PubMed

Metab Brain Dis. 2024 Jul 13. doi: 10.1007/s11011-024-01387-8. Online ahead of print.ABSTRACTIschemic stroke is the most important cause of disability and death worldwide, but current treatments remain limited. Traditional Chinese medicine (TCM) including the herb pair of Zhiqiao-Danggui (ZD) offers a multifaceted treatment approach through promoting blood circulation, yet its specific anti-ischemic mechanism remains unclear. This study used the photochemically induced thrombosis (PIT) mouse model and the oxygen glucose deprivation/reoxygenation (OGD/R) cell model to explore the therapeutic effect of ZD on ischemic stroke. Mice were treated with high and low doses of ZD extract or positive control. Behavior was assessed using the grid test. The brain tissue was then subjected to infarct volume assessment, histopathology, oxidative stress marker detection, LC/MS metabolomic analysis and qRT-PCR validation. The therapeutic effect of ZD-medicated serum on OGD/R model was tested on cells. Experimental results show that ZD can improve motor function, reduce infarct size, neuronal damage and apoptosis as well as alleviate oxidative stress in mice. ZD-medicated serum promotes endothelial cell proliferation, improves cell survival against OGD/R-induced injury, reduces oxidative damage and protects mitochondrial function. Metabolomics reveals ZD regulation of metabolites in energy metabolism, amino acid metabolism, TCA cycle, and angiogenesis signaling pathways. qRT-PCR results also showed that ZD could attenuate abnormal conduction of angiogenic signals and enhance vessel stability. This study confirmed the neuroprotective and vasoprotective effects of ZD, highlighted its potential in treating ischemic stroke, and provided a scientific basis for the traditional use of ZD.PMID:39002017 | DOI:10.1007/s11011-024-01387-8

Biodegradation. 2024 Jul 13. doi: 10.1007/s10532-024-10090-5. Online ahead of print.ABSTRACTAcetaminophen [N-(4-hydroxyphenyl) acetamide, APAP] is an extensively and frequently consumed over-the-counter analgesic and antiphlogistic medication. It is being regarded as an emerging pollutant due to its continuous increment in the environment instigating inimical impacts on humans and the ecosystem. Considering its wide prevalence in the environment, there is an immense need of appropriate methods for the removal of APAP. The present study indulged screening and isolation of APAP degrading bacterial strains from pharmaceuticals-contaminated sites, followed by their molecular characterization via 16S rRNA sequencing. The phylogenetic analyses assigned the isolates to the genera Pseudomonas, Bacillus, Paracoccus, Agrobacterium, Brucella, Escherichia, and Enterobacter based on genetic relatedness. The efficacy of these strains in batch cultures tested through High-performance Liquid Chromatography (HPLC) revealed Paracoccus sp. and Enterobacter sp. as the most promising bacterial isolates degrading up to 88.96 and 85.92%, respectively of 300 mg L-1 of APAP within 8 days of incubation. Michaelis-Menten kinetics model parameters also elucidated the high degradation potential of these isolates. The major metabolites identified through FTIR and GC-MS analyses were 4-aminophenol, hydroquinone, and 3-hydroxy-2,4-hexadienedioic. Therefore, the outcomes of this comprehensive investigation will be of paramount significance in formulating strategies for the bioremediation of acetaminophen-contaminated sites through a natural augmentation process via native bacterial strains.PMID:39001976 | DOI:10.1007/s10532-024-10090-5

Antioxid Redox Signal. 2024 Jul 13. doi: 10.1089/ars.2024.0594. Online ahead of print.ABSTRACTSickle cell disease (SCD) affects two-thirds of African and Indian children. Understanding the molecular mechanisms contributing to oxidative stress may be useful for therapeutic development in SCD. We evaluated plasma elemental levels of Indian SCD patients, trait and healthy controls (n=10/per group) via ICP-MS. Additionally, erythrocyte metabolomics of Indian SCD and healthy (n=5/per group) was carried out using LC-MS mass-spectrometry. Followed by assessment of antioxidant defence enzymes namely glutathione reductase (GR), superoxide dismutase (SOD), and catalase (CAT) in erythrocytes and plasma of Indian SCD patients (n=31) compared to trait (n=8) and healthy (n=9). In SCD plasma an elevated plasma 24Mg, 44Ca, 66Zn, 208Pb, 39K and reduced 57Fe, 77Se, 85Rb levels indicating higher hemolysis and anemia. Erythrocyte metabolome of SCD patients clustered separately from heathy revealing 135 significantly deregulated metabolic features including trimethyllysine, pyroglutamate, glutathione, aminolevulinate, and D-glutamine indicating oxidative stress and membrane fragility. Repressed GR, SOD, and CAT activities were observed in SCD patients of which GR and CAT activities did not change under hypoxia. These findings lead to the hypothesis that SCD-associated metabolic deregulations and a shift to ATP-consuming aberrant γ-glutamyl cycle leads to anemia, dehydration, oxidative stress and hemolysis driving the biomechanical pathophysiology of erythrocyte of SCD patients.PMID:39001817 | DOI:10.1089/ars.2024.0594

