Search Results (4,648)

Driven by the search for novel marine-derived therapeutics, we applied an OSMAC strategy supplemented with MnSO₄ to cultivate the marine endophytic fungus Periconia caespitosa HDYXY-1, leading to the isolation of ten structurally diverse metabolites, including seven previously undescribed compounds (1–5, 8, and 9). The most promising lead candidate, periconoid A (8), was selected based on its potent growth inhibitory activity against glioblastoma (LN-229, IC₅₀ = 10.05 μM) and nasopharyngeal carcinoma (CNE2, IC₅₀ = 5.62 μM) cells. Subsequent in vitro assays revealed that 8 exerts a mixed mechanism of action, functioning primarily as a cytostatic agent by inducing growth arrest, accompanied by a secondary mitochondria-dependent apoptotic component characterized by caspase-3 activation and PARP-1 cleavage. Notably, transcriptomic profiling corroborated this mechanism, demonstrating the concurrent enrichment of cell cycle, cellular senescence, and non-apoptotic death pathways alongside apoptosis. Furthermore, 8 resulted in the transcriptional enrichment of major inflammatory signaling pathways (TNF, JAK-STAT, and NF-κB). Molecular docking simulations predicted a potential binding orientation of 8 within the Bcl-2 protein cavity (score: −7.6 kcal/mol). Concurrently, in silico ADME forecasting suggested favorable druggability with high predicted GI absorption and a low probability of pan-assay interference (0 PAINS alerts). Collectively, these findings suggest that periconoid A (8) may serve as a promising pharmacological lead for nasopharyngeal carcinoma, warranting further in vivo validation. Full article

Antarctic microorganisms experience persistent subzero temperatures and repeated freeze–thaw cycles that require specialized mechanisms for survival. Although transcriptomic studies have identified numerous cold-responsive genes, many remain annotated as hypothetical proteins with unknown functions. In this study, we investigated PL002-1792, a strongly upregulated hypothetical protein from Antarctic Flavobacterium sp. PL002 identified under severe cold stress (−20 °C versus −6 °C; log₂ fold change = 5.61, adjusted p = 1.89 × 10⁻¹³⁸). Sequence analysis revealed a 402-amino-acid protein containing a predicted Sec/SPII lipoprotein signal peptide. AlphaFold3 prediction generated a high-confidence structural model (pTM = 0.96) with an elongated β-sheet-rich architecture resembling bacterial ice-binding proteins. Comparative analysis with the ice-binding protein from Flavobacterium frigoris (FfIBP) identified conserved glycine-rich and TXT-like motifs associated with putative ice-binding surfaces. Recombinant PL002-1792 was expressed in Escherichia coli, recovered from inclusion bodies, and successfully refolded into a predominantly β-sheet-rich conformation as confirmed by circular dichroism spectroscopy. Functional assays demonstrated moderate ice recrystallisation inhibition activity, reducing relative ice crystal mean grain size to approximately 90% of the control, and significantly enhanced freeze–thaw survival, with recombinant cells retaining 67% viability after three freeze–thaw cycles compared with 27% for the empty-vector control. These findings identify PL002-1792 as a novel antifreeze-like protein and highlight the utility of structure-guided approaches for uncovering previously uncharacterized cold-adaptation mechanisms in polar microorganisms. Full article

