Diagnosis of liver cancer from blood sera using FTIR microspectroscopy: a preliminary study

Infrared Spectroscopy for Rapid Triage of Cancer Using Blood Derivatives: A Reality Check

Infrared (IR) spectroscopy of serum/plasma represents an alluring molecular diagnostic tool, especially for cancer, as it can provide a molecular fingerprint of clinical samples based on vibrational modes of chemical bonds. However, despite the superior performance, the routine adoption of this technique for clinical settings has remained elusive. This is due to the potential confounding factors that are often overlooked and pose a significant barrier to clinical translation. In this Perspective, we summarize the concerns associated with various confounding factors, such as fluid sampling, optical effects, hemolysis, abnormal cardiovascular and/or hepatic functions, infections, alcoholism, diet style, age, and gender of a patient or normal control cohort, and improper selection of numerical methods that ultimately would lead to improper spectral diagnosis. We also propose some precautionary measures to overcome the challenges associated with these confounding factors.

Advances in far-infrared research: therapeutic mechanisms of disease and application in cancer detection

Far infrared (FIR) irradiation is commonly used as a convenient, non-contact, non-invasive treatment for diseases such as myocardial ischemia, diabetes, and chronic kidney disease. In this review, we focus on reviewing the potential therapeutic mechanisms of FIR and its cutting-edge applications in cancer detection. Firstly, we searched the relevant literature in the last decade for systematic screening and briefly summarized the biophysical properties of FIR. We then focused on the possible mechanisms of FIR in wound healing, cardiovascular diseases, and other chronic diseases. In addition, we review recent applications of FIR in cancer detection, where Fourier transform infrared spectroscopy and infrared thermography provide additional diagnostic methods for the medical diagnosis of cancer. Finally, we conclude and look into the future development of FIR for disease treatment and cancer detection. As a high-frequency non-ionizing wave, FIR has the advantages of safety, convenience, and low cost. We hope that this review can provide biological information reference and relevant data support for those who are interested in FIR and related high-frequency non-ionizing waves, to promote the further application of FIR in the biomedical field.

FTIR Spectroscopy and Blood-Derived Extracellular Vesicles Duo in Alzheimer's Disease

Background

Alzheimer's disease (AD) diagnosis is difficult, and new accurate tools based on peripheral biofluids are urgently needed. Extracellular vesicles (EVs) emerged as a valuable source of biomarker profiles for AD, since their cargo is disease-specific and these can be easily isolated from easily accessible biofluids, as blood. Fourier Transform Infrared (FTIR) spectroscopy can be employed to analyze EVs and obtain the spectroscopic profiles from different regions of the spectra, simultaneously characterizing carbohydrates, nucleic acids, proteins, and lipids.

Objective

The aim of this study was to identify blood-derived EVs (bdEVs) spectroscopic signatures with AD discriminatory potential.

Methods

Herein, FTIR spectra of bdEVs from two biofluids (serum and plasma) and distinct sets of Controls and AD cases were acquired, and EVs' spectra analyzed.

Results

Analysis of bdEVs second derivative peaks area revealed differences between Controls and AD cases in distinct spectra regions, assigned to carbohydrates and nucleic acids, amides, and lipids.

Conclusions

EVs' spectroscopic profiles presented AD discriminatory value, supporting the use of bdEVs combined with FTIR as a screening or complementary tool for AD diagnosis.

Diagnosis and monitoring of hepatocellular carcinoma in Hepatitis C virus patients using attenuated total reflection Fourier transform infrared spectroscopy

BACKGROUND

Current diagnostic methods for assessment of hepatitis C virus related hepatocellular carcinoma and subsequent categorization of hepatocellular carcinoma into non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma, to establish appropriate treatment strategies, are costly, invasive and requires multiple screening steps. This demands alternative diagnostic approaches that are cost-effective, time-efficient, and minimally invasive, while maintaining their efficacy for screening of hepatitis c virus related hepatocellular carcinoma. In this study, we propose that attenuated total reflection Fourier transform infrared in conjunction with principal component analysis - linear discriminant analysis and support vector machine multivariate algorithms holds a potential as a sensitive tool for the detection of hepatitis C virus-related hepatocellular carcinoma and the subsequent categorization of hepatocellular carcinoma into non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma.

METHODS

Freeze-dried sera samples collected from 31 hepatitis c virus related hepatocellular carcinoma patients and 30 healthy individuals, were used to acquire mid-infrared absorbance spectra (3500-900 cm-1) using attenuated total reflection Fourier transform infrared. Chemometric machine learning techniques were utilized to build principal component analysis - linear discriminant analysis and support vector machine discriminant models for the spectral data of hepatocellular carcinoma patients and healthy individuals. Sensitivity, specificity, and external validation on blind samples were calculated.

RESULTS

Major variations were observed in the two spectral regions i.e., 3500-2800 and 1800-900 cm-1. IR spectral signatures of hepatocellular carcinoma were reliably different from healthy individuals. Principal component analysis - linear discriminant analysis and support vector machine models computed 100% accuracy for diagnosing hepatocellular carcinoma. To classify the non-angio-invasive hepatocellular carcinoma/ angio-invasive hepatocellular carcinoma status, diagnostic accuracy of 86.21% was achieved for principal component analysis - linear discriminant analysis. While the support vector machine showed a training accuracy of 98.28% and a cross-validation accuracy of 82.75%. External validation for support vector machine based classification observed 100% sensitivity and specificity for accurately classifying the freeze-dried sera samples for all categories.

