Improved protocols for vibrational spectroscopic analysis of body fluids

Determination of platinum-resistance of women with ovarian cancer by FTIR spectroscopy combined with multivariate analyses and machine learning methods

Patients with high-grade ovarian cancer have a poor prognosis, thus effective treatment remains an unmet medical issue of high importance. Moreover, finding the reason for resistance to cisplatin is a crucial task for the improvement of anti-cancer drugs. In this study, we showed for the first time a chemical difference in a serum collected from platinum-resistance and platinum-sensitive women suffering from ovarian cancer using Fourier Transform InfraRed (FTIR) spectroscopy followed by a data analysis by Principal Component Analysis (PCA), Hierarchical Component Analysis (HCA) and 4 different machine learning algorithms. Obtained results showed a shift of PO2-symmetric vibrations, amide III and amide II were observed on the FTIR spectrum of the serum collected from platinum-resistance women in comparison with the spectrum of the serum from platinum-sensitive women. Furthermore, PCA analysis clearly demonstrated the most important role of amide II and amide I in the differentiation of platinum-sensitive and platinum-resistance women. In addition, machine learning algorithms showed the important role of wavenumber at 1631 cm-1(amide I) and wavenumber at 2993 cm-1 (asymmetric stretching CH3 vibrations). The accuracy of the obtained results was above 92%. Summarizing, FTIR can be used in detection platinum-resistance phenomena.

FTIR monitoring of the 13-valent pneumococcal conjugate vaccine for lung cancer patients: Changes in amides vibrations correlated with biochemical assays

Lung cancer is one of the most lethal cancers. Unfortunately, respiratory tract infections are very common in lung cancer patients, delaying appropriate anticancer therapy. To increase therapy efficiency, in this study we examined the effect of 13-Valent Pneumococcal Conjugate Vaccine on the immune response in lung cancer patients, which indirectly affects the success of anticancer therapy. The study was done using biochemical tests and Fourier Transform InfraRed (FTIR) spectroscopy. For this purpose, serum from lung cancer patients aged 52 ± 9 years (III and IV clinical stage; 79 %; n = 103) before and seven as well as 30 days after vaccination was collected. Obtained results showed increasing concentrations of immunoglobulin IgG and IgG2 groups in patients after vaccination in comparison with group before vaccination. This result was confirmed by FTIR spectroscopy, where higher absorbances of amides vibrations were observed after vaccination. Interestingly, lack of differences in the amides absorbances between patients 7 and 30 days after vaccination were noticed. FTIR spectra also showed changes in the ratio between amide I and amide III as well as between amide II and amide III in the groups of patients after vaccination. From deconvolution of made I range (1600 cm-1-1700 cm-1) decrease of the ratio between α-helix and β-sheet around 0.05 was noticed in serum collected from patients after vaccination in comparison with patients before vaccination. Using Principal Component Analysis (PCA) analysis of FTIR data it was observed that serum collected from all three analyzed groups of samples was possible to differentiate. The highest accuracy in differentiation group of samples before and 7 days after vaccination was visible in amide I, while before and 30 days after vaccination using amide II. Correlation between immunoglobulin IgG and IgG2 concentrations obtained by biochemical assays and FTIR were noticed only in the group of serum collected 30 days after vaccination, which suggested that FTIR spectroscopy reflects biochemical data.

Infrared spectroscopy combined with chemometrics in transflectance mode: An alternative approach in the photodiagnosis of COVID-19 using saliva

The Coronavirus Disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has required the search for sensitive, rapid, specific, and lower-cost diagnostic methods to meet the high demand. The gold standard method of laboratory diagnosis is real-time reverse transcription polymerase chain reaction (RT-PCR). However, this method is costly and results can take time. In the literature, several studies have already described the potential of Fourier transform infrared spectroscopy (FTIR) as a tool in the biomedical field, including the diagnosis of viral infections, while being fast and inexpensive. In view of this, the objective of this study was to develop an FTIR model for the diagnosis of COVID-19. For this analysis, all private clients who had performed a face-to-face collection at the Univates Clinical Analysis Laboratory (LAC Univates) within a period of six months were invited to participate. Data from clients who agreed to participate in the study were collected, as well as nasopharyngeal secretions and a saliva sample. For the development of models, the RT-PCR result of nasopharyngeal secretions was used as a reference method. Absorptions with high discrimination (p < 0.001) between GI (28 patients, RT-PCR test positive to SARS-CoV-2 virus) and GII (173 patients who did not have the virus detected in the test) were most relevant at 3512 cm-1, 3385 cm-1 and 1321 cm-1 after 2nd derivative data transformation. To carry out the diagnostic modeling, chemometrics via FTIR and Discriminant Analysis of Orthogonal Partial Least Squares (OPLS-DA) by salivary transflectance mode with one latent variable and one orthogonal signal correction component were used. The model generated predictions with 100 % sensitivity, specificity and accuracy. With the proposed model, in a single application of an individual's saliva in the FTIR equipment, results related to the detection of SARS-CoV-2 can be obtained in a few minutes of spectral evaluation.

Quantitative determination of alcohols in human biological fluids through Raman spectroscopy: An alternative alcohol test

The severe effects of alcohols on humans trigger the continuous research on the alcohols level measurement in biological fluids. The officially established technique is Headspace Gas Chromatography (HS-GC), while breathalyzers are commonly used by police on the road. However, they all exhibit drawbacks; HS-GC is expensive and labor-intensive, while the precision of breathalyzers is controversial. In the present study, a novel method was developed, for ethanol and methanol detection and quantification in human urine, saliva and blood serum, based on Raman spectroscopy. Biological fluids from healthy adult volunteers were collected, standard solutions of the alcohols in a concentration range from 0.00 μL/mL to 5.00 μL/mL were prepared and analysed using an air-tight and small volume sample carrier. Calibration curves for each binary system (alcohol - biological fluid) were created. Ethanol calculated detectable concentrations were below permissible limits for all biological fluids. In the case of methanol, the limits were not as satisfactory, but lower than intoxication level, due to the difficult spectral discrimination. For both alcohols, the lowest detection limits were recorded for saliva. All detection limits were verified by visual inspection of the spectra. The proposed quantitative method was validated in all cases regarding their specificity, working range, accuracy, precision and sensitivity.

