Boar fertility is negatively affected by subfertility and elevated temperatures, which alter seminal plasma (SP) composition and reduce semen quality. Extracellular vesicles (EVs) in SP transfer microRNAs (miRNAs) to sperm and may influence sperm function. This study aimed to identify SP-EV microRNAs associated with differences in boar semen quality during the summer season. Semen collected from Duroc boars was evaluated and classified as Passed (≥70%) or Failed (<70%) based on sperm quality parameters. SP-EVs were isolated and characterized, and small RNA sequencing was performed to profile miRNA content. SP-EVs ranged from 90 to 200 nm, with concentrations of 4.33 × 1010 particles/mL in the Passed group and 1.85 × 1011 particles/mL in the Failed group. Western blotting confirmed the presence of EV surface markers CD9, CD63, and CD81. A total of 446 unique miRNAs were identified, with 28 downregulated and two upregulated miRNAs in Passed compared with Failed SP-EVs. Additionally, functional enrichment analysis revealed that target genes of upregulated miRNAs were involved in sperm-related biological processes and PI3K-Akt, regulation of actin cytoskeleton, and ErbB signaling pathways. These findings demonstrate that SP-EV miRNAs reflect physiological responses to changes in environmental conditions and may contribute to the regulation of boar semen quality.

Saposin-like protein 2 (SAP2) exhibits strong immunogenicity as an antigen for immunodiagnosis in ruminant and human fasciolosis. Most available immunodiagnostic test kits are based on polyclonal and monoclonal antibodies against antigens from Fasciola spp. Previous studies demonstrated that polyclonal and monoclonal antibodies against SAP2 showed high specificity and could effectively detect Fasciola spp. infections at an early stage. However, polyclonal antibodies are extremely difficult to produce, and quality control is not possible during production; the procedure also involves considerable financial investment. To overcome these problems, we developed a single-chain variable fragment (scFv) to control quality in each production cycle and reduce the cost of manufacturing immunodiagnostic kits. Our objectives were to produce and characterize an scFv that binds the SAP2 from the liver fluke Fasciola gigantica. We constructed the scFv by genetic engineering: we cloned immunoglobulin genes and linked them with flexible polypeptide linkers composed of repeating glycine and serine residues. We selected an scFv with high affinity for binding SAP2 using the phage-display technique and produced it using a prokaryotic expression system. The scFv was characterized via in silico and in vitro methods to confirm its specificity for SAP2, including IMGT/V-QUEST, IMGT/Collier-de-Perles, HADDOCK 2.4, ELISA, immunoblotting, and immunohistochemistry. The scFv was successfully produced and purified using Ni-NTA affinity chromatography. The purified scFvFgSAP2 was approximately 27 kDa, as confirmed by SDS-PAGE and immunoblot analysis. An indirect ELISA and immunoblotting indicated that scFvFgSAP2 had strong reactivity with F. gigantica compared to other parasite species. Moreover, immunolocalization of scFvFgSAP2 confirmed that it binds specifically to natural SAP2 in the cecal epithelium cells of F. gigantica. Therefore, this scFv targeting SAP2 is an effective material and can be used to develop immunodiagnostic procedures.

