Search Results (28,528)

The outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged as one of the most significant global health crises in recent history. Coronaviruses are a diverse group of RNA viruses classified into alpha, beta, gamma, and delta genera, with SARS-CoV-2 belonging to the beta-coronavirus family. The virus exhibits high transmissibility and causes a wide spectrum of clinical manifestations ranging from mild respiratory symptoms to severe complications such as acute respiratory distress syndrome, multi-organ failure, and death, particularly among elderly and immunocompromised individuals. Structurally, SARS-CoV-2 possesses a large single-stranded RNA genome encoding major structural proteins, including spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, which play critical roles in host-cell recognition and viral infection. Understanding the molecular mechanisms of virus–host interactions, especially protein–protein interactions (PPIs), is essential for uncovering viral pathogenesis and identifying potential therapeutic targets. Traditional experimental techniques for PPI detection, such as yeast two-hybrid and affinity purification methods, are often expensive, labor-intensive, and prone to inaccuracies. Consequently, computational approaches based on machine learning (ML) and deep learning (DL) have gained significant attention for efficient and scalable PPI prediction. These methods use diverse biological information, including protein sequences, structural features, genomic data, Gene Ontology annotations, and interaction networks, to model complex biological relationships. This survey reviews computational approaches to PPI prediction, highlighting ML- and DL-based techniques, methodological advances, performance evaluation practices, and limitations that affect benchmark comparability. It also discusses biological databases and data sources commonly used in PPI studies and explicitly considers how models trained in coronavirus-centered settings may generalize to other viral families with different mechanisms of host interaction. Full article

Silver nanoparticles (AgNPs) synthesized via fungal-mediated biosynthesis have gained attention as eco-friendly alternatives to chemically produced nanomaterials, with broad biomedical potential. Fungi represent particularly attractive systems because their secretomes contain diverse biomolecules, including enzymes, proteins, polysaccharides, and secondary metabolites, capable of reducing silver ions and stabilizing the resulting nanoparticles. Despite extensive investigation, the molecular mechanisms underlying fungal-mediated AgNP formation remain poorly defined. This review critically examines the key biomolecular drivers involved in this process, with emphasis on nitrate reductases, oxidoreductases, extracellular proteins, polysaccharides, and secondary metabolites as potential reducing and capping agents. Proposed mechanisms, including nitrate reductase-dependent, superoxide-mediated, and metabolite-driven pathways, are evaluated. The influence of process parameters such as silver nitrate concentration, incubation time, culture medium composition, pH, temperature, and fungal species on nanoparticle yield, size, and stability is also assessed. Analysis of the current literature highlights significant knowledge gaps, including limited application of proteomic and metabolomic approaches, a lack of causal mechanistic studies, and insufficient standardization of experimental protocols. Overall, evidence indicates that fungal AgNP biosynthesis is governed by complex interactions among multiple biomolecular classes rather than a single universal mechanism, underscoring priorities for improving reproducibility, scalability, and mechanistic understanding. Full article

Human endogenous retroviruses (HERVs) originate from ancient retroviral integration into the primate germline. Although most are defective proviruses, the most recently endogenized groups, like the HERV-K family, retain intact ORFs encoding retroviral proteins. HERVs usually remain transcriptionally silent, yet this status is reversible. Multiple HIV-HERV interactions, mainly mediated by the HIV Tat protein, lead to HERV transcription and protein production. The present study investigates HERV-K transcription in particular of Human MMTV-like (HML) group-2 and 6 in peripheral blood of people with HIV (PWH). Using different experimental approaches—such as single-cell and plasma transcriptomics-, we found that HERV-K transcripts may be detected during both acute and chronic phases of the infection, with HML-6 showing higher expression compared to HML-2, predominantly within myeloid cells. Effective combined antiretroviral therapy (cART) was able to significantly reduce HML-6 transcription, regardless of whether the treatment was initiated in the acute or late chronic phases of HIV infection. Notably, chronic infections showed higher HML-6 transcript levels compared to acute infections in both naïve and successfully cART-treated subjects, potentially associated with persistent immune dysregulation observed in chronic HIV infection, although a direct causal role of HML-6 expression remains to be established. Full article