Application of Fourier Transform InfraRed spectroscopy of machine learning with Support Vector Machine and principal components analysis to detect biochemical changes in dried serum of patients with primary myelofibrosis

Primary myelofibrosis (PM) is a myeloproliferative neoplasm characterized by stem cell-derived clonal neoplasms. Several factors are involved in diagnosing PM, including physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. Commonly gene mutations are used. Also, these gene mutations exist in other diseases, such as polycythemia vera and essential thrombocythemia. Hence, understanding the molecular mechanism and finding disease-related biomarker characteristics only for PM is crucial for the treatment and survival rate. For this purpose, blood samples of PM (n = 85) vs. healthy controls (n = 45) were collected for biochemical analysis, and, for the first time, Fourier Transform InfraRed (FTIR) spectroscopy measurement of dried PM and healthy patients' blood serum was analyzed. A Support Vector Machine (SVM) model with optimized hyperparameters was constructed using the grid search (GS) method. Then, the FTIR spectra of the biomolecular components of blood serum from PM patients were compared to those from healthy individuals using Principal Components Analysis (PCA). Also, an analysis of the rate of change of FTIR spectra absorption was studied. The results showed that PM patients have higher amounts of phospholipids and proteins and a lower amount of H-O=H vibrations which was visible. The PCA results indicated that it is possible to differentiate between dried blood serum samples collected from PM patients and healthy individuals. The Grid Search Support Vector Machine (GS-SVM) model showed that the prediction accuracy ranged from 0.923 to 1.00 depending on the FTIR range analyzed. Furthermore, it was shown that the ratio between α-helix and β-sheet structures in proteins is 1.5 times higher in PM than in control people. The vibrations associated with the CO bond and the amide III region of proteins showed the highest probability value, indicating that these spectral features were significantly altered in PM patients compared to healthy ones' spectra. The results indicate that the FTIR spectroscope may be used as a technique helpful in PM diagnostics. The study also presents preliminary results from the first prospective clinical validation study.

Detection of primary myelofibrosis in blood serum via Raman spectroscopy assisted by machine learning approaches; correlation with clinical diagnosis

Primary myelofibrosis (PM) is one of the myeloproliferative neoplasm, where stem cell-derived clonal neoplasms was noticed. Diagnosis of this disease is based on: physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. However, the molecular marker of PM, which is a mutation in the JAK2V617F gene, was observed also in other myeloproliferative neoplasms such as polycythemia vera and essential thrombocythemia. Therefore, there is a need to find methods that provide a marker unique to PM and allow for higher accuracy of PM diagnosis and consequently the treatment of the disease. Continuing, in this study, we used Raman spectroscopy, Principal Components Analysis (PCA), and Partial Least Squares (PLS) analysis as helpful diagnostic tools for PM. Consequently, we used serum collected from PM patients, which were classified using clinical parameters of PM such as the dynamic international prognostic scoring system (DIPSS) for primary myelofibrosis plus score, the JAK2V617F mutation, spleen size, bone marrow reticulin fibrosis degree and use of hydroxyurea drug features. Raman spectra showed higher amounts of C-H, C-C and C-C/C-N and amide II and lower amounts of amide I and vibrations of CH3 groups in PM patients than in healthy ones. Furthermore, shifts of amides II and I vibrations in PM patients were noticed. Machine learning methods were used to analyze Raman regions: (i) 800 cm-1 and 1800 cm-1, (ii) 1600 cm-1-1700 cm-1, and (iii) 2700 cm-1-3000 cm-1 showed 100 % accuracy, sensitivity, and specificity. Differences in the spectral dynamic showed that differences in the amide II and amide I regions were the most significant in distinguishing between PM and healthy subjects. Importantly, until now, the efficacy of Raman spectroscopy has not been established in clinical diagnostics of PM disease using the correlation between Raman spectra and PM clinical prognostic scoring. Continuing, our results showed the correlation between Raman signals and bone marrow fibrosis, as well as JAKV617F. Consequently, the results revealed that Raman spectroscopy has a high potential for use in medical laboratory diagnostics to quantify multiple biomarkers simultaneously, especially in the selected Raman regions.

Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy

Raman spectroscopy is a well-established technique for the molecular characterisation of samples and does not require extensive pre-analytical processing for complex cosmetic products. As an illustration of its potential, this study investigates the quantitative performance of Raman spectroscopy coupled with partial least squares regression (PLSR) for the analysis of Alginate nanoencapsulated Piperonyl Esters (ANC-PE) incorporated into a hydrogel. A total of 96 ANC-PE samples covering a 0.4% w/w-8.3% w/w PE concentration range have been prepared and analysed. Despite the complex formulation of the sample, the spectral features of the PE can be detected and used to quantify the concentrations. Using a leave-K-out cross-validation approach, samples were divided into a training set (n = 64) and a test set, samples that were previously unknown to the PLSR model (n = 32). The root mean square error of cross-validation (RMSECV) and prediction (RMSEP) was evaluated to be 0.142% (w/w PE) and 0.148% (w/w PE), respectively. The accuracy of the prediction model was further evaluated by the percent relative error calculated from the predicted concentration compared to the true value, yielding values of 3.58% for the training set and 3.67% for the test set. The outcome of the analysis demonstrated the analytical power of Raman to obtain label-free, non-destructive quantification of the active cosmetic ingredient, presently PE, in complex formulations, holding promise for future analytical quality control (AQC) applications in the cosmetics industry with rapid and consumable-free analysis.