Mayo Clin Proc. 2024 Jul 9:S0025-6196(24)00105-8. doi: 10.1016/j.mayocp.2024.02.019. Online ahead of print.ABSTRACTOBJECTIVE: To investigate the causal effect of protein intake on hypertension and the related mediating pathways.PATIENTS AND METHODS: Using genome-wide association study summary statistics of European ancestry, we applied univariable and multivariable Mendelian randomization to estimate the bidirectional associations of relative protein intake and related metabolomic signatures with hypertension (FinnGen: Ncase=42,857/Ncontrol=162,837; UK Biobank: Ncase=77,723/Ncontrol=330,366) and blood pressure (International Consortium of Blood Pressure: N=757,601) and two-step Mendelian randomization to assess the mediating roles of 40 cardiometabolic factors therein. Mendelian randomization estimates of hypertension from FinnGen and UK Biobank were meta-analyzed without heterogeneity. We performed the study from May 15, 2023, to September 15, 2023.RESULTS: Each 1-SD higher relative protein intake was causally associated with 69% (odds ratio, 0.31; 95% CI, 0.11 to 0.89) lower hypertension risk independent of the effects of other macronutrients, and was the only macronutrient associated with 2.21 (95% CI, 0.52 to 3.91) mm Hg lower pulse pressure, in a unidirectional manner. Higher plant protein-related metabolomic signature (glycine) was associated with lower hypertension risk and pulse pressure, whereas higher animal protein-related metabolomic signatures (leucine, isoleucine, valine, and isovalerylcarnitine [only systolic blood pressure]) were associated with higher hypertension risk, pulse pressure, and systolic blood pressure. The effect of relative protein intake on hypertension was causally mediated by frailty index (mediation proportion, 40.28%), monounsaturated fatty acids (13.81%), saturated fatty acids (11.39%), grip strength (5.34%), standing height (3.99%), and sitting height (3.61%).CONCLUSION: Higher relative protein intake causally reduces the risk of hypertension, partly mediated by physical fitness and circulating fatty acids.PMID:39001774 | DOI:10.1016/j.mayocp.2024.02.019

J Cachexia Sarcopenia Muscle. 2024 Jul 13. doi: 10.1002/jcsm.13550. Online ahead of print.ABSTRACTBACKGROUND: Overeating and inactivity are associated with type 2 diabetes. This study aimed to investigate its pathological basis using integrated omics and db/db/mice, a model representing this condition.METHODS: The study involved housing 8-week-old db/m and db/db mice for 8 weeks. Various analyses were conducted, including gene expression in skeletal muscle and small intestine using next-generation sequencing; cytokine arrays of serum; assessment of metabolites in skeletal muscle, stool, and serum; and analysis of the gut microbiota. Histone modifications in small intestinal epithelial cells were profiled using CUT&Tag.RESULTS: Compared with db/m mice, db/db mice had 22.4% lower grip strength and approximately five times the visceral fat weight (P < 0.0001). Serum cytokine arrays showed a 2.8-fold relative concentration of VEGF-A in db/db mice (P < 0.0001) and lower concentrations of several other cytokines. mRNA sequencing revealed downregulation of Myh expression in skeletal muscle, upregulation of lipid and glucose transporters, and downregulation of amino acid transporters in the small intestine of db/db/mice. The concentrations of saturated fatty acids in skeletal muscle were significantly higher, and the levels of essential amino acids were lower in db/db mice. Analysis of the gut microbiota, 16S rRNA sequencing, revealed lower levels of the phylum Bacteroidetes (59.7% vs. 44.9%) and higher levels of the phylum Firmicutes (20.9% vs. 31.4%) in db/db mice (P = 0.003). The integrated signal of histone modifications of lipid and glucose transporters was higher, while the integrated signal of histone modifications of amino acid transporters was lower in the db/db mice.CONCLUSIONS: The multi-omics approach provided insights into the epigenomic alterations in the small intestine, suggesting their involvement in the pathogenesis of inactivity-induced muscle atrophy in obese mice.PMID:39001701 | DOI:10.1002/jcsm.13550