This review evaluates multi-omics applications in dairy research across nutrition, safety, and health. Through multi-omics integration, we reveal nutrient differences driven by species, rearing practices, and processing techniques, identify protein patterns and allergen profiles, and construct adulteration detection fingerprints and species-specific peptide markers, thereby improving the timeliness and accuracy of safety assessment. The coupling of metagenomics and metabolomics effectively predicts spoilage-related microbial risks, enabling better risk control. Furthermore, multi-omics approaches systematically elucidate the functional mechanisms of bioactive peptides (e.g., ACE-inhibitory peptides), clarify the prebiotic effects of functional oligosaccharides, and build interaction networks between dairy components and gut microbiota. The introduction of machine learning enables origin and shelf-life prediction, as well as the discovery of novel biomarkers, promoting personalized nutrition and precision fermentation strategies. However, the field is currently constrained by severe reproducibility issues arising from the absence of standardized operating procedures, excessive optimism regarding machine learning models that rarely generalize across laboratories or product matrices, and a persistent disconnect between laboratory-scale biomarker discovery and industrial implementation. Without rigorous cross-platform validation and openly shared multi-omics reference datasets, most published markers remain unfit for regulatory or industrial application. Future efforts should establish standardized workflows and expand the evidence base to drive the dairy industry toward safer, healthier, and more traceable directions. Full article

Accessory proteins of SARS-CoV-2 play crucial roles in viral pathogenesis, yet their structural properties remain elusive. ORF7b, a small accessory protein comprising only 43 amino acids, is widely assumed to parallel the structure–function relationships of its SARS-CoV ortholog based solely on sequence homology. In this study, we challenge this paradigm through direct physicochemical and structural characterization. Sequence analysis and electrostatic profiling reveal that the SARS-CoV-2 protein is a macromolecular polyanion with a net charge of −4 at neutral pH, featuring a diffuse negative surface that is highly responsive to pH changes. Complete 3D structures generated via ab initio modeling display a helical core flanked by two highly fluctuating, disordered termini. Residue Interaction Network (RIN) topology and Normal Mode Analysis (NMA) identified specific hinges governing these flexible extremities. Furthermore, the calculated dipole moment vector is tilted outward by 24°, misaligning with the central axis. Molecular dynamics simulations suggest that while the soluble structure is highly stable in water, it undergoes severe distortions and insufficient solvation within a membrane-mimetic environment. Thermodynamic association profiles and verified interactomic data from BioGRID reveal a strong propensity for ORF7b to participate in liquid–liquid phase transitions alongside human and viral partners. Taken together, these unique properties suggest that ORF7b operates as a dynamic peripheral membrane protein rather than a sedentary transmembrane component, providing a fresh framework for future therapeutic targeting. Overall, these in silico findings shift the current paradigm on ORF7b2 topology and provide a robust, physically grounded framework that identifies specific molecular priorities for future in vitro and in vivo validation. Full article

Triphenyl phosphate (TPhP) is a ubiquitous environmental contaminant and endocrine disruptor potentially associated with an increased risk of thyroid cancer (TC). However, whether TPhP directly contributes to TC remains unclear. This study integrated network toxicology and machine learning to investigate potential molecular associations between TPhP exposure and thyroid oncogenesis. By integrating multi-source databases and transcriptomic data, we constructed a TPhP–TC interaction network and established a TC risk prediction model using 127 machine learning algorithm combinations, identifying ten candidate hub genes. GO and KEGG enrichment analyses indicated that these genes are predominantly enriched in phosphorus metabolism, purine metabolism, and nuclear receptor signaling pathways, implying that TPhP may be linked to tumorigenesis through the disruption of metabolic reprogramming. SHAP analysis highlighted AHR and SLC20A2 as critical contributors to model performance. Molecular docking predicted stable binding between TPhP and all hub proteins in silico, with binding energies ranging from −9.2 to −6.6 kcal/mol. This study offers two computational contributions: (1) a quantifiable framework for predicting pollutant-associated TC risk and (2) systematic computational evidence for potential TPhP thyroid toxicity. These findings address a critical gap in understanding potential links between endocrine-disrupting chemical exposure and thyroid carcinogenesis, generating hypotheses for future experimental validation. Full article