Fourier-transform infrared spectroscopy: a universal optical sensing technique with auspicious application prospects in the diagnosis and management of autoimmune diseases

Autoimmune diseases (AIDs) are poorly understood clinical syndromes due to breakdown of immune tolerance towards specific types of self-antigens. They are generally associated with an inflammatory response mediated by lymphocytes T, autoantibodies or both. Ultimately, chronic inflammation culminates in tissue damages and clinical manifestations. AIDs affect 5% of the world population, and they represent the main cause of fatality in young to middle-aged females. In addition, the chronic nature of AIDs has a devastating impact on the patient's quality of life. It also places a heavy burden on the health care system. Establishing a rapid and accurate diagnosis is considered vital for an ideal medical management of these autoimmune disorders. However, for some AIDs, this task might be challenging. Vibrational spectroscopies, and more particularly Fourier-transform infrared (FTIR) spectroscopy, have emerged as universal analytical techniques with promising applications in the diagnosis of various types of malignancies and metabolic and infectious diseases. The high sensitivity of these optical sensing techniques and their minimal requirements for test reagents qualify them to be ideal analytical techniques. The aim of the current review is to explore the potential applications of FTIR spectroscopy in the diagnosis and management of most common AIDs. It also aims to demonstrate how this technique has contributed to deciphering the biochemical and physiopathological aspects of these chronic inflammatory diseases. The advantages that can be offered by this optical sensing technique over the traditional and gold standard methods used in the diagnosis of these autoimmune disorders have also been extensively discussed.

Raman spectroscopy-based biomarker screening by studying the fingerprint and lipid characteristics of Polycythemıa Vera cases blood serum

This study aimed to develop a novel approach for diagnosing Polycythemia Vera (PV), a stem cell-derived neoplasm of the myeloid lineage. The approach utilized Raman spectroscopy coupled with multivariate analysis to analyze blood serum samples collected from PV patients. The results showed that PV serum exhibited lower protein and lipid levels and structural changes in the functional groups that comprise proteins and lipids. The study also demonstrated differences in lipid biosynthesis and protein levels in PV serum. Using the Partial Least Square Discriminant Analysis (PLS-DA) model, Raman-based multivariate analysis achieved high accuracy rates of 96.49% and 93.04% in the training sets and 93.10% and 89.66% in the test sets for the 800-1800 cm-1 and 2700-3000 cm-1 ranges, respectively. The area under the curve (AUC) values of the test datasets were calculated as 0.92 and 0.89 in the 800-1800 cm-1 and 2700-3000 cm-1 spectral regions, respectively, demonstrating the effectiveness of the PLS-DA models for the diagnosis of PV. This study highlights the potential of Raman spectroscopy-based analysis in the early and accurate diagnosis of PV, enabling the application of effective treatment strategies.

Surface-Enhanced Raman Analysis of Uric Acid and Hypoxanthine Analysis in Fractionated Bodily Fluids

In recent years, the disease burden of hyperuricemia has been increasing, especially in high-income countries and the economically developing world with a Western lifestyle. Abnormal levels of uric acid and hypoxanthine are associated with many diseases, and therefore, to demonstrate improved methods of uric acid and hypoxanthine detection, three different bodily fluids were analysed using surface-enhanced Raman spectroscopy (SERS) and high-performance liquid chromatography (HPLC). Gold nanostar suspensions were mixed with series dilutions of uric acid and hypoxanthine, 3 kDa centrifugally filtered human blood serum, urine and saliva. The results show that gold nanostars enable the quantitative detection of the concentration of uric acid and hypoxanthine in the range 5-50 μg/mL and 50-250 ng/mL, respectively. The peak areas of HPLC and maximum peak intensity of SERS have strongly correlated, notably with the peaks of uric acid and hypoxanthine at 1000 and 640 cm^-1, respectively. The r² is 0.975 and 0.959 for uric acid and hypoxanthine, respectively. Each of the three body fluids has a number of spectral features in common with uric acid and hypoxanthine. The large overlap of the spectral bands of the SERS of uric acid against three body fluids at spectra peaks were at 442, 712, 802, 1000, 1086, 1206, 1343, 1436 and 1560 cm^-1. The features at 560, 640, 803, 1206, 1290 and 1620 cm^-1 from hypoxanthine were common to serum, saliva and urine. There is no statistical difference between HPLC and SERS for determination of the concentration of uric acid and hypoxanthine (p > 0.05). For clinical applications, 3 kDa centrifugal filtration followed by SERS can be used for uric acid and hypoxanthine screening is, which can be used to reveal the subtle abnormalities enhancing the great potential of vibrational spectroscopy as an analytical tool. Our work supports the hypnosis that it is possible to obtain the specific concentration of uric acid and hypoxanthine by comparing the SER signals of serum, saliva and urine. In the future, the analysis of other biofluids can be employed to detect biomarkers for the diagnosis of systemic pathologies.

2D-IR spectroscopy of proteins in H2O-A Perspective

The form of the amide I infrared absorption band provides a sensitive probe of the secondary structure and dynamics of proteins in the solution phase. However, the frequency coincidence of the amide I band with the bending vibrational mode of H₂O has necessitated the widespread use of deuterated solvents. Recently, it has been demonstrated that ultrafast 2D-IR spectroscopy allows the detection of the protein amide I band in H₂O-based fluids, meaning that IR methods can now be applied to study proteins in physiologically relevant solvents. In this perspective, we describe the basis of the 2D-IR method for observing the protein amide I band in H₂O and show how this development has the potential to impact areas ranging from our fundamental appreciation of protein structural dynamics to new applications for 2D-IR spectroscopy in the analytical and biomedical sciences. In addition, we discuss how the spectral response of water, rather than being a hindrance, now provides a basis for new approaches to data pre-processing, standardization of 2D-IR data collection, and signal quantification. Ultimately, we visualize a direction of travel toward the creation of 2D-IR spectral libraries that can be linked to advanced computational methods for use in high-throughput protein screening and disease diagnosis.

Rapid discrimination of hepatic echinococcosis patients' serum using vibrational spectroscopy combined with support vector machines

Echinococcosis is a severe zoonotic parasitic disease, and it is continuing to be a significant public health issue. The course of the disease is usually slow, and patients often remain asymptomatic for years. There is no standardized and widely accepted treatment, so early and accurate diagnosis is essential. Herein, this study utilized vibrational spectroscopic techniques, namely Raman and Fourier Transform Infrared (FTIR) spectroscopy, to quickly and accurately distinguish hepatic echinococcosis (HE) patients' serum from the healthy group. Serum samples were collected from HE patients as well as healthy control subjects, and then the Raman and FTIR spectra of the two groups were recorded. After a series of pre-processing, support vector machines (SVMs) were then used to establish the classification models for the two spectral data sets. The performance of each diagnostic model was evaluated using leave-one-out cross-validation (LOOCV) and hold-out validation methods, respectively. For the distinction between HE and healthy groups, these two spectroscopic techniques had achieved satisfactory classification results, and the diagnostic capabilities of the Raman technique were comparable to that of the FTIR method. The results demonstrate that vibrational spectroscopy has great potential in the rapid and accurate detection of HE and is expected to make up for the shortcomings of the existing clinical diagnosis methods.

