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PubMed2026

Identification of aquaporin (AQP) genes in the noble scallop Chlamys nobilis and characterization of their expression under low-temperature stress.

Aquaporins (AQPs) are transmembrane channel proteins essential for water homeostasis and cellular stress responses. In marine bivalves, their roles in cold tolerance remain poorly understood despite frequent winter mortality events in aquaculture. Here, we identified nine AQP genes in the genome of the economically important noble scallop Chlamys nobilis. Phylogenetic analysis revealed strong conservation with other bivalve AQPs, and structural features, including conserved NPA motifs and ar/R selectivity filters, support their canonical water/glycerol transport functions. Tissue-specific expression profiling showed predominant enrichment in osmoregulatory tissues (gills, intestine) and gonads. Under both chronic and acute low-temperature stress from 23 °C to 9 °C, most CnAQP genes exhibited transient upregulation followed by suppression. Notably, CnAQP4 displayed sustained upregulation, implicating it as a key mediator of long-term cold adaptation. Promoter analysis further revealed abundant cis-elements linked to growth and development as well as immune regulation. Our findings provide the first comprehensive characterization of the AQP family in C. nobilis, highlighting its critical role in maintaining cellular integrity during cold stress and offering molecular targets for selective breeding of cold-tolerant scallop strains.

Animals↗

PubMed2026

Urban Design Quality and Clinical Mental Health: A Systematic Review.

ObjectivesThis systematic review synthesizes empirical evidence on core urban design dimensions that affect clinical mental health outcomes and examines how environmental exposures mediate or moderate these relationships.BackgroundUrban design has increasingly been recognized as a determinant of psychological well-being, yet a standardized framework to evaluate its mental health impact remains underdeveloped.MethodsFollowing PRISMA 2020 guidelines, we systematically reviewed 19 quantitative empirical studies published through January 2025, examining relationships between outdoor urban design features and validated clinical mental health indicators across four major databases.ResultsFindings reveal that urban design influences clinical mental health outcomes (depression, anxiety, stress, cognitive decline) through two objective spatial scales: street-level features (imageability, enclosure, human scale, complexity) and neighborhood environments (land use mix, density, green infrastructure). Environmental exposures (traffic, noise, air pollution) operate as perceptual and experiential mechanisms that mediate or moderate the mental health effects of these spatial design features.ConclusionsWe propose an integrated three-domain conceptual framework distinguishing objective spatial design scales from subjective exposure mechanisms. This framework provides evidence-based guidance for urban planners and policymakers toward creating mentally healthier urban environments.

Humans↗

PubMed2026

A review on the environmental distribution, toxic effects, bioaccumulation characteristics and risk assessment of short-chain chlorinated paraffins.

Chlorinated paraffins (CPs) are synthetic chemicals, widely used as flame retardants and plasticizers. As emerging contaminants, short chain chlorinated paraffins (SCCPs) have attracted tremendous attention due to their persistence, chronic toxicity, long-range transport potential and bioaccumulation potential. This review synthesizes global data on SCCPs' environmental occurrence, toxicological impacts, and bioaccumulation characteristics. SCCPs are ubiquitously detected in various environmental media, including water, sediment, air, soil, and biota. Ecotoxicological studies reveal that SCCPs have lethality, carcinogenicity, growth and developmental toxicities, organs toxicities and endocrine-disrupting effects across species, which pose risks to ecological systems and human health. In addition, the bioaccumulation effects of SCCPs in terrestrial and aquatic ecosystems were analyzed, and proposed the key factors affecting the bioaccumulation of SCCPs. Finally, the risk assessment of SCCPs contamination in the surface water and the soil was carried out, and all soil and most water bodies were found to be low risk. The present study could provide scientific basis and reference for environmental management of CPs products.

Paraffin↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗

PubMed2026

Culture of infectious human norovirus isolated from live contaminated oysters.