The effects of red seaweed, psyllium husk, and chia seeds on the structural and functional properties of comminuted meat batters were evaluated. Meat batters were formulated with 1% of each ingredient or their combinations totaling 1% and evaluated for pH, cooking loss, microstructure, texture profile analysis, color, rheology, and protein interactions. Formulation did not affect (p ≥ 0.08) pH or cooking loss, indicating that water- and lipid-holding capacity and emulsion stability were preserved across treatments. Hardness increased (p ≤ 0.05) in treatments containing red seaweed, alone or combined with psyllium husk. Fiber addition did not influence (p ≥ 0.17) raw batter color; however, cooked products showed differences (p ≤ 0.05) in lightness (L*) and total color change (ΔE*). Rheological analysis indicated similar viscoelastic behavior among treatments with no significant differences among treatments (p ≥ 0.07) for storage modulus, loss modulus, or tangent delta at the start, peak, or end of the small-amplitude oscillatory shear test. Microstructural observations revealed treatment-dependent networks, and protein solubility analysis showed changes (p ≤ 0.05) in ionic and hydrogen bonding, while disulfide bonds were unaffected (p = 0.60). Incorporation of 1% of these ingredients maintained desirable physicochemical, textural, and functional properties, highlighting their potential as ingredients in meat batters. Full article

This study presents an in-depth analysis of an interactome comprising approximately 1033 nodes, focusing on its topology, reliability, and functional implications, with particular attention to the small mitochondrial proteins of the Humanin family and their nuclear-encoded MTRNR2Lx paralogs. The analysis, conducted through stringent high-reliability filters and experimentally supported interaction data, produced a curated network model in which approximately 70% of the retained interactions were supported by experimental evidence, providing a solid basis for network-based functional interpretation. The topology of the interactome showed scale-free and modular network characteristics, with hub and bottleneck nodes defining highly connected stress-response and regulatory modules. Humanin-related proteins, positioned at the periphery of the interactome, emerged as candidate modulatory nodes linking peripheral signaling interfaces to broader functional modules. Mitochondrial Humanin may contribute to early cytoprotective responses, including pathways associated with BAX-dependent apoptosis regulation, whereas nuclear MTRNR2Lx proteins appear to be connected to more sustained regulatory networks involving neuroprotection- and apoptosis-associated modules under chronic stress conditions. In particular, the MTRNR2Lx–FPR2/G-protein module, including GNB1, emerged as a candidate signaling interface that may contribute to the downstream organization of Humanin-related responses. This network-based distinction supports the view that Humanin-family peptides may operate as modulators of stress-response networks rather than as isolated effectors of intrinsic mitochondrial functions. Overall, the methodological approach, results, and proposed model provide new insights into the systems-level organization of Humanin biology and identify prioritized molecular candidates for future in vitro and in vivo validation in the context of neurodegeneration, apoptosis, and cellular stress. Full article

Frailty is a multidimensional geriatric syndrome that lacks a consistent definition, complicating its clinical management. Epigenetic data suggest that frailty involves altered CpG sites, potentially driven by environmental epigenetic factors (the exposome) that influence aging. Systematically reviewing studies from 2009 to 2025, we quantified frailty prevalence, pooled weighted methylation beta values for associated CpG sites, performed enrichment analysis, and conducted structural network analysis to evaluate chemical interactions, following the PRISMA 2020 guidelines and with the study prospectively registered in PROSPERO (ID 1159037). Results showed a pooled frailty prevalence of 17.4% with extreme heterogeneity (I² = 98.88%), and a combined methylated beta effect of −0.1378 (CI: −0.4156, 0.1400) with high heterogeneity (I² = 100%), highlighting sources of variability. Interestingly, we found a CpG site (cg04772644) shared between Chinese and German cohorts, and, upon mapping, four frailty-related genes (CDC42BPB, SLC1A5, RXRB, and SLC22A18AS) were shared across cohorts. Indeed, these genes are significantly enriched in pathways including thrombin signaling, G protein-coupled receptor signaling, and immune cell differentiation signaling. Finally, our system toxicology analysis demonstrated that arsenite, bisphenol A, benzamide, dorsomorphin, and trichostatin A directly interact with the four shared genes, suggesting that the chemical exposome contributes to the observed epigenetic heterogeneity of frailty and the concomitant clinical manifestations. Full article