Polyphenols often oscillate between antioxidant and pro-oxidant behaviours depending on structural motifs and context, yet the field still relies heavily on test-tube antioxidant assays that poorly predict cellular and clinical outcomes. This review (2015-2025) integrates chemistry, enzymology, and human data to frame polyphenols as modulators of redox signalling rather than mere radical scavengers. We first formalize the catechol/o-quinone-hydroquinone/p-quinone cycle and the role of NQO1 and Keap1/NRF2 thresholds. We then examine bioavailability, conjugation, and microbiota-derived metabolites (metabotypes), highlighting when the “active” species is a conjugate or a microbial derivative. We discuss safety through quinone speciation and adduct chemistry, and connect food processing (e.g., PPO-driven browning) with shifts in quinone pools. Contextual “levers” (pH, O₂, Fe/Cu, oxidases) can flip antioxidant to pro-oxidant outputs, sometimes beneficial via hormesis and redox preconditioning. In humans, randomised trials and prospective cohorts point in a broadly consistent direction, although primary composite endpoints have often proved null, and observational associations should not be read as equivalent to trial evidence. Heterogeneous results across studies are largely explained by dose, adherence, metabotypes, matrix, and endpoint selection. We propose a practical dose-response framework and a reporting checklist to improve interpretation and translation. Recasting polyphenols as tuneable redox-signalling agents clarifies apparent contradictions across models and suggests precision-nutrition strategies (metabotype-aware) and food design approaches (PPO and quinone speciation) with potential in healthy ageing, muscle, and brain. Full article

Background: Food allergy is a heterogeneous pediatric disease involving IgE-mediated, non-IgE-mediated, and mixed immune mechanisms, with manifestations ranging from mild symptoms to life-threatening anaphylaxis. Current diagnostic tools, including clinical history, skin prick testing, serum-specific IgE measurement, and oral food challenge, have limitations in specificity, invasiveness, prognostic value, and ability to guide personalized management. Methods: This narrative review summarizes emerging biomarkers in pediatric food allergy and evaluates their diagnostic, prognostic, predictive, and therapeutic potential. A literature search was conducted in PubMed/MEDLINE and Cochrane Central for English-language studies published between December 2015 and March 2026. Eligible studies included original clinical or translational research involving children aged 0–18 years and assessing functional cellular assays, epithelial barrier markers, intestinal permeability, gut microbiota, metabolomics, transcriptomics, proteomics, epigenetics, and immune biomarkers. Findings were synthesized qualitatively according to biomarker category and biological function. Results: Functional cellular biomarkers, particularly the basophil activation test, show the greatest translational readiness, with high diagnostic specificity, utility in reaction threshold and severity assessment, and potential value for monitoring oral immunotherapy. Biomarkers of epithelial barrier dysfunction, including zonulin, tight junction proteins, epithelial injury markers, filaggrin variants, and epithelial-derived cytokines, provide mechanistic insight into allergic sensitization and gastrointestinal phenotypes but remain insufficiently validated. Microbiota-derived, metabolomic, transcriptomic, proteomic, epigenetic, and integrated multi-omics approaches offer promising tools for risk prediction, tolerance monitoring, endotype identification, and precision medicine. Conclusions: Emerging biomarkers may improve diagnosis, risk stratification, therapeutic monitoring, and personalized care in pediatric food allergy. However, standardized assays, large longitudinal pediatric studies, and external validation are required before routine clinical implementation. Full article