CONCLUSIONS

We present the specific spectral signatures for non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma, which were prominently differentiated from healthy individuals. This study provides an initial insight into the potential of attenuated total reflection Fourier transform infrared to diagnose hepatitis C virus related hepatocellular carcinoma but also to further categorize into non-angio-invasive and angio-invasive hepatocellular carcinoma.

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.

Mroue K, Mall R, Ullah E, S. Al-Akl N, Arredouani A. Investigation of the Effect of Exendin-4 on Oleic Acid-Induced Steatosis in HepG2 Cells Using Fourier Transform Infrared Spectroscopy

Non-alcoholic fatty liver disease (NAFLD) is a common liver lesion that is untreatable with medications. Glucagon-like peptide-1 receptor (GLP-1R) agonists have recently emerged as a potential NAFLD pharmacotherapy. However, the molecular mechanisms underlying these drugs’ beneficial effects are not fully understood. Using Fourier transform infrared (FTIR) spectroscopy, we sought to investigate the biochemical changes in a steatosis cell model treated or not with the GLP-1R agonist Exendin-4 (Ex-4). HepG2 cells were made steatotic with 400 µM of oleic acid and then treated with 200 nM Ex-4 in order to reduce lipid accumulation. We quantified steatosis using the Oil Red O staining method. We investigated the biochemical alterations induced by steatosis and Ex-4 treatment using Fourier transform infrared (FTIR) spectroscopy and chemometric analyses. Analysis of the Oil Red O staining showed that Ex-4 significantly reduces steatosis. This reduction was confirmed by FTIR analysis, as the phospholipid band (C=O) at 1740 cm⁻¹ in Ex-4 treated cells is significantly decreased compared to steatotic cells. The principal component analysis score plots for both the lipid and protein regions showed that the untreated and Ex-4-treated samples, while still separated, are clustered close to each other, far from the steatotic cells. The biochemical and structural changes induced by OA-induced lipotoxicity are at least partially reversed upon Ex-4 treatment. FTIR and chemometric analyses revealed that Ex-4 significantly reduces OA-induced lipid accumulation, and Ex-4 also restored the lipid and protein biochemical alterations caused by lipotoxicity-induced oxidative stress. In combination with chemometric analyses, FTIR spectroscopy may offer new approaches for investigating the mechanisms underpinning NAFLD.

Metabolic Profile Characterization of Different Thyroid Nodules Using FTIR Spectroscopy: A Review

Thyroid cancer’s incidence has increased in the last decades, and its diagnosis can be a challenge. Further and complementary testing based in biochemical alterations may be important to correctly identify thyroid cancer and prevent unnecessary surgery. Fourier-transform infrared (FTIR) spectroscopy is a metabolomic technique that has already shown promising results in cancer metabolome analysis of neoplastic thyroid tissue, in the identification and classification of prostate tumor tissues and of breast carcinoma, among others. This work aims to gather and discuss published information on the ability of FTIR spectroscopy to be used in metabolomic studies of the thyroid, including discriminating between benign and malignant thyroid samples and grading and classifying different types of thyroid tumors.

Diagnosis of liver cancer by FTIR spectra of serum

Liver cancer is the most common fatal malignant tumor in the world. Early diagnosis of liver cancer can improve the survival rate of the patients with liver disease. In this paper, Fourier transform infrared (FTIR) spectroscopy combined with curve fitting and chemometrics was used to distinguish the serum from patients from that of healthy people. The curve fitting results in protein range of 1700-1600 cm^-1 showed that there were differences in the secondary structure of protein in serum between the patients with liver cancer and healthy people. Principal component analysis (PCA) in lipid range of 2900-2800 cm^-1 could distinguish the serum of patients with liver cancer from that of healthy people. The first two principal components PC1 and PC2 explained 95% of the total data variance. The sensitivity and specificity of partial least squares discriminant analysis (PLS-DA) in lipid range of 2900-2800 cm^-1 reached 92.85% and 95.23% respectively. It is shown that FTIR spectroscopy might be developed as an effective method for the diagnosis of liver cancer.

Detection of Human Cholangiocarcinoma Markers in Serum Using Infrared Spectroscopy

Simple Summary

Cholangiocarcinoma is a form of liver cancer that is found, predominantly, in Thailand. Due to the non-specific symptoms and laboratory investigation, it is difficult to rule out cholangiocarcinoma from other liver conditions. Here, we demonstrate the development of a diagnostic tool for cholangiocarcinoma, based on the ATR-FTIR analyses of sera, coupled with multivariate analyses and machine learning tools to obtain a better specificity. The innovative approach that shows highly promising results for this otherwise difficult to diagnose cancer.

