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In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5 kcal/mol, Wogonin (-9.3 kcal/mol) and Xanthohumol (-8.1 kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans

Microbial allies in a cotton pest: A descriptive account of associated microbiota dynamics in Dysdercus cingulatus across development.

BACKGROUND: Hemipteran insects harbour several symbiotic partners, mainly bacteria, which play pivotal roles for hosts like dietary provision, support overall physiology, xenobiotic degradation and manipulate/regulate behaviour. Most of these symbionts usually reside and operate from the digestive tracts of the animals. Cotton is one of the major cash crops in India and Dysdercus cingulatus (D. cingulatus) though a secondary pest, is causing significant destruction of cotton bolls, poor lint quality and reduce oil content of seeds. Premature opening of cotton bolls often leads to bacterial and fungal infections, thus resulting in extensive economic loss worldwide. D. cingulatus is a hemimetabolous insect that comprises of developmental stages like egg, nymph (5 instar stages), and adult. The present work explored the ontogeny specific diversity in the associated microbiota and predicted their probable functional inputs in D. cingulatus. RESULTS: The data obtained using 16S rRNA gene sequencing (NovaSeq 6000) revealed presence of members of Proteobacteria (65.83%), Firmicutes (24%), Actinobacteria (10%) phyla throughout the ontogeny of D. cingulatus. Highest alpha diversity of these symbiotic bacteria was recorded in the third instar nymphs in contrast to rest of the developmental stages. Among all the observed genera, Stenotrophomonas, Hungatella and Glutamicibacter were predominant from egg to adult stages. MicFunPred, a tool used for predicting the probable functional inputs of these symbionts, hinted at their probable stage specific contribution in crucial biochemical pathways such as polyketide biosynthesis, ascorbate/aldarate metabolism, pentose phosphate and glyoxylate cycles, steroid hormone and peptidoglycan biosynthesis, and glycolysis/pyruvate metabolism. CONCLUSIONS: The primary investigations on the ontogenetic composition and diversity of associated microbiota, suggest dynamic shifts in D. cingulatus, concurrent with their probable functions/roles in the host development and metabolism. To the best of our knowledge, this is the first report on symbiotic microbiota variation across the developmental stages of D. cingulatus that provides preliminary descriptive observations that may guide future functional and experimental investigations into microbiota-based pest management.

Animals

Cross-kingdom dynamics of the subgingival bacteriome and mycobiome: A pilot study on the effects of a novel HA-H₂O₂-Glycine formulation to treat periodontitis.

OBJECTIVES: Traditional periodontal therapy primarily focuses on bacterial biofilm control; however, recent evidence also suggests a critical role for the oral mycobiome. This study evaluated the clinical and ecological impact of a novel mouthwash formulation containing hyaluronic acid (HA), hydrogen peroxide (H2O2), and glycine on periodontal patients METHODS: This prospective, randomized split-mouth trial included 13 adult participants with periodontitis treated with HA-H2O2-glycine formula (BMG0703A) used twice a day for seven days. Subgingival plaque samples were collected from periodontal pocket and healthy control sites at baseline (T0) and one-week post-treatment (T1). Microbial and fungal communities were characterized using Next-Generation Sequencing (NGS) of the 16S rRNA and ITS2 regions. Linear Mixed Models (LMM) and Spearman correlation were used to assess taxonomic shifts and cross-kingdom relationships. RESULTS: Sequencing revealed a promising ecological shift: the bacteriome shifted from anaerobic dominance (Olsenella, Peptostreptococcus) toward a health-associated aerobic profile, with Rothia near-doubling (11.91% to 22.68%). The mycobiome underwent a "normalization" effect: Candida abundance decreased significantly (22.8% to 9.1%), while fungal Shannon diversity in pockets returned to healthy-site levels. Inter-kingdom analysis identified antagonistic relationships between expanding commensal bacteria and opportunistic fungi, suggesting that the intervention may help re-establish a protective bacterial niche. CONCLUSIONS: The HA-H2O2-glycine formulation seems to facilitate a rapid, cross-kingdom modulation of the subgingival niche. By reducing anaerobic pathogens and normalizing the mycobiome it appear to induce short-term changes, suggesting potential as adjunctive strategy in periodontal management. CLINICAL SIGNIFICANCE: The present work underlines the possible cross-Kingdom effects of a novel compound.

Humans

Cerebellar iTBS enhances gait adaptation by modulating cortical sensorimotor network dynamics: a randomized controlled trial.

Gait adaptation enables individuals to maintain locomotor stability under persistent perturbations. Although the cerebellum is critical for sensory prediction error-based (SPE) adaptation, how cerebellar neuromodulation reshapes cortical sensorimotor networks to enhance gait adaptation remains unclear. This study investigated the behavioral effects and underlying cortical neurodynamic mechanisms of cerebellar intermittent theta-burst stimulation (iTBS) on gait adaptation. Thirty-two healthy adults received either active or sham cerebellar iTBS. Participants performed a split-belt treadmill adaptation task before and after intervention. Cortical responsiveness was evaluated using TMS-evoked EEG over primary motor cortex (M1), while resting-state EEG was analyzed to assess spectral power and directional functional connectivity. Compared to sham, cerebellar iTBS significantly enhanced gait adaptation, evidenced by a faster adaptation rate (p = 0.035) and enhanced Early Adaptation SLS (p = 0.011), without altering initial perturbation responses or post-adaptation outcomes. The iTBS increased TMS-evoked α (p = 0.031) and γ (p = 0.022) power in M1, while the α power was correlated with faster adaptation (r = 0.526, p = 0.002). Furthermore, iTBS strengthened PPC-to-M1 directed connectivity in the β (p = 0.025) and γ (p = 0.013) bands. Enhanced parieto-motor directionality were positively associated with adaptation rate (β: r = 0.515, p = 0.003; γ: r = 0.463, p = 0.009). These findings suggest that cerebellar iTBS facilitates gait adaptation by modulating cortical responsiveness and directional sensorimotor network connectivity, providing multi-level neurodynamic evidence for the cerebello-cortical modulation during gait adaptation and offering a strong physiological rationale for targeted neuromodulation in gait rehabilitation strategies.

