Impact of Gut Microbiota and SCFAs in the Pathogenesis of PCOS and the Effect of Metformin Therapy.

Polycystic ovary syndrome (PCOS) is a complex disorder that impacts both the endocrine and metabolic systems, often resulting in infertility, obesity, insulin resistance, and cardiovascular complications. The aim of this study is to investigate the role of intestinal flora and its metabolites, particularly short-chain fatty acids (SCFAs), in the development of PCOS, and to assess the effects of metformin therapy on these components. SCFA levels in fecal and blood samples from women with PCOS (n=69) and healthy controls (n=18) were analyzed using Gas Chromatography-Mass Spectrometry (GC/MS) for precise measurement. Fecal microbiota were quantitatively detected by real-time polymerase chain reaction (PCR). To assess the efficacy of six months of metformin treatment, changes in the microbiota and SCFAs in the PCOS group (n=69) were also evaluated. The results revealed that women with PCOS exhibited a significant reduction in beneficial bacteria (namely, the C. leptum group and Prevotella spp.) alongside a notable overgrowth of opportunistic microorganisms (C. perfringens, C. difficile, Staphylococcus spp., and Streptococcus spp.). An overproduction of acetic acid (AA, FC=0.47, p<0.05) and valeric acid (VA, FC=0.54, p<0.05) suggests a link between elevated SCFAs and the development of obesity and PCOS. Interestingly, AA in the bloodstream might offer a protective effect against PCOS by ameliorating key symptoms such as high body mass index (r=-0.33, p=0.02), insulin resistance (r=-0.39, p=0.02), and chronic inflammation. Although serum SCFA levels showed non-significant changes following metformin treatment (p>0.05), the normalization of AA in the gut underscores that metformin exerts a more pronounced effect locally within the gastrointestinal tract. Furthermore, the study identified the most effective model for predicting the success of metformin therapy, based on serum concentrations of butyric acid (BA) and VA, achieving a 91% accuracy rate, 100% sensitivity, and 80% specificity. These promising findings highlight the potential for developing targeted interventions and personalized treatments, ultimately improving clinical outcomes for women with PCOS.

First-Trimester Preeclampsia-Induced Disturbance in Maternal Blood Serum Proteome: A Pilot Study.

Preeclampsia (PE) is a complex and multifaceted obstetric syndrome characterized by several distinct molecular subtypes. It complicates up to 5% of pregnancies and significantly contributes to maternal and newborn morbidity, thereby diminishing the long-term quality of life for affected women. Due to the widespread dissatisfaction with the effectiveness of existing approaches for assessing PE risk, there is a pressing need for ongoing research to identify newer, more accurate predictors. This study aimed to investigate early changes in the maternal serum proteome and associated signaling pathways. The levels of 125 maternal serum proteins at 11-13 weeks of gestation were quantified using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with the BAK-125 kit. Ten serum proteins emerged as potential early markers for PE: Apolipoprotein M (APOM), Complement C1q subcomponent subunit B (C1QB), Lysozyme (LYZ), Prothrombin (F2), Albumin (ALB), Zinc-alpha-2-glycoprotein (AZGP1), Tenascin-X (TNXB), Alpha-1-antitrypsin (SERPINA1), Attractin (ATRN), and Apolipoprotein A-IV (APOA4). Notably, nine of these proteins have previously been associated with PE in prior research, underscoring the consistency and reliability of our findings. These proteins play key roles in critical molecular processes, including complement and coagulation cascades, platelet activation, and insulin-like growth factor pathways. To improve the early prediction of PE, a highly effective Support Vector Machine (SVM) model was developed, analyzing 19 maternal serum proteins from the first trimester. This model achieved an area under the curve (AUC) of 0.91, with 87% sensitivity and 95% specificity, and a hazard ratio (HR) of 13.5 (4.6-40.8) with p < 0.001. These findings demonstrate that serum protein-based SVM models possess significantly higher predictive power compared to the routine first-trimester screening test, highlighting their superior utility in the early detection and risk stratification of PE.

Dietary Regulation of Lipid Metabolism in Gestational Diabetes Mellitus: Implications for Fetal Macrosomia.