Quantitative Determination of Diosmin in Tablets by Infrared and Raman Spectroscopy

Diosmin is widely used in the treatment of chronic venous diseases and hemorrhoids. Based on Raman and infrared reflection spectra of powdered tablets in the mid- and near-infrared regions and results of reference high-performance liquid chromatographic analysis, partial least squares models that enable fast and reliable quantification of the studied active ingredient in tablets, without the need for extraction, were elaborated. Eight commercial preparations containing diosmin in the 66-92% (w/w) range were analyzed. In order to assess and compare the quality of the developed chemometric models, the relative standard errors of prediction for calibration and validation sets were calculated. We found these errors to be in the 1.0-2.4% range for the three spectroscopic techniques used. Diosmin content in the analyzed preparations was obtained with recoveries in the 99.5-100.5% range.

Comparative Study of Sample Carriers for the Identification of Volatile Compounds in Biological Fluids Using Raman Spectroscopy

Vibrational spectroscopic techniques and especially Raman spectroscopy are gaining ground in substituting the officially established chromatographic methods in the identification of ethanol and other volatile substances in body fluids, such as blood, urine, saliva, semen, and vaginal fluids. Although a couple of different carriers and substrates have been employed for the biochemical analysis of these samples, most of them are suffering from important weaknesses as far as the analysis of volatile compounds is concerned. For this reason, in this study three carriers are proposed, and the respective sample preparation methods are described for the determination of ethanol in human urine samples. More specifically, a droplet of the sample on a highly reflective carrier of gold layer, a commercially available cuvette with a mirror to enhance backscattered radiation sealed with a lid, and a home designed microscope slide with a cavity coated with gold layer and covered with transparent cling film have been evaluated. Among the three proposed carriers, the last one achieved a quick, simple, and inexpensive identification of ethanol, which was used as a case study for the volatile compound, in the biological samples. The limit of detection (LoD) was found to be 1.00 μL/mL, while at the same time evaporation of ethanol was prevented.

Clinical Spectroscopy: Lost in Translation?

This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.

Infrared Spectroscopy in Aqueous Solutions: Capabilities and Challenges

Fourier-transform infrared (FTIR) spectroscopy provides rapid, reliable, quantitative, and qualitative analysis of samples in different aggregation states, i.e., gases, thin films, solids, liquids, etc. However, when analyzing aqueous solutions, particular issues associated with the rather pronounced IR absorption characteristics of water appear to interfere with the solute determination. In this review, Fourier-transform infrared spectroscopic techniques and their analytical capabilities for analyzing aqueous solutions are reviewed, and highlight examples are discussed.

Raman, Infrared and Brillouin Spectroscopies of Biofluids for Medical Diagnostics and for Detection of Biomarkers

This review surveys Infrared, Raman/SERS and Brillouin spectroscopies for medical diagnostics and detection of biomarkers in biofluids, that include urine, blood, saliva and other biofluids. These optical sensing techniques are non-contact, noninvasive and relatively rapid, accurate, label-free and affordable. However, those techniques still have to overcome some challenges to be widely adopted in routine clinical diagnostics. This review summarizes and provides insights on recent advancements in research within the field of vibrational spectroscopy for medical diagnostics and its use in detection of many health conditions such as kidney injury, cancers, cardiovascular and infectious diseases. The six comprehensive tables in the review and four tables in supplementary information summarize a few dozen experimental papers in terms of such analytical parameters as limit of detection, range, diagnostic sensitivity and specificity, and other figures of merits. Critical comparison between SERS and FTIR methods of analysis reveals that on average the reported sensitivity for biomarkers in biofluids for SERS vs FTIR is about 103 to 105 times higher, since LOD SERS are lower than LOD FTIR by about this factor. High sensitivity gives SERS an edge in detection of many biomarkers present in biofluids at low concentration (nM and sub nM), which can be particularly advantageous for example in early diagnostics of cancer or viral infections.HighlightsRaman, Infrared spectroscopies use low volume of biofluidic samples, little sample preparation, fast time of analysis and relatively inexpensive instrumentation.Applications of SERS may be a bit more complicated than applications of FTIR (e.g., limited shelf life for nanoparticles and substrates, etc.), but this can be generously compensated by much higher (by several order of magnitude) sensitivity in comparison to FTIR.High sensitivity makes SERS a noninvasive analytical method of choice for detection, quantification and diagnostics of many health conditions, metabolites, and drugs, particularly in diagnostics of cancer, including diagnostics of its early stages.FTIR, particularly ATR-FTIR can be a method of choice for efficient sensing of many biomarkers, present in urine, blood and other biofluids at sufficiently high concentrations (mM and even a few µM)Brillouin scattering spectroscopy detecting visco-elastic properties of probed liquid medium, may also find application in clinical analysis of some biofluids, such as cerebrospinal fluid and urine.

Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications

Herein, we show differences in blood serum of asymptomatic and symptomatic pregnant women infected with COVID-19 and correlate them with laboratory indexes, ATR FTIR and multivariate machine learning methods. We collected the sera of COVID-19 diagnosed pregnant women, in the second trimester (n = 12), third-trimester (n = 7), and second-trimester with severe symptoms (n = 7) compared to the healthy pregnant (n = 11) women, which makes a total of 37 participants. To assign the accuracy of FTIR spectra regions where peak shifts occurred, the Random Forest algorithm, traditional C5.0 single decision tree algorithm and deep neural network approach were used. We verified the correspondence between the FTIR results and the laboratory indexes such as: the count of peripheral blood cells, biochemical parameters, and coagulation indicators of pregnant women. CH₂ scissoring, amide II, amide I vibrations could be used to differentiate the groups. The accuracy calculated by machine learning methods was higher than 90%. We also developed a method based on the dynamics of the absorbance spectra allowing to determine the differences between the spectra of healthy and COVID-19 patients. Laboratory indexes of biochemical parameters associated with COVID-19 validate changes in the total amount of proteins, albumin and lipase.