Abstract

Cholangiocarcinoma (CCA) is a malignancy of the bile duct epithelium. Opisthorchis viverrini infection is a known high-risk factor for CCA and in found, predominantly, in Northeast Thailand. The silent disease development and ineffective diagnosis have led to late-stage detection and reduction in the survival rate. Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) is currently being explored as a diagnostic tool in medicine. In this study, we apply ATR-FTIR to discriminate CCA sera from hepatocellular carcinoma (HCC), biliary disease (BD) and healthy donors using a multivariate analysis. Spectral markers differing from healthy ones are observed in the collagen band at 1284, 1339 and 1035 cm⁻¹, the phosphate band (vsPO2−) at 1073 cm⁻¹, the polysaccharides band at 1152 cm⁻¹ and 1747 cm⁻¹ of lipid ester carbonyl. A Principal Component Analysis (PCA) shows discrimination between CCA and healthy sera using the 1400–1000 cm⁻¹ region and the combined 1800—1700 + 1400–1000 cm⁻¹ region. Partial Least Square-Discriminant Analysis (PLS-DA) scores plots in four of five regions investigated, namely, the 1400–1000 cm⁻¹, 1800–1000 cm⁻¹, 3000–2800 + 1800–1000 cm⁻¹ and 1800–1700 + 1400–1000 cm⁻¹ regions, show discrimination between sera from CCA and healthy volunteers. It was not possible to separate CCA from HCC and BD by PCA and PLS-DA. CCA spectral modelling is established using the PLS-DA, Support Vector Machine (SVM), Random Forest (RF) and Neural Network (NN). The best model is the NN, which achieved a sensitivity of 80–100% and a specificity between 83 and 100% for CCA, depending on the spectral window used to model the spectra. This study demonstrates the potential of ATR-FTIR spectroscopy and spectral modelling as an additional tool to discriminate CCA from other conditions.

Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes

Vitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3.

Graphic abstract

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.

Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring

Health state transitions are reflected in characteristic changes in the molecular composition of biofluids. Detecting these changes in parallel, across a broad spectrum of molecular species, could contribute to the detection of abnormal physiologies. Fingerprinting of biofluids by infrared vibrational spectroscopy offers that capacity. Whether its potential for health monitoring can indeed be exploited critically depends on how stable infrared molecular fingerprints (IMFs) of individuals prove to be over time. Here we report a proof-of-concept study that addresses this question. Using Fourier-transform infrared spectroscopy, we have fingerprinted blood serum and plasma samples from 31 healthy, non-symptomatic individuals, who were sampled up to 13 times over a period of 7 weeks and again after 6 months. The measurements were performed directly on liquid serum and plasma samples, yielding a time- and cost-effective workflow and a high degree of reproducibility. The resulting IMFs were found to be highly stable over clinically relevant time scales. Single measurements yielded a multiplicity of person-specific spectral markers, allowing individual molecular phenotypes to be detected and followed over time. This previously unknown temporal stability of individual biochemical fingerprints forms the basis for future applications of blood-based infrared spectral fingerprinting as a multiomics-based mode of health monitoring.

Vibrational Spectroscopic Investigation of Blood Plasma and Serum by Drop Coating Deposition for Clinical Application

In recent decades, vibrational spectroscopic methods such as Raman and FT-IR spectroscopy are widely applied to investigate plasma and serum samples. These methods are combined with drop coating deposition techniques to pre-concentrate the biomolecules in the dried droplet to improve the detected vibrational signal. However, most often encountered challenge is the inhomogeneous redistribution of biomolecules due to the coffee-ring effect. In this study, the variation in biomolecule distribution within the dried-sample droplet has been investigated using Raman and FT-IR spectroscopy and fluorescence lifetime imaging method. The plasma-sample from healthy donors were investigated to show the spectral differences between the inner and outer-ring region of the dried-sample droplet. Further, the preferred location of deposition of the most abundant protein albumin in the blood during the drying process of the plasma has been illustrated by using deuterated albumin. Subsequently, two patients with different cardiac-related diseases were investigated exemplarily to illustrate the variation in the pattern of plasma and serum biomolecule distribution during the drying process and its impact on patient-stratification. The study shows that a uniform sampling position of the droplet, both at the inner and the outer ring, is necessary for thorough clinical characterization of the patient’s plasma and serum sample using vibrational spectroscopy.

Gelation and vibrational spectroscopy of tropical surimi induced by ascorbic acid and hydrogen peroxide

The combined effect of ascorbic acid (AsA) and hydrogen peroxide (H₂ O₂ ) on gel-forming ability and structural changes of lizardfish (LZ) and threadfin bream (TB) surimi were investigated. Addition of 0.15% AsA and 0.1% H₂ O₂ greatly increased breaking force and distance of LZ surimi by 300% and 55%, respectively. Combination of 0.2% AsA and 0.15% H₂ O₂ resulted in the maximum TB surimi gel improvement with 150% and 90% increase in breaking force and distance, respectively. Browning reaction obviously occurred when combined AsA and H₂ O₂ was added, due to ascorbic acid oxidation. Polymerization of myosin heavy chain via disulfide bonds was promoted, and the formation of disulfide bonds was involved through oxidation of sulfhydryl groups with increasing AsA and H₂ O₂ . Fourier-transform infrared (FT-IR) spectroscopy revealed a decrease in α-helix and an increase in β-sheet content as AsA and H₂ O₂ increased in both species. A decrease of band area of aliphatic (2,800 to 3,000 and 1,450 cm^-1 ), aromatic (1,208, 757, and ratio 850/830 cm^-1 ), and change of disulfide bonds (525 and 540 cm^-1 ) suggested an increase in hydrophobic interactions and disulfide bonds with addition of these additives. Based on principal component analysis (PCA), textural characteristics were positively correlated with β-sheet content. Our study suggested that combination of AsA and H₂ O₂ greatly enhanced gelation of LZ and TB by increasing not only disulfide bonds but also hydrophobic interactions. PRACTICAL APPLICATION: The combined ascorbic acid and hydrogen peroxide can be used to improve gelation of two important tropical surimi species, namely threadfin bream and lizardfish surimi, without requirement of setting. The optimum concentration of each additive varied with fish species.