Cancers (Basel). 2024 Jul 6;16(13):2473. doi: 10.3390/cancers16132473.ABSTRACTBACKGROUND: Neoadjuvant chemotherapy (NACT) has arisen as a treatment option for breast cancer (BC). However, the response to NACT is still unpredictable and dependent on cancer subtype. Metabolomics is a tool for predicting biomarkers and chemotherapy response. We used plasma to verify metabolomic alterations in BC before NACT, relating to clinical data.METHODS: Liquid chromatography coupled to mass spectrometry (LC-MS) was performed on pre-NACT plasma from patients with BC (n = 75). After data filtering, an SVM model for classification was built and validated with 75%/25% of the data, respectively.RESULTS: The model composed of 19 identified metabolites effectively predicted NACT response for training/validation sets with high sensitivity (95.4%/93.3%), specificity (91.6%/100.0%), and accuracy (94.6%/94.7%). In both sets, the panel correctly classified 95% of resistant and 94% of sensitive females. Most compounds identified by the model were lipids and amino acids and revealed pathway alterations related to chemoresistance.CONCLUSION: We developed a model for predicting patient response to NACT. These metabolite panels allow clinical gain by building precision medicine strategies based on tumor stratification.PMID:39001535 | DOI:10.3390/cancers16132473

Diagnostics (Basel). 2024 Jun 27;14(13):1364. doi: 10.3390/diagnostics14131364.ABSTRACTBACKGROUND: Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes mellitus, and early detection is crucial for effective management. Metabolomics profiling has emerged as a promising approach for identifying potential biomarkers associated with DR progression. This study aimed to develop a hybrid explainable artificial intelligence (XAI) model for targeted metabolomics analysis of patients with DR, utilizing a focused approach to identify specific metabolites exhibiting varying concentrations among individuals without DR (NDR), those with non-proliferative DR (NPDR), and individuals with proliferative DR (PDR) who have type 2 diabetes mellitus (T2DM).METHODS: A total of 317 T2DM patients, including 143 NDR, 123 NPDR, and 51 PDR cases, were included in the study. Serum samples underwent targeted metabolomics analysis using liquid chromatography and mass spectrometry. Several machine learning models, including Support Vector Machines (SVC), Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), and Multilayer Perceptrons (MLP), were implemented as solo models and in a two-stage ensemble hybrid approach. The models were trained and validated using 10-fold cross-validation. SHapley Additive exPlanations (SHAP) were employed to interpret the contributions of each feature to the model predictions. Statistical analyses were conducted using the Shapiro-Wilk test for normality, the Kruskal-Wallis H test for group differences, and the Mann-Whitney U test with Bonferroni correction for post-hoc comparisons.RESULTS: The hybrid SVC + MLP model achieved the highest performance, with an accuracy of 89.58%, a precision of 87.18%, an F1-score of 88.20%, and an F-beta score of 87.55%. SHAP analysis revealed that glucose, glycine, and age were consistently important features across all DR classes, while creatinine and various phosphatidylcholines exhibited higher importance in the PDR class, suggesting their potential as biomarkers for severe DR.CONCLUSION: The hybrid XAI models, particularly the SVC + MLP ensemble, demonstrated superior performance in predicting DR progression compared to solo models. The application of SHAP facilitates the interpretation of feature importance, providing valuable insights into the metabolic and physiological markers associated with different stages of DR. These findings highlight the potential of hybrid XAI models combined with explainable techniques for early detection, targeted interventions, and personalized treatment strategies in DR management.PMID:39001254 | DOI:10.3390/diagnostics14131364