Cyclin-dependent kinases (CDKs) and cyclins are master regulators of the cell cycle, playing critical roles in plant growth, development, and stress responses. While these gene families have been extensively studied in model plants, a comprehensive analysis in soybean remains underexplored. To address this gap, we performed a genome-wide identification and systematic analysis of these families in soybean using bioinformatic approaches. Expression profiles and protein interactions of selected GmCDK and GmCyclin candidates were tested by qRT-PCR and BiFC assays. A total of 28 GmCDK and 101 GmCyclin genes were identified, revealing a significant expansion compared to Arabidopsis, rice, and maize, primarily driven by whole-genome and segmental duplications. Phylogenetic analysis classified GmCDKs into seven conserved clades (CDKA-CDKG) and GmCyclins into ten distinct subfamilies. Expression profiling demonstrated dynamic, tissue-specific patterns, with distinct modules active during seed development and in tissues. Promoter analysis further linked these genes to hormonal and stress-responsive pathways. Crucially, BiFC assay identified specific interactions between GmCDKA2, GmCDKA3, GmCDKB1 and GmCYCA3-3, suggesting evolutionary divergence in soybean CDK-Cyclin regulatory networks. This study provides a foundational resource for the soybean cell cycle regulome, highlighting its evolutionary plasticity and implicating specific CDK-Cyclin pairs as potential targets for manipulating agronomic traits such as seed development and stress resilience. Full article

The autism spectrum disorder-associated SCN2A, ANK2, and SHANK-family genes encode molecularly distinct proteins that converge functionally on dendritic integration. Recent work established that ankyrin-B, encoded by ANK2, acts as an obligate dendritic scaffold for NaV1.2, encoded by SCN2A, in neocortical pyramidal neurons. Loss of this module mislocalizes dendritic NaV1.2, reduces dendritic Na⁺ influx, weakens backpropagating action potentials, and impairs synaptic maturation and long-term potentiation. SHANK proteins organize a complementary postsynaptic receptor scaffold within dendritic spines, coupling N-methyl-D-aspartate (NMDA), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), and metabotropic glutamate receptor (e.g., mGluR5) signaling to the actin cytoskeleton through layered PSD-95/GKAP/Homer interactions. Disruption of this scaffold can destabilize excitatory transmission, spine morphology, and plasticity. We propose that these dendritic shaft and spine-associated modules jointly regulate dendritic input–output gain and that their disruption may contribute to autism spectrum disorder by destabilizing, rather than uniformly shifting, excitatory integration across cortico-subcortical circuits relevant to sensory reactivity, behavioral flexibility, and social-valence processing. Here, we review the cortical evidence for this layered dendritic convergence and evaluate its potential relevance beyond the cortex. We assess the striatum, thalamus, and amygdala as subcortical sites where related dendritic scaffolding mechanisms may operate. The striatum provides the strongest current test case, with established roles for both NaV1.2 and SHANK3 in medium spiny neuron physiology and corticostriatal connectivity. Thalamic and amygdalar extensions are supported mainly by SHANK-related circuit and channelopathy data but lack direct evidence for ANK2–SCN2A involvement. The framework is experimentally testable: conditional Ank2 deletion in striatal, thalamic, and amygdalar cell types; dendritic Na⁺/Ca²⁺ imaging across Scn2a, Ank2, and Shank3 models; adult rescue experiments; and genetic-interaction designs would determine whether ankyrin-B supports dendritic excitability beyond the cortex and whether these genes converge on, rather than merely parallel, dendritic input–output gain. Validation in human subcortical tissue would then establish whether this dendritic scaffolding logic represents a shared point of convergence through which genetically distinct autism spectrum disorder-risk variants alter circuit function. Full article

Pancreatic β-cells maintain glucose homeostasis through tightly regulated insulin biosynthesis, storage, and secretion. To prevent pathological accumulation of excess or aging secretory granules (SGs), β-cells use crinophagy, a selective lysosomal degradation pathway in which mature insulin-containing granules fuse directly with lysosomes to form hybrid organelles termed crinosomes. Crinophagy was historically considered a simple mechanism for discarding obsolete, aged SGs. The acidic, protease-rich environment of crinosomes is proposed to generate unconventional insulin-derived epitopes through cathepsin-mediated proteolysis and transpeptidation reactions. These cryptic epitopes, which include hybrid insulin peptides (HIPs) resulting from the covalent fusion of insulin fragments with peptides from co-resident granule proteins, are largely absent from the thymic epitope repertoire. This creates a “peripheral–thymic mismatch” that allows autoreactive CD4+ T cells to escape central tolerance, ultimately driving β-cell destruction in type 1 diabetes (T1D). Recent studies demonstrate that pharmacological or genetic inhibition of crinophagy reduces crinosome abundance, narrows the pathogenic epitope repertoire, and delays the onset of diabetes in preclinical models. In type 2 diabetes (T2D), a related pathway termed stress-induced nascent granule degradation (SINGD) diverts newly synthesized insulin granules to lysosomes under glucolipotoxic conditions, contributing to insulin depletion and progressive β-cell failure. This review summarizes the current understanding of the molecular mechanisms behind crinophagy. It discusses its two main functions: maintaining physiological quality control and generating pathological antigens. Additionally, the review explores how crinophagy interacts with other cellular stress pathways and highlights new therapeutic strategies aimed at targeting this process to protect pancreatic β-cell function and potentially prevent or delay diabetes. Full article

Prostate cancer (PCa) is one of the most common causes of cancer-related mortality in men globally. Although current therapies can control early-stage disease, advanced PCa remains difficult to treat because of therapeutic resistance and adverse side effects, highlighting the need for new treatment strategies. Syzygium nervosum (SN), a medicinal plant rich in bioactive compounds such as gallic acid and ellagic acid, has demonstrated anticancer properties in several malignancies; however, its effects on PCa remain unclear. This study investigated the anticancer potential of SN using integrated computational and in vitro approaches. DU145 and PC-3 prostate cancer cells were treated with SN extract at concentrations of 25–400 µg/mL for 24 and 48 h. Cell viability, colony formation, and cell-cycle progression were evaluated to determine antiproliferative activity. In parallel, computational analyses were performed to predict molecular targets of SN-derived compounds. Our results displayed that SN extract reduced cell viability, suppressed clonogenic growth, and disrupted cell-cycle progression in both cell lines. Computational findings suggested that gallic and ellagic acids may interact with key regulatory proteins related to cell proliferation and survival, including AKT and CDK2. Overall, SN demonstrates promising anticancer activity and may represent a potential therapeutic source for prostate cancer treatment. Full article

Triple negative breast cancer (TNBC) is an aggressive and heterogeneous subtype of breast cancer characterized by the absence of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), resulting in limited options for targeted therapy and high rates of metastasis, recurrence and death. Extracellular vesicles (EVs) have emerged as central mediators of TNBC pathophysiology, functioning as key intercellular communication vehicles transporting oncogenic proteins, nucleic acids; lipids, and metabolites. These EV-mediated interactions promote tumor microenvironment (TME) remodeling, immune evasion, metastatic niche formation, and therapeutic resistance. Given their stability, accessibility, and molecular complexity, EVs also represent promising diagnostic and prognostic biomarkers for TNBC. Advances in isolation and molecular profiling technologies have enabled the identification of EV-associated signatures that predict therapeutic response and stratify patient risk. Beyond their utility as biomarkers, EVs are rapidly emerging as therapeutic targets and delivery platforms, demonstrating efficacy in transporting chemotherapeutics, RNA-based therapeutics, immune modulators, and photosensitizers with enhanced targeting specificity and therapeutic efficiency. Collectively, EVs play a multifaceted role in TNBC biology, serving simultaneously as drivers of disease progression, minimally invasive biomarkers, and versatile therapeutic vehicles. The integration of EV-centered diagnostics, multi-omic profiling, and engineered therapeutics holds significant potential to transform TNBC management and advance precision oncology for this challenging breast cancer subtype. Full article

Protea venus, a hybrid of Protea repens and Protea aristata, is a commonly found flower in the South African market. To date, there are no reported chemical or biological studies on this hybrid. This study presents the first investigation of the chemical composition and preliminary biological activity of the methanolic extract of P. venus. Phytochemical analysis of the methanolic extract led to the isolation of nine known phenolic compounds (2–10) and one new compound, p-coumaroyl calleryanin (1). The identified known constituents include calleryanin derivatives (2–4), lacticolorin (5), quercetin derivatives (6–8), protocatechuic acid (9), and p-hydroxybenzoic acid (10). Notably, calleryanin (2), protocatechuoyl calleryanin (3), kaempferol-3-O-rhamnoside (6), and quercetin-3-O-rhamnoside (7) are reported for the first time in the genus Protea. Compounds 3 and 9 exhibited strong antioxidant activity in the ferric reducing antioxidant power (FRAP) assay, with 9 exceeding vitamin C. Molecular docking studies suggest that the isolated compounds may interact with Kelch-like ECH-associated protein 1 (KEAP1). In H9c2 cardiomyocytes exposed to high glucose (40 mM) and palmitate (0.15 mM), the extract and compound 6 were non-cytotoxic (≤100 µg/mL) and produced a moderate restoration of ATP levels under glucolipotoxic conditions. These findings expand the phytochemical profile of P. venus and provide preliminary insight into its biological activity under metabolic stress. Full article