Y-box binding protein 1 (YB-1; encoded by YBX1) is a multifunctional DNA- and RNA-binding protein implicated in cell cycle regulation, DNA repair, stress adaptation, and therapy resistance. Elevated YBX1 expression has been associated with aggressive disease across multiple cancer types; however, its pan-cancer genomic and clinical correlates, and the extent to which these reflect proliferative activity versus genomic instability, remain incompletely defined. Here, we performed an integrative pan-cancer analysis across 53 independent datasets spanning 33 tumour types, incorporating transcriptomic (YBX1 mRNA), proteomic (RPPA), genomic, and clinical data. We found that YBX1 is rarely altered at the genomic level, whereas its mRNA expression is highly variable within tumour cohorts. Tumours with high YBX1 mRNA expression consistently exhibited conserved transcriptional programmes enriched for cell cycle, mitotic, RNA processing, and signalling pathways, patterns that were also reflected at the protein level by concordant pathway associations with elevated YB-1 abundance. These molecular features co-occurred with clinicopathological characteristics indicative of aggressive disease. High YBX1 mRNA expression was associated with increased mutation burden, chromosomal alteration burden, hypoxia, and homologous recombination deficiency at the pan-cancer level, with similar molecular associations observed in tumours stratified by elevated YB-1 protein levels. The association between YBX1 expression and chromosomal alteration burden was largely attenuated after accounting for proliferative activity, particularly G2/M-associated transcriptional programmes used as a proxy for mitotic activity. While the relationship with mutation burden was heterogeneous across tumour types, this pattern suggests that links between YBX1 expression and chromosomal instability primarily reflect shared proliferative and mitotic tumour biology rather than an independent genomic instability programme. Clinically, high YBX1 mRNA expression was associated with advanced disease stage, higher histologic grade, reduced progression-free survival, and poorer overall survival. Elevated YB-1 protein levels were also associated with advanced disease stage and poorer survival outcomes and demonstrated a similar, although non-significant, directional trend with histologic grade. Collectively, these findings demonstrate that elevated YBX1 expression marks proliferative and clinically aggressive tumour states within which genomic instability-related features arise in a context-dependent manner, providing a clarified pan-cancer framework for interpreting YB-1-associated tumour biology.

Atopic dermatitis (AD) is a chronic inflammatory skin disease increasingly prevalent in adults. Vitamin D plays an important role in regulating immune responses, cellular differentiation, and inflammation. Several single-nucleotide polymorphisms (SNPs) in the vitamin D receptor (VDR) gene have been suggested as biomarkers of AD susceptibility and severity. The aim of this study was to investigate six SNPs in the VDR gene (rs3847987, rs731236, rs7975232, rs1544410, rs2228570, and rs11168293) and their association with AD and blood biomarkers. Genotyping was performed in 91 adult patients with AD and 102 controls using real-time polymerase chain reaction. The genotype and allele distributions did not differ significantly between AD patients and controls. However, the G and T alleles of VDR rs731236 and rs1544410 were more frequently detected in individuals with serum 25-hydroxyvitamin D (25(OH)D) levels above 30 ng/mL. In contrast, the VDR rs7975232 C allele appears to be associated with lower odds of having a serum 25(OH)D level above 30 ng/mL. In genotype-stratified analysis, the T allele of VDR rs11168293 was more prevalent among individuals with eosinophil counts of 300 cells/μL. These findings suggest that VDR polymorphisms may contribute to variability in vitamin D status and inflammatory responses in adults with AD.

Transfer RNA-derived fragments (tRFs) have been recently recognized for their multiple roles in gene expression, including modulation of translation, mRNA stability, and cellular signaling pathways. Sensory organs, such as the eyes, skin, and oral cavity, are continuously exposed to environmental stressors, including oxidative stress, ultraviolet radiation, microbial challenges, and mechanical stimuli, making them particularly susceptible to dysregulation of RNA-mediated processes. This review comprehensively summarizes current evidence on the role of tRFs in sensory organ physiology and pathology with a focus on their involvement in key processes, such as angiogenesis, inflammation, immune regulation, and fibrosis. tRFs have been shown to influence critical signaling pathways that are central to diseases such as retinal neovascularization, inflammatory skin conditions, wound healing, tissue remodeling, etc. Despite these advances, the field remains limited by a lack of experimentally validated tRF-target interactions, as most available data rely on computational predictions. The findings from the literature emphasize the need for rigorous functional validation in disease-relevant models of tRFs in biofluids, such as saliva and serum, to support their potential as minimally invasive biomarkers. Further translational studies are required to fully elucidate their biological roles and explore their potential in diagnostic and therapeutic applications.