The primary therapeutic approach for managing hyperglycemia today is diet therapy. Lipids are not only a source of nutrients but also play a role in initiating adipocyte differentiation in the fetus, which may explain the development of fetal macrosomia and future metabolic disorders in children born to mothers with gestational diabetes mellitus (GDM). Alterations in the maternal blood lipid profile, influenced by adherence to a healthy diet in mothers with GDM and the occurrence of fetal macrosomia, represent a complex and not fully understood process. The aim of this study was to examine the characteristics of the blood plasma lipid profile in pregnant women with GDM across all trimesters based on adherence to diet therapy. The clinical part of the study followed a case-control design, including 110 women: 80 in the control group, 20 in a GDM group adhering to the diet, and 10 in a GDM group not adhering to the diet. The laboratory part was conducted as a longitudinal dynamic study, with venous blood samples collected at three time points: 11-13, 24-26, and 30-32 weeks of pregnancy. A significant impact of diet therapy on the composition of blood lipids throughout pregnancy was demonstrated, starting as early as the first trimester. ROC analysis indicated high effectiveness of the models developed, with an AUC of 0.98 for the 30- to 32-week model and sensitivity and specificity values of 1 and 0.9, respectively. An association was found between dietary habits, maternal blood lipid composition at 32 weeks, and newborn weight. The changes in lipid profiles during macrosomia development and under diet therapy were found to be diametrically opposed, confirming at the molecular level that diet therapy can normalize not only carbohydrate metabolism but also lipid metabolism in both the mother and fetus. Based on the data obtained, it is suggested that after further validation, the developed models could be used to improve the prognosis of macrosomia by analyzing blood plasma lipid profiles at various stages of pregnancy.

Diagnostic Value of Menstrual Blood Lipidomics in Endometriosis: A Pilot Study.

Endometriosis is a prevalent chronic inflammatory disease characterized by a considerable delay between initial symptoms and diagnosis through surgery. The pressing need for a timely, non-invasive diagnostic solution underscores the focus of current research efforts. This study examines the diagnostic potential of the menstrual blood lipidome. The lipid profile of 39 samples (23 women with endometriosis and 16 patients in a control group) was acquired using reverse-phase high-performance liquid chromatography-mass spectrometry with LipidMatch processing and identification. Profiles were normalized based on total ion counts. Significant differences in lipids were determined using the Mann-Whitney test. Lipids for the diagnostic model, based on logistic regression, were selected using a combination of variance importance projection filters and Akaike information criteria. Levels of ceramides, sphingomyelins, cardiolipins, triacylglycerols, acyl- and alkenyl-phosphatidylethanolamines, and alkenyl-phosphatidylcholines increased, while acyl- and alkyl-phosphatidylcholines decreased in cases of endometriosis. Plasmenylphosphatidylethanolamine PE P-16:0/18:1 and cardiolipin CL 16:0_18:0_22:5_22:6 serve as marker lipids in the diagnostic model, exhibiting a sensitivity of 81% and specificity of 85%. The diagnostic approach based on dried spots of menstrual blood holds promise as an alternative to traditional non-invasive methods for endometriosis screening.

Dried Blood Spot Metabolome Features of Ischemic-Hypoxic Encephalopathy: A Neonatal Rat Model.

Hypoxic-ischemic encephalopathy (HIE) is a severe neurological disorder caused by perinatal asphyxia with significant consequences. Early recognition and intervention are crucial, with therapeutic hypothermia (TH) being the primary treatment, but its efficacy depends on early initiation of treatment. Accurately assessing the HIE severity in neonatal care poses challenges, but omics approaches have made significant contribution to understanding its complex pathophysiology. Our study further explores the impact of HIE on the blood metabolome over time and investigated changes associated with hypothermia's therapeutic effects. Using a rat model of hypoxic-ischemic brain injury, we comprehensively analyzed dried blood spot samples for fat-soluble compounds using HPLC-MS. Our research shows significant changes in the blood metabolome after HIE, with a particularly rapid recovery of lipid metabolism observed. Significant changes in lipid metabolites were observed after 3 h of HIE, including increases in ceramides, carnitines, certain fatty acids, phosphocholines, and phosphoethanolamines, while sphingomyelins and N-acylethanolamines (NAEs) decreased (p < 0.05). Furthermore, NAEs were found to be significant features in the OPLS-DA model for HIE diagnosis, with an area under the curve of 0.812. TH showed a notable association with decreased concentrations of ceramides. Enrichment analysis further corroborated these observations, showing modulation in several key metabolic pathways, including arachidonic acid oxylipin metabolism, eicosanoid metabolism via lipooxygenases, and leukotriene C4 synthesis deficiency. Our study reveals dynamic changes in the blood metabolome after HIE and the therapeutic effects of hypothermia, which improves our understanding of the pathophysiology of HIE and could lead to the development of new rapid diagnostic approaches for neonatal HIE.