Monitoring the Progression of Liver Fluke-Induced Cholangiocarcinoma in a Hamster Model Using Synchrotron FTIR Microspectroscopy and Focal Plane Array Infrared Imaging

Cholangiocarcinoma (CCA) is a bile duct cancer that originates in the bile duct epithelium. Northeastern Thailand has the highest incidence of CCA, and there is a direct correlation with liver fluke (Opisthorchis viverrini) infection. The high mortality rate of CCA is a consequence of delayed diagnosis. Fourier transform infrared (FTIR) spectroscopy is a powerful technique that detects the absorbance of molecular vibrations and is perfectly suited for the interrogation of biological samples. In this study, we applied synchrotron radiation-FTIR (SR-FTIR) microspectroscopy and focal plane array (FPA-FTIR) microspectroscopy to characterize periductal fibrosis and bile duct cells progressing to CCA induced by inoculating O. viverrini metacercariae into hamsters. SR-FTIR and FPA-FTIR measurements were performed in liver sections harvested from 1-, 2-, 3-, and 6-month post-infected hamsters compared to uninfected liver tissues. Principal component analysis (PCA) of the tissue samples showed a clear discrimination among uninfected and early-stage (1 and 2 months) and cancerous-stage (3 and 6 months) tissues. The discrimination is based on intensity changes in the phosphodiester band (1081 cm^-1), amino acid residue (∼1396 cm^-1), and C═O stretching carboxylic esters (1745 cm^-1). Infected tissues also show definitive bands at ∼1280, 1234, and 1201 cm^-1 characteristic of the collagen triplet and indicative of fibrosis. Hierarchical cluster analysis (HCA) was performed on the FPA data and showed a classification into specific cell types. Hepatocyte, fibrotic lesion, and bile duct (cancer) were classified and HCA mapping showed similar cellular distribution pattern compared to Sirius red staining. This study was also extended to less invasive sample analysis using attenuated total reflectance-FTIR (ATR-FTIR) spectroscopy. Sera from O. viverrini-infected and uninfected hamsters were analyzed using multivariate analysis, including principal component analysis (PCA), and partial least squares-discriminant analysis (PLS-DA). PCA was able to classify spectra of normal, early-stage CCA, and CCA, while the PLS-DA gave 100% accuracy for the validation. The model was established from 17 samples (11 normal, 6 cancer) in the calibration set and 9 samples in the validation set (4 normal, 2 cancer, 3 precancerous). These results indicate that FTIR-based technology is a potential tool to detect the progression of CCA, especially in the early stages of the disease.

Investigation of molecular mechanisms of experimental compounds in murine models of chronic allergic airways disease using synchrotron Fourier-transform infrared microspectroscopy

The ovalbumin-induced (OVA) chronic allergic airways murine model is a well-established model for investigating pre-clinical therapies for chronic allergic airways diseases, such as asthma. Here, we examined the effects of several experimental compounds with potential anti-asthmatic effects including resveratrol (RV), relaxin (RLN), l-sulforaphane (LSF), valproic acid (VPA), and trichostatin A (TSA) using both a prevention and reversal model of chronic allergic airways disease. We undertook a novel analytical approach using focal plane array (FPA) and synchrotron Fourier-transform infrared (S-FTIR) microspectroscopic techniques to provide new insights into the mechanisms of action of these experimental compounds. Apart from the typical biological effects, S-FTIR microspectroscopy was able to detect changes in nucleic acids and protein acetylation. Further, we validated the reduction in collagen deposition induced by each experimental compound evaluated. Although this has previously been observed with conventional histological methods, the S-FTIR technique has the advantage of allowing identification of the type of collagen present. More generally, our findings highlight the potential utility of S-FTIR and FPA-FTIR imaging techniques in enabling a better mechanistic understanding of novel asthma therapeutics.

Vibrational spectroscopy as a powerful tool for follow-up immunoadsorption therapy treatment of dilated cardiomyopathy - a case report