Diagnostics (Basel). 2024 Jun 26;14(13):1353. doi: 10.3390/diagnostics14131353.ABSTRACTAcute Myocardial Infarction (AMI), a common disease that can have serious consequences, occurs when myocardial blood flow stops due to occlusion of the coronary artery. Early and accurate prediction of AMI is critical for rapid prognosis and improved patient outcomes. Metabolomics, the study of small molecules within biological systems, is an effective tool used to discover biomarkers associated with many diseases. This study intended to construct a predictive model for AMI utilizing metabolomics data and an explainable machine learning approach called Explainable Boosting Machines (EBM). The EBM model was trained on a dataset of 102 prognostic metabolites gathered from 99 individuals, including 34 healthy controls and 65 AMI patients. After a comprehensive data preprocessing, 21 metabolites were determined as the candidate predictors to predict AMI. The EBM model displayed satisfactory performance in predicting AMI, with various classification performance metrics. The model's predictions were based on the combined effects of individual metabolites and their interactions. In this context, the results obtained in two different EBM modeling, including both only individual metabolite features and their interaction effects, were discussed. The most important predictors included creatinine, nicotinamide, and isocitrate. These metabolites are involved in different biological activities, such as energy metabolism, DNA repair, and cellular signaling. The results demonstrate the potential of the combination of metabolomics and the EBM model in constructing reliable and interpretable prediction outputs for AMI. The discussed metabolite biomarkers may assist in early diagnosis, risk assessment, and personalized treatment methods for AMI patients. This study successfully developed a pipeline incorporating extensive data preprocessing and the EBM model to identify potential metabolite biomarkers for predicting AMI. The EBM model, with its ability to incorporate interaction terms, demonstrated satisfactory classification performance and revealed significant metabolite interactions that could be valuable in assessing AMI risk. However, the results obtained from this study should be validated with studies to be carried out in larger and well-defined samples.PMID:39001243 | DOI:10.3390/diagnostics14131353

Int J Mol Sci. 2024 Jul 8;25(13):7492. doi: 10.3390/ijms25137492.ABSTRACTSeminal plasma contains a heterogeneous population of extracellular vesicles (sEVs) that remains poorly characterized. This study aimed to characterize the lipidomic profile of two subsets of differently sized sEVs, small (S-) and large (L-), isolated from porcine seminal plasma by size-exclusion chromatography and characterized by an orthogonal approach. High-performance liquid chromatography-high-resolution mass spectrometry was used for lipidomic analysis. A total of 157 lipid species from 14 lipid classes of 4 major categories (sphingolipids, glycerophospholipids, glycerolipids, and sterols) were identified. Qualitative differences were limited to two cholesteryl ester species present only in S-sEVs. L-sEVs had higher levels of all quantified lipid classes due to their larger membrane surface area. The distribution pattern was different, especially for sphingomyelins (more in S-sEVs) and ceramides (more in L-sEVs). In conclusion, this study reveals differences in the lipidomic profile of two subsets of porcine sEVs, suggesting that they differ in biogenesis and functionality.PMID:39000599 | DOI:10.3390/ijms25137492

Int J Mol Sci. 2024 Jul 8;25(13):7481. doi: 10.3390/ijms25137481.ABSTRACTSand pear is the main cultivated pear species in China, and brown peel is a unique feature of sand pear. The formation of brown peel is related to the activity of the cork layer, of which lignin is an important component. The formation of brown peel is intimately associated with the biosynthesis and accumulation of lignin; however, the regulatory mechanism of lignin biosynthesis in pear peel remains unclear. In this study, we used a newly bred sand pear cultivar 'Xinyu' as the material to investigate the biosynthesis and accumulation of lignin at nine developmental stages using metabolomic and transcriptomic methods. Our results showed that the 30 days after flowering (DAF) to 50DAF were the key periods of lignin accumulation according to data analysis from the assays of lignin measurement, scanning electron microscope (SEM) observation, metabolomics, and transcriptomics. Through weighted gene co-expression network analysis (WGCNA), positively correlated modules with lignin were identified. A total of nine difference lignin components were identified and 148 differentially expressed genes (DEGs), including 10 structural genes (PAL1, C4H, two 4CL genes, HCT, CSE, two COMT genes, and two CCR genes) and MYB, NAC, ERF, and TCP transcription factor genes were involved in lignin metabolism. An analysis of RT-qPCR confirmed that these DEGs were involved in the biosynthesis and regulation of lignin. These findings further help us understand the mechanisms of lignin biosynthesis and provide a theoretical basis for peel color control and quality improvement in pear breeding and cultivation.PMID:39000588 | DOI:10.3390/ijms25137481