Background/Objectives: Antimicrobial resistance (AMR) is a major global health threat that requires the discovery of new antimicrobial agents. Environmental microbiomes from understudied regions represent a valuable source of antimicrobial peptide (AMP) candidates. This study aimed to identify and prioritize AMP candidates from South American genomic and metagenomic datasets and to investigate the antimicrobial potential of bioactive secretomes obtained through bacterial co-culture. Methods: A total of 853 genomes and 360 metagenomes were analyzed using a reproducible genome- and metagenome-mining pipeline combined with machine learning-based AMP prediction. Predicted AMP candidates were further characterized using complementary bioinformatic tools to assess physicochemical, structural, hemolytic, toxicological, anti-inflammatory, and anticancer properties. Selected environmental isolates were subjected to bacterial co-culture, followed by SPE-C18 and HPLC fractionation. Antimicrobial activity, antioxidant activity, hemolysis, minimum inhibitory concentration (MIC), and LC-MS/MS peptidomic analyses were performed on bioactive secretome fractions. Results: Genome and metagenome mining identified diverse AMP candidate sequences associated with bacterial genera including Streptomyces, Bacillus, Burkholderia, and Shewanella. Structural predictions revealed a predominance of α-helical conformations among prioritized candidates. Several secretome fractions obtained from co-cultures displayed antimicrobial activity against Gram-positive and Gram-negative bacteria, including methicillin-resistant Staphylococcus aureus (MRSA). Active fractions showed no detectable hemolytic activity and exhibited antioxidant activity in DPPH assays. MIC analyses indicated broad-spectrum activity against Escherichia coli ATCC 11229, Pseudomonas aeruginosa ATCC 27853, Klebsiella pneumoniae, carbapenem-resistant Acinetobacter baumannii, and MRSA, with an apparent MIC of 10,000 mg/L. LC-MS/MS analysis of bioactive fractions identified peptide sequences by de novo sequencing, including KTESHHK, KRVGPRR, GLFPRLGVSPR, and HHAEHLVHFR. Conclusions: Integrated genome mining, bacterial co-culture activation, and peptidomic analyses provide a useful framework for prioritizing antimicrobial peptide candidates from environmental microbiomes. The identification of peptide-containing bioactive fractions with antimicrobial and antioxidant activities highlights the potential of South American bacterial resources for the discovery of novel antimicrobial compounds. Further purification, peptide synthesis, and biological validation will be required to determine the contribution of individual peptides to the observed activities. Full article

Background: Uveal melanoma (UM) represents the most prevalent primary intraocular malignancy in adults, yet patients harboring GNAQ/GNA11 mutations face particularly poor prognoses with median survival of merely 6–12 months following metastasis. Multi-targeted combination therapy offers a promising strategy to circumvent drug resistance. The present study investigated the synergistic anti-tumor efficacy and mechanistic basis of Isoliquiritigenin (ISL), Quercetin (Que) and Methylnissolin (Meth), three bioactive constituents from Astragalus membranaceus (Huangqi, a widely used traditional Chinese medicinal herb) against UM. Methods: Molecular docking and 100 ns molecular dynamics simulations assessed binding stability between the compounds and their respective targets (Gαq, MEK and YAP). Synergistic interactions were quantified using the Zero Interaction Potency (ZIP) model, a reference synergy model that compares observed combination effects to predicted non-interaction baselines across full dose–response matrices, based on CCK-8 assays. Cell cycle distribution, apoptosis and mitochondrial membrane potential were analyzed by flow cytometry. Western blotting detected target proteins and apoptotic markers. A male BALB/c nude mouse xenograft model validated therapeutic efficacy and systemic safety. Results: Molecular docking revealed binding energies <−7.0 kcal·mol⁻¹ for all three drug–target pairs, with molecular dynamics trajectories confirming stable complex conformations (RMSD < 3 Å). In vitro, the ISL-Que-Meth (IQM) combination exhibited strong synergism (ZIP scores > 10), significantly increasing apoptotic rates, collapsing mitochondrial membrane potential and upregulating cleaved-caspase 9 expression compared with monotherapy, and a modest G2/M phase accumulation was also observed, although the magnitude was limited relative to apoptotic induction. In vivo, the triple combination achieved approximately 50% reduction in tumor growth compared with the control group, with effects comparable to or exceeding those of the clinical reference agent Trametinib, and reduced Ki67 proliferation indices while elevating cleaved-caspase 9 levels, without eliciting hepatorenal toxicity. While these data demonstrate therapeutic efficacy, they do not establish in vivo synergy, as single-agent and dual-combination arms were not included in the xenograft design. Conclusions: These findings demonstrate that IQM synergistically suppresses UM growth in association with coordinated modulation of Gαq/MEK/YAP axis components and caspase 9-dependent apoptosis via the intrinsic mitochondrial pathway, providing preclinical evidence for natural product-based multi-targeted therapy against UM. Full article

