Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a major global health concern and encompasses a spectrum ranging from hepatic steatosis and metabolic dysfunction-associated steatohepatitis to liver fibrosis, cirrhosis, and ultimately hepatocellular carcinoma. Insulin resistance, the pathogenic cornerstone of MASLD, drives enhanced peripheral lipolysis and increased hepatic de novo lipogenesis, thereby overloading the liver with lipids and inducing steatosis. Subsequent lipotoxicity, inflammation, and gut microbiota dysbiosis further exacerbate disease progression. The gut microbiota and their metabolites communicate with the liver via the gut-liver axis, forming a complex signaling network that directly or indirectly modulates hepatic metabolism, systemic immune responses, oxidative stress, and intestinal barrier integrity. In this review, we synthesize evidence for the beneficial and detrimental effects of the major human gut microbial communities and their metabolites during the course of MASLD. We delineate how these gut-derived factors regulate hepatic function through an integrated tripartite “gut-liver axis–oxidative stress–metabolic reprogramming” mechanism. These insights may inform microbiome-based precision interventions and accelerate the development of therapeutic strategies targeting MASLD.

Normalization can standardize and improve machine learning (ML) performance on omics data. However, it is unclear whether normalization is associated with overfitting (i.e., worse cross-dataset performance than intra-dataset performance). Therefore, we aimed to examine associations of normalization and regularization with overfitting of ML on omics data.

Using three paired transcriptomic and clinical datasets (lung adenocarcinoma: the Cancer Genome Atlas (TCGA)/Oncology Singapore; melanoma: TCGA/Dana-Farber Cancer Institute; glioblastoma: TCGA/Clinical Proteomic Tumor Analysis Consortium), we applied ANOVA-based gene selection methods, six normalization methods, and six ML models to classify cancer patients’ deaths. Balanced accuracy (BA) and area under the curve (AUC) in intra- and cross-dataset settings were compared using inferential analyses.

Normalization consistently improved intra-dataset performance (median BA/AUC changes: 0.035–0.214/0.115–0.279) on all data, particularly with Z_Raw, but decreased or slightly increased cross-dataset performance (median BA/AUC changes: −0.029–0.079/0.029–0.064). Least Absolute Shrinkage and Selection Operator (LASSO) model without normalization consistently outperformed most of the ML models in cross-dataset testing across cancer types. ML models on all and molecular-alone data showed similar best performances.

Normalization increases ML’s intra-dataset performance and overfitting in three paired cancer transcriptomic and clinical datasets. Regularized models such as LASSO appear to mitigate overfitting and achieve robust cross-dataset performance. Therefore, cross-dataset evaluation and regularized models are recommended to assess and reduce overfitting, while normalization should be used cautiously. Adding clinical data seems to have little impact on ML models’ performance. However, future work on other diseases and datasets is warranted.

Vulvovaginal candidiasis, an infection caused by an abnormal proliferation of Candida species in the vagina and vulva, is particularly relevant, affecting up to 75% of women of reproductive age. Because of antifungal drug resistance, a significant number of plants are used to treat vaginal candidoses in Cameroon. Thus, the scientific validation of the use of these plants in treating candidiasis is valuable. This study sought to identify medicinal plants used to treat vaginal infections in the Dschang district and evaluate the antifungal activity of the most promising plants on five Candida species.

The ethnobotanical survey was conducted in Dschang (Menoua Division, West Cameroon) through individual interviews using a semi-structured questionnaire. Extracts from seventeen plants were obtained by maceration using water or a water–ethanol solution (3:7; v/v). Antifungal activity was evaluated using the microdilution method.

Forty-eight plants belonging to 33 families were identified as treating vaginal infections. Decoction and formulation of ovules were the prevalent modes of plant preparation, with leaves and bark being the predominant plant organs used. Out of thirty-four extracts tested, two (CSEHAlc and MIEHAlc) showed antifungal activity, with minimum inhibitory concentrations ranging from 0.315 to 2.5 mg/mL. The determination of the minimum fungicidal concentrations revealed the fungicidal orientation of these bioactive extracts.

This study identifies medicinal plants used to treat vaginal infections in Dschang and their modes of preparation. The in vitro antifungal screening of selected plants indicated Mangifera indica and Canarium schweinfurthii as the anti-Candida plants that can be further exploited for antifungal drug discovery.

Chronic hepatitis B (CHB) remains a major global public health challenge. Current therapies based on nucleos(t)ide analogues and interferon mainly achieve long-term viral suppression, whereas only a small proportion of patients attain a functional cure, defined as sustained hepatitis B surface antigen loss with hepatitis B virus (HBV) DNA below the limit of quantification for at least 24 weeks after treatment discontinuation, with or without anti-HBs seroconversion. Emerging evidence from the gut–liver axis indicates that gut microbiota–derived metabolites, particularly short-chain fatty acids (SCFAs) and bile acids (BAs), modulate the HBV life cycle and immune regulation in CHB, thereby offering therapeutic targets to overcome immune tolerance. This review summarizes the biological characteristics of SCFAs and BAs and their mechanistic roles across different stages of HBV infection, with emphasis on translational relevance. In vitro and animal studies suggest that butyrate and related SCFAs suppress HBV gene expression by inhibiting histone deacetylases and remodeling covalently closed circular DNA minichromatin. SCFAs may also enhance antiviral immunity, although they may reinforce immune tolerance in certain contexts. For BAs, the farnesoid X receptor, Takeda G protein–coupled receptor 5, and the HBV entry receptor sodium taurocholate cotransporting polypeptide form a key signaling hub with dual effects on viral replication and host responses. Early-phase studies suggest that farnesoid X receptor agonists, pegylated interferon-α, or nucleos(t)ide analogues are associated with hepatitis B surface antigen reductions, though larger trials are needed. This review proposes biomarker-guided stratification and multi-target combination strategies to improve functional cure rates in CHB.