Int J Mol Sci. 2024 Jul 8;25(13):7469. doi: 10.3390/ijms25137469.ABSTRACTAt many crime scenes, investigators are able to trace and find traces of blood. For many years, it was believed that such traces could only be subjected to genetic investigations, such as those aimed at comparing DNA profiling with a suspect to verify his identity, and that it was therefore not possible to backdate the traces. In recent years, various works have used experimental models to investigate the possibility of identifying markers and methodologies for estimating the time since deposition (TSD) of bloodstains. Despite the results, these methods are still not part of standard procedures, and there is no univocal analysis methodology. In this work we carried out a systematic literature review of all the papers published in the last ten years on this topic, comparing the experimental models created. This review demonstrates the potential that different molecular approaches, such as transcriptomics, metabolomics, proteomics, and spectrometry, can have in the analysis of TSD, with notable sensitivity and specificity. This paper also analyzes the intrinsic and extrinsic limits of these models and emphasizes the need to continue research work on this topic, considering the importance that this parameter can assume in forensic investigations against a suspect.PMID:39000576 | DOI:10.3390/ijms25137469

Int J Mol Sci. 2024 Jul 7;25(13):7449. doi: 10.3390/ijms25137449.ABSTRACTObesity is an important risk factor for the development of pregnancy complications. We investigated the effects of pregestational overweight and obesity on maternal lipidome during pregnancy and on newborns' characteristics. The study encompassed 131 pregnant women, 99 with pre-pregnancy body mass index (BMI) < 25 kg/m2 and 32 with BMI ≥ 25 kg/m2. Maternal lipid status parameters, plasma markers of cholesterol synthesis and absorption and sphingolipids were determined in each trimester. Data on neonatal height, weight and APGAR scores were assessed. The results showed a higher prevalence (p < 0.05) of pregnancy and childbirth complications among the participants with elevated pregestational BMI. Levels of total cholesterol, HDL-cholesterol (p < 0.05) and LDL-cholesterol (p < 0.01) were significantly lower, and concentrations of triglycerides were higher (p < 0.05) in women with increased pre-gestational BMI. Lower concentrations of the cholesterol synthesis marker, desmosterol, in the 2nd trimester (p < 0.01) and the cholesterol absorption marker, campesterol, in each trimester (p < 0.01, p < 0.05, p < 0.01, respectively) were also found in this group. Markers of maternal cholesterol synthesis were in positive correlation with neonatal APGAR scores in the group of mothers with healthy pre-pregnancy weight but in negative correlation in the overweight/obese group. Our results indicate that gestational adaptations of maternal lipidome depend on her pregestational nutritional status and that such changes may affect neonatal outcomes.PMID:39000556 | DOI:10.3390/ijms25137449

Int J Mol Sci. 2024 Jul 6;25(13):7436. doi: 10.3390/ijms25137436.ABSTRACTStroke remains the second leading cause of mortality worldwide, and the third leading cause of death and morbidity combined, affecting more than 12 million people every year. Stroke pathophysiology results from complex interactions of several risk factors related to age, family history, gender, lifestyle, and the presence of cardiovascular and metabolic diseases. Despite all the evidence, it is not possible to fully prevent stroke onset. In recent years, there has been an exploration of innovative methodologies for metabolite analysis aimed at identifying novel stroke biomarkers. Utilizing Nuclear Magnetic Resonance (NMR) spectroscopy, we investigated small molecule variations in urine across different stages of stroke risk. The Framingham Stroke Risk Score was used in people over 63 years of age living in long-term care facilities (LTCFs) to calculate the probability of suffering a stroke: low stroke risk (LSR, control), moderate stroke risk (MSR), and high stroke risk (HSR). Univariate statistical analysis showed that urinary 4-hydroxyphenylacetate levels increased while glycolate levels decreased across the different stroke risk groups, from the LSR to the HSR groups. Trimethylamine N-oxide (TMAO) had average concentration values that were significantly higher in elderly people in the HSR group, while trigonelline levels were significantly lower in the MSR group. These metabolic markers can be used for early detection and to differentiate stages of stroke risk more efficiently.PMID:39000542 | DOI:10.3390/ijms25137436

Int J Mol Sci. 2024 Jul 6;25(13):7417. doi: 10.3390/ijms25137417.ABSTRACTAbiotic stress, especially drought stress, poses a significant threat to terrestrial plant growth, development, and productivity. Although mulberry has great genetic diversity and extensive stress-tolerant traits in agroforestry systems, only a few reports offer preliminary insight into the biochemical responses of mulberry leaves under drought conditions. In this study, we performed a comparative metabolomic and transcriptomic analysis on the "drooping mulberry" (Morus alba var. pendula Dippel) under PEG-6000-simulated drought stress. Our research revealed that drought stress significantly enhanced flavonoid accumulation and upregulated the expression of phenylpropanoid biosynthetic genes. Furthermore, the activities of superoxide dismutase (SOD), catalase (CAT) and malondialdehyde (MDA) content were elevated. In vitro enzyme assays and fermentation tests indicated the involvement of flavonol synthase/flavanone 3-hydroxylase (XM_010098126.2) and anthocyanidin 3-O-glucosyltransferase 5 (XM_010101521.2) in the biosynthesis of flavonol aglycones and glycosides, respectively. The recombinant MaF3GT5 protein was found to recognize kaempferol, quercetin, and UDP-glucose as substrates but not 3-/7-O-glucosylated flavonols and UDP-rhamnose. MaF3GT5 is capable of forming 3-O- and 7-O-monoglucoside, but not di-O-glucosides, from kaempferol. This implies its role as a flavonol 3, 7-O-glucosyltransferase. The findings from this study provided insights into the biosynthesis of flavonoids and could have substantial implications for the future diversified utilization of mulberry.PMID:39000525 | DOI:10.3390/ijms25137417

Int J Mol Sci. 2024 Jul 5;25(13):7384. doi: 10.3390/ijms25137384.ABSTRACTThe capsule-associated protein 10 gene (CAP10) is indispensable due to its involvement in pod formation and virulence maintenance in Cryptococcus neoformans. The function of the CAP10 gene in nematode-predatory fungi remains unreported. As a typical nematode-trapping fungus, Dactylellina haptotyla efficiently captures nematodes using adhesive knobs, which has potential applications in the biological control of plant-parasitic nematodes. In this study, we investigated the function of DHXT1 (a CAP10 homologous protein) in D. haptotyla-nematode interactions based on the disruption and overexpression of DHXT1, phenotypic analysis and metabolomic analysis. As a result, it was shown that the disruption of the DHXT1 gene causes a marked decrease in the number of adhesive knobs, and on the contrary, the overexpression of the DHXT1 gene causes a substantial increase in the number of adhesive knobs. Interestingly, the variety of metabolites increased with the disruption of the DHXT1 and decreased with the overexpression of the DHXT1 gene. The results suggest that DHXT1 effects pathogenicity through its involvement in adhesive knobs' formation and metabolite synthesis and serves as a key virulence factor in D. haptotyla.PMID:39000488 | DOI:10.3390/ijms25137384

Int J Mol Sci. 2024 Jul 5;25(13):7376. doi: 10.3390/ijms25137376.ABSTRACTCirculating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Here, we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR-Egger. We use the MR-base resource (v0.5.6) from Hemani et al. 2018 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan). We report novel causal relationships found by four or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in four or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction. This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.PMID:39000484 | DOI:10.3390/ijms25137376

Int J Mol Sci. 2024 Jul 4;25(13):7347. doi: 10.3390/ijms25137347.ABSTRACTChronic obstructive pulmonary disease (COPD) plays a significant role in global morbidity and mortality rates, typified by progressive airflow restriction and lingering respiratory symptoms. Recent explorations in molecular biology have illuminated the complex mechanisms underpinning COPD pathogenesis, providing critical insights into disease progression, exacerbations, and potential therapeutic interventions. This review delivers a thorough examination of the latest progress in molecular research related to COPD, involving fundamental molecular pathways, biomarkers, therapeutic targets, and cutting-edge technologies. Key areas of focus include the roles of inflammation, oxidative stress, and protease-antiprotease imbalances, alongside genetic and epigenetic factors contributing to COPD susceptibility and heterogeneity. Additionally, advancements in omics technologies-such as genomics, transcriptomics, proteomics, and metabolomics-offer new avenues for comprehensive molecular profiling, aiding in the discovery of novel biomarkers and therapeutic targets. Comprehending the molecular foundation of COPD carries substantial potential for the creation of tailored treatment strategies and the enhancement of patient outcomes. By integrating molecular insights into clinical practice, there is a promising pathway towards personalized medicine approaches that can improve the diagnosis, treatment, and overall management of COPD, ultimately reducing its global burden.PMID:39000454 | DOI:10.3390/ijms25137347