Increasing incidence of candidiasis and emergence of antifungal resistance necessitate the development of alternative antifungal strategies. In this context, the antifungal activity of the crude extract of Punica granatum L. peel (PGPE) and its chitosan nanoparticle-coated formulation (PGPE-CSNPs) was investigated against Candida albicans (ATCC 10231), Candida glabrata (ATCC 66032), Candida kefyr (ATCC 46764), Candida parapsilosis (ATCC 22019), and Candida tropicalis (ATCC 13803). Although the individual antimicrobial activities of PGPE and CSNPs have been investigated, their combined application against Candida spp. remains unexplored in the literature. The antifungal efficacy was evaluated using agar well diffusion, disk diffusion, minimum inhibitory concentration (MIC), and minimum fungicidal concentration (MFC) testing, and compared with fluconazole and amphotericin B. The morphological characterization of PGPE-CSNPs was performed using scanning electron microscopy (SEM), which confirmed successful encapsulation and revealed a smoother surface with uniformly distributed nanometric pore structures and reduced aggregation compared to uncoated CSNPs. PGPE-CSNPs showed greater inhibition zones than amphotericin B, except against C. albicans. The CSNPs formulation reduced the MIC from 8 µg/mL to 4 µg/mL and the MFC from 16 µg/mL to 8 µg/mL, representing a two-fold enhancement against C. albicans. No enhancement in activity was observed against C. glabrata, whereas for C. kefyr, only MFC values decreased from 8 µg/mL to 4 µg/mL. For both C. parapsilosis and C. tropicalis, MIC values reduced from 16 µg/mL to 8 µg/mL, and MFC values reduced from 32 µg/mL to 16 µg/mL for both species. PGPE-CSNPs exhibited significantly lower MIC and MFC values than the crude extract alone (p < 0.05). These findings suggest that chitosan-based nanocarriers may enhance the antifungal efficacy of plant-derived bioactive compounds, highlighting their potential as a promising alternative antifungal strategy, a combinatorial approach not previously reported in the literature.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by dysbiosis of the gut microbiota. Helminth infections are known to modulate host immunity and intestinal microbial composition; however, the therapeutic use of live parasites poses safety challenges. The recombinant Fasciola hepatica fatty acid-binding protein Fh15 is a helminth-derived molecule with anti-inflammatory effects in models of septic shock and dextran sulfate sodium (DSS)-induced colitis. Whether Fh15 also influences gut microbial composition during colitis remains unknown. Male C57BL/6 mice received 4% DSS in drinking water for 7 days to induce colitis and were treated intraperitoneally with Fh15 (2 mg/kg) on days 1, 3, and 5. Fecal samples were collected on days 2, 4, and 7 for 16S rRNA gene sequencing. Standard microbiota pipelines were used to evaluate community diversity. Acute DSS treatment disrupted gut microbial diversity and community structure compared with non-colitic controls. Fh15 treatment partially restored early microbial balance by shifting microbial composition toward that of healthy mice and reducing microbial dispersion, indicating enhanced community stability despite severe dysbiosis. Although alpha diversity did not return to control levels, Fh15 mitigated the expansion of pro-inflammatory genera (Enterococcus and Turicibacter) and preserved beneficial taxa, including Adlercreutzia.

The exponential growth of genomic and proteomic data has made computational protein–protein interaction (PPI) prediction indispensable, driving the need for a comprehensive and method-aware evaluation of supervised learning approaches. PPIs are fundamental to understanding cellular processes and disease mechanisms, yet experimental identification remains slow, costly, and difficult to scale. This survey systematically investigates ten supervised learning models—Extreme Learning Machine (ELM), Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), Deep Neural Networks (DNNs), Naïve Bayes, Probabilistic Decision Tree, Support Vector Machine (SVM), Least Squares SVM (LS-SVM), K-Nearest Neighbor (KNN), and Weighted K-Nearest Neighbor (WKNN)—through a tri-layered framework that integrates Comparative Quantitative Analysis, Comparative Observational Analysis, and Experimental Evaluations. Beyond conventional accuracy summaries, this work provides critical commentary tied to real-world use, analyzing where techniques succeed or fail in practice—for instance, when instance-based methods bottleneck during inference, when kernel choices influence SVM variance, or when deep architectures trade accuracy for computational cost. The survey also offers concrete deployment guidance, such as calibration insights for WKNN versus KNN under varying feature noise or dataset curation quality, delivering operational perspectives that typical surveys omit. Comparative Quantitative Analysis consolidates metrics such as accuracy, F1-score, and computational time from the existing literature, while Comparative Observational Analysis evaluates interpretability, scalability, dataset suitability, and efficiency. Complementing these, Experimental Evaluations conducted by the authors empirically validate model performance on benchmark datasets. Together, these layers provide a unified and evidence-backed perspective on algorithmic strengths, weaknesses, and practical applicability. Findings show that GNNs and DNNs achieve the highest predictive accuracy due to their ability to capture structural and topological relationships, whereas ELM and Naïve Bayes offer superior efficiency. SVM and LS-SVM maintain robust stability under noisy conditions, and CNNs are well-suited for sequence-based prediction tasks. By combining empirical validation, critical insights, and deployment-focused recommendations, this survey delivers decision-grade guidance that bridges theoretical understanding with real-world implementation, thus clarifying the trade-offs among accuracy, efficiency, and scalability in PPI detection research.