Immunothrombosis, the interplay between immune activation and coagulation, contributes to disease progression in inflammatory disorders. Its role in hepatitis B virus–related acute-on-chronic liver failure (HBV-ACLF) and the involvement of neutrophil extracellular traps (NETs) remain unclear. This study aimed to elucidate NETs-mediated immunothrombosis in HBV-ACLF.

Liver single-cell RNA sequencing data from HBV-ACLF patients and healthy controls were analyzed to define immune and endothelial transcriptional profiles. A cohort of 46 HBV-ACLF patients, 20 chronic hepatitis B patients, and 20 healthy controls was assessed for circulating NETs, endothelial injury markers, and coagulation parameters. Histopathology and in vitro assays examined NETs distribution and endothelial interactions.

NETs were markedly elevated in HBV-ACLF and correlated with endothelial injury markers (syndecan-1, von Willebrand factor, soluble thrombomodulin), coagulopathy, and prognostic scores. Histology revealed NETs colocalization with endothelial cells and platelets within hepatic microthrombi. NETs from patient neutrophils impaired endothelial integrity and enhanced procoagulant activity in vitro. Mechanistically, toll-like receptor 2 (TLR2) and complement component 5a receptor 1 (C5aR1) signaling were involved in NETs formation, and their pharmacological inhibition reduced NETs generation.

NETs are associated with endothelial injury and immunothrombosis in HBV-ACLF. Mechanistic analyses suggest a role for TLR2 and C5aR1 pathways in NETs formation, indicating potential targets for future therapeutic investigation.

Fast inverse planning in radiosurgery planning is limited by an excessive number of isocenters, which is clinically hypothesized to be driven by the morphological irregularity of the target volume. This retrospective cross-sectional study aimed to empirically evaluate this hypothesis in vestibular schwannoma cases.

Consecutive patients diagnosed with vestibular schwannoma and receiving Gamma Knife radiosurgery in 2023 were included, and their treatment plans designed using the GammaPlan planning system were collected. Morphological irregularity–related parameters, including standard sphericity (SS), volume ratio sphericity (VRS), and the coefficient of variance of diameters (DCV), were calculated based on parameters provided by the system. Basic demographic and clinical data were collected to evaluate their impact on sphericity. The effects of different sphericity assessment methods on common treatment plan parameters were analyzed.

Treatment plans of 280 patients with vestibular schwannoma were collected. The SS, VRS, and DCV of the tumors were 0.85 (0.77–0.91), 0.46 ± 0.16, and 0.22 (0.14–0.34), respectively. Multivariate analysis showed that lesion volume, acoustic neuroma consensus on systems for reporting results grade, and age were significant factors influencing sphericity. All other planning parameters, except prescription dose and homogeneity index, were significantly correlated with sphericity. DCV was more closely correlated with SS than with VRS.

DCV may serve as a simple quantitative metric of target morphological irregularity, showing strong consistency with SS. Incorporating morphological irregularity into Gamma Knife treatment plan evaluation may help improve future planning strategies and support optimization of isocenter utilization.

Synucleinopathies, including Parkinson’s disease (PD), dementia with Lewy bodies, and multiple system atrophy (MSA), are a group of neurodegenerative diseases characterized by the oligomerization of α-synuclein protein in neurons or glial cells. Various splicing isoforms of α-synuclein have been described, each with different aggregation properties. The α-synuclein gene (SNCA) has been identified as a highly significant genetic risk locus associated with various synucleinopathies across populations. This study aimed to assess the association of SNCA genetic variants with MSA and the levels of SNCA transcripts in peripheral blood mononuclear cells (PBMCs) from MSA and PD patients.

In this retrospective case–control study, 96 MSA patients, 1086 PD patients, and 485 healthy volunteers were included. PCR followed by restriction endonuclease analysis was used to detect four SNCA single-nucleotide polymorphisms (rs356219, rs3756063, rs11931074, and rs356168) in these individuals. In addition, RT-qPCR was performed to detect the levels of α-synuclein transcripts (SNCA mRNA isoforms -140, -126, and -112) in PBMCs of 24 MSA patients (including parkinsonian (MSA-P) and cerebellar (MSA-C) variants), 31 PD patients, and 32 healthy volunteers.

The frequency of the ‘T’ allele (of rs11931074) was significantly higher in MSA patients than in the healthy controls. The level of SNCA-140 mRNA was significantly decreased in MSA and PD patients compared with the controls, while the level of SNCA-112 mRNA was significantly increased in MSA-P patients than in PD patients and the controls. SNCA-112 mRNA/SNCA-140 mRNA and SNCA-112 mRNA/SNCA-126 mRNA ratios were significantly increased in MSA patients than in the controls.

The SNCA rs11931074 polymorphism is associated with MSA. There is a pronounced alteration in the expression of SNCA transcripts in PBMCs of MSA and PD patients.