Int J Mol Sci. 2024 Jul 4;25(13):7336. doi: 10.3390/ijms25137336.ABSTRACTmTOR inhibitors (mTOR-Is) may induce proteinuria in kidney transplant recipients through podocyte damage. However, the mechanism has only been partially defined. Total cell lysates and supernatants of immortalized human podocytes treated with different doses of everolimus (EVE) (10, 100, 200, and 500 nM) for 24 h were subjected to mass spectrometry-based proteomics. Support vector machine and partial least squares discriminant analysis were used for data analysis. The results were validated in urine samples from 28 kidney transplant recipients receiving EVE as part of their immunosuppressive therapy. We identified more than 7000 differentially expressed proteins involved in several pathways, including kinases, cell cycle regulation, epithelial-mesenchymal transition, and protein synthesis, according to gene ontology. Among these, after statistical analysis, 65 showed an expression level significantly and directly correlated with EVE dosage. Polo-Like Kinase 1 (PLK1) content was increased, whereas osteopontin (SPP1) content was reduced in podocytes and supernatants in a dose-dependent manner and significantly correlated with EVE dose (p < 0.0001, FDR < 5%). Similar results were obtained in the urine of kidney transplant patients. This study analyzed the impact of different doses of mTOR-Is on podocytes, helping to understand not only the biological basis of their therapeutic effects but also the possible mechanisms underlying proteinuria.PMID:39000447 | DOI:10.3390/ijms25137336

Int J Mol Sci. 2024 Jul 2;25(13):7288. doi: 10.3390/ijms25137288.ABSTRACTAs a widely distributed plant in Northeast China, Carex meyeriana Kunth (CMK) is generally considered to have antibacterial properties; however, there is a lack of scientific evidence for this. Therefore, we investigated the chemical composition of CMK extract and its effect against C. albicans. A total of 105 compounds were identified in the alcohol extracts of CMK by UPLC-Q-TOF-MS. Most were flavonoids, with Luteolin being the most represented. Among them, 19 compounds are found in the C. albicans lysates. After treatment with CMK ethanol extract, a significant reduction in the number of C. albicans colonies was observed in a vaginal douche solution from day 5 (p < 0.05). Furthermore, the CMK extract can reduce the number of C. albicans spores. The levels of IL-4, IL-6, IL-10, IL-1β, and TNF-α in vaginal tissues all exhibited a significant decrease (p < 0.05) compared to those in the model group as determined by ELISA. The results of HE staining showed that CMK extract can eliminate vaginal mucosa inflammation. CMK adjusts the vaginal mucosa cells by targeting twenty-six different metabolites and five specific metabolic pathways in order to effectively eliminate inflammation. Simultaneously, the CMK regulates twenty-three types of metabolites and six metabolic pathways against C. albicans infection. So, CMK strongly inhibits the growth of C. albicans and significantly reduces vaginal inflammation, making it a promising candidate for treating C. albicans infection.PMID:39000395 | DOI:10.3390/ijms25137288

Int J Mol Sci. 2024 Jun 30;25(13):7250. doi: 10.3390/ijms25137250.ABSTRACTThe glucose-lowering drug metformin alters the composition of the gut microbiome in patients with type 2 diabetes mellitus (T2DM) and other diseases. Nevertheless, most studies on the effects of this drug have relied on fecal samples, which provide limited insights into its local effects on different regions of the gut. Using a high-fat diet (HFD)-induced mouse model of T2DM, we characterize the spatial variability of the gut microbiome and associated metabolome in response to metformin treatment. Four parts of the gut as well as the feces were analyzed using full-length sequencing of 16S rRNA genes and targeted metabolomic analyses, thus providing insights into the composition of the microbiome and associated metabolome. We found significant differences in the gut microbiome and metabolome in each gut region, with the most pronounced effects on the microbiomes of the cecum, colon, and feces, with a significant increase in a variety of species belonging to Akkermansiaceae, Lactobacillaceae, Tannerellaceae, and Erysipelotrichaceae. Metabolomics analysis showed that metformin had the most pronounced effect on microbiome-derived metabolites in the cecum and colon, with several metabolites, such as carbohydrates, fatty acids, and benzenoids, having elevated levels in the colon; however, most of the metabolites were reduced in the cecum. Thus, a wide range of beneficial metabolites derived from the microbiome after metformin treatment were produced mainly in the colon. Our study highlights the importance of considering gut regions when understanding the effects of metformin on the gut microbiome and metabolome.PMID:39000356 | DOI:10.3390/ijms25137250