Dilated cardiomyopathy (DCM) is a leading cardiomyopathy condition and is the leading reason for heart transplantation. Due to high etiologic and genetic heterogeneity of the pathologies, different therapeutic treatment strategies are available and have been successful for different treatments. Immunoadsorption (IA) therapy removes the circulating anticardiac antibodies and improves the left ventricular function in substantial proportion of DCM patients. Powerful, non-invasive analytical tools are highly desired to investigate the efficiency and success of IA therapy. In this contribution, we followed the changes of a female DCM patient undergoing IA therapy at different treatment time points in a label-free, non-invasive manner from blood samples (plasma and serum) on the basis of vibrational spectroscopy (Raman scattering and IR absorption). Chemometric methods, including dimension reduction and statistical modeling, were used to interpret spectral data. The impact of different time points of the IA treatment can be identified in both the plasma and serum, using both techniques, with high accuracy. The removal of antibodies of immunoglobulin G (IgG) group during IA therapy and their restoration was reflected in both Raman and FTIR spectra. Relative changes in the spectral bands assigned to IgG agreed well with the immunoturbidimetry measurement of total IgG. Successful clinical treatment was accompanied by spectral differences between vibrational spectra obtained at initial disease state and 11 months after the IA treatment. The long-term follow-up of the patient reveals the stabilization of the health state after therapy. It is noteworthy that the treatment time points were distinguished with a better accuracy using spectra from plasma compared to those from serum samples, which might indicate the involvement of corresponding proteins in the coagulation. Vibrational spectroscopy is a powerful tool for personalized medicine to follow-up the treatment success of IA therapy for the DCM disorder.

The mid-infrared spectroscopy: A novel non-invasive diagnostic tool for NASH diagnosis in severe obesity

There is an urgent medical need to develop non-invasive tests for non-alcoholic steatohepatitis (NASH). This study evaluates the diagnostic performance of an innovative model based on mid-infrared (MIR) spectroscopy for the diagnosis of NASH.

Methods

Severely obese patients who underwent a bariatric procedure at the University Hospital of Nice, France (n = 395) were prospectively recruited. The clinico-biological characteristics were measured prior to surgery. Liver biopsies were collected during the surgical procedure and assessed by a pathologist. A training group (316 patients, NASH: 16.8%) and a validation group (79 patients, NASH: 16.5%) were randomly defined. MIR spectra were acquired by fiber evanescent wave spectroscopy, using chalcogenide glass fiber optic sensors and a spectrometer. This absorption spectroscopic technique delivers a spectrum that identifies the molecular composition of a sample, defining a patient's metabolic fingerprint.

Results

The areas under the receiver operating curve (AUROC) for the diagnosis of NASH were 0.82 and 0.77 in the training and validation groups, respectively. The best threshold was 0.15, which was associated with a sensitivity of 0.75 and 0.69, and a specificity of 0.72 and 0.76. Negative predictive values of 0.94 and 0.93 and positive predictive values of 0.35 and 0.36, as well as correctly classified patient rates of 72% and 75% were obtained in the training and validation groups, respectively. A composite model using aspartate aminotransferase level, triglyceride level and waist circumference alongside the MIR spectra led to an increase in AUROC (0.88 and 0.84 for the training and validations groups, respectively).

Conclusions

MIR spectroscopy provides good sensitivity and negative predictive values for NASH screening in patients with severe obesity.

Lay summary

There is an urgent need for tools to non-invasively diagnose and monitor non-alcoholic steatohepatitis (NASH). This study evaluates the performance of a new tool for fast NASH diagnosis based on mid-infrared (MIR) spectroscopy. Using serum samples from severely obese patients who underwent a bariatric procedure, which enabled a concomitant liver biopsy to be performed, the MIR spectroscopy model performed well in screening patients for NASH compared to a traditional, histological diagnosis.

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There is no validated non-invasive diagnostic tool for NASH in routine care.

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NASH follow-up requires a non-invasive diagnostic method.

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Using a simple drop of serum, the mid-infrared spectrum captures a patient’s metabolic fingerprint.

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A model based on mid-infrared spectroscopy provides efficient NASH screening for patients with severe obesity.

An investigation on annular cartilage samples for post-mortem interval estimation using Fourier transform infrared spectroscopy

Many attempts have been made to estimate the post-mortem interval (PMI) using bioanalytical methods based on multiple biological samples. Cartilage tissues could be used as an alternative for this purpose because their rate of degradation is slower than that of other soft tissue or biofluid samples. In this study, we applied Fourier transform infrared (FTIR) spectroscopy to acquire bioinformation from human annular cartilages within 30 days post-mortem. Principal component analysis (PCA) showed that sex and causes of death have almost no impact on the overall spectral variations caused by post-mortem changes. With pre-processing approaches, several predicted models were established using a conventional machine learning method, known as the partial least square (PLS) regression. The best model achieved a satisfactory prediction with a low error of 1.49 days using the second derivative transform of 3-point smoothing and extended multiplicative scatter correction (EMSC), and the spectral regions from proteins and carbohydrates contributed greatly to the PMI prediction. This study demonstrates the feasibility of cartilage-based FTIR analysis for PMI estimation. Further work will introduce advanced algorithms for more accurate and precise PMI prediction.

New approach to investigate Common Variable Immunodeficiency patients using spectrochemical analysis of blood

Common variable immune deficiency (CVID) is a primary immunodeficiency disease, characterized by hypogammaglobulinemia, recurrent infections and various complications. The clinical heterogeneity of CVID has hindered identification of an underlying immune defect; diagnosis relies on clinical judgement, alongside evidence-based criteria. The lack of pathognomonic clinical or laboratory features leads to average diagnostic delays of 5 years or more from the onset. Vibrational spectroscopic techniques such as Fourier-transform infrared (FTIR) spectroscopy have recently gained increasing clinical importance, being rapid-, non-invasive and inexpensive methods to obtain information on the content of biological samples. This has led us to apply FTIR spectroscopy to the investigation of blood samples from a cohort of CVID patients; revealing spectral features capable of stratifying CVID patients from healthy controls with sensitivities and specificities of 97% and 93%, respectively for serum, and 94% and 95%, respectively for plasma. Furthermore we identified several discriminating spectral biomarkers; wavenumbers in regions indicative of nucleic acids (984 cm⁻¹, 1053 cm⁻¹, 1084 cm⁻¹, 1115 cm⁻¹, 1528 cm⁻¹, 1639 cm⁻¹), and a collagen-associated biomarker (1528 cm⁻¹), which may represent future candidate biomarkers and provide new knowledge on the aetiology of CVID. This proof-of-concept study provides a basis for developing a novel diagnostic tool for CVID.