Human noroviruses are a major cause of foodborne outbreaks worldwide. Filter-feeding shellfish, such as oysters, can bioaccumulate these viruses in their digestive tissue when grown in sewage-impacted coastal areas and are often implicated in norovirus foodborne outbreaks. Despite the high sensitivity of current molecular assays, these methods for norovirus detection in shellfish fail to distinguish between infectious and non-infectious particles. Assessing norovirus infectivity in shellfish remains a challenge due to the lack of suitable isolation methods that maintain capsid integrity. In this study, a protocol for isolating infectious norovirus from oyster tissues, based on chloroform-butanol elution and polyethylene glycol concentration (CB-PEG), was optimized for the recovery of human norovirus GI and GII. While CB-PEG method recovered various norovirus GI and GII genotypes, it was less efficient at the genomic level than a protocol based on proteinase K elution (adapted from ISO 15216) and showed genotype-dependent viral recovery rates. By optimizing the flocculation step, we improved the method's compatibility with human intestinal enteroid (HIE) cultures. Using this approach, we successfully quantified infectious norovirus GII.3 titers recovered from artificially-contaminated live oysters. Interestingly, infectious virus was better isolated following a freezing step of the digestive tissues, with titers ranging from 13 to 40 TCID50/mL for positive samples. In conclusion, this study established an optimized methodological approach for the relative quantification of infectious norovirus GII.3 in shellfish, paving the way for future research on viral persistence and inactivation strategies in this foodstuff.

Norovirus↗

PubMed2026

Non-linear predictive modeling and comprehensive meta-analysis of rectal temperature in Santa Inês sheep: a systematic review of thermal challenges and biometerological trends.

A systematic and bibliometric review, combined with a meta-analysis, was used to adjust an equation for estimating the physiological responses of Santa Inês sheep subjected to different thermal challenges. The systematic review compiled data on physiological responses and the thermal environment, which were then used in the meta-analysis to adjust regression models. The bibliometric analysis mapped the relationships among studies, highlighting their usefulness in interpreting research findings and biases. Addressing prior methodological critiques, the core of this study involves replacing the linear approach with a non-linear segmented regression model to accurately define the Thermal Neutral Zone (TNZ). The Segmented Regression Model was crucial, establishing the upper limit of the Thermal Neutral Zone (TNZ) at an air temperature (tair) of 34.64 °C, where trectal begins to increase abruptly. The model, while identifying a biologically significant breakpoint, exhibited a moderate Multiple R-squared of 0.3529, highlighting the high heterogeneity and methodological variability in the current Santa Inês literature. This non-linear approach offers a biologically superior tool for identifying the onset of thermal distress.

Animals↗

PubMed2026

Accurate quantification of canine mitochondrial DNA copy number from canine blood and brain samples.

Acute brain injury is difficult to evaluate in veterinary medicine and tools to investigate the potential involvement of mitochondrial involvement are limited. The brain is highly enriched in mitochondria and contains thousands of copies of mitochondrial DNA (mtDNA) per cell, but robust methods for quantifying mitochondrial DNA copy number (mtDNA-CN) in canine tissues are lacking. We describe the development of a quantitative real-time PCR assay for absolute measurement of mtDNA-CN which was validated in canine blood and brain tissue. To minimize amplification of nuclear mitochondrial insertion sequences (NumtS) and repetitive regions, species-specific oligonucleotide primers were designed following in silico genomic filtering. The assay was applied to a small pilot cohort comprising blood samples from dogs with and without acute brain injury (n = 4-6 per group) and cerebral cortex samples (n = 1 per group) to assess feasibility and biological plausibility. In non-brain injury dogs, blood mtDNA-CN ranged from 98 to 288 copies per nuclear genome (mean 193 ± 72), while values in brain-injured cases ranged from 163 to 228 copies per genome (mean 200 ± 33). Cerebral cortex samples exhibited higher mtDNA-CN than blood, consistent with known tissue-specific mitochondrial enrichment. In a single brain-injured case with serial sampling, mtDNA-CN increased over five days. This study presents a validated assay and pilot data for mtDNA-CN quantification in canine samples. While not powered for biomarker evaluation, this method may enable future studies of mitochondrial dynamics in canine brain injury and metabolic disease.