Metabolite Biomarkers for Early Ischemic-Hypoxic Encephalopathy: An Experimental Study Using the NeoBase 2 MSMS Kit in a Rat Model.

Hypoxic-ischemic encephalopathy (HIE) is one of the most common causes of childhood disability. Hypothermic therapy is currently the only approved neuroprotective approach. However, early diagnosis of HIE can be challenging, especially in the first hours after birth when the decision to use hypothermic therapy is critical. Distinguishing HIE from other neonatal conditions, such as sepsis, becomes a significant problem in diagnosis. This study explored the utility of a metabolomic-based approach employing the NeoBase 2 MSMS kit to diagnose HIE using dry blood stains in a Rice-Vannucci model of HIE in rats. We evaluated the diagnostic fidelity of this approach in a range between 3 and 6 h after the onset of HIE, including in the context of systemic inflammation and concomitant hypothermic therapy. Discriminant analysis revealed several metabolite patterns associated with HIE. A logistic regression model using glycine levels achieved high diagnostic fidelity with areas under the receiver operating characteristic curve of 0.94 at 3 h and 0.96 at 6 h after the onset of HIE. In addition, orthogonal partial least squares discriminant analysis, which included five metabolites, achieved 100% sensitivity and 80% specificity within 3 h of HIE. These results highlight the significant potential of the NeoBase 2 MSMS kit for the early diagnosis of HIE and could improve patient management and outcomes in this serious illness.

Quantitative Proteomics of Maternal Blood Plasma in Isolated Intrauterine Growth Restriction.

Intrauterine growth restriction (IUGR) remains a significant concern in modern obstetrics, linked to high neonatal health problems and even death, as well as childhood disability, affecting adult quality of life. The role of maternal and fetus adaptation during adverse pregnancy is still not completely understood. This study aimed to investigate the disturbance in biological processes associated with isolated IUGR via blood plasma proteomics. The levels of 125 maternal plasma proteins were quantified by liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with corresponding stable isotope-labeled peptide standards (SIS). Thirteen potential markers of IUGR (Gelsolin, Alpha-2-macroglobulin, Apolipoprotein A-IV, Apolipoprotein B-100, Apolipoprotein(a), Adiponectin, Complement C5, Apolipoprotein D, Alpha-1B-glycoprotein, Serum albumin, Fibronectin, Glutathione peroxidase 3, Lipopolysaccharide-binding protein) were found to be inter-connected in a protein-protein network. These proteins are involved in plasma lipoprotein assembly, remodeling, and clearance; lipid metabolism, especially cholesterol and phospholipids; hemostasis, including platelet degranulation; and immune system regulation. Additionally, 18 proteins were specific to a particular type of IUGR (early or late). Distinct patterns in the coagulation and fibrinolysis systems were observed between isolated early- and late-onset IUGR. Our findings highlight the complex interplay of immune and coagulation factors in IUGR and the differences between early- and late-onset IUGR and other placenta-related conditions like PE. Understanding these mechanisms is crucial for developing targeted interventions and improving outcomes for pregnancies affected by IUGR.

COVID-19 Infection during Pregnancy: Disruptions in Lipid Metabolism and Implications for Newborn Health.

The COVID-19 pandemic has raised questions about indirect impact in pregnant women on the development of their future children. Investigating the characteristics of lipid metabolism in the "mother-placenta-fetus" system can give information about the pathophysiology of COVID-19 infection during pregnancy. A total of 234 women were included in study. Maternal plasma, cord blood, and amniotic fluid lipidome were analyzed using HPLC-MS/MS. Differences in lipid profile were searched by Mann-Whitney and Kruskall-Wallis test, and diagnostic model based on logistic regression were built by AIC. Elevated levels of lysophospholipids, triglycerides, sphingomyelins, and oxidized lipids were registered in patients' maternal and cord plasma after COVID-19 infection. An increase in maternal plasma sphingomyelins and oxidized lipids was observed in cases of infection during the second trimester. In amniotic fluid, compared to the control group, nine lipids were reduced and six were elevated. Levels of phosphoglycerides, lysophosphoglycerides, and phosphatidylinositols decreased during infection in the second and third trimesters of pregnancy. A health diagnostic model for newborns based on maternal plasma was developed for each group and exhibited good diagnostic value (AUC > 0.85). Maternal and cord plasma's lipidome changes during delivery, which are associated with COVID-19 infection during pregnancy, are synergistic. The most significant disturbances occur with infections in the second trimester of pregnancy.

