Rapid diagnosis of malignant pleural mesothelioma and its discrimination from lung cancer and benign exudative effusions using blood serum

Application of ATR-FTIR spectroscopy and multivariate statistical analysis in cancer diagnosis

Lung cancer is one of the most prevalent and lethal malignant tumors worldwide. Currently, clinical diagnosis primarily relies on chest X-ray examinations, histopathological analysis, and the detection of tumor markers in blood. However, each of these methods has inherent limitations. The current study aims to explore novel diagnostic approaches for lung cancer by employing attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy in conjunction with multiple machine learning models. Fourier transform infrared spectroscopy can detect subtle differences in the material structures that reflect the carcinogenic process between lung cancer tissues and normal tissues. By applying principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to analyze infrared spectral data, these subtle differences can be amplified. The study revealed that the combination of spectral bands within the 3500-3000 cm-1 and 1600-1500 cm-1 ranges is particularly significant for differentiating between the two groups. Three classification models-Support Vector Machine (SVM), k-Nearest Neighbor (kNN), and Linear Discriminant Analysis (LDA)-were constructed for spectral analysis of various band combinations. The results indicated that in detecting lung cancer samples, the combination of the 3500-3000 cm-1 and 1600-1500 cm-1 bands offers significant advantages. The analysis of the receiver operating characteristic (ROC) curve demonstrated that the area under the curve (AUC) exceeded 0.95 for all models, with the LDA model achieving an accuracy rate of 99.4% in identifying lung cancer patients compared to healthy individuals. The findings suggest that the integration of ATR-FTIR spectroscopy with multiple machine learning models represents a promising auxiliary diagnostic method for clinical lung cancer diagnosis, enabling detection at the molecular level.

Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques

Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly sensitive and minimally invasive early diagnostic methods. Near-infrared spectroscopy (NIRS) offers unique advantages in probing molecular vibrational information from blood, effectively capturing potential structural changes in haemoglobin (Hb) in lung cancer patients. In this study, we address the challenge of detecting subtle Hb features within the broader blood matrix and introduce an innovative two-stage spectral analysis framework. First, continuous wavelet transform (CWT) is employed to enhance spectral resolution and reinforce the key absorption bands of Hb. Subsequently, two-trace two-dimensional correlation spectroscopy (2T2D-COS) is applied to examine the fine vibrational differences-in both synchronous and asynchronous spectra-between lung cancer patients and healthy controls, revealing alterations in Hb secondary structures (e.g., α-helices and β-sheets). Results show that critical Hb-related peaks at 4862 cm-1, 4615 cm-1, and 4432 cm-1 undergo significant changes in lung cancer samples. Furthermore, combining these refined spectral features with machine learning classifiers (e.g., support vector machines) achieves an overall accuracy of 97.50 % and a sensitivity of 100.00 %. This work not only confirms the value of NIRS in detecting protein-level molecular information in blood but also presents a promising, efficient spectroscopic strategy for early lung cancer diagnosis, offering broad biomedical applicability.

Zerumbone Induces Apoptosis in Non-Small-Cell Lung Cancer via Biomolecular Alterations: A Microscopic and Spectroscopic Study

Zerumbone is a sesquiterpene phytochemical with cytotoxic activity against cancer. This study aimed to evaluate the effect of zerumbone on cell viability by WST-1 test, apoptosis by TUNEL, lipid peroxidation markers (malondialdehyde, MDA, and 4-hydroxynonenal, HNE) by using assay kits, and biomolecular changes by ATR-FTIR spectroscopy in A549 cells. After zerumbone (0-100 μM) incubation for 24, 48, and 72 h, the number of TUNEL-positive cells was found to be higher in zerumbone-treated cells than in controls, in consistent with cell morphology results. MDA levels increased significantly, although HNE levels increased non-significantly in zerumbone-treated cells. Spectral analyses revealed that the zerumbone-treated groups had higher levels of total saturated and unsaturated lipids as well as comparatively shorter-chain lipids. On the contrary, reduced RNA/DNA ratio, total nucleic acid, and protein content were found in zerumbone-treated groups. Consequently, zerumbone-induced apoptosis was accompanied by increased aldehyde products during lipid peroxidation as well as biomolecular alterations.

Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19

This study explores the molecular alterations and disease progression in COVID-19 patients using ATR-FTIR spectroscopy combined with spectrochemical and explainable artificial intelligence (XAI) approaches. Blood serum samples from intubated patients (IC), those receiving hospital services (SC), and recovered patients (PC) were analyzed to identify potential spectrochemical serum biomarkers. Spectrochemical parameters such as lipid, protein, nucleic acid concentrations, and IgG glycosylation were quantified, revealing significant alterations indicative of disease severity. Notably, increased lipid content, altered protein concentrations, and enhanced protein phosphorylation were observed in IC patients compared to SC and PC groups. The serum AGR (Albumin/Globulin Ratio) index demonstrated a distinct shift among patient groups, suggesting its potential as a rapid biochemical marker for COVID-19 severity. Additionally, alterations in IgG glycosylation and glucose concentrations were associated with disease severity. Spectral analysis highlighted specific bands indicative of nucleic acid concentrations, with notable changes observed in IC patients. XAI techniques further elucidated the importance of various spectral features in predicting disease severity across patient categories, emphasizing the heterogeneity of COVID-19's impact. Overall, this comprehensive approach provides insights into the molecular mechanisms underlying COVID-19 pathogenesis and offers a transparent and interpretable prediction algorithm to aid decision-making and patient management.

Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning

Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time-consuming, burden patients financially, and sometimes all test results can be negative. Therefore, rapid, cost-effective novel methods are essential for the early accurate diagnosis of MG. Here, we aimed to determine MG-induced spectral biomarkers from blood serum using infrared spectroscopy. Furthermore, infrared spectroscopy coupled with multivariate analysis methods e.g., principal component analysis (PCA), support vector machine (SVM), discriminant analysis and Neural Network Classifier were used for rapid MG diagnosis. The detailed spectral characterization studies revealed significant increases in lipid peroxidation; saturated lipid, protein, and DNA concentrations; protein phosphorylation; PO2-asym + sym /protein and PO2-sym/lipid ratios; as well as structural changes in protein with a significant decrease in lipid dynamics. All these spectral parameters can be used as biomarkers for MG diagnosis and also in MG therapy. Furthermore, MG was diagnosed with 100% accuracy, sensitivity and specificity values by infrared spectroscopy coupled with multivariate analysis methods. In conclusion, FTIR spectroscopy coupled with machine learning technology is advancing towards clinical translation as a rapid, low-cost, sensitive novel approach for MG diagnosis.

The investigation of the molecular changes during lipopolysaccharide-induced systemic inflammation on rat hippocampus by using FTIR spectroscopy

The aim of this study is to reveal the molecular changes accompanying the neuronal hyper-excitability during lipopolysaccharide (LPS)-induced systemic inflammation on rat hippocampus using Fourier transform infrared (FTIR) spectroscopy. For this aim, the body temperature of Wistar albino rats administered LPS or saline was recorded by radiotelemetry. The animals were decapitated when their body temperature began to decrease by 0.5°C after LPS treatment and the hippocampi of them were examined by FTIR spectroscopy. The results indicated that systemic inflammation caused lipid peroxidation, an increase in the amounts of lipids, proteins and nucleic acids, a decrease in membrane order, an increase in membrane dynamics and changes in the secondary structure of proteins. Principal component analysis successfully separated control and LPS-treated groups. In conclusion, significant structural, compositional and functional alterations occur in the hippocampus during systemic inflammation and these changes may have specific characteristics which can lead to neuronal hyper-excitability.

Understanding the transition to viable but non-culturable state in Escherichia coli W3110: a comprehensive analysis of potential spectrochemical biomarkers

The viable but non-culturable (VBNC) state is considered a survival strategy employed by bacteria to endure stressful conditions, allowing them to stay alive. Bacteria in this state remain unnoticed in live cell counts as they cannot proliferate in standard culture media. VBNC cells pose a significant health risk because they retain their virulence and can revive when conditions normalize. Hence, it is crucial to develop fast, reliable, and cost-effective methods to detect bacteria in the VBNC state, particularly in the context of public health, food safety, and microbial control assessments. This research examined the biomolecular changes in Escherichia coli W3110 induced into the VBNC state in artificial seawater under three different stress conditions (temperature, metal, and antibiotic). Initially, confirmation of VBNC cells under various stresses was done using fluorescence microscopy and plate counts. Subsequently, lipid peroxidation was assessed through the TBARS assay, revealing a notable increase in peroxidation end-products in VBNC cells compared to controls. ATR-FTIR spectroscopy and chemomometrics were employed to analyze biomolecular changes, uncovering significant spectral differences in RNA, protein, and nucleic acid concentrations in VBNC cells compared to controls. Notably, RNA levels increased, while protein and nucleic acid amounts decreased. ROC analyses identified the 995 cm- 1 RNA band as a consistent marker across all studied stress conditions, suggesting its potential as a robust biomarker for detecting cells induced into the VBNC state under various stressors.

Supplementing probiotics during intermittent fasting proves more effective in restoring ileum and colon tissues in aged rats

This study aimed to explore the impact of SCD Probiotics supplementation on biomolecule profiles and histopathology of ileum and colon tissues during a 30-day intermittent fasting (IF) program. Male Sprague-Dawley rats, aged 24 months, underwent 18-h daily fasting and received 3 mL (1 × 108 CFU) of SCD Probiotics. The differences in biomolecule profiles were determined using FTIR Spectroscopy and two machine learning techniques, Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), which showed significant differences with high accuracy rates. Spectrochemical bands indicating alterations in lipid, protein and nucleic acid profiles in both tissues. The most notable changes were observed in the group subjected to both IF and SCD Probiotics, particularly in the colon. Both interventions, individually and in combination, decreased protein carbonylation levels. SCD Probiotics exerted a more substantial impact on membrane dynamics than IF alone. Additionally, both IF and SCD Probiotics were found to have protective effects on intestinal structure and stability by reducing mast cell density and levels of TNF-α and NF-κB expression in ileum and colon tissues, thus potentially mitigating age-related intestinal damage and inflammation. Furthermore, our results illustrated that while IF and SCD Probiotics individually instigate unique changes in ileum and colon tissues, their combined application yielded more substantial benefits. This study provides evidence for the synergistic potential of IF and SCD Probiotics in combating age-related intestinal alterations.

Comparison of serum from lung cancer patients and from patients with benign lung nodule using FTIR spectroscopy

Lungcancer remains the leading cause of cancer related deaths in worldwide. Earlydiagnosis oflungcancer can significantly improve survival rate. However, due to its close resemblance to the malignant nodules, the possible existence of benign nodules often leads to erroneous decisions. The aim of this study was to explore whether fourier transform infrared (FTIR) spectroscopy could improve the accuracy of early diagnosis of lung cancer by distinguishing lung cancer patients' (LCP') serum from patients with benign lung nodules' (PBLN') serum. In this study, A1243+1081/A1652+1539 ratio in LCP group was increased significantly compared with that in PBLN group, indicating that the ratio could be used to distinguish the serum of LCP from that of PBLN. In addition, the ratios of A2926/A2969, A1744/A2926+2859, A2926+2859/A1652+1539 were also increased significantly in LCP group compared with that in PBLN group. These findings suggest that FTIR spectroscopy might be a potentially effective method for the early diagnosis of lung cancer.

SCD Probiotics mitigate cafeteria diet-induced liver damage in Wistar rats during development

BACKGROUND AND AIM

The liver plays a critical role in metabolic homeostasis, and its health is often compromised by poor dietary habits. This study aimed to investigate the therapeutic potential of SCD Probiotics in mitigating adverse liver effects induced by a cafeteria diet in male Wistar rats during their developmental period.

METHODS

Four groups of seven male Wistar rats each were subjected to different dietary regimens from day 21 (weaning) to day 56. The groups were as follows: a control group on normal feed; a probiotic-supplemented group on normal feed; a group on a cafeteria diet mixed with normal feed; and a group on a cafeteria diet mixed with normal feed, supplemented with SCD Probiotics. Liver health was assessed using Fourier transform infrared spectroscopy and histopathological evaluations.

RESULTS

Rats on the cafeteria diet exhibited significant disruptions in lipid, protein, cholesterol, triglyceride levels, and glycogen/phosphate content. Histopathological abnormalities such as lymphocytic infiltration, steatosis, and necrosis were also observed. However, SCD Probiotics supplementation led to notable improvements in the liver's biomolecular composition and mitigated histopathological abnormalities. Serum liver enzyme levels (AST, ALT, ALP, and LDH) also showed beneficial effects, while serum albumin levels remained stable.