As endemic or regionally distinctive taxa in China, Ottelia species exhibit notable ecological adaptability as well as potential nutritional and medicinal value. Nevertheless, a comprehensive characterization and comparative analysis of the chemical constituents across this genus remain lacking, particularly for O. acuminata var. jingxiensis, O. fengshanensis, and O. guanyangensis. This knowledge gap has hindered the systematic exploitation and value-added utilization of Ottelia resources. In the present study, five Ottelia taxa—O. acuminata, O. acuminata var. jingxiensis, O. fengshanensis, O. guanyangensis, and O. alismoides—were investigated. By integrating widely targeted metabolomics, network pharmacology, and in vitro experimental validation, we identified Rivularin, Tenaxin I, Sinensetin, 8-Methoxyapigenin, Chrysoeriol, Hispidulin, Genkwanin, 5,2′-Dihydroxy-7,8-dimethoxyflavone, Kumatakenin, and Pectolinarigenin as key antioxidant constituents in the Genus Ottelia. Network-based analyses further indicated that these compounds predominantly act on PTGS1/2 and AR, and may mediate antioxidant activity primarily through the PI3K–Akt signaling pathway and pathways associated with EGFR tyrosine kinase inhibitor resistance. Collectively, these findings provide a scientific basis for the further development, functional evaluation, and sustainable utilization of the Genus Ottelia.

Organic-type solar cells containing an active layer of block copolymer donor PTB7-Fx (x = 0, 20, and 100), based on benzo [1,2-b:4,5-b’]dithiophene and variably fluorinated thieno [3,4-b]thiophene units, and fullerene acceptor [6,6]phenyl-C71-methylbutyrate, were constructed. The active layer thin film of the solar cells was obtained from a dichlorobenzene solution at an established concentration via spin-coating of the donor–acceptor mixture in the presence of solvent additives such as 3% diiodooctane and 1% triethyl phosphate. Organic photovoltaic elements with normal device architecture were prepared on glass substrates using an indium tin oxide anode, a spin-coated hole transporting layer of poly(ethylene dioxythiophene):polystyrenesulfonate, the aforementioned active layer, followed by an electron transporting layer of zinc oxide nanoparticles, and finally a magnetron sputtered silver (Ag) top-electrode. The optical properties, thin film morphology, and the thickness of the active layers were investigated. Additionally, current density–voltage characteristics and impedance spectra of photovoltaic devices were measured. It was found that PTB7-Fx:PC71BM-based solar cells processed in the presence of two types of solvent additives, diiodooctane and triethyl phosphate, with a sputtered Ag top-electrode display similar absorption and quantum efficiency spectra, as well as comparable current density–voltage characteristics and efficiencies to the same devices fabricated without additives. The diiodooctane solvent additive preferably dissolves the fullerene component and has a positive effect on fill factor enhancement, impedance spectra improvement, and amelioration in charge carrier transport and collection, whereas the triethyl phosphate solvent additive preferentially dissolves the copolymer donor and has a more pronounced impact on the refined morphology of the thin film active layers.