Postmortem diagnosis of fatal hypothermia/hyperthermia by spectrochemical analysis of plasma

Postmortem diagnosis of extreme-weather-related deaths is a challenging forensic task. Here, we present a state-of-the-art study that employed attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy in combination with Chemometrics for postmortem diagnosis of fatal hypothermia/hyperthermia by biochemical investigation of plasma in rats. The results of principal component analysis (PCA) and spectral analysis revealed that plasma samples from the fatal hypothermia, fatal hyperthermia, and control groups, are substantially different from each other based on the spectral variations associated with the lipid, carbohydrate and nucleic acid components. Two partial least squares-discriminant analysis (PLS-DA) classification models (hypothermia-nonhypothermia and hyperthermia-nonhyperthermia binary models) with a 100% accuracy rate were constructed. Subsequently, internal cross-validation was performed to assess the robustness of these two models, which resulted in 98.1 and 100% accuracy. Ultimately, classification predictions of 42 unknown plasma samples were performed by these two models, and both models achieved 100% accuracy. Additionally, our results demonstrated that hemolysis and postmortem hypothermic/hyperthermic effects did not weaken the prediction ability of these two classification models. In summary, this work demonstrates ATR-FTIR spectroscopy's great potential for postmortem diagnosis of fatal hypothermia/hyperthermia.

Phenotype Profiling for Forensic Purposes: Determining Donor Sex Based on Fourier Transform Infrared Spectroscopy of Urine Traces

Forensic science is an important field of analytical chemistry where vibrational spectroscopy, in particular Fourier transform infrared spectroscopy and Raman spectroscopy, present advantages as they have a nondestructive nature, high selectivity, and no need for sample preparation. Herein, we demonstrate a method for determination of donor sex, based on attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy of dry urine traces. Trace body fluid evidence is of special importance to the modern criminal investigation as a source of individualizing DNA evidence. However, individual identification of a urine donor is generally difficult because of the small amount of DNA. Therefore, the development of an innovative method to provide phenotype information about the urine donor-including sex-is highly desirable. In this study, we developed a multivariate discriminant model for the ATR FT-IR spectra of dry urine to identify the donor sex. Rigorous selection of significant wavenumbers on the spectrum using a genetic algorithm enabled superb discrimination performance for the model and conclusively indicated a chemical origin for donor sex differences, which was supported by physiological knowledge. Although further investigations need to be conducted, this proof-of-concept study demonstrates the great potential of the developed methodology for phenotype profiling based on the analysis of urine traces.

Comments on recent reports on infrared spectral detection of disease markers in blood components

The search for disease markers in whole blood, or easily accessible blood components by spectral methods is a highly important aspect in the field of biophotonic research for disease diagnostics and screening, since it promises a minimally invasive approach to assess an individual's state of health. Fourier transform infrared spectroscopy, in particular, promises to be a fast, inexpensive method to search for markers of disease, since it detects variation in the proteome, lipidome and metabolome of biofluids, or activation of immune cells. However, the analysis of any materials by spectral methods is confounded by external factors such as those related to sample deposition and data acquisition, and by inherent variations in blood plasma concentration of small molecules (lactate, carbonate, phosphate, glucose) that varies between individual subjects and even for a given individual, as a function of time. Furthermore, observed differences in spectral patterns between patient samples and the control group may be due to the body's immune response (in particular, to the albumin to globulin ratio) and therefore, may not be specific to disease. These factors need to be accounted for in any effort to reliably detect much smaller variations in the concentration of disease-specific markers.

A possible Fourier transform infrared-based plasma fingerprint of angiotensin-converting enzyme inhibitor-induced reversal of endothelial dysfunction in diabetic mice

Angiotensin-converting enzyme inhibitors (ACE-I) display vasoprotective activity and represent the cornerstone in the treatment of cardiovascular diseases. In this study, we tested whether Fourier transform infrared (FTIR)-based analysis of blood plasma is sensitive to detect vasoprotective effects of treatment with perindopril including reversal of endothelial dysfunction in diabetes. For this purpose, plasma samples were collected from untreated db/db mice, db/db mice treated with 2 or 10 mg/kg perindopril and db+ mice. The effect of perindopril on endothelial function was examined in ex vivo aortic rings; 10 mg/kg but not 2 mg/kg of perindopril reversed endothelial dysfunction. In plasma of db/db mice, the balance between conformations of plasma proteins was noted, and treatment with perindopril at a high dose but not at a low dose reversed this effect. This was revealed by amide II/amide I ratio attributed to increased β-sheet formation. Spectral markers at 3010, 1520/1238 cm^-1 , representative for unsaturation degree of lipids and phosphorylation of tyrosine, respectively, were also affected by perindopril treatment. In conclusion, although metabolic abnormalities associated with type 2 diabetes mellitus such as hypertriglyceridemia and hyperglycemia strongly affected spectral FTIR profile of diabetic plasma, we identified FTIR features that seem to be associated with the vasoprotective activity of ACE-I.