Application of FTIR Spectroscopy for Quantitative Analysis of Blood Serum: A Preliminary Study

The aim of this study was to analyze the possibility of simultaneous determination of the concentration of components from the characteristics of FTIR spectra using the example of a model blood serum. To prepare model solutions, a set of freeze-dried control sera based on bovine blood serum was used, certified for approximately 38 parameters. Based on the values of the absorbance and areas of absorption bands in the FTIR spectra of model solutions, a regression equation was constructed by solving a nonlinear problem using the generalized reduced gradient method. By using the absorbance of the absorption bands at 1717 and 3903 cm⁻¹ and the areas of the absorption bands at 616, 3750, and 3903 cm⁻¹, it is possible to simultaneously determine the concentrations of 38 components with an error of less than 0.1%. The results obtained confirm the potential clinical use of FTIR spectroscopy as a reagent-free express method for the analysis of blood serum. However, its practical implementation requires additional research, in particular, analysis of real blood serum samples and validation of the method.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

In situ Analytical Quality Control of chemotherapeutic solutions in infusion bags by Raman spectroscopy

Analytical Quality Control (AQC) in centralised preparation units of oncology centers is a common procedure relying on the identification and quantification of the prepared chemotherapeutic solutions for safe intravenous administration to patients. Although the use of Raman spectroscopy for AQC has gained much interest, in most applications it remains coupled to a flow injection analyser (FIA) requiring withdrawal of the solution for analysis. In addition to current needs for more rapid and cost-effective analysis, the risk of exposure of clinical staff to the toxic molecules during daily handling is a serious concern to address. Raman spectroscopic analysis, for instance by Confocal Raman Microscopy (CRM), could enable direct analysis (non-invasive) for AQC directly in infusion bags. In this study, 3 anticancer drugs, methotrexate (MTX), 5-fluorouracil (5-FU) and gemcitabine (GEM) have been selected to highlight the potential of CRM for withdrawal free analysis. Solutions corresponding to the clinical range of each drug were prepared in 5% glucose and data was collected from infusion bags placed under the Raman microscope. Firstly, 100% discrimination has been obtained by Partial Least Squares Discriminant Analysis (PLS-DA) confirming that the identification of drugs can be performed. Secondly, using Partial Least Squares Regression (PLSR), quantitative analysis was performed with mean % error of predicted concentrations of respectively 3.31%, 5.54% and 8.60% for MTX, 5-FU and GEM. These results are in accordance with the 15% acceptance criteria used for the current clinical standard technique, FIA, and the Limits of Detection for all drugs were determined to be substantially lower than the administered range, thus highlighting the potential of confocal Raman spectroscopy for direct analysis of chemotherapeutic solutions.

Biomedical applications of vibrational spectroscopy: Oral cancer diagnostics

Vibrational spectroscopy, based on either infrared absorption or Raman scattering, has attracted increasing attention for biomedical applications. Proof of concept explorations for diagnosis of oral potentially malignant disorders and cancer are reviewed, and recent advances critically appraised. Specific examples of applications of Raman microspectroscopy for analysis of histological, cytological and saliva samples are presented for illustrative purposes, and the future prospects, ultimately for routine, chairside in vivo screening are discussed.

The potential of FT-IR spectroscopy for improving healthcare in sepsis - An animal model study

Fourier Transform-Infrared (FT-IR) absorption spectroscopy has been used to investigate pathophysiological changes caused by sepsis. Sepsis has been defined as a potentially fatal organic dysfunction caused by a dysregulated host response to infection and can lead a patient to risk of death. This study used samples consisting of the blood plasma of mice which were induced to sepsis state, compared to a healthy group using FT-IR associated with attenuated total reflectance (ATR) spectroscopy. For statistical analysis, principal components analysis (PCA) and linear discriminant analysis (LDA) were applied, independently, to the second derivative spectra of both the fingerprint (900-1800 cm^-1) and the high wavenumber (2800-3100 cm^-1) regions. The technique efficiently differentiated the blood plasma of the two groups, sepsis and healthy mice, the analysis indicating that fatty acids and lipids in the blood samples could be an important biomarker of sepsis.

Assessment of structural protein expression by FTIR and biochemical assays as biomarkers of metabolites response in gastric and colon cancer

Colon and gastric cancers are the widespread benign types of cancers which are synchronous and metachronous neoplasms. In terms of the progression and progress of the disease, metabolic processes and differentiation in protein structures have an important role in for treatment of the disease. In this study we proposed to investigate the metabolic process and the differentiation of protein secondary structure among colon and gastric cancer as well as healthy controls using biochemistry and Fourier Transform InfraRed spectroscopy (FTIR) methods. For this purpose, we measured blood serum of 133 patients, which were conducted upon oncology department (45 colon cancer, 45 gastric cancer and 43 control individuals). The obtained spectroscopic results and biochemical assays showed significant reduction in the amount of functional groups in cancer groups contrary with total protein measurements and structure of protein differences between colon and gastric cancers. Differentiations were visible in serum levels of CEA, CA-125, CA-15-3, CA-19-9 AFP (Alpha fetoprotein) of gastric and colon cancer patients as well as in amide III and secondly described amide I regions. Our findings suggest that amide I bonds in colon cancer cells can be helpful in diagnosis of colon cancer. Indeed, our results showed that metabolic processes were higher in gastric cancer group than in colon cancer. Hence, FTIR spectroscopy and curve-fitting analysis of amide I profile can be successfully applied as tools for identifying quantitative and qualitative changes of proteins in human cancerous blood serum. However, what is very important, in PCA analysis we see, that the scatter plot of PC1 (variability 80%) and PC2 (variability 15%) show that the data related to the control and two cancer groups are clustered together with different magnitudes and directions.