Humans

Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics

The Acute Effects of Blood Flow Restriction on Ankle Muscle Reaction Time and Proprioception in Healthy Individuals.

Blood flow restriction (BFR) induces hypoxic and metabolic stress, which may alter afferent feedback and neuromuscular control. However, its acute effects on ankle sensorimotor function remain unclear. The aim of the study was to investigate the acute effects of lower-limb BFR on multidimensional ankle sensorimotor function in healthy adults. Twenty-four participants (12 females, 12 males) completed two conditions in randomized order and a crossover design: BFR at 60% arterial occlusion pressure (AOP) and a control condition (20 mmHg). All measurements were performed during occlusion. Outcomes included joint position sense (active and passive), kinesthesia, static and dynamic balance, lower-limb muscle activation (surface electromyography), and muscle reaction time during sudden ankle inversion. BFR impaired active joint position sense at 20 degrees of inversion (p = 0.011), with no changes at other angles or in kinesthesia. Static balance deteriorated, with increases in sway area (p = 0.017), sway distance (p = 0.029), and sway velocity (p < 0.001), particularly under eyes-closed single-leg stance. Posterolateral reach distance decreased (p = 0.023), accompanied by reduced lower-limb muscle activation. Tibialis anterior muscle reaction time during 30 degrees of inversion in the ankle neutral position was shortened (p < 0.001), whereas peroneus longus muscle responses were unchanged. Acute lower-limb BFR impairs ankle sensorimotor control by reducing proprioceptive accuracy, balance performance, and muscle activation, while shortening reaction time. These findings suggest caution when applying BFR during tasks that require high postural demands or end-range control. Registration number and date: NCT07307339, 12/26/2025.

Humans

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics

Novel environmental contaminant 6PPD-quinone promotes malignant phenotypes in colorectal cancer cells and identifies candidate response-associated genes.

6PPD-quinone (6PPDQ), an oxidative transformation product of the widely used tire antioxidant 6PPD, is a ubiquitous environmental contaminant with bioaccumulation potential and widespread human exposure. Recent epidemiological evidence indicates a positive association between urinary 6PPDQ levels and colorectal cancer (CRC) risk; however, its biological effects on CRC-related phenotypes and associated molecular responses remain unclear. We integrated bioinformatics analysis, prognostic modeling, molecular docking and dynamics simulations, and in vitro experiments to investigate cellular and molecular responses to 6PPDQ in CRC models. Predicted 6PPDQ targets were intersected with CRC prognosis-related genes from The Cancer Genome Atlas, followed by functional enrichment and LASSO regression to construct a prognostic risk model, with 1-, 3-, and 5-year AUC values of 0.727, 0.754, and 0.778, respectively. Molecular docking and 100-ns molecular dynamics simulations suggested interactions between 6PPDQ and candidate proteins, including CPT2, SHC2, SRMS, and STK35. Functional assays showed that 6PPDQ exposure altered proliferation, wound-closure capacity, and invasion in Caco-2 and HCT116&#x202f;cells across the nanomolar concentration range, with non-monotonic and cell-line-dependent responses. In contrast, NCM460&#x202f;cells showed no increase in EdU incorporation at 10 or 100&#x202f;nM, whereas reduced proliferation at higher concentrations was accompanied by increased LDH release. 6PPDQ also altered the expression of several prognosis-associated candidate genes. These findings identify cellular phenotypes and candidate molecular responses associated with 6PPDQ exposure under the tested in vitro conditions, but do not establish their causal roles or in vivo relevance. Further mechanistic and in vivo studies are required.

Humans

Insights into the fate and dynamics of antibiotic resistance in multidrug-resistant Bacillus cereus during in vitro simulated gastrointestinal digestion.

Bacillus cereus, an important pathogen responsible for causing foodborne diseases worldwide, releases pore-forming enterotoxins, which target host epithelial cells, leading to osmotic lysis and ultimately manifesting as diarrheal syndrome. Moreover, some B. cereus strains carry antimicrobial resistance genes that confer multidrug resistance against a spectrum of antibiotics. Characterizing the survival traits of multidrug-resistant (MDR) B. cereus strains in the intestinal microenvironment is essential for developing targeted strategies to effectively manage diarrheal foodborne diseases caused by this pathogen. This study used whole-genome sequencing (WGS) to evaluate the pre- and post-digestion toxigenic potential, antimicrobial resistance profiles, and genetic diversity of MDR B. cereus strains isolated from food samples in Guangdong Province, China. The four B. cereus isolates investigated in this study exhibited a genetic diversity, as determined by multilocus sