 100029"},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666054723000066/pdfft?md5=f6d590d7eeddc8488d1533606c6ff167&pid=1-s2.0-S2666054723000066-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91959426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Raman spectroscopic analysis of human serum samples of convalescing COVID-19 positive patients","authors":"Naomi Jackson ,&nbsp;Jaythoon Hassan ,&nbsp;Hugh J. Byrne","doi":"10.1016/j.clispe.2023.100028","DOIUrl":"https://doi.org/10.1016/j.clispe.2023.100028","url":null,"abstract":"<div><p>Rapid screening, detection and monitoring of viral infection is of critical importance, as exemplified by the rapid spread of SARS-CoV-2, leading to the worldwide pandemic of COVID-19. This is equally the case for the stages of patient convalescence as for the initial stages of infection, to understand the medium and long terms effects, as well as the efficacy of therapeutic interventions. Optical spectroscopic techniques potentially offer an alternative to currently employed techniques of screening for the presence, or the response to infection. In this study, the ability of Raman spectroscopy to distinguish between samples of the serum of convalescent COVID-19 positive patients and COVID-19 negative serum samples, and to further analyse and quantify systemic responses, was explored. The study included serum samples of patients who had been tested for SARS-CoV-2 specific IgG and IgM responses between 25 and 134 days after the infection was identified. Both COVID-19 positive and negative groups included males and females who ranged in age from 21 to 81 years old. No correlation was apparent between the specified SARS-CoV-2 specific IgG and IgM immunoglobulin levels of the positive group, their sex, or age. Raman spectroscopic measurements were performed at 785 nm, in liquid serum, thawed from frozen, and spectra were pre-processed to remove the contribution of water, normalising to the water content. Principal components analysis of the spectral dataset over the range 400–1800 cm^-1 provided no clear indication of a difference between normal serum and SARS-CoV-2 positive serum. A selection of 5 of the samples, which were available in sufficient volume, were fractionated by centrifugal filtration, and the 100 kDa, 50 kDa, 30 kDa, and 10 kDa concentrates similarly analysed by Raman spectroscopy. Partial least squares regression analysis revealed a negative correlation between the spectral profile of the 30 kDa fractions and SARS-CoV-2 specific IgG antibody levels, potentially indicating an association with depleted glutathione levels. The study supports a potential role of Raman screening of blood serum for monitoring of SARS-CoV-2 infection, but also in longitudinal studies of disease progression, long term effects, and therapeutic interventions.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"5 ","pages":"Article 100028"},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49708552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of optical spectroscopy in diagnosing and monitoring breast cancers: A technical review","authors":"Afshan Shirkavand ,&nbsp;Mozhdeh Babadi ,&nbsp;Leila Ataie Fashtami ,&nbsp;Ezeddin Mohajerani","doi":"10.1016/j.clispe.2023.100027","DOIUrl":"https://doi.org/10.1016/j.clispe.2023.100027","url":null,"abstract":"<div><p>Breast cancer is one of the most prevalent cancers among the global women population. It is due to the development of malignant cells in the breast tissue based on external or internal causes. The stages of detecting breast cancer include screening, diagnosis, and prognosis. Multiple imaging modalities, including digital Mammography, Ultrasonography, breast MRI, CT scan, and PET are applied for screening, diagnosis, identifying the stage of the tumor, classifying the developmental trend of the disease, and monitoring the treatment response. These modalities are commonly used in most fields of medicine, and have their merits and drawbacks. There are some optical technologies which have been developed in the diagnostic field. Optical imaging, and spectroscopy are known as real-time, sensitive, and non-invasive detecting approaches for human cancers in inaccessible locations, which use light propagation through the tissue to assess the optical properties. Optical techniques are used to measure optical and physiological properties of healthy breast tissue to discriminate abnormalities. Optical spectroscopy and fluorescence spectroscopy are some of the technologies for breast cancer detection. Such technologies can be combined with other modalities based on the capability of light guidance using optical fibers. Moreover, optical imaging offers potency for image-guided surgery. We review and discuss the broad range of methodologies and applications. Through a brief review of breast physiology, we discuss the various instrumental techniques and the related methods of optical spectroscopy and data analysis.