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

Quantitative or qualitative biomolecular changes in blood serum composition induced by childhood obesity: A Fourier transform infrared examination

Childhood obesity (CO) negatively affects one in three children and stands as the fourth most common risk factor of health and well-being. Clarifying the molecular and structural modifications that transpire during the development of obesity is crucial for understanding its progression and devising effective therapies. The study was indeed conducted as part of an ongoing CO treatment trial, where data were collected from children diagnosed with CO before the initiation of non-drug treatment interventions. Our primary aim was to analyze the biochemical changes associated with childhood obesity, specifically focusing on concentrations of lipids, lipoproteins, insulin, and glucose. By comparing these parameters between the CO group (n = 60) and a control group of healthy children (n = 43), we sought to elucidate the metabolic differences present in individuals with CO. Our biochemical analyses unveiled lower LDL (low-density lipoproteins) levels and higher HDL (high-density lipoproteins), cholesterol, triglycerides, insulin, and glucose levels in CO individuals compared to controls. To scrutinize these changes in more detail, we employed Fourier transform infrared (FTIR) spectroscopy on the serum samples. Our results indicated elevated levels of lipids and proteins in the serum of CO, compared to controls. Additionally, we noted structural changes in the vibrations of glucose, β-sheet, and lipids in CO group. The FTIR technique, coupled with principal component analysis (PCA), demonstrated a marked differentiation between CO and controls, particularly in the FTIR region corresponding to amide and lipids. The Pearson test revealed a stronger correlation between biochemical data and FTIR spectra than between 2nd derivative FTIR spectra. Overall, our study provides valuable insights into the molecular and structural changes occurring in CO.

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

BACKGROUND

Glioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation.

METHODS

Plasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations.

RESULTS

The derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of β-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas.

CONCLUSIONS

The plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of β-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.

The Hydrolysis of Pigment-Protein Phycoerythrin by Bromelain Enhances the Color Stability

Phycoerythrin (PE) is a natural protein-pigment complex with a strong pink color, but it is sensitive to thermal and light variations. In this study, PE was extracted from Porphyra haitanensis in a yield of 0.2% (w/w). The phycoerythrin hydrolysates (PEH) (3-10 kDa) were prepared by enzymatic hydrolysis of PE with bromelain (8000 U/g) at 47 °C for 30 min, with a degree of hydrolysis (DH) of 11.57 ± 0.39% and a color degradation rate of 7.98 ± 0.39%. The physicochemical properties of PEH were evaluated. The UV and fluorescence spectra indicated that bromelain changed the microenvironment around phycoerythrobilin (PEB). The infrared spectrum revealed that the bromelain hydrolysis increased the α-helix content of PEH. The scanning electron microscope showed that bromelain destroyed the dense and smooth structure of PE, resulting in irregular porous structures. The radical scavenging activities of DPPH and ABTS of PEH were increased relative to that of PE (p < 0.05). The thermal (50-80 °C)-, UV (0.5-3 h)-, visible light irradiation (2-8 h)-, and metal ion exposing stabilities of PEH were significantly improved (p < 0.05). This study provides a potential scheme for overcoming the sensitivity of PE to thermal and light variations and facilitates PEH as a natural colorant ingredient in food and pigment applications.

FTIR- based serum structure analysis in molecular diagnostics of essential thrombocythemia disease