Serum-based diagnostic prediction of oral submucous fibrosis using FTIR spectrometry

Oral submucous fibrosis (OSF) is found to have the highest malignant potentiality among all other pre-cancerous lesions. However, its detection prior to tissue biopsy can be challenging in clinics. Moreover, biopsy examination is invasive and painful. Hence, there is an urgent need of new technology that facilitates accurate diagnostic prediction of OSF prior to biopsy. Here, we used FTIR spectroscopy coupled with chemometric techniques to distinguish the serum metabolic signatures of OSF patients (n=30) and healthy controls (n=30). Serum biochemical analyses have been performed to further support the FTIR findings. Absorbance intensities of 45 infrared wavenumbers differed significantly between OSF and normal serum FTIR spectra representing alterations in carbohydrates, proteins, lipids and nucleic acids. Nineteen prominent significant wavenumbers (P≤0.001) at 1020, 1025, 1035, 1039, 1045, 1078, 1055, 1100, 1117, 1122, 1151, 1169, 1243, 1313, 1398, 1453, 1544, 1650 and 1725cm^-1 provided excellent segregation of OSF spectra from normal using multivariate statistical techniques. These findings provided essential information on the metabolic features of blood serum of OSF patients and established that FTIR spectroscopy coupled with chemometric analysis can be potentially useful in the rapid and accurate preoperative screening/diagnosis of OSF.

Mid-infrared spectroscopy of serum, a promising non-invasive method to assess prognosis in patients with ascites and cirrhosis

Background & aims

Prognostic tests are critical in the management of patients with cirrhosis and ascites. Biological tests or scores perform poorly in that situation. Mid-infrared fibre evanescent wave spectroscopy (MIR-FEWS) which allows for global serum metabolic profiling may provide more relevant information by measuring a wider range of metabolic parameters in serum. Here we present the accuracy of a MIR-FEWS based predictive model for the prognosis of 6 months survival in patients with ascites and cirrhosis.

Methods

Patients with ascites were prospectively included and followed up for 6 months. MIR-FEWS spectra were measured in serum samples. The most informative spectral variables obtained by MIR-FEWS were selected by FADA algorithm and then used to build the MIR model. Accuracy of this model was assessed by ROC curves and 90%/10% Monte Carlo cross-validation. MIR model accuracy for 6 months survival was compared to that of the Child-Pugh and MELD scores.

Results

119 patients were included. The mean age was 57.36±13.70, the MELD score was 16.32±6.26, and the Child-Pugh score was 9.5±1.83. During follow-up, 23 patients died (20%). The MIR model had an AUROC for 6 months mortality of 0.90 (CI95: 0.88–0.91), the MELD 0.77 (CI95: 0.66–0.89) and Child-Pugh 0.76 (CI95: 0.66–0.88). MELD and Child-Pugh AUROCs were significantly lower than that of the MIR model (p = 0.02 and p = 0.02 respectively). Multivariate logistic regression analysis showed that MELD (p<0.05, OR:0.86;CI95:0.76–0.97), Beta blockers (p = 0.036;OR:0.20;CI95:0.04–0.90), and the MIR model (p<0.001; OR:0.50; CI95:0.37–0.66), were significantly associated with 6 months mortality.

Conclusions

In this pilot study MIR-FEWS more accurately assess the 6-month prognosis of patients with ascites and cirrhosis than the MELD or Child-Pugh scores. These promising results, if confirmed by a larger study, suggest that mid infrared spectroscopy could be helpful in the management of these patients.

Spectral Mining for Discriminating Blood Origins in the Presence of Substrate Interference via Attenuated Total Reflection Fourier Transform Infrared Spectroscopy: Postmortem or Antemortem Blood?

Often in criminal investigations, discrimination of types of body fluid evidence is crucially important to ascertain how a crime was committed. Compared to current methods using biochemical techniques, vibrational spectroscopic approaches can provide versatile applicability to identify various body fluid types without sample invasion. However, their applicability is limited to pure body fluid samples because important signals from body fluids incorporated in a substrate are affected strongly by interference from substrate signals. Herein, we describe a novel approach to recover body fluid signals that are embedded in strong substrate interferences using attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy and an innovative multivariate spectral processing. This technique supported detection of covert features of body fluid signals, and then identified origins of body fluid stains on substrates. We discriminated between ATR FT-IR spectra of postmortem blood (PB) and those of antemortem blood (AB) by creating a multivariate statistics model. From ATR FT-IR spectra of PB and AB stains on interfering substrates (polyester, cotton, and denim), blood-originated signals were extracted by a weighted linear regression approach we developed originally using principal components of both blood and substrate spectra. The blood-originated signals were finally classified by the discriminant model, demonstrating high discriminant accuracy. The present method can identify body fluid evidence independently of the substrate type, which is expected to promote the application of vibrational spectroscopic techniques in forensic body fluid analysis.