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"5 ","pages":"Article 100027"},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49708741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep UV resonance Raman spectroscopy for sensitive detection and quantification of the fluoroquinolone antibiotic drug moxifloxacin and the β-lactam meropenem in human plasma","authors":"Christian Domes ,&nbsp;Juergen Popp ,&nbsp;Stefan Hagel ,&nbsp;Mathias W. Pletz ,&nbsp;Torsten Frosch","doi":"10.1016/j.clispe.2023.100026","DOIUrl":"https://doi.org/10.1016/j.clispe.2023.100026","url":null,"abstract":"<div><p>Quantification of antibiotics in body fluids is of major clinical interest. A sensitive detection of the fluoroquinolone moxifloxacin and the β-lactam meropenem in the complex matrix human blood plasma was achieved with help of deep UV resonance Raman spectroscopy. Multivariate curve resolution was applied for quantification and low limits of detection in order of magnitude of the clinical concentration were detected in human plasma. Moxifloxacin and meropenem were detected down to minimum concentrations of 4 µM (2 mg/L) and 2 µM (1 mg/L). The acquired results and the benefits of enhanced Raman spectroscopy, i.e., short analysis time, small sample volume, and high sensitivity with the potential for multicomponent detection based on multivariate quantification, will pave the path as future point-of-care approach for sensitive detection of antibiotics in complex body fluids.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"5 ","pages":"Article 100026"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49708702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of several respiratory viruses with Surface-Enhanced Raman Spectroscopy coupled with Artificial Intelligence","authors":"Delphine Garsuault ,&nbsp;Sanaa El Messaoudi ,&nbsp;Mookkan Prabakaran ,&nbsp;Ian Cheong ,&nbsp;Anthony Boulanger ,&nbsp;Marion Schmitt-Boulanger","doi":"10.1016/j.clispe.2023.100025","DOIUrl":"https://doi.org/10.1016/j.clispe.2023.100025","url":null,"abstract":"<div><p>Diagnoses of viral infections are a challenge when facing a crisis like COVID-19, where their speed and reliability are critical to minimize diseases spread. The gold standard of diagnostics, quantitative Polymerase Chain Reaction, is time- and reagent-consuming and requires qualified personnel. Therefore, it is necessary to find new detection techniques to overcome these barriers. Surface Enhanced Raman Spectroscopy (SERS) is a detection method, based on light and metallic particles admixed with the samples, already used in different fields of research. In this study, we discriminate three respiratory viruses using a combination of SERS and Artificial Intelligence (AI). Our technique appears to be fast, reproducible, and reliable, achieving between 95 % and 100 % of accuracy, standing out as a powerful tool usable for viral diagnostics.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"5 ","pages":"Article 100025"},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49708725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biochemical characterization and discrimination of Leishmania major parasites and infected macrophages with Raman spectroscopy and chemometrics","authors":"Thulya Chakkumpulakkal Puthan Veettil ,&nbsp;Rebekah N. Duffin ,&nbsp;Supti Roy ,&nbsp;Philip C. Andrews ,&nbsp;Bayden R. Wood","doi":"10.1016/j.clispe.2023.100024","DOIUrl":"https://doi.org/10.1016/j.clispe.2023.100024","url":null,"abstract":"<div><p>Leishmaniasis is classified as one of the neglected tropical disease (NTD), which are caused by a group of parasitic protozoans called <em>Leishmania.