Animals↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one‑carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals↗

PubMed2026

Antennal transcriptome analysis of chemosensory proteins in the raspberry weevil, Aegorhinus superciliosus (Coleoptera: Curculionidae).

Aegorhinus superciliosus (Coleoptera: Curculionidae) is a polyphagous pest of economic importance in southern Chile, the chemical ecology of which remains poorly characterized. Across insect species, chemosensory proteins, including odorant receptors (ORs), gustatory receptors (GRs), ionotropic receptors (IRs), odorant-binding proteins (OBPs), chemosensory proteins (CSPs), and sensory neuron membrane proteins (SNMPs), mediate the detection of chemical cues involved in host selection, reproduction, and other ecologically relevant behaviors. In this study, the antennal transcriptome of adult A. superciliosus was sequenced and analyzed using a de novo RNA-seq approach. Three independent biological replicates per sex were used for RNA-seq, and the same number of independent biological replicates was used for RT-qPCR validation; sequencing yielded 147,409,936 high-quality reads after quality filtering. A total of 112 candidate chemosensory genes were identified, comprising 43 ORs, 34 OBPs, 10 CSPs, 18 IRs, 5 GRs, and 2 SNMPs. Phylogenetic analyses assigned these candidate proteins to established clades, providing a comparative framework for functional inference for ORs and OBPs. Sex- and tissue-biased expression analyses revealed that several ORs, including AsupOR4, AsupOR19, and AsupOBP13, exhibit antennal enrichment and sex-specific expression patterns. Notably, AsupOR19 and AsupOBP13 displayed strong female-biased expression. In addition, transcripts of selected ORs and OBPs were detected in non-antennal tissues, such as the rostrum and legs, suggesting potential functional versatility beyond canonical olfaction. Together, these findings represent the first molecular identification of the chemosensory repertoire of A. superciliosus. This study establishes a foundation for reverse chemical ecology approaches aimed at identifying behaviorally active volatile organic compounds (VOCs) toward environmentally sustainable strategies for integrated pest management.

Animals↗

PubMed2026

Multi-omics reveal microbial functional traits and antifungal metabolites associated with lower Pseudogymnoascus destructans loads in bat cave soils.

White-nose syndrome, caused by Pseudogymnoascus destructans (Pd), is a major fungal disease threatening hibernating bats. Cave soils can serve as environmental reservoirs for Pd, yet the microbial and biochemical mechanisms underlying naturally low Pd burdens in some cave environments remain poorly understood. Here, we integrated soil microbiome profiling, metagenomics, metabolomics, multi-omics network analysis, and in vitro validation to investigate the ecological and functional basis of differential Pd loads in hibernating bat caves in Northeast China. The three caves shared cold, humid, and weakly acidic microenvironments, but differed significantly in electrical conductivity, soil water content, nutrient availability, and extracellular enzyme activities. Soil microbial communities showed significant inter-cave variation in composition, diversity, and niche breadth, with stochastic processes contributing substantially to community assembly. Environmental variables, particularly pH and Pd load, were important predictors of microbial community structure. Functional analyses revealed that the low-Pd Gezi Cave was enriched in genes associated with organic carbon degradation, nitrogen input and retention, and secondary metabolism. Metabolomic profiling further identified cave-specific metabolite signatures, among which Biochanin A, 4-Hydroxybenzaldehyde, Vanillin, and Arachidonic acid were negatively correlated with Pd loads. Integrated pathway and network analyses showed that differential genes and metabolites jointly mapped to secondary metabolite biosynthesis, aminobenzoate degradation, and flavonoid degradation pathways, forming a microbe-metabolite-functional gene coupling network involving key taxa such as Rhodococcus, Pseudorhodoplanes, and Rhodoplanes. In vitro assays confirmed that 4-Hydroxybenzaldehyde, Coumarin, and Vanillin inhibited Pd growth. Structural equation modelling further indicated that environmental heterogeneity was associated with variation in Pd loads through microbial functional attributes and metabolite profiles. These findings suggest that naturally low-Pd cave soils are associated with coordinated environmental filtering, microbial functional specialization, and antifungal metabolite production, providing mechanistic insight into microbial and biochemical constraints on Pd persistence in cave reservoirs.