Blood Plasma Small Non-Coding RNAs as Diagnostic Molecules for the Progesterone-Receptor-Negative Phenotype of Serous Ovarian Tumors.

The expression level of the progesterone receptor (PGR) plays a crucial role in determining the biological characteristics of serous ovarian carcinoma. Low PGR expression is associated with chemoresistance and a poorer outcome. In this study, our objective was to explore the relationship between tumor progesterone receptor levels and RNA profiles (miRNAs, piwiRNAs, and mRNAs) to understand their biological characteristics and behavior. To achieve this, we employed next-generation sequencing of small non-coding RNAs, quantitative RT-PCR, and immunohistochemistry to analyze both FFPE and frozen tumor samples, as well as blood plasma from patients with benign cystadenoma (BSC), serous borderline tumor (SBT), low-grade serous ovarian carcinoma (LGSOC), and high-grade serous ovarian carcinoma (HGSOC). Our findings revealed significant upregulation of MMP7 and MUC16, along with downregulation of PGR, in LGSOC and HGSOC compared to BSC. We observed significant correlations of PGR expression levels in tumor tissue with the contents of miR-199a-5p, miR-214-3p, miR-424-3p, miR-424-5p, and miR-125b-5p, which potentially target MUC16, MMP7, and MMP9, as well as with the tissue content of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p, which are associated with the epithelial-mesenchymal transition (EMT) of cells. The levels of EMT-associated miRNAs were significantly correlated with the content of hsa_piR_022437, hsa_piR_009295, hsa_piR_020813, hsa_piR_004307, and hsa_piR_019914 in tumor tissues. We developed two optimal logistic regression models using the quantitation of hsa_piR_020813, miR-16-5p, and hsa_piR_022437 or hsa_piR_004307, hsa_piR_019914, and miR-93-5p in the tumor tissue, which exhibited a significant ability to diagnose the PGR-negative tumor phenotype with 93% sensitivity. Of particular interest, the blood plasma levels of miR-16-5p and hsa_piR_022437 could be used to diagnose the PGR-negative tumor phenotype with 86% sensitivity even before surgery and chemotherapy. This knowledge can help in choosing the most effective treatment strategy for this aggressive type of ovarian cancer, such as neoadjuvant chemotherapy followed by cytoreduction in combination with hyperthermic intraperitoneal chemotherapy and targeted therapy, thus enhancing the treatment's effectiveness and the patient's longevity.

Direct mass spectrometry analysis of exhaled human breath in real-time.

The molecular composition of exhaled human breath can reflect various physiological and pathological conditions. Considerable progress has been achieved over the past decade in real-time analysis of exhaled human breath using direct mass spectrometry methods, including selected ion flow tube mass spectrometry, proton transfer reaction mass spectrometry, extractive electrospray ionization mass spectrometry, secondary electrospray ionization mass spectrometry, acetone-assisted negative photoionization mass spectrometry, atmospheric pressure photoionization mass spectrometry, and low-pressure photoionization mass spectrometry. Here, recent developments in direct mass spectrometry analysis of exhaled human breath are reviewed with regard to analytical performance (chemical sensitivity, selectivity, quantitative capabilities) and applications of the developed methods in disease diagnosis, targeted molecular detection, and real-time metabolic monitoring.

Integrating Proteomics and Lipidomics for Evaluating the Risk of Breast Cancer Progression: A Pilot Study.