Detection of Glycine as a Model Protein in Blood Serum Using 2D-IR Spectroscopy

Glycine (Gly) is used as a model system to evaluate the ability of ultrafast two-dimensional infrared (2D-IR) spectroscopy to detect and quantify the low-molecular-weight proteinaceous components of blood serum. Combining data acquisition schemes to suppress absorption bands of H₂O that overlap with the protein amide I band with analysis of peak patterns appearing in the off-diagonal region of the 2D-IR spectrum allows separation of the Gly spectral signature from that of the dominant protein fraction of serum in a transmission-mode 2D-IR measurement without any sample manipulation, e.g., filtration or drying. 2D-IR spectra of blood serum samples supplemented with varying concentrations of Gly were obtained, and a range of data analysis methods compared, leading to a detection limit of ∼3 mg/mL for Gly. The reported methodology provides a platform for a critical assessment of the sensitivity of 2D-IR for measuring the concentrations of amino acids, peptides, and low-molecular-weight proteins present in serum samples. We conclude that, in the case of several clinically relevant diagnostic molecules and their combinations, the potential exists for 2D-IR to complement IR absorption methods as the benefits of the second frequency dimension offered by 2D-IR spectroscopy outweigh the added technical complexity of the measurement.

Interrogation of IDH1 Status in Gliomas by Fourier Transform Infrared Spectroscopy

Mutations in the isocitrate dehydrogenase 1 (IDH1) gene are found in a high proportion of diffuse gliomas. The presence of the IDH1 mutation is a valuable diagnostic, prognostic and predictive biomarker for the management of patients with glial tumours. Techniques involving vibrational spectroscopy, e.g., Fourier transform infrared (FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer detection, and have the potential to contribute to diagnostics. The implementation of FTIR microspectroscopy during surgical biopsy could present a fast, label-free method for molecular genetic classification. For example, the rapid determination of IDH1 status in a patient with a glioma diagnosis could inform intra-operative decision-making between alternative surgical strategies. In this study, we utilized synchrotron-based FTIR microanalysis to probe tissue microarray sections from 79 glioma patients, and distinguished the positive class (IDH1-mutated) from the IDH1-wildtype glioma, with a sensitivity and specificity of 82.4% and 83.4%, respectively. We also examined the ability of attenuated total reflection (ATR)-FTIR spectroscopy in detecting the biomolecular events and global epigenetic and metabolic changes associated with mutations in the IDH1 enzyme, in blood serum samples collected from an additional 72 brain tumour patients. Centrifugal filtration enhanced the diagnostic ability of the classification models, with balanced accuracies up to ~69%. Identification of the molecular status from blood serum prior to biopsy could further direct some patients to alternative treatment strategies.

Quantitative analysis of human blood serum using vibrational spectroscopy

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State of the art of quantitative Vibrational Spectroscopic analysis of human blood serum is reviewed.

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Technical considerations for infrared absorption and Raman analysis are discussed.

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Quantitative analyses of Endogenous and Exogenous constituents are presented.

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The potential for clinical translation of spectroscopic serology is argued.

Analysis of bodily fluids using vibrational spectroscopy has attracted increasing attention in recent years. In particular, infrared spectroscopic screening of blood products, particularly blood serum, for disease diagnostics has been advanced considerably, attracting commercial interests. However, analyses requiring quantification of endogenous constituents or exogenous agents in blood are less well advanced. Recent advances towards this end are reviewed, focussing on infrared and Raman spectroscopic analyses of human blood serum. The importance of spectroscopic analysis in the native aqueous environment is highlighted, and the relative merits of infrared absorption versus Raman spectroscopy are considered, in this context. It is argued that Raman spectroscopic analysis is more suitable to quantitative analysis in liquid samples, and superior performance for quantification of high and low molecular weight components, is demonstrated. Applications for quantitation of viral loads, and therapeutic drug monitoring are also discussed.

Raman Analysis Reveals Biochemical Differences in Plasma of Crohn's Disease Patients

BACKGROUNDS AND AIMS

There is no accurate and reliable circulating biomarker to diagnose Crohn's disease [CD]. Raman spectroscopy is a relatively new approach that provides information on the biochemical composition of samples in minutes and virtually without any sample preparation. We aimed to test the use of Raman spectroscopy analysis of plasma samples as a potential diagnostic tool for CD.

METHODS

We analysed by Raman spectroscopy dry plasma samples obtained from 77 CD patients [CD] and 45 healthy controls [HC]. In the dataset obtained, we analysed spectra differences between CD and HC, as well as among CD patients with different disease behaviours. We also developed a method, based on principal component analysis followed by a linear discrimination analysis [PCA-LDA], for the automatic classification of individuals based on plasma spectra analysis.

RESULTS

Compared with HC, the CD spectra were characterised by less intense peaks corresponding to carotenoids [p <10-4] and by more intense peaks corresponding to proteins with β-sheet secondary structure [p <10-4]. Differences were also found on Raman peaks relative to lipids [p = 0.0007] and aromatic amino acids [p <10-4]. The predictive model we developed was able to classify CD and HC subjects with 83.6% accuracy [sensitivity 80.0% and specificity 85.7%] and F1-score of 86.8%.

CONCLUSIONS

Our results indicate that Raman spectroscopy of blood plasma can identify metabolic variations associated with CD and it could be a rapid pre-screening tool to use before further specific evaluation.

Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and "digital drying"

In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR-FTIR on both liquid and air-dried samples to investigate "digital drying" as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least-squares method, have demonstrated a greater random forest (RF) classification performance than the air-dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL-IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep-penetration light source on disease classification. The RF classification of QCL-IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively.

Age and Gender Characteristics of the Infrared Spectra of Normal Human Saliva

The comparison of the characteristics of the infrared (IR) spectra of saliva of healthy volunteers was carried out based on gender and age. It is shown that statistically significant differences between male and female groups are observed for the absorption bands of proteins and lipids. At the same time, the absorbance of the bands assigned to proteins and nucleic acids is higher for males, whereas the absorbance of the bands assigned to lipids is higher in the group of females. It is established that the correlation relationships of the characteristics of the spectra and age are weakly expressed. Thus, when forming the criteria of the norm and pathology for saliva, it is necessary to take into account the gender of the subjects, while there are no strict requirements for taking into account age periodization. Nevertheless, the revealed patterns are valid only for the composition of the saliva of healthy volunteers, the extension of the results to groups of patients with various diseases, as well as other biological fluids, requires additional testing.