</em> The high case load and severity of the disease make Leishmaniasis second only to malaria in terms of both severity and infectivity. However, due to the low economic interest in research and development, it may become a major world-wide health threat. Current diagnostics including serological assessment of infected tissue by either light microscopy, or antibody tests or by the culturing of potential infection via <em>in vitro</em> or <em>in vivo</em> animal inoculation, parasitological tests using samples aspirated from the spleen and bone marrow, Immunological tests such as the Montenegro test, Fluorescence assays, and polymerase chain reaction (PCR) techniques are suffer from several limitations including time and expense. Herein, we first apply Raman microscopy to distinguish the two <em>L. Major</em> parasitic forms namely promastigotes and amastigotes and secondly, distinguish infected from non-infected macrophages using multivariate data analysis including Principal Component Analysis (PCA) and unsupervised hierarchical cluster imaging analysis (UHCA). The maximum variance between infected and uninfected macrophage groups are visible in the lipid region (92.20 %) as compared to the fingerprint region (46.13 %) along PC1. The contributions from nucleic acids can be found at 805 cm⁻¹ (phosphodiester - Z-marker), 767 cm⁻¹ (pyrimidine ring breathing mode), 742 cm⁻¹ (ring breathing mode of DNA/RNA bases), and 568 cm⁻¹ (cytosine/guanine). These amplified nucleic acid signals in infected macrophages indicate the presence of infection compared to the uninfected macrophage group. Similarly, the maximum variance between amastigotes and promastigotes groups are observed in the lipid region (88.45%) as compared to the fingerprint region (28.34 %). Moreover, the UHCA of infected macrophages revealed the accumulation of lipid bodies or droplets inside or close proximity parasitophorous vacuole, which is consistent with the reported literature. Once established macrophages were infected with <em>Leishmania in vitro</em> and the differences between infected and non-infected established with high reproducibility. The reported spectral differences between infected and non-infected macrophages lays the ground work for developing a diagnostic tool for detection of leishmaniasis in a buffy coat preparation and also offers the potential of monitoring the effects of new therapeutics.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"5 ","pages":"Article 100024"},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49708723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contributions of vibrational spectroscopy to virology: A review","authors":"Iqra Chaudhary ,&nbsp;Naomi Jackson ,&nbsp;Denise Denning ,&nbsp;Luke O’Neill ,&nbsp;Hugh J. Byrne","doi":"10.1016/j.clispe.2022.100022","DOIUrl":"https://doi.org/10.1016/j.clispe.2022.100022","url":null,"abstract":"<div><p>Vibrational spectroscopic techniques, both infrared absorption and Raman scattering, are high precision, label free analytical techniques which have found applications in fields as diverse as analytical chemistry, pharmacology, forensics and archeometrics and, in recent times, have attracted increasing attention for biomedical applications. As analytical techniques, they have been applied to the characterisation of viruses as early as the 1970 s, and, in the context of the coronavirus disease 2019 (COVID-19) pandemic, have been explored in response to the World Health Organisation as novel methodologies to aid in the global efforts to implement and improve rapid screening of viral infection. This review considers the history of the application of vibrational spectroscopic techniques to the characterisation of the morphology and chemical compositions of viruses, their attachment to, uptake by and replication in cells, and their potential for the detection of viruses in population screening, and in infection response monitoring applications. Particular consideration is devoted to recent efforts in the detection of severe acute respiratory syndrome coronavirus 2, and monitoring COVID-19.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"4 ","pages":"Article 100022"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666054722000035/pdfft?md5=7cf34d19e60e79b702ac26e74b2c88a7&pid=1-s2.0-S2666054722000035-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91755705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved tissue preparation for multimodal vibrational imaging of biological tissues","authors":"Callum Gassner ,&nbsp;John A. Adegoke ,&nbsp;Sheila K. Patel ,&nbsp;Varun J. Sharma ,&nbsp;Kamila Kochan ,&nbsp;Louise M. Burrell ,&nbsp;Jaishankar Raman ,&nbsp;Bayden R. Wood","doi":"10.1016/j.clispe.2022.100021","DOIUrl":"https://doi.org/10.1016/j.clispe.2022.100021","url":null,"abstract":"<div><p>The complementary nature of Infrared (IR) and Raman spectroscopies enables a thorough understanding of biological tissue – so called multimodal vibrational spectroscopic imaging. However, new approaches in terms of sample preparation and data analysis are required to release the full potential of multimodal spectroscopy. Herein, we propose an inexpensive and relatively simple sample preparation technique incorporating mirror-finished stainless-steel slides and polyethylene glycol as an embedding medium that is compatible for both infrared and Raman spectroscopy of tissue sections. K-Means Clustering and Principal Component Analysis (PCA) were used to evaluate the performance of multimodal vibrational spectroscopic imaging compared with IR and Raman spectroscopic imaging individually using a rat kidney as a model. The K-Means cluster maps generated with the multimodal dataset showed the best correlation between different tissue types identified by an adjacent section stained with Masson’s Trichrome compared to either Raman or IR spectroscopy analysed independently. PCA score maps of the multimodal dataset produced a clear separation of individual tissue types along the first three Principal Components. Additionally, PCA permitted the correlation of IR and Raman peaks arising mainly from collagen vibrational modes. Finally, polyethylene glycol embedding is shown as an attractive alternative to paraffin embedding for spectroscopic analyses, due to significantly less fluorescence in Raman measurements and retention of lipids in the tissue, without any retention of the medium within the tissue.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"4 ","pages":"Article 100021"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666054722000023/pdfft?md5=3a4dd458baf53708648005affd5da096&pid=1-s2.0-S2666054722000023-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91755704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An observational cohort study to evaluate the use of serum Raman spectroscopy in a rapid diagnosis center setting","authors":"Freya E.R. Woods ,&nbsp;Susan Chandler ,&nbsp;Natalia Sikora ,&nbsp;Rachel Harford ,&nbsp;Ahmad Souriti ,&nbsp;Helen Gray ,&nbsp;Heather Wilkes ,&nbsp;Catherine Lloyd-Bennett ,&nbsp;Dean A. Harris ,&nbsp;Peter R. Dunstan","doi":"10.1016/j.clispe.2022.100020","DOIUrl":"10.1016/j.clispe.2022.100020","url":null,"abstract":"<div><p>Cancer presenting with non-specific vague symptoms remains a clinical challenge. The purpose of this study was to assess the feasibility of serum Raman spectroscopy for cancer detection in a rapid diagnosis center (RDC) setting. The primary aim was to identify significant spectral peaks of change in sera from cancer patients and the secondary aim was to assign molecular species at Raman peaks.</p><p>In this prospective observation study of a secondary care RDC, patients referred with vague cancer-related symptoms were recruited. Raman spectra of blood sera of 54 patients was obtained. Of these, 10 patients were diagnosed with cancer, and 44 no significant pathology (control). Common spectral increase/decrease between control and cancer was seen in spectral peaks 830 cm⁻¹, 878 cm⁻¹, 1031 cm⁻¹, 1174 cm⁻¹, 1397 cm⁻¹ tentatively attributed to amino acids, carbohydrates, fatty acids, and proteins. Individual differences between cancer and control via statistical analysis identifies 3 peaks with significance for all 10 of the cancer patients. The peaks are 878 cm⁻¹, 1449 cm⁻¹ and 1519 cm⁻¹, tentatively attributed to proteins, amino acids, lipids, fatty acids, glycoproteins, carbohydrates, and carotenoids. Differences are also seen for at least 9 of the cancers in the peaks at 830 cm⁻¹, 851 cm⁻¹, 1127 cm⁻¹, 1174 cm⁻¹, 1270 cm⁻¹, and 1656 cm⁻¹, tentatively attributed to amino acids, lactate, lipids, triglycerides, carbohydrates, and proteins.</p><p>Raman spectroscopy has the potential to enhance RDC referral criteria through the detection of peak differences seen commonly with different cancer types. Development of Artificial Intelligence (AI) based models could enable rapid detection and discrimination of different cancer types with more data availability.</p></div>","PeriodicalId":100277,"journal":{"name":"Clinical Spectroscopy","volume":"4 ","pages":"Article 100020"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666054722000011/pdfft?md5=a38da2fa1c0f767d9816475014e4c224&pid=1-s2.0-S2666054722000011-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87196030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}