Metastasis is a serious and often life-threatening condition, representing the leading cause of death among women with breast cancer (BC). Although the current clinical classification of BC is well-established, the addition of minimally invasive laboratory tests based on peripheral blood biomarkers that reflect pathological changes in the body is of utmost importance. In the current study, the serum proteome and lipidome profiles for 50 BC patients with (25) and without (25) metastasis were studied. Targeted proteomic analysis for concertation measurements of 125 proteins in the serum was performed via liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) using the BAK 125 kit (MRM Proteomics Inc., Victoria, BC, Canada). Untargeted label-free lipidomic analysis was performed using liquid chromatography coupled to tandem mass-spectrometry (LC-MS/MS), in both positive and negative ion modes. Finally, 87 serum proteins and 295 lipids were quantified and showed a moderate correlation with tumor grade, histological and biological subtypes, and the number of lymph node metastases. Two highly accurate classifiers that enabled distinguishing between metastatic and non-metastatic BC were developed based on proteomic (accuracy 90%) and lipidomic (accuracy 80%) features. The best classifier (91% sensitivity, 89% specificity, AUC = 0.92) for BC metastasis diagnostics was based on logistic regression and the serum levels of 11 proteins: alpha-2-macroglobulin, coagulation factor XII, adiponectin, leucine-rich alpha-2-glycoprotein, alpha-2-HS-glycoprotein, Ig mu chain C region, apolipoprotein C-IV, carbonic anhydrase 1, apolipoprotein A-II, apolipoprotein C-II and alpha-1-acid glycoprotein 1.

Transplacental Therapeutic Drug Monitoring in Pregnant Women with Fetal Tachyarrhythmia Using HPLC-MS/MS.

Fetal arrhythmia develops in 0.1-5% of pregnancies and may cause fetal heart failure and fetal hydrops, thus increasing fetal, neonatal, and infant mortality. The timely initiation of transplacental antiarrhythmic therapy (ART) promotes the conversion of fetal tachycardia to sinus rhythm and the regression of the concomitant non-immune fetal hydrops. The optimal treatment regimen search for the fetus with tachyarrhythmia is still of high value. Polymorphisms of these genes determines the individual features of the drug pharmacokinetics. The aim of this study was to study the pharmacokinetics of transplacental anti-arrhythmic drugs in the fetal therapy of arrhythmias using HPLC-MS/MS, as well as to assess the effect of the multidrug-resistance gene ABCB1 3435C > T polymorphism on the efficacy and maternal/fetal complications of digoxin treatment. The predisposition to a decrease in the bioavailability of the digoxin in patients with a homozygous variant of the CC polymorphism showed a probable association with the development of ART side effects. A pronounced decrease in heart rate in women with the 3435TT allele of the ABCB1 gene was found. The homozygous TT variant in the fetus showed a probable association with an earlier response to ART and rhythm disruptions on the digoxin dosage reduction. high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS) methods for digoxin and sotalol therapeutic drug monitoring in blood plasma, amniotic fluid, and urine were developed. The digoxin and sotalol concentrations were determined in the plasma blood, urine, and amniotic fluid of 30 pregnant women at four time points (from the beginning of the transplacental antiarrhythmic therapy to delivery) and the plasma cord blood of 30 newborns. A high degree of correlation between the level of digoxin and sotalol in maternal and cord blood was found. The ratio of digoxin and sotalol in cord blood to maternal blood was 0.35 (0.27 and 0.46) and 1.0 (0.97 and 1.07), accordingly. The digoxin concentration in the blood of the fetus at the moment of the first rhythm recovery episode, 0.58 (0.46, 0.8) ng/mL, was below the therapeutic interval. This confirms the almost complete transplacental transfer of sotalol and the significant limitation in the case of digoxin. Previously, ABCB1/P-glycoprotein had been shown to limit fetal exposure to drugs. Further studies (including multicenter ones) to clarify the genetic features of the transplacental pharmacokinetics of antiarrhythmic drugs are needed.

Specific changes in amino acid profiles in monocytes of patients with breast, lung, colorectal and ovarian cancers.