Developing infrared spectroscopic detection for stratifying brain tumour patients: glioblastoma multiforme vs. lymphoma

Over a third of brain tumour patients visit their general practitioner more than five times prior to diagnosis in the UK, leading to 62% of patients being diagnosed as emergency presentations. Unfortunately, symptoms are non-specific to brain tumours, and the majority of these patients complain of headaches on multiple occasions before being referred to a neurologist. As there are currently no methods in place for the early detection of brain cancer, the affected patients' average life expectancy is reduced by 20 years. These statistics indicate that the current pathway is ineffective, and there is a vast need for a rapid diagnostic test. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy is sensitive to the hallmarks of cancer, as it analyses the full range of macromolecular classes. The combination of serum spectroscopy and advanced data analysis has previously been shown to rapidly and objectively distinguish brain tumour severity. Recently, a novel high-throughput ATR accessory has been developed, which could be cost-effective to the National Health Service in the UK, and valuable for clinical translation. In this study, 765 blood serum samples have been collected from healthy controls and patients diagnosed with various types of brain cancer, contributing to one of the largest spectroscopic studies to date. Three robust machine learning techniques - random forest, partial least squares-discriminant analysis and support vector machine - have all provided promising results. The novel high-throughput technology has been validated by separating brain cancer and non-cancer with balanced accuracies of 90% which is comparable to the traditional fixed diamond crystal methodology. Furthermore, the differentiation of brain tumour type could be useful for neurologists, as some are difficult to distinguish through medical imaging alone. For example, the highly aggressive glioblastoma multiforme and primary cerebral lymphoma can appear similar on magnetic resonance imaging (MRI) scans, thus are often misdiagnosed. Here, we report the ability of infrared spectroscopy to distinguish between glioblastoma and lymphoma patients, at a sensitivity and specificity of 90.1% and 86.3%, respectively. A reliable serum diagnostic test could avoid the need for surgery and speed up time to definitive chemotherapy and radiotherapy.

Investigating pre-analytical requirements for serum and plasma based infrared spectro-diagnostic

Infrared spectroscopy is a rapid, easy-to-operate, label-free and therefore cost-effective technique. Many studies performed on biofluids (eg, serum, plasma, urine, sputum, bile and cerebrospinal fluid) have demonstrated its promising application as a clinical diagnostic tool. Given all these characteristics, infrared spectroscopy appears to be an ideal candidate to be implemented into the clinics. However, before considering its translation, a clear effort is needed to standardise protocols for biofluid spectroscopic analysis. To reach this goal, careful investigations to identify and track errors that can occur during the pre-analytical phase is a crucial step. Here, we report for the first time, results of investigations into pre-analytical factors that can affect the quality of the spectral data acquired on serum and plasma, such as the impact of long-term freezing time storage of samples as well as the month-to-month reproducibility of the spectroscopic analysis. The spectral data discrimination has revealed to be majorly impacted by a residual water content variation in serum and plasma dried samples.

Fourier transform infrared spectroscopic signature of blood plasma in the progression of breast cancer with simultaneous metastasis to lungs

Despite advanced diagnostic techniques used for detecting cancer, this disease still remains a leading cause of death in the developed world. What is more, the greatest danger for patients is not related with growing of tumor but rather with metastasis of cancer cells to the distant organs. In this study, Fourier transform infrared (FTIR) spectroscopy was used to track chemical changes in blood plasma to find spectral markers of metastatic breast cancer during the disease progression. Plasma samples were taken 1-5 weeks after orthotropic inoculation of 4T1 metastatic breast cancer cells to mice. The earliest changes detected by FTIR spectroscopy in plasma were correlated with unsaturation of phospholipids and secondary structures of proteins that appeared 2 and 3 weeks, respectively, after 4T1 cells inoculation (micrometastatic phase). Significant alternations in the content and structure of lipids and carbohydrates were identified in plasma at the later stages (macrometastatic phase). When large primary tumors in breast and macrometastases in lung were developed, all bands in FTIR spectra significantly differed from those at earlier phases of the cancer progression. In conclusion, we showed that each phase of the breast cancer progression and its pulmonary metastasis can be characterized by a specific panel of spectral markers.

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

In the last two decades, Fourier Transform Infrared (FTIR) and Raman spectroscopies turn out to be valuable tools, capable of providing fingerprint-type information on the composition and structural conformation of specific molecular species. Vibrational spectroscopy's multiple features, namely highly sensitive to changes at the molecular level, noninvasive, nondestructive, reagent-free, and waste-free analysis, illustrate the potential in biomedical field. In light of this, the current work features recent data and major trends in spectroscopic analyses going from in vivo measurements up to ex vivo extracted and processed materials. The ability to offer insights into the structural variations underpinning pathogenesis of diseases could provide a platform for disease diagnosis and therapy effectiveness evaluation as a future standard clinical tool.

Development of a flow cell based Raman spectroscopy technique to overcome photodegradation in human blood

Raman spectroscopy of blood offers significant potential for label-free diagnostics of disease. However, current techniques are limited by the use of low laser power to avoid photodegradation of blood; this translates to a low signal to noise ratio in the Raman spectra. We developed a novel flow cell based Raman spectroscopy technique that provides reproducible Raman spectra with a high signal to noise ratio and low data acquisition time while ensuring a short dwell time in the laser spot to avoid photodamage in blood lysates. We show that our novel setup is capable of detecting minute changes in blood lysate spectral features from natural aging. Moreover, we demonstrate that by rigorously controlling the experimental conditions, the aging effect due to natural oxidation does not confound the Raman spectral measurements and that blood treated with hydrogen peroxide to induce oxidative stress can be discriminated from normal blood with a high accuracy of greater than 90% demonstrating potential for use in a clinical setting.

Raman spectroscopy as a potential tool for label free therapeutic drug monitoring in human serum: the case of busulfan and methotrexate

A methodology is proposed, based on Raman spectroscopy coupled with multivariate analysis, to determine the Limit of Detection (LOD) and Limit of Quantification (LOQ) for therapeutic drug monitoring in human serum, using the examples of Busulfan and Methotrexate.