Animals↗

PubMed2026

Early hepatic protein responses to dietary restriction-refeeding in Japanese quail: A proteomic investigation.

Feed intake and refeeding after nutrient scarcity induce rapid metabolic adaptations in the poultry liver; however, hepatic proteomic recovery pathways in the early hours post-refeeding remain poorly defined. This study aimed to characterize early liver protein signatures in Japanese quail (Coturnix japonica) recovering from nutritional stress under two refeeding conditions. Eighteen 12-week-old male quails (245.20 ± 0.213 g) were assigned to three groups (n = 6): control fed ad libitum (12.13 MJ/kg), 24 h feed deprivation followed by 6 h refeeding, and 24 h low metabolizable energy (6.30 MJ/kg) diet followed by 6 h refeeding. In total, 854 proteins were identified, of which 515 met the filtering criteria. The low metabolizable energy refeeding showed higher abundance of proteins linked to ATP binding and carbohydrate/carboxylic acid metabolism, alongside detoxification-related proteins, while suppressing translation/RNA-binding machinery and antioxidant pathways. Feed-deprived refeeding enriched in oxidative phosphorylation and mitochondrial complex I assembly with reduced cytoplasmic translation, NMD-related components, and sulfur compound metabolism. A direct comparison indicated divergent recovery strategies: low metabolizable energy refeeding mainly reflected oxidoreductase activity and translation initiation, whereas feed-deprived refeeding potentially enriched mitochondrial ATP production and glutathione-based defenses. Our analysis indicate that 6 h of refeeding initiates an early, incomplete recovery toward hepatic homeostasis, with the severity of prior nutritional restriction dictating distinct liver metabolic priorities. Collectively, these findings might provide a preliminary understanding of the hepatic mechanisms involved in recovery from nutrient deprivation and may help in the development of feeding strategies for managing metabolic recovery in poultry. However, these findings should be considered hypothesis-generating pending further validation.

Animals↗

PubMed2026

Climate and soil shape Daqu wheat quality and seed microbiome via rhizosphere taxa and microbial assembly.

The grain quality and seed microbiome of Daqu wheat are fundamental determinants of Daqu fermentation performance; however, the mechanisms by which cultivation environments influence these traits via rhizosphere microbial communities remain unclear. Bacterial and fungal communities across the bulk soil-rhizosphere-seed continuum of three wheat cultivars grown in four ecoregions were characterized using absolute quantitative amplicon sequencing. The rhizosphere microbiome was treated as a central intermediary, while the response variables were seed microbial diversity and grain-quality traits, including starch content, protein content, and grain hardness. Twelve physicochemical properties of soil and 11 climatic factors were integrated into a multidimensional association framework. Environmental conditions exerted stronger influences on both seed quality traits and microbial diversity than cultivar identity. Distinct regional signatures were also evident in rhizosphere microbiomes, with environmental gradients explaining community variation more effectively than geographic distance. Bacterial communities exhibited greater sensitivity to environmental fluctuations than fungi. Mantel analyses identified available nitrogen, precipitation, and atmospheric pressure as significant drivers of core rhizosphere taxa (P < 0.05). iCAMP revealed that stochastic processes predominantly governed rhizosphere bacterial assembly, whereas stochastic and deterministic mechanisms jointly shaped fungal assembly. Partial least squares path modeling further uncovered a rhizosphere-mediated environment-seed cascade, wherein sunlight intensity and duration, atmospheric pressure, and soil nitrogen directly or indirectly affected seed wet gluten content, grain hardness, and seed microbial diversity through their influences on rhizosphere microbiota. Rhizosphere bacterial diversity was negatively associated with seed bacterial diversity (path coefficient = -0.118, P < 0.05), indicating that rhizosphere communities may shape seed endophytic bacterial assemblages via environmental filtering and competitive interactions. Collectively, these findings elucidate how environments shape the quality and seed microbiomes of Daqu wheat, providing scientific guidance for optimal site selection and the standardized production of high-quality brewing wheat for industrial Baijiu.