Essential thrombocythemia (ET) reflects the transformation of a multipotent hematopoietic stem cell, but its molecular pathogenesis remains obscure. Nevertheless, tyrosine kinase, especially Janus kinase 2 (JAK2), has been implicated in myeloproliferative disorders other than chronic myeloid leukaemia. FTIR analysis was performed on the blood serum of 86 patients and 45 healthy volunteers as control with FTIR spectra-based machine learning methods and chemometrics. Thus, the study aimed to determine biomolecular changes and separation of ET and healthy control groups illustration by applying chemometrics and ML techniques to spectral data. The FTIR-based results showed that in ET disease with JAK2 mutation, there are alterations in functional groups associated with lipids, proteins and nucleic acids significantly. Moreover, in ET patients the lower amount of proteins with simultaneously higher amount of lipids was noted in comparison with the control one. Furthermore, the SVM-DA model showed 100% accuracy in calibration sets in both spectral regions and 100.0% and 96.43% accuracy in prediction sets for the 800-1800 cm^-1 and 2700-3000 cm^-1 spectral regions, respectively. While changes in the dynamic spectra showed that CH₂ bending, amide II and CO vibrations could be used as a spectroscopy marker of ET. Finally, it was found a positive correlation between FTIR peaks and first bone marrow fibrosis degree, as well as the absence of JAK2 V617F mutation. The findings of this study contribute to a better understanding of the molecular pathogenesis of ET and identifying biomolecular changes and may have implications for early diagnosis and treatment of this disease.

Application of Fourier transform infrared spectroscopy to detect biochemical changes in blood serum of obese patients

Obesity is frequently a significant risk factor for multiple obesity-associated diseases that have been increasing in prevalence worldwide. Anthropometric data such as body mass index, fat, and fat mass values are assessed for obesity. Therefore, we aimed to propose two Fourier transform infrared (FT-IR) spectral regions, 800-1800 cm^-1 and 2700-3000 cm^-1 , as sensitive potential band assignments for obesity-related biochemical changes. A total of 134 obese (n = 89) and controls (n = 45) biochemical characteristics and clinical parameters indicative of obesity were evaluated. The FT-IR spectra of dried blood serum were measured. Anthropometric data of the obese have the highest body mass index, %fat, and fat mass values compared to the healthy group (p < 0.01). Also, the triglyceride and high-density lipoprotein cholesterol levels were higher than in healthy subjects (p < 0.01). Principal component analysis (PCA) technique successfully distinguished obese and control groups in the fingerprint, accounting for 98.5% and 99.9% of the total variability (800-1800 cm^-1 ) and lipids (2700-3000 cm^-1 ) regions presented as 2D and 3D score plots. The loading results indicated that peaks corresponding to phosphonate groups, glucose, amide I, and lipid groups were shifted in the obese group, indicating their potential as biomarkers of obesity. This study suggests that FTIR analysis based on PCA can provide a detailed and reliable method for the analysis of blood serum in obese patients.

Influence of measurement mode on the results of glioblastoma multiforme analysis with the FTIR microspectroscopy

Fourier Transform Infrared (FTIR) microspectroscopy is well known for its effectiveness in spectral and biochemical analyses of various materials. It enables to determine the sample biochemical composition by assigning detected frequencies, characteristic for functional groups of main biological macromolecules. In analysis of tissue sections one of two measurement modes, namely transmission and transflection, is usually applied. The first one has relatively straightforward geometry, hence it is considered to be more precise and accurate. However, IR-transparent media are very fragile and expensive. Transflection does not require expensive substrates, but is more prone to disruptive influence of Mie scattering as well as electric field standing wave effect. The excessive comparison of spectra' characteristics, obtained via both measurement modes, was performed in this paper. By the means of Mann-Whitney non-parametrical U test and PCA, the comparison of results obtained with both modes and assessment of usefulness of IR spectra obtained with transmission and transflection modes to differentiate between healthy and GBM-affected tissue, were performed. The main objective of the presented research is to compare the results of FTIR analysis of unfixed biological samples performed with transflection and transmission mode. In frame of the study we demonstrated the discrepancies between results of biochemical analysis performed based on data obtained with transmission and transflection. Such observation suggests that caution should be taken in drawing conclusions from the results obtained with transflection geometry, as its more prone to disruptive effects. Despite that, IR spectra developed with both modes allowed to distinguish GBM area from healthy tissue, which proves their diagnostic potential. Especially, application of the ME-EMSC correction of spectra before PCA enhances the performance of both methods to distinguish the analysed tissue areas.