Analysis of bodily fluids using vibrational spectroscopy: a direct comparison of Raman scattering and infrared absorption techniques for the case of glucose in blood serum

Analysis of biomarkers present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies.

Raman spectroscopic screening of high and low molecular weight fractions of human serum

This study explores the suitability of Raman spectroscopy as a bioanalytical tool, when coupled with ultra-filtration and multivariate analysis, to detect imbalances in both high molecular weight and low molecular weight fractions of the same samples of human patient serum, in the native liquid form.

Development of a high throughput (HT) Raman spectroscopy method for rapid screening of liquid blood plasma from prostate cancer patients

Extensive research has been undertaken on the examination of tissue biopsies using vibrational spectroscopic techniques. However, fewer studies have focused on less invasive and commonly acquired blood samples. Recent studies have shown the ability of Raman and Fourier transform infrared (FTIR) spectroscopy to discriminate between non-cancer controls and cancer cases using blood serum or plasma. Even though many studies have proposed Raman spectroscopy as a potential diagnostic tool in various cancers, the Raman spectroscopic technique has not been introduced as a routine clinical technology. This is due to multiple drawbacks with the application of the technique, including sample preparation, the requirement for expensive substrates and long acquisition times. The current study aims to overcome these limitations and focuses on the translation of Raman spectroscopy into a high throughput clinical diagnostic tool for prostate cancer. In this study, the effect of different instrumental and sample preparation parameters were investigated, with the aim of identifying a combination that would reduce the overall acquisition time for spectra from peripheral blood plasma, reduce the complexity of sample preparation and retain the classification accuracy from Raman spectroscopic diagnostics. A high throughput (HT) system was developed and Raman spectroscopic measurements were performed on plasma samples from 10 prostate cancer patients and 10 healthy volunteers. The spectra were pre-processed and classified by principal component analysis - linear discriminant analysis (PCA-LDA) in the R environment. Statistically significant differences were observed between Raman spectra of prostate cancer patients and non-cancer controls. The (HT) classification resulted in a sensitivity and specificity of 96.5% and 95% respectively. Overall, this study has overcome some of the limitations associated with clinical translation of Raman spectroscopy. The HT-Raman spectroscopy method developed in this study can be used for rapid and accurate diagnosis of prostate cancer using liquid plasma samples.

Multicomponent analysis using a confocal Raman microscope

Measuring the concentration of multiple chemical components in a low-volume aqueous mixture by Raman spectroscopy has received significant interest in the literature. All of the contributions to date focus on the design of optical systems that facilitate the recording of spectra with high signal-to-noise ratio by collecting as many Raman scattered photons as possible. In this study, the confocal Raman microscope setup is investigated for multicomponent analysis. Partial least-squares regression is used to quantify physiologically relevant aqueous mixtures of glucose, lactic acid, and urea. The predicted error is 17.81 mg/dL for glucose, 10.6 mg/dL for lactic acid, and 7.6 mg/dL for urea, although this can be improved with increased acquisition times. A theoretical analysis of the method is proposed, which relates the numerical aperture and the magnification of the microscope objective, as well as the confocal pinhole size, to the performance of the technique.

Biofluid infrared spectro-diagnostics: pre-analytical considerations for clinical applications

Several proof-of-concept studies on the vibrational spectroscopy of biofluids have demonstrated that the methodology has promising potential as a clinical diagnostic tool. However, these studies also show that there is a lack of a standardised protocol in sample handling and preparation prior to spectroscopic analysis. One of the most important sources of analytical errors is the pre-analytical phase. For the technique to be translated into clinics, it is clear that a very strict protocol needs to be established for such biological samples. This study focuses on some of the aspects of the pre-analytical phase in the development of the high-throughput Fourier Transform Infrared (FTIR) spectroscopy of some of the most common biofluids such as serum, plasma and bile. Pre-analytical considerations that can impact either the samples (solvents, anti-coagulants, freeze-thaw cycles…) and/or spectroscopic analysis (sample preparation such as drying, deposit methods, volumes, substrates, operators dependence…) and consequently the quality and the reproducibility of spectral data will be discussed in this report.

Biofluid spectroscopic disease diagnostics: A review on the processes and spectral impact of drying

The complex patterns observed from evaporated liquid drops have been examined extensively over the last 20 years. Complete understanding of drop deposition is vital in many medical processes, and one which is essential to the translation of biofluid spectroscopic disease diagnostics. The promising use of spectroscopy in disease diagnosis has been hindered by the complicated patterns left by dried biological fluids which may inhibit the clinical translation of this technology. Coffee-ring formation, cracking and gelation patterns have all been observed in biofluid drops, and with surface homogeneity being a key element to many spectroscopic techniques, experimental issues have been found to arise. A better understanding of the fundamental processes involved in a drying droplet could allow efficient progression in this research field, and ultimately benefit the population with the development of a reliable cancer diagnostic.

In vitro label-free screening of chemotherapeutic drugs using Raman microspectroscopy: Towards a new paradigm of spectralomics

This overview groups some of the recent studies highlighting the potential application of Raman microspectroscopy as an analytical technique in preclinical development to predict drug mechanism of action and in clinical application as a companion diagnostic and in personalised therapy due to its capacity to predict cellular resistance and therefore to optimise chemotherapeutic treatment efficacy. Notably, the anthracyclines, doxorubicin and actinomycin D, elicit similar spectroscopic signatures of subcellular interaction characteristic of the mode of action of intercalation. Although cisplatin and vincristine show markedly different signatures, at low exposure doses, their signatures at higher doses show marked similarities to those elicited by the intercalating anthracyclines, confirming that anticancer agents can have different modes of action with different spectroscopic signatures, depending on the dose. The study demonstrates that Raman microspectroscopy can elucidate subcellular transport and accumulation pathways of chemotherapeutic agents, characterise and fingerprint their mode of action, and potentially identify cell-resistant strains. The consistency of the spectroscopic signatures for drugs of similar modes of action, in different cell lines, suggests that this fingerprint can be considered a "spectralome" of the drug-cell interaction suggesting a new paradigm of representing spectroscopic responses.