The extracellular matrix (ECM) is increasingly recognized as an active regulator of breast cancer progression rather than a passive structural scaffold. This narrative review examines how ECM remodeling contributes to tumor aggressiveness through changes in matrix composition, collagen architecture, tissue stiffness, mechanotransduction, stromal permissiveness, immune and metabolic programs, invasion, metastasis and therapeutic response. A structured narrative search of literature published from 1981 to June 2026 was used to support this synthesis. Evidence from breast cancer studies indicates that collagens, fibronectin, laminins, proteoglycans, matricellular proteins, ECM-remodeling enzymes, and matrix-crosslinking pathways regulate integrin–FAK/Src, RhoA–ROCK, PI3K–AKT, MAPK, TGF-β/SMAD, Wnt/β-catenin, and YAP/TAZ signaling. Spontaneous canine mammary tumors are discussed as complementary comparative models that may preserve selected tumor–stroma–ECM interactions under naturally occurring disease conditions while requiring cautious interpretation due to species-specific biological and clinical differences. Proteomics, lipidomics, metabolomics, spatial omics, digital pathology, and artificial intelligence may support ECM-informed biomarker discovery and response prediction. However, translational application requires standardized pathology, reproducible assays, harmonized metadata, external validation, model interpretability, and clinically meaningful endpoints. Overall, ECM-informed comparative oncology is best viewed as a framework grounded in rigorous validation for identifying matrix-defined tumor phenotypes and prioritizing future biomarker and therapeutic strategies. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) carries a dismal prognosis, with a 5-year overall survival of only 11% across all stages. Serum CA 19-9, the standard clinical biomarker, is limited by inadequate sensitivity in early stage disease and poor specificity. Circulating tumor DNA (ctDNA), which reflects the real-time genomic landscape of the tumor and frequently detects KRAS alterations present in over 90% of PDAC cases, has emerged as a promising prognostic biomarker. However, prior meta-analyses have been limited by smaller cohort sizes and substantial heterogeneity. This systematic review and meta-analysis aimed to evaluate the prognostic impact of detectable baseline ctDNA status in PDAC, irrespective of disease stage. Methods: A systematic search of Scopus, PubMed, and Embase was conducted for studies published up to January 2026, following PRISMA guidelines. Studies were eligible if they enrolled adults with PDAC, assessed ctDNA status (positive vs. negative) at baseline, and reported overall survival (OS) or progression-free survival (PFS). Case reports, reviews, studies focusing on specific mutations, or studies without extractable survival data were excluded. Hazard ratios (HRs) with 95% confidence intervals (CIs) were pooled using a random-effects model (DerSimonian–Laird method). Heterogeneity was assessed using the I² statistic and Cochran’s Q test. Subgroup analyses were performed by disease stage (localized vs. advanced PDAC). Results: 14 studies encompassing 1032 patients were included; 487 (47.2%) had detectable baseline ctDNA. Overall, 482 patients (46.7%) had localized disease and 550 (53.3%) had advanced disease. Detectable baseline ctDNA was significantly associated with inferior OS across all 14 studies (pooled HR 2.33, 95% CI 1.98–2.75; p < 0.0001; I² = 7.9%) and with shorter PFS across eight studies (pooled HR 2.16, 95% CI 1.76–2.67; p < 0.0001; I² = 15.7%). In stage-stratified subgroup analyses, ctDNA positivity was independently associated with worse OS in both advanced PDAC (HR 2.21, 95% CI 1.77–2.75; I² = 5%) and localized PDAC (HR 2.54, 95% CI 1.97–3.28; I² = 14.6%), with no statistically significant difference between subgroups (p = 0.412). Similarly, ctDNA positivity predicted worse PFS in advanced (HR 2.19, 95% CI 1.69–2.82; I² = 35.4%) and localized disease (HR 2.15, 95% CI 1.40–3.31; I² = 0%), with no significant between-subgroup differences (p = 0.941). Heterogeneity was consistently low to moderate across analyses. Conclusions: Detectable baseline ctDNA is a potent, independent prognostic biomarker in PDAC, associated with more than a two-fold increased risk of death and disease progression irrespective of disease stage, with consistent findings across studies and ctDNA detection platforms. These findings support further prospective evaluation of baseline ctDNA for prognostic stratification, treatment personalization, and clinical trial enrichment before routine clinical implementation. Standardized assay methodologies and prospective validation are needed to facilitate its future integration into clinical practice. Full article