Triticum↗

PubMed2026

Physical reconfiguration of limb electrodes for Precordial Bipolar Lead acquisition: Morphological validation against digital subtraction.

BACKGROUND: The V2 - V1 Precordial Bipolar Lead (PBL) selectively evaluates the right-to-left retrosternal axis and has shown diagnostic value beyond the standard 12‑lead electrocardiogram. However, its use has been limited by the need for raw electrocardiographic data and post-processing software. This study evaluated whether a simple physical reconfiguration of limb electrodes could reproduce the digitally derived V2 - V1 morphology with sufficient accuracy for clinical application. METHODS: Thirty-seven subjects underwent two sequential 10-s 12‑lead recordings using a Cardiovit FT-1 electrocardiograph sampled at 1000 Hz. In the standard recording, the digital PBL was calculated as V2 - V1. In the second recording, the right-arm and left-arm electrodes were repositioned to the V1 and V2 sites so that Lead I directly recorded the retrosternal dipole. Signals were filtered, synchronized, and analyzed using median beats. Morphological agreement was assessed with Pearson correlation on Z-normalized signals, while absolute agreement was evaluated using Lin's concordance correlation coefficient (CCC), intraclass correlation coefficient (ICC (Lewis, 1931; Nehb, 1938 [1,2])), root mean square error (RMSE), and Bland-Altman analysis. RESULTS: Mean Pearson correlation between digital and physical PBL was 0.955 (SD 0.043), with segment-specific correlations of 0.953 (SD 0.054) for QRS and 0.967 (SD 0.052) for ST-T. Lin's CCC and ICC(2,1) were both 0.871 (SD 0.110), and RMSE was 0.091 (SD 0.049) mV. Bland-Altman analysis showed minimal bias (-0.008 mV). CONCLUSIONS: Physical acquisition of the V2 - V1 PBL achieved high agreement with the digitally derived signal, supporting a simplified analog method for broader clinical implementation.

Humans↗

PubMed2026

Systematic multi-domain screening of lead-specific electrocardiographic features associated with sudden cardiac death.

UNLABELLED: Electrocardiogram (ECG) provides four-dimensional view to the electrical properties of the heart. We performed a comprehensive multi-domain screening to find the most significant lead-specific ECG features associated with sudden cardiac death (SCD). METHODS: We analyzed retrospective data from 21,176 consecutive patients undergoing coronary angiography in Tampere University Hospital between 2007 and 2018. 937 ECG variables provided by the 12SL algorithm were used for the analysis. From those, the significant lead-specific ECG variables were categorized into three subgroups: P-wave, QRS complex, and ST-segment/T-wave. The most significant (i.e., lowest P-value) independent lead-specific ECG variables were tested in multivariate analysis after filtering correlating variables with weaker associations with SCD. RESULTS: Among ventricular depolarization (QRS complex) variables, the strongest associations with SCD were observed for QRS intrinsicoid deflection (lead I) (p = 4.6 × 10-8), QRS peak-to-peak amplitude (lead aVR) (p = 1.9 × 10-5), and Q-wave amplitude (lead V1) (p = 7.6 × 10-6). Among repolarization (ST-segment and T-wave) variables, the strongest predictors of SCD were T-wave amplitude (lead aVR) (p = 3.5 × 10-7) and ST-segment end amplitude (lead aVL) (p = 8.1 × 10-5). The strongest associations with SCD among atrial depolarization (P-wave) variables were P-wave onset amplitude (lead V6) (p = 3.1 × 10-6), P'-wave amplitude (lead V2) (p = 2.1 × 10-5), and P-wave duration (lead V2) (p = 2.4 × 10-3). These variables remained significant in multivariate analysis alongside global ECG variables (e.g., heart rate, QRS duration, and LVH). CONCLUSION: Systematic screening and utilizing the full prognostic potential of the 12‑lead ECG reveal several key elements of the electrical properties of the heart that associate with SCD.