Correlation between human colon cancer specific antigens and Raman spectra. Attempting to use Raman spectroscopy in the determination of tumor markers for colon cancer

Colorectal cancer is the second most common cause of cancer-related deaths worldwide. To follow up on the progression of the disease, tumor markers are commonly used. Here, we report serum analysis based on Raman spectroscopy to provide a rapid cancer diagnosis with tumor markers and two new cell adhesion molecules measured using the ELİSA method. Raman spectra showed higher Raman intensities at 1447 cm^-1 1560 cm^-1, 1665 cm^-1, and 1769 cm^-1, which originated from CH₂ proteins and lipids, amide II and amide I, and CO lipids vibrations. Furthermore, the correlation test showed, that only the CEA colon cancer marker correlated with the Raman spectra. Importantly, machine learning methods showed, that the accuracy of the Raman method in the detection of colon cancer was around 95 %. Obtained results suggest, that Raman shifts at 1302 cm^-1 and 1306 cm^-1 can be used as spectroscopy markers of colon cancer.

Prognostic significance of serum CA125 in the overall management for patients with gastrointestinal stromal tumors

BACKGROUND

Carbohydrate antigen 125 (CA125) is elevated as a tumor marker in many carcinomas, but its association with gastrointestinal stromal tumor (GIST) has received less attention. This study intends to evaluate whether CA125 level can predict tumor progression and overall survival (OS) of GIST patients.

METHODS

We retrospectively analyzed the clinical data and follow-up records of GIST patients who underwent surgical resection in Nanjing Drum Tower Hospital from August 2010 to December 2020. All patients were classified according to serum CA125 level. The relationship between CA125 and clinical outcomes was then examined.

RESULTS

A total of 406 GIST patients were enrolled in this study, among which 46 patients had preoperative elevated serum CA125 level and 13 patients with high CA125 level both preoperative and postoperative were observed. Preoperative CA125 concentration was significantly related to rupture status, resection style, tumor site, tumor size, mitotic index, NIH risk grade and c-kit exons. According to Kaplan-Meier curve analysis, high expression of postoperative CA125 was significantly correlated with worse progression-free survival (PFS) and OS among patients with preoperative elevated CA125 level. Ultimately, Cox proportional regression model analysis revealed that increase of preoperative and concurrent postoperative CA125 concentration was an independent predictive factor for PFS.

CONCLUSIONS

The concurrent abnormality of serum CA125 before and after operation was an independent risk factor for GIST progression, suggesting its significance as a serum biomarker in the overall management of GIST patients.

Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers

Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cancers (DTC) to detect abundant changes and select specific markers in a broad spectrum of molecular species. Here, we present a diagnostic protocol of DTC in which the in-situ blood-based ATR-FTIR spectroscopic data mining pathway was designed for the identification of DTC triages in 252 blood serum samples, divided into the following groups: liver cancer (LC), gastric cancer (GC), colorectal cancer (CC), and their different three stages respectively. The infrared molecular fingerprints (IMFs) of DTC were measured and used to build a 2-dimensional second derivative spectrum (2D-SD-IR) feature dataset for classification, including absorbance and wavenumber shifts of FTIR vibration peaks. By comparison, the Partial Least-Squares Discriminant Analysis (PLS-DA) and backpropagation (BP) neural networks are suitable to differentiate DTCs and pathological stages with a high sensitivity and specificity of 100% and averaged more than 95%. Furthermore, the measured IMF data was mutually validated via clinical blood biochemistry testing, which indicated that the proposed 2D-SD-IR-based machine learning protocol greatly improved DTC classification performance.

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.

Apocynin reduces cytotoxic effects of monosodium glutamate in the brain: A spectroscopic, oxidative load, and machine learning study

Herein, we examined the modulatory effects ofApocynum (APO) on Monosodium Glutamate (MSG)-induced oxidative damage on the brain tissue of rats after long-term consumption of blood serum components by biochemical assays, Fourier transform infrared spectroscopy(FTIR), and machine learning methods. Sprague-Dawley male rats were randomly divided into the Control, Control + APO, MSG, and MSG + APO groups (n = 8 per group). All administrations were made by oral gavage saline, MSG, or APO and they were repeated for 28 days of the experiments. Brain tissue and blood serum samples were collected and analyzed for measurement levels ofmalondialdehyde (MDA),glutathione (GSH),myeloperoxidase (MPO), superoxide dismutase (SOD) activity, and Spectroscopic analysis. After 29 days, the results were evaluated using machine learning (ML). The levels of MDA and MPO showed changes in the MSG and MSG + APO groups, respectively. Changes in the proteins and lipids were observed in the FTIR spectra of the MSG groups. Additionally, APO in these animals improved the FTIR spectra to be similar to those in the Control group. The accuracy of the FTIR results calculated by ML was 100%. The findings of this study demonstrate that Apocynin treatment protectsagainst MSG-induced oxidative damage by inhibitingreactive oxygen speciesand upregulatingantioxidant capacity, indicating its potential in alleviatingthe toxic effects of MSG.

Blood serum lipid profiling may improve the management of recurrent miscarriage: a combination of machine learning of mid-infrared spectra and biochemical assays

The present article is focused on developing and validating an efficient, credible, minimally invasive technique based on spectral signatures of blood samples of women with recurrent miscarriage vs. those of healthy individuals who were followed in the Department of Obstetrics and Gynecology for 2 years. For this purpose, blood samples from a total of 120 participants, including healthy women (n=60) and women with diagnosed recurrent miscarriage (n=60), were obtained. The lipid profile (high-density lipoprotein, low-density lipoprotein, triglyceride, and total cholesterol levels) and lipid peroxidation (malondialdehyde and glutathione levels) were evaluated with a Beckman Coulter analyzer system for chemical analysis. Biomolecular structure and composition were determined using an attenuated total reflectance sampling methodology with Fourier transform infrared spectroscopy alongside machine learning technology to advance toward clinical translation. Here, we developed and validated instrumentation for the analysis of recurrent miscarriage patient serum that was able to differentiate recurrent miscarriage and control patients with an accuracy of 100% using a Fourier transform infrared region corresponding to lipids. We found that predictors of lipid profile abnormalities in maternal serum could significantly improve this patient pathway. The study also presents preliminary results from the first prospective clinical validation study of its kind.

One-Drop Serum Screening Test for Anal Cancer in Men via Infrared Attenuated Total Reflection Spectroscopy

Rare cancers are a challenge for clinical practice, the treatment experience at major centers to which rare cancers are referred is limited and are the most difficult to diagnose. Research to identify causes or develop prevention and early detection strategies is extremely challenging. Anal cancer is an example of a rare cancer, with the human papillomavirus (HPV) infection being the most important risk factor associated. In the early stages, anal cancer does not exhibit evident symptoms. This disease is diagnosed by means of anoscopy, which diagnoses some cases of early cancer; nevertheless, sensitivity of this test ranges between 47 and 89%. Therefore, the development of new, effective, and evidence-based screening methodologies for the early detection of rare cancers is of great relevance. In this study, the potential of ATR-FTIR spectroscopy has been explored as a sensitive, nondestructive, and inexpensive analytical method for developing disease screening platforms in serum. Spectral differences were found in the regions of 1700-1100 and 1700-1400 cm^-1 between the control group and the anal cancer group related to the presence of proteins and nucleic acids. The chemometric analysis presented differences in the spectral fingerprints for both spectral regions with a high sensitivity ranging from 95.2 to 99.9% and a specificity ranging from 99.2 to 100%. This is the first step that we report for a methodology that is fast, nondestructive, and easy to perform, and the high sensitivity and specificity of the method are the basis for extensive research studies to implement these technologies in the clinical field.

Differential of cholangiocarcinoma disease using Raman spectroscopy combined with multivariate analysis

Cholangiocarcinoma (CCA) is a type of cancer, which 5-year survival is lower than 20 %, and which is detected mostly in advanced stage of the disease. Unfortunately, there are no diagnostic tools, which could show changes in the body indicating the development of the disease. Therefore, in this study, we investigate Raman spectroscopy as a promising analytical tool in medical diagnostics and as a method, which would allow to distinguish between healthy patients and patients suffering from cholangiocarcinoma. The obtained Raman spectra showed, that lower intensities of peaks corresponding to amino acids and proteins, as well as higher intensities of peaks originating from lipids vibrations were observed in healthy individuals in comparison with cancer patients. Moreover, Partial Last Square (PLS), Principal Component Analysis (PCA) and Hierarchical Component Analysis (HCA) of Raman spectra indicate that the ranges between 800 cm^-1 and 1800 cm^-1, 3477 cm^-1 -3322 cm^-1 and 1394 cm^-1 -1297 cm^-1 allow to distinguish cancer patients from healthy ones. The obtained results showed, that Raman spectroscopy is a good candidate, to become in future one of the diagnostic tools of Cholangiocarcinoma.

Determination of idiopathic female infertility from infrared spectra of follicle fluid combined with gonadotrophin levels, multivariate analysis and machine learning methods

By in vitro fertilization, oocytes can be removed and the embryo can be cultured, and then trans cervically replaced when they reach cleavage or when the blastocyst stage. The characterization of the follicular fluid is important for the treatment process. Women who applied to the Academic Hospital in vitro fertilization (IVF) Center diagnosed with idiopathic female infertility (IFI) were sought in the patient group. Demographics and clinical gonadotropin measurements of the study population were recorded. Of the 116 follicular fluid samples (n=58 male-induced infertility; n=58 control) were analyzed using the FTIR system. To identify FTIR spectral characteristics of follicular fluids associated with an ovarian reserve and reproductive hormone levels from control and IFI, six machine learning methods and multivariate analysis were used. To assess the quantitative information about the total biochemical composition of a follicular fluid across various diagnoses. FTIR spectra showed a higher level of vibrations corresponding to lipids and a lower level of amide vibrations in the IFI group. Furthermore, the T square plot from Partial Last Square (PLS) analysis showed, that these vibrations can be used to distinguish IFI from the control group which was obtained by principal component analysis (PCA). Proteins and lipids play an important role in the development of IFI. The absorption dynamics of FTIR spectra showed wavenumbers with around 100% discrimination probability, which means, that the presented wavenumbers can be used as a spectroscopic marker of IFI. Also, six machine learning methods showed, that classification accuracy for the original set was from 93.75% to 100% depending on the learning algorithm used. These results can inform about IFI women's follicular fluid has biomacromolecular differentiation in their follicular fluid. By using a safe and effective tool for the characterization of changes in follicular fluid during in vitro fertilization, this study builds upon a comprehensive examination of the idiopathic female infertility remodeling process in human studies. We anticipate that this technology will be a valuable adjunct for clinical studies.

Effect of Agricultural Organic Inputs on Nanoplastics Transport in Saturated Goethite-Coated Porous Media: Particle Size Selectivity and Role of Dissolved Organic Matter

The transport of nanoplastics (NPs) through porous media is influenced by dissolved organic matter (DOM) released from agricultural organic inputs. Here, cotransport of NPs with three types of DOM (biochar_DOM (BC_DOM), wheat straw_DOM (WS_DOM), and swine manure_DOM (SM_DOM)) was investigated in saturated goethite (GT)-coated sand columns. The results showed that codeposition of 50 nm NPs (50NPs) with DOM occurred due to the formation of a GT-DOM-50NPs complex, while DOM loaded on GT-coated sand and 400 nm NPs (400NPs) aided 400NPs transport due to electrostatic repulsion. According to the quantum chemical calculation, humic acid and cellulose played a significant role in 50NPs retardation. Owing to its high concentration, moderate humification index (HIX), and cellulose content, SM_DOM exhibited the highest retardation of 50NPs transport and promoting effect on 400NPs transport. Owing to a high HIX, the effect of BC_DOM on the mobility of 400NPs was higher than that of WS_DOM. However, high cellulose content in WS_DOM caused it to exhibit a 50NPs retardation ability that was similar to that of BC_DOM. Our results highlight the particle size selectivity and significant influence of DOM type on the transport of NPs and elucidate their quantum and colloidal chemical-interface mechanisms in a typical agricultural environment.