Analytical Techniques in Lipidomics: State of the Art

Current studies related to lipid identification and determination, or lipidomics in biological samples, are one of the most important issues in modern bioanalytical chemistry. There are many articles dedicated to specific analytical strategies used in lipidomics in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to a comprehensive review of the actual analytical methodologies used in lipidomics. The aim of this article is to characterize the lipidomics methods used in modern bioanalysis according to the methodological point of view: (1) chromatography/separation methods, (2) spectroscopic methods and (3) mass spectrometry and also hyphenated methods. In the first part, we discussed thin layer chromatography (TLC), high-pressure liquid chromatography (HPLC), gas chromatography (GC) and capillary electrophoresis (CE). The second part includes spectroscopic techniques such as Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR). The third part is a synthetic review of mass spectrometry, matrix-assisted laser desorption/ionization (MALDI), hyphenated methods, which include liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and also multidimensional techniques. Other aspects are the possibilities of the application of the described methods in lipidomics studies. Due to the fact that the exploration of new methods of lipidomics analysis and their applications in clinical and medical studies are still challenging for researchers working in life science, we hope that this review article will be very useful for readers.

Modern trends in biophotonics for clinical diagnosis and therapy to solve unmet clinical needs

This contribution covers recent original research papers in the biophotonics field. The content is organized into main techniques such as multiphoton microscopy, Raman spectroscopy, infrared spectroscopy, optical coherence tomography and photoacoustic tomography, and their applications in the context of fluid, cell, tissue and skin diagnostics. Special attention is paid to vascular and blood flow diagnostics, photothermal and photodynamic therapy, tissue therapy, cell characterization, and biosensors for biomarker detection.

Alterations in plasma biochemical composition in NO deficiency induced by L-NAME in mice analysed by Fourier Transform Infrared Spectroscopy

Mouse model of nitric oxide deficiency, induced by prolonged treatment with N^G -nitro-L-arginine methyl ester (L-NAME) was used for infrared spectroscopy (FTIR) analysis of plasma. L-NAME leads to increased peripheral resistance and systemic hypertension. Classification of spectral response was by principal component analysis (PCA) and linear discriminant analysis (LDA). PCA allowed to separate each animal group showing that FTIR spectra are sensitive to development of NO-deficiency on contrary to blood pressure values indicating hypertension. Globally, the most pronounced spectral alternations were observed in the second and third week of L-NAME treatment indicating that infrared signature of blood plasma can serve as indicator of early and late stages of the disease. The PLS-DA method provided >95% classification accuracy. Spectral features characteristic for L-NAME treatment were mainly associated with an elevated level of proteins accompanied by a decrease of a tyrosine content and changes in lipids/phospholipid concentration. In our work we discuss these changes for which statistically significant differences (p < 0.05 - 0.005) were observed between spectra collected for each time-point of the L-NAME treatment versus control subjects. We demonstrated for the first time that NO-deficiency and hypertension resulted in changes in biochemical profile of plasma that was detected by FTIR spectroscopy.

FT-IR imaging for quantitative determination of liver fat content in non-alcoholic fatty liver

In this work we apply FT-IR imaging of large areas of liver tissue cross-section samples (∼5 cm × 5 cm) for quantitative assessment of steatosis in murine model of Non-Alcoholic Fatty Liver (NAFLD). We quantified the area of liver tissue occupied by lipid droplets (LDs) by FT-IR imaging and Oil Red O (ORO) staining for comparison. Two alternative FT-IR based approaches are presented. The first, straightforward method, was based on average spectra from tissues and provided values of the fat content by using a PLS regression model and the reference method. The second one – the chemometric-based method – enabled us to determine the values of the fat content, independently of the reference method by means of k-means cluster (KMC) analysis. In summary, FT-IR images of large size liver sections may prove to be useful for quantifying liver steatosis without the need of tissue staining.

Mid-infrared fibre evanescent wave spectroscopy of serum allows fingerprinting of the hepatic metabolic status in mice

Infrared spectroscopy from mice unveils a transition in the time course of steatosis.

Plasma biomarkers of pulmonary hypertension identified by Fourier transform infrared spectroscopy and principal component analysis

The main goal of this study was to find specific plasma spectral markers associated with pulmonary arterial hypertension (PAH) induced by monocrotaline injection in rats. FTIR was used to monitor biochemical changes in plasma caused by PAH as compared with the systemic hypertension induced by partial ligation on the left artery and with the control group. Both pathologies, systemic and pulmonary hypertension, induced a unique response in the biochemical content of plasma, mainly related to the composition and secondary structure of plasma proteins. For PAH, β-pleated sheet components of plasma proteins were identified whereas the protein composition in systemic hypertension was dominated by unordered structures. In addition, a higher concentration of tyrosine-rich proteins was found in plasma in PAH than in systemic hypertension. The differences between both pathologies were identified also in terms of lipid composition/metabolism as well as in the content of RNA and glucose, suggesting that lipid peroxidation appears upon pulmonary hypertension development. In summary, this work demonstrates that FTIR spectroscopy supported by principal component analysis (PCA) has the potential to become a fast and non-destructive method for biochemical characterization of plasma that consequently could have a diagnostic significance in pulmonary hypertension.

Comparison of FTIR transmission and transfection substrates for canine liver cancer detection

FTIR spectroscopy is a widely used technique that provides insights into disease processes at the molecular level.