CONCLUSIONS

SCD Probiotics demonstrated a promising potential to counteract the adverse liver effects induced by a cafeteria diet in male Wistar rats. The study revealed significant improvements in biomolecular composition, histopathology, and serum enzyme levels. However, these findings are preliminary and necessitate further in vivo studies and clinical trials for validation.

The rejuvenating influence of young plasma on aged intestine

This study aims to investigate the effects of plasma exchange on the biomolecular profiles and histology of ileum and colon tissues in young and aged Sprague-Dawley male rats. Fourier transform infrared (FTIR) spectroscopy, linear discriminant analysis and support vector machine (SVM) techniques were employed to analyse the lipid, protein, and nucleic acid indices in young and aged rats. Following the application of young plasma, aged rats demonstrated biomolecular profiles similar to those of their younger counterparts. Histopathological and immunohistochemical assessments showed that young plasma had a protective effect on the intestinal tissues of aged rats, increasing cell density and reducing inflammation. Additionally, the expression levels of key inflammatory mediators tumour necrosis factor-alpha and cyclooxygenase-2 significantly decreased after young plasma administration. These findings underscore the therapeutic potential of young plasma for mitigating age-related changes and inflammation in the intestinal tract. They highlight the critical role of plasma composition in the ageing process and suggest the need for further research to explore how different regions of the intestines respond to plasma exchange. Such understanding could facilitate the development of innovative therapies targeting the gastrointestinal system, enhancing overall health during ageing.

A Review of Machine Learning Methods Recently Applied to FTIR Spectroscopy Data for the Analysis of Human Blood Cells

Machine learning (ML) is a broad term encompassing several methods that allow us to learn from data. These methods may permit large real-world databases to be more rapidly translated to applications to inform patient-provider decision-making. This paper presents a review of articles that discuss the use of Fourier transform infrared (FTIR) spectroscopy and ML for human blood analysis between the years 2019-2023. The literature review was conducted to identify published research of employed ML linked with FTIR for distinction between pathological and healthy human blood cells. The articles' search strategy was implemented and studies meeting the eligibility criteria were evaluated. Relevant data related to the study design, statistical methods, and strengths and limitations were identified. A total of 39 publications in the last 5 years (2019-2023) were identified and evaluated for this review. Diverse methods, statistical packages, and approaches were used across the identified studies. The most common methods included support vector machine (SVM) and principal component analysis (PCA) approaches. Most studies applied internal validation and employed more than one algorithm, while only four studies applied one ML algorithm to the data. A wide variety of approaches, algorithms, statistical software, and validation strategies were employed in the application of ML methods. There is a need to ensure that multiple ML approaches are used, the model selection strategy is clearly defined, and both internal and external validation are necessary to be sure that the discrimination of human blood cells is being made with the highest efficient evidence.

The recovery effect of Vitamin C on structural alterations due to Streptozotocin-Induced diabetes in rat testicular tissues

Type I Diabetes is a multisystem disease that causes alterations in carbohydrate, protein, and fat metabolisms due to hyperglycemia. It has an extensive pathology, especially the mechanism involving oxidative stress is still complex. Type I diabetes is correlated with increased formation of free radicals and decreased levels of antioxidant potential. Vitamin C (Vit C) is a powerful antioxidant that participates in antioxidant defense, protecting lipid membranes and proteins from oxidative damage by donating electrons to free radicals. The effect of type I diabetes and the recovery role of Vit C on the structure and composition of the biomolecular content of testicular tissue is still unknown. Therefore, the current study aimed to investigate the alterations in the biomolecules of rat testes due to Streptozotocin (STZ)-induced type I diabetes using Attenuated Total Reflectance (ATR)-Fourier Transform Infrared (FTIR) spectroscopy and histological staining. The results revealed that the biomolecular structure and composition of testicular tissue are highly affected due to the development of diabetes. We obtained decreased saturation levels and increased unsaturation index in the lipids indicating the presence of lipid peroxidation in the diabetic state. The elevated lipid peroxidation levels have been implicated in the pathogenesis of naturally occurring and chemically induced diabetes. On the other hand, the protein content of diabetic rat testicular tissue was shown to decrease considerably, indicating an increase in proteolysis processes. Supporting the ratio of protein structural and conformational change, protein secondary structural components were also found to alter substantially in the diabetic state. Diabetes was also shown to lead to a decrease in the content of nucleic acids compared to proteins. These diabetes-induced alterations were found to be substantially recovered with the administration of Vit C. Although different doses and administration types of Vit C have been reported in the literature, there is no consensus yet. Therefore, we used three different doses of Vit C in our study as high (100 mg/kg/day), medium (50 mg/kg/day) and low (15 mg/kg/day) doses intraperitoneally in the present study, and the medium dose was found to be the most effective in the recovery from the diabetes-induced structural damages on rat testicular tissue. Vit C may have a therapeutic effect to be used as a complementary therapy in the treatment of diabetes.

Identification of circulating biomarkers of Crohn's disease and spondyloarthritis using Fourier transform infrared spectroscopy

Crohn's disease (CD) and spondyloarthritis (SpA) are two inflammatory diseases sharing many common features (genetic polymorphism, armamentarium). Both diseases lack diagnostic markers of certainty. While the diagnosis of CD is made by a combination of clinical, and biological criteria, the diagnosis of SpA may take several years to be confirmed. Based on the hypothesis that CD and SpA alter the biochemical profile of plasma, the objective of this study was to evaluate the analytical capability of Fourier transform infrared spectroscopy (FTIR) in identifying spectral biomarkers. Plasma from 104 patients was analyzed. After data processing of the spectra by Extended Multiplicative Signal Correction and linear discriminant analysis, we demonstrated that it was possible to distinguish CD and SpA from controls with an accuracy of 97% and 85% respectively. Spectral differences were mainly associated with proteins and lipids. This study showed that FTIR analysis is efficient to identify plasma biosignatures specific to CD or SpA.

Rapid and sensitive detection of esophageal cancer by FTIR spectroscopy of serum and plasma

Fourier transform infrared (FTIR) spectroscopy, as a platform technology for cancer detection, must be up to the challenge of clinical transformation. To this end, detection of esophageal squamous cell carcinoma (ESCC) was hereby explored using serum and plasma scrape-coated on barium fluoride (BaF₂) disk by transmission FTIR method, and the classification model was built using six multivariate statistical analyses, including support vector machine (SVM), principal component linear discriminant analysis (PC-LDA), decision tree (DT), k-nearest neighbor (KNN) classification, ensemble algorithms (EA) and partial least squares for discriminant analysis (PLS-DA). All statistical analyses methods demonstrated that late-stage cancer could be well classified from healthy people employing either serum or plasma with different anticoagulants. Resulting PC-LDA model differentiated late-stage cancer from normal group with an accuracy of 99.26%, a sensitivity of 98.53%, and a specificity of 100%. The accuracy and sensitivity reached 97.08% and 91.43%, respectively for early-stage cancer discrimination from normal group. This pilot exploration demonstrated that transmission FTIR provided a rapid, cost effective and sensitive method for ESCC diagnosis using either serum or plasma.

Infrared spectrochemical findings on intermittent fasting-associated gross molecular modifications in rat myocardium

Cardiovascular diseases are among the primary life-threatening conditions affecting human society. Intermittent fasting is shown to be functional in the prevention of cardiovascular diseases, however, the information on fasting-associated modifications in myocardial biomolecules is limited. This study aimed to determine the impact of 18-h intermittent fasting administered for five weeks on 12 months-old rats using supervised linear discriminant analysis and support vector machine algorithms constructed on spectrochemical data obtained from myocardial tissues. These algorithms revealed gross biomolecular modifications, while quantitative analyses demonstrated higher amounts of saturated lipids (19%), triglycerides (11%), and lipids (56%), in addition to enhancement in membrane dynamics (18%). The concentrations of nucleic acids and glucose are increased by 52%, while the glycogen content is diminished by 61%. The protein carbonylation/oxidation is reduced by 38%, whereas a 35% increase in protein content was measured. Phosphorylated proteins have been calculated to be at higher concentrations in the 13-62% range. The study findings demonstrated significant molecular changes in the myocardium of rats subjected to intermittent fasting.