Humans↗

PubMed2026

Comparison of paralog identification methods and their impact on species tree topologies in target capture phylogenomics within the Sindora clade (Detarioideae: Leguminosae).

Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because their evolutionary history may differ from the divergence history of species. Here, we use as a case study a target enrichment dataset of 88 species of Detarioideae (Leguminosae) with a focus on the Sindora clade to examine approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, plus subsequent steps using Putative Paralog Detection and the tree-based Yang & Smith orthology inference approach. We compare the paralogs flagged using these methods and verify their performance with BLAST mapping against a reference genome sequence of Sindora glabra, and then subsequently compare the species tree topologies produced across these methods. Our comparisons of paralogs flagged across the Sindora clade show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs in terms of its similarity to the BLAST mapping, followed by the built-in paralog identification function of CAPTUS. However, the results we recovered for the Detarioideae subfamily suggest that the largest differences in species tree topology resulted from the use of paralog-filtered alignments (such as with the Putative Paralog Detection pipeline and the Yang & Smith orthology inference approaches) rather than just by removing the sequences of identified paralogous genes. This was the true for HybPiper-assembled datasets but was not seen in CAPTUS-assembled datasets. In all comparisons, the topological differences caused by different paralog handling methods tended to be confined to clades where processes such as hybridisation and introgression are prevalent. Our study provides a roadmap to establish the best approach to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for a study group, and highlights the importance of careful data inspection and processing in addition to understanding the extent of paralogy and paralog characteristics (e.g. sequence divergence between copies) for their study group.

Phylogeny↗

PubMed2026

The association between prenatal PM2.5 constituent exposure and gestational diabetes mellitus: Exploratory analysis of the potential modifying role of thyroid hormones.

The associations of PM2.5 constituents with blood glucose and GDM remain unclear, and the interplay between PM2.5 exposure and thyroid hormone levels in relation to GDM has not been well characterized. This retrospective cohort study included 1314 pregnant women with data collected through multiple methods. A generalized linear model analyzed PM2.5-glucose links, logistic regression assessed pollutant-GDM associations, and stratified analyses explored these relationships at different thyroid hormone levels. In the study population, first-trimester exposure to SO42- and BC correlated positively with FBG, as did PM2.5 and its components in the second trimester. First-trimester SO4²⁻ exposure (OR=1.26, 95% CI: 1.06, 1.51) and second-trimester exposures to PM2.5 (OR=1.67, 95% CI: 1.19, 2.35), NO3⁻ (OR=1.34, 95% CI: 1.06, 1.68), and NH4⁺ (OR=1.33, 95% CI: 1.06, 1.65) were associated with increased GDM risk. Stratified analyses showed that second-trimester BC and OM were positively correlated with FBG in the high-TSH and low-FT4 strata, respectively. In addition, first-trimester exposure to SO42- (high TSH: OR = 1.42, 95% CI: 1.10, 1.84; low FT4: OR = 1.35, 95% CI: 1.05, 1.74) and to PM2.5 (high TSH: OR = 1.93, 95% CI: 1.14, 3.27; low FT4: OR = 1.82, 95% CI: 1.46, 2.25) in the second trimester were associated with higher odds of GDM. These findings show that PM2.5 exposure was associated with glucose dysregulation and GDM in pregnant women differently by trimester and component. Across the separate TSH- and FT4-stratified analyses, women in the high-TSH and low-FT4 strata, respectively, appeared to show greater susceptibility to air pollution-related GDM. These subgroup findings should therefore be interpreted as exploratory and require validation in future studies.

Effect modification↗