The bioactivity and applications of pomegranate peel extract: A review

Pomegranate peel (PP) is a by-product in the processing of pomegranate products, which is usually discarded as a waste. However, a large number of researches have shown that pomegranate peel extract (PPE) is rich in a variety of phenolic substances, among which ellagic acid (EA), as one of the main active components, has significant biological activities, such as anti-oxidation, anti-tumor, anti-inflammatory, neuroprotection, anti-viral, and anti-bacterial. We analyzed the mechanism of EA's biological activity, and discussed its application in the food industry, for instance, food preservation, food additives, and functional foods. Combined with the research status of PPE, we discussed the limitations and development potential of PPE, in order to provide theoretical reference and scientific basis for the development and utilization of pomegranate by-products. PRACTICAL APPLICATIONS: Pomegranate peel (PP), the inedible part of the fruit, is usually treated as waste. In recent years, researchers have been committed to exploring various bioactive ingredients in PP and exploring its potential benefits to human health, which has far-reaching significance. In this paper, the chemical constituents of polyphenols in PP were reviewed, mainly focusing on the biological activity and mechanism of ellagic acid (EA). We reviewed the applications and invention patents of pomegranate peel extract (PPE) in food field, including food preservation, food additive, and functional foods, providing reference for the recycling and reuse of PP.

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.

Diagnosis of endometriosis using endometrioma volume and vibrational spectroscopy with multivariate methods as a noninvasive method

Endometriomas are typically an advanced form of endometriosis that leads to the formation of scar tissue, adhesions, and an inflammatory reaction. There is no certain serum marker for the diagnosis of endometriosis. This study aims to research the correlation between the amount of peaks corresponding to proteins and lipids with the volume of endometrioma and determine the chemical structure of blood serum collected from women suffering from endometriosis patients with endometrioma and healthy subjects using Fourier Transform Infrared (FTIR) spectroscopy. FTIR spectroscopy is used as a non-invasive diagnostic technique for the discrimination of endometriosis women with endometrioma and control blood sera. The FTIR spectra of 100 serum samples acquired from 50 patients and 50 healthy individuals were used for this study. For this purpose, multivariate analyses such as Principal Component Analysis (PCA), Partial Last Square analysis (PLS) with Variables Importance in Projection (VIP), and probability models, were performed. Our results showed that FTIR range 1500 cm^-1 and 1700 cm^-1 and around 2700 cm^-1 - 3000 cm^-1, regions may be used for the diagnosis of endometriosis. Also, we find that proteins and lipids fraction increase with the volume of endometrioma. Moreover, PLS and VIP analysis suggested that lipids could be helpful in the diagnosis of endometriosis women with endometrioma.

Assessment of the effect of endocrine abnormalities on biomacromolecules and lipids by FT-IR and biochemical assays as biomarker of metabolites in early Polycystic ovary syndrome women

Polycystic ovary syndrome (PCOS) is a common endocrinopathy associated with metabolic disturbances. Both in the development and improvement of the disease, the structure of phospholipids and proteins in the blood serum plays important role in the treatment of these disease. Herein, to investigate the metabolic process and the variations of biomacromolecules and lipids between young PCOS women and healthy subjects, biochemistry and Fourier Transform InfraRed spectroscopy (FTIR) methods, were used. Moreover, partial least squares regression (PLS) and Principal component analysis (PCA) to research differentiation of biomacromolecules, were performed. We obtained blood serum of of 100 individuals including 57 with PCOS and 43 healthy controls. The biochemical blood profile of PCOS women was presented by spectroscopic measurements, which is an analytical technique, as well as by laboratory indexes and oxidative stress status measurements. There was a significant structural differentiation between studied groups in the number of functional groups and biomolecules differentiation depending on the protein expression and oxidative stress status. Hence, FTIR spectroscopy and oxidative load can be effectively utilized as tools for classifying quantitative and qualitative changes of biomolecules in PCOS samples. PCOS samples did not correlate with luteinizing hormone (LH) level and proteins but had a negative correlation between carbohydrates and fatty acids, compared with control group.