Introduction: Immunometabolism is essential factor of tumor progression, and tumor-associated macrophages are characterized by substantial changes in their metabolic status. In this study for the first time, we applied targeted amino acid LC-MS/MS analysis to compare amino acid metabolism of circulating monocytes isolated from patients with breast, ovarian, lung, and colorectal cancer. Methods: Monocyte metabolomics was analyzed by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/ MS) analysis of amino acid extracts. The targeted analysis of 26 amino acids was conducted by LCMS/MS on an Agilent 6460 triple quadrupole mass spectrometer equipped with an electrospray ionization source and an Agilent 1260 II liquid chromatograph. Results: Comparison of monocytes of cancer patients with monocytes of healthy control individuals demonstrated that in breast cancer most pronounced changes were identified for tryptophan (AUC = 0.76); for ovarian cancer, aminobutyric acid was significantly elevated (AUC= 1.00); for lung cancer significant changes we indented for citrulline (AUC = 0.70). In order to identify key amino acids that are characteristic for monocytes in specific cancer types, we compared each individual cancer with other 3 types of cancer. We found, that aspartic acid and citrulline are specific for monocytes of patients with colorectal cancer (p<0.001, FC = 1.40 and p=0.003, FC = 1.42 respectively). Citrulline, sarcosine and glutamic acid are ovarian cancer-specific amino acids (p = 0.003, FC = 0.78, p = 0.003, FC = 0.62, p = 0.02, FC = 0.78 respectively). Glutamine, methionine and phenylalanine (p = 0.048, FC = 1.39. p = 0.03, FC = 1.27 and p = 0.02, FC = 1.41) are lung cancer-specific amino acids. Ornithine in monocytes demonstrated strong positive correlation (r = 0.63) with lymph node metastasis incidence in breast cancer patients. Methyl histidine and cysteine in monocytes had strong negative correlation with lymph node metastasis in ovarian cancer patients (r = -0.95 and r = -0.95 respectively). Arginine, citrulline and ornithine have strong negative correlation with tumor size (r = -0.78, citrulline) and lymph node metastasis (r = -0.63 for arginine and r = -0.66 for ornithine). Discussion: These alterations in monocyte amino acid metabolism can reflect the reaction of systemic innate immunity on the growing tumor. Our data indicate that this metabolic programming is cancer specific and can be inhibiting cancer progression. Cancer-specific differences in citrulline, as molecular link between metabolic pathways and epigenetic programing, provide new option for the development and validation of anti-cancer therapies using inhibitors of enzymes catalyzing citrullination.

Search for New Participants in the Pathogenesis of High-Grade Serous Ovarian Cancer with the Potential to Be Used as Diagnostic Molecules.

Recent studies have attempted to develop molecular signatures of epithelial ovarian cancer (EOC) based on the quantitation of protein-coding and non-coding RNAs to predict disease prognosis. Due to the heterogeneity of EOC, none of the developed prognostic signatures were directly applied in clinical practice. Our work focuses on high-grade serous ovarian carcinoma (HGSOC) due to the highest mortality rate relative to other types of EOC. Using deep sequencing of small non-coding RNAs in combination with quantitative real-time PCR, we confirm the dualistic classification of epithelial ovarian cancers based on the miRNA signature of HGSOC (type 2), which differs from benign cystadenoma and borderline cystadenoma-precursors of low-grade serous ovarian carcinoma (type 1)-and identified two subtypes of HGSOC, which significantly differ in the level of expression of the progesterone receptor in the tumor tissue, the secretion of miR-16-5p, miR-17-5p, miR-93-5p, miR-20a-5p, the level of serum CA125, tumor size, surgical outcome (optimal or suboptimal cytoreduction), and response to chemotherapy. It was found that the combined determination of the level of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p circulating in blood plasma of patients with primary HGSOC tumors makes it possible to predict optimal cytoreduction with 80.1% sensitivity and 70% specificity (p = 0.022, TPR = 0.8, FPR = 0.3), as well as complete response to adjuvant chemotherapy with 77.8% sensitivity and 90.9% specificity (p = 0.001, TPR = 0.78, FPR = 0.09). After the additional verification of the obtained data in a larger HGSOC patient cohort, the combined quantification of these four miRNAs is proposed to be used as a criterion for selecting patients either for primary cytoreduction or neoadjuvant chemotherapy followed by interval cytoreduction.

Non-Invasive Differential Diagnosis of Cervical Neoplastic Lesions by the Lipid Profile Analysis of Cervical Scrapings.