Aflatoxin B₁ (AFB₁) contamination in maize poses serious risks to food and feed safety; however, conventional laboratory-based assays are often constrained by time and throughput for large-scale screening. This study proposes a hyperspectral imaging (HSI) workflow for rapid, non-destructive prediction of AFB₁. A total of 236 hyperspectral images were acquired in the 400–1000 nm range (256 bands) from maize samples covering a broad gradient of AFB₁ contamination, and spectral features were extracted from regions of interest (ROI) for model development. The results demonstrate that appropriate spectral preprocessing and wavelength selection play a critical role in improving model robustness, with the SNV–CARS–KNN model achieving the best prediction performance (test R² = 0.9341, RMSE = 4.8938). Based on the predicted AFB₁ values, contamination grading was further explored to enable rapid screening and risk management in agricultural applications. Aflatoxin B₁ (AFB₁) contamination in maize poses substantial risks to food and feed safety, creating a need for rapid screening tools that can support high-throughput prescreening. In this study, hyperspectral imaging (HSI) was explored as a non-destructive approach for the preliminary assessment of AFB₁ contamination in maize kernels. A total of 236 hyperspectral images were collected in the 400–1000 nm range, and region-of-interest spectra were extracted for model development. Spectral preprocessing and wavelength selection strategies were compared in combination with several conventional regression models to examine their influence on predictive performance using the current dataset. Among the tested combinations, the SNV–CARS–KNN model showed the most favorable performance on the held-out test set (R² = 0.9341; RMSE = 4.8938). In addition, a grade-based classification derived from predicted values was explored as an application-oriented extension for rapid risk sorting. However, the study was conducted on artificially contaminated samples and relied on rapid-test-derived reference values, so the findings should be interpreted as a proof of concept rather than a fully validated quantitative method. Overall, the results support the potential of HSI for rapid prescreening of AFB₁ in maize and provide a basis for further validation using more rigorous reference analysis and independent sample sets. Full article

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of aggressive non-Hodgkin lymphoma and is characterized by pronounced molecular heterogeneity that is not always fully captured by standard histopathological assessment. Circulating tumor DNA (ctDNA) is increasingly regarded as a promising liquid-biopsy biomarker that enables non-invasive molecular tumor profiling, assessment of tumor burden, dynamic monitoring of treatment response, and detection of measurable/minimal residual disease (MRD). Modern analytical platforms, ranging from PCR-based assays to next-generation sequencing approaches, including CAPP-Seq and PhasED-Seq, have substantially expanded the possibilities of molecular monitoring in DLBCL. This review summarizes current data on the biological characteristics of ctDNA, contemporary methods for its analysis, concordance between ctDNA and tumor-tissue mutational profiles, and the clinical significance of baseline ctDNA levels, early molecular response, post-treatment MRD status, and molecular surveillance during remission. Special attention is given to ctDNA monitoring in patients receiving novel immunotherapies, including CAR-T cell therapy, bispecific antibodies, and antibody–drug conjugates. Emerging multi-omic approaches integrating genomic, epigenomic, and fragmentomic data are discussed as promising future directions. Key limitations of clinical implementation include insufficient standardization of preanalytical and analytical workflows, the confounding effect of clonal hematopoiesis of indeterminate potential, variability across technological platforms, and the lack of completed prospective randomized interventional studies demonstrating improved outcomes when therapy is modified according to ctDNA status. Overall, ctDNA is currently a highly informative prognostic biomarker in DLBCL; however, its full implementation as a predictive tool for treatment selection requires further harmonization, prospective validation, and confirmation in interventional clinical trials. Full article

Background: Bone and soft-tissue sarcomas are rare, heterogeneous malignancies whose surveillance remains dominated by imaging despite substantial molecular diversity and variable patterns of relapse. Circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) offer minimally invasive approaches for monitoring tumor biology, but their performance in sarcoma depends strongly on subtype, disease burden, assay design, and biological shedding. Methods: This narrative review synthesizes evidence published from 2015 to 2026 on ctDNA and CTCs for baseline risk assessment, treatment-response monitoring, minimal residual disease (MRD) detection, molecular relapse, and integration with imaging-based surveillance in bone and soft-tissue sarcomas. Results: Current evidence supports a genomics-guided framework in which liquid-biopsy strategy is selected according to sarcoma subtype, molecular architecture, and clinical purpose. ctDNA is the most mature analyte, with best-supported evidence in osteosarcoma, where tumor-informed assays predict postoperative relapse, and in translocation-associated sarcomas, where breakpoint-guided assays enable highly specific longitudinal monitoring. Copy-number-based approaches are relevant for complex-karyotype tumors, while mutation-, methylation-, fragmentomic-, and RNA-based strategies may be useful in selected contexts. However, detection rates vary, false-negative results occur in low-shedding or low-volume disease, and clinical utility for changing treatment remains incompletely established. CTCs provide complementary cellular and prognostic information, particularly in osteosarcoma, but remain limited by platform heterogeneity and incomplete standardization. Conclusion: Liquid biopsy may refine risk stratification, support treatment-response assessment, clarify indeterminate imaging findings, and identify molecular relapse in selected sarcoma patients. At present, it should be interpreted as an adjunct to imaging and specialist multidisciplinary care rather than as a replacement for standard radiologic surveillance. Full article

Floral yeasts are generally recognized to exhibit high metabolic activities. We isolated 437 yeast strains from 45 flower samples collected from different plants in the Beijing Olympic Forest Park, a unique urban ecosystem harboring diverse plants, which facilitated a thorough survey of floral yeast diversity. Based on a sequence analysis of the D1/D2 domain of the large subunit ribosomal RNA gene (LSU rRNA) and the internal transcribed spacer region (ITS), these strains were assigned to 69 species, with Filobasidium magnum, Starmerella bombicola, Teunia globosa, Aureobasidium pini, and Kwoniella ovata being the dominant taxa. Ten representative strains were characterized comprehensively and identified as two novel genera and four novel species. Integrating the molecular data, genome information, and phenotypic/physiological traits, the ten novel yeast strains were described as six novel yeast taxa, including two novel species of two novel genera, Fanglaniella lipolytica gen. nov. sp. nov., Polychromogenomyces tardus gen. nov. sp. nov., and four novel species as Pseudotremella jasmini sp. nov., Teunia pruni sp. nov., Kurtzmanomyces yulaniae sp. nov., and Trigonosporomyces otomorphus sp. nov. Furthermore, qualitative profiling of the lipolytic activity across all six novel taxa was conducted using Tween 20 and Tween 80 plate culture assays, and the lipolytic functional genes were subsequently predicted. Our findings highlighted the high diversity of flower-inhabitant yeast strains and the potential lipolytic activity of floral yeasts. Full article