Cervical cancer is one of the most common cancers in women with pronounced stages of precancerous lesions. Accurate differential diagnosis of such lesions is one of the primary challenges of medical specialists, which is vital to improving patient survival. The aim of this study was to develop and test an algorithm for the differential diagnosis of cervical lesions based on lipid levels in scrapings from the cervical epithelium and cervicovaginal canal. The lipid composition of the samples was analyzed by high-performance chromato-mass spectrometry. Lipid markers were selected using the Mann-Whitney test with a cutoff value of 0.05 and by projections to latent structures discriminant analysis, where a projection threshold of one was chosen. The final selection of variables for binomial logistic regressions was carried out using the Akaike information criterion. As a result, a final neoplasia classification method, based on 20 logistic regression sub-models, has an accuracy of 79% for discrimination NILM/cervicitis/LSIL/HSIL/cancer. The model has a sensitivity of 83% and a specificity of 88% for discrimination of several lesions (HSIL and cancer). This allows us to discuss the prospective viability of further validation of the developed non-invasive method of differential diagnosis.

Shotgun Lipidomics for Differential Diagnosis of HPV-Associated Cervix Transformation.

A dramatic increase in cervical diseases associated with human papillomaviruses (HPV) in women of reproductive age has been observed over the past decades. An accurate differential diagnosis of the severity of cervical intraepithelial neoplasia and the choice of the optimal treatment requires the search for effective biomarkers with high diagnostic and prognostic value. The objective of this study was to introduce a method for rapid shotgun lipidomics to differentiate stages of HPV-associated cervix epithelium transformation. Tissue samples from 110 HPV-positive women with cervicitis (n = 30), low-grade squamous intraepithelial lesions (LSIL) (n = 30), high-grade squamous intraepithelial lesions (HSIL) (n = 30), and cervical cancers (n = 20) were obtained. The cervical epithelial tissue lipidome at different stages of cervix neoplastic transformation was studied by a shotgun label-free approach. It is based on electrospray ionization mass spectrometry (ESI-MS) data of a tissue extract. Lipidomic data were processed by the orthogonal projections to latent structures discriminant analysis (OPLS-DA) to build statistical models, differentiating stages of cervix transformation. Significant differences in the lipid profile between the lesion and surrounding tissues were revealed in chronic cervicitis, LSIL, HSIL, and cervical cancer. The lipids specific for HPV-induced cervical transformation mainly belong to glycerophospholipids: phosphatidylcholines, and phosphatidylethanolamines. The developed diagnostic OPLS-DA models were based on 23 marker lipids. More than 90% of these marker lipids positively correlated with the degree of cervix transformation. The algorithm was developed for the management of patients with HPV-associated diseases of the cervix, based on the panel of 23 lipids as a result. ESI-MS analysis of a lipid extract by direct injection through a loop, takes about 25 min (including preparation of the lipid extract), which is significantly less than the time required for the HPV test (several hours for hybrid capture and about an hour for PCR). This makes lipid mass spectrometric analysis a promising method for express diagnostics of HPV-associated neoplastic diseases of the cervix.

Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis.

Panax notoginseng is a highly valuable and widely used herb in traditional Chinese medicine. The quality and efficacy of Panax notoginseng grown under different conditions can greatly vary due to the differences in chemical composition. The analysis of chemical composition in Panax notoginseng typically involves various experimental steps including extraction, chromatographic separation and characterization, which can be time- and labor-consuming. Therefore, the efficient quality assessment and control of Panax notoginseng requires the development of more rapid methods for the chemical characterization and classification of Panax notoginseng. In this study, a method based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) was developed to characterize chemical components of Panax notoginseng samples under different growth conditions (e.g., place of origin, soil quality, growth season) at the speed of 0.5 min per sample, without sample pretreatment and chromatographic separation. A total of 35 chemical components, including sugars, saponins, organic acids, etc., were identified in Panax notoginseng samples. Clear separation was observed in the multivariate analysis of the iEESI-MS data from Panax notoginseng samples grown under different conditions. The difference in the content of sucrose, fructose, Rg1, Rf, Rb1, Noto-R1, malonyl-Rb1, malonyl-Rg1, malonyl-Rf, Rd, Re, linoleic acid, palmitic acid and malic acid can be used as key characteristic indicators to discriminate origin, commercial specifications, and cultivation conditions of Panax notoginseng samples. The results of our study indicate the high power of iEESI-MS for the rapid molecular characterization and classification of Panax notoginseng under different growth conditions, which can be used for the quality assessment of traditional herbal medicines as well as in pharmaceutical and clinical analysis.

Past COVID-19: The Impact on IVF Outcomes Based on Follicular Fluid Lipid Profile.