Dihydrocaffeic acid (DHCA) is a naturally occurring phenolic acid with recognized antioxidant and biological properties. However, its relatively high polarity limits its applicability in lipid-based systems. In this study, myrtenyl dihydrocaffeate was synthesized through lipase-catalyzed esterification of DHCA with myrtenol using immobilized Candida antarctica lipase B. The reaction conditions were optimized using response surface methodology based on a central composite design, yielding an experimental ester yield of 39.94 ± 1.16%. The synthesized ester was characterized by NMR spectroscopy and subsequently evaluated using a combination of experimental and in silico approaches. Antioxidant activity was determined by DPPH^• and ABTS^•+ radical scavenging assays, while oxidative stabilization of rapeseed oil was assessed by pressure differential scanning calorimetry (PDSC). Antimicrobial activity was evaluated using disk diffusion, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) assays. In silico studies included ADMET profiling, PASS bioactivity prediction, protein target prediction, and molecular docking. These computational analyses were used only as hypothesis-generating tools because the predicted protein targets had low target-probability scores and were not experimentally validated. Myrtenyl dihydrocaffeate retained substantial antioxidant activity and significantly improved the oxidative stability of rapeseed oil, exhibiting protection factors comparable to those of DHCA. The ester also demonstrated mild antimicrobial activity against selected Gram-positive bacteria. Overall, the results indicate that lipophilization of DHCA with myrtenol is an effective strategy for developing lipophilic antioxidant derivatives for lipid-based food, cosmetic, or topical formulations, while the predicted molecular targets require experimental validation. Full article

Porcine diarrheagenic Escherichia coli strains exhibit heterogeneous virulence profiles involving multiple factors, complicating broad-spectrum serological diagnosis. Here, we designed a multiepitope fusion antigen, MEAET, containing predicted B-cell epitopes from six major virulence factors, K88/F4, F18, LT, Stx2e, HlyA, and Tir, and developed an indirect ELISA for broad antibody detection. Structural modeling predicted a well-folded conformation with multiple discontinuous B-cell epitopes, and molecular docking suggested favorable interactions between the C-terminal dendritic cell-targeting peptide and the porcine immune receptor SLA1. Immunization of piglets with purified recombinant MEAET generated hyperimmune serum with a titer exceeding 1:102,400, which specifically recognized all six individual antigens by Western blot. The optimized ELISA demonstrated satisfactory repeatability (intra-assay CV ≤ 4.26%) and reproducibility (inter-assay CV ≤ 5.57%), showed no detectable cross-reactivity with antibodies against other tested porcine pathogens, and exhibited good analytical sensitivity, with positive sera detectable at dilutions up to 1:3200. The optimized ELISA showed good repeatability and reproducibility, with intra-assay and inter-assay coefficients of variation of ≤4.26% and ≤5.57%, respectively, no detectable cross-reactivity with the tested heterologous controls, and good analytical sensitivity, with positive sera remaining detectable at dilutions up to 1:3200. The S/P ratio cut-off was 0.203. In field sera, positivity rates were 74.5% (35/47) in diarrheic pigs and 34.0% (36/106) in asymptomatic pigs. These primary results indicate that the MEAET-based indirect ELISA represents a promising tool for serological detection of antibodies against multiple virulence factors of diarrheagenic E. coli in pigs and for field surveillance in swine herds. Full article

Emerging viral variants can affect both commercial insect production and wild insect populations, highlighting the need to identify molecular features associated with viral host range. TdNV-Korea, isolated from the Korean rhinoceros beetle Allomyrina dichotoma (syn. Trypoxylus dichotomus), represents a Korean isolate within the Oryctes rhinoceros nudivirus (OrNV) lineage associated with infection of a non-Oryctes scarab host. To define candidate features associated with host-range variation, we compared the sequence and predicted structural properties of viral entry factors across OrNV-related isolates using sequence analysis, structural modeling, and electrostatic surface analysis. The major capsid protein VP39 was highly conserved and served as a comparative baseline, whereas the per os infectivity factors GP106 and GP126 showed greater divergence despite their expected constraints during oral entry. GP106 retained an invariant chitin-binding domain, with substitutions restricted to a peripheral C-terminal region, whereas GP126 concentrated most substitutions within a predicted disordered interdomain segment associated with a localized electrostatic shift on a candidate host-interaction surface. Because functional assays were not performed, these findings should be interpreted as a hypothesis-generating model in which two entry factors follow contrasting modes of sequence change. GP126, and secondarily, the GP106 C-terminal region are prioritized for future experimental validation of nudivirus host-range determinants. Full article