Follicular fluid is an important component of follicle growth and development. Negative effects of COVID-19 on follicular function are still open. The aim of this work was to study the features of the lipid profile of follicular fluid and evaluate the results of the in vitro fertilization (IVF) program in women after COVID-19 to identify biomarkers with prognostic potential. The study involved samples of follicular fluid collected from 237 women. Changes in the lipid composition of the follicular fluid of patients who underwent COVID-19 in mild and severe forms before entering the IVF program and women who did not have COVID-19 were studied by mass spectrometry. Several lipids were identified that significantly changed their level. On the basis of these findings, models were developed for predicting the threat of miscarriage in patients who had a severe course of COVID-19 and models for predicting the success of the IVF procedure, depending on the severity of COVID-19. Of practical interest is the possibility of using the developed predictive models in working with patients who have undergone COVID-19 before entering the IVF program. The results of the study suggest that the onset of pregnancy and its outcome after severe COVID-19 may be associated with changes in lipid metabolism in the follicular fluid.

The Effect of Bisphenol A on the IVF Outcomes Depending on the Polymorphism of the Detoxification System Genes.

The aim of the study was to analyze the relationship between the level of bisphenol A (BPA) in the blood and follicular fluid, the polymorphism of the detoxification system genes, and the outcomes of IVF cycles. The data of 300 infertile patients with fresh IVF-ET cycles were analyzed. The level of BPA in the blood and follicular fluid was determined by HPLC-MRM-MS/MS. Determination of genotypes of the detoxification system genes was carried out by the real-time PCR. The threshold level for determining BPA was 0.1 ng/mL. BPA was detected in 92.3% (277/300) blood and in 16.8% (49/292) follicular fluid (FF) samples. There was no correlation between BPA level in the blood and FF. In patients with the absence of the A allele of the SULT1A1 gene, BPA was detected in FF significantly more often (22.6% vs. 13.5%, p = 0.0341). There was an association (not statistically significant) between the level of BPA in the blood and the presence of the G allele of the GSTP1 gene (rs1695) and the C allele in the GSTP1 gene (rs1138272). Our data suggests the role of detoxification system genes in the metabolism of BPA in the human body. The influence of BPA and detoxification system genes on the IVF outcomes requires further research.

Alterations in lipid profile upon uterine fibroids and its recurrence.

Uterine fibroids (UF) is the most common (about 70% cases) type of gynecological disease, with the recurrence rate varying from 11 to 40%. Because UF has no distinct symptomatology and is often asymptomatic, the specific and sensitive diagnosis of UF as well as the assessment for the probability of UF recurrence pose considerable challenge. The aim of this study was to characterize alterations in the lipid profile of tissues associated with the first-time diagnosed UF and recurrent uterine fibroids (RUF) and to explore the potential of mass spectrometry (MS) lipidomics analysis of blood plasma samples for the sensitive and specific determination of UF and RUF with low invasiveness of analysis. MS analysis of lipid levels in the myometrium tissues, fibroids tissues and blood plasma samples was carried out on 66 patients, including 35 patients with first-time diagnosed UF and 31 patients with RUF. The control group consisted of 15 patients who underwent surgical treatment for the intrauterine septum. Fibroids and myometrium tissue samples were analyzed using direct MS approach. Blood plasma samples were analyzed using high performance liquid chromatography hyphened with mass spectrometry (HPLC/MS). MS data were processed by discriminant analysis with projection into latent structures (OPLS-DA). Significant differences were found between the first-time UF, RUF and control group in the levels of lipids involved in the metabolism of glycerophospholipids, sphingolipids, lipids with an ether bond, triglycerides and fatty acids. Significant differences between the control group and the groups with UF and RUF were found in the blood plasma levels of cholesterol esters, triacylglycerols, (lyso) phosphatidylcholines and sphingomyelins. Significant differences between the UF and RUF groups were found in the blood plasma levels of cholesterol esters, phosphotidylcholines, sphingomyelins and triacylglycerols. Diagnostic models based on the selected differential lipids using logistic regression showed sensitivity and specificity of 88% and 86% for the diagnosis of first-time UF and 95% and 79% for RUF, accordingly. This study confirms the involvement of lipids in the pathogenesis of uterine fibroids. A diagnostically significant panel of differential lipid species has been identified for the diagnosis of UF and RUF by low-invasive blood plasma analysis. The developed diagnostic models demonstrated high potential for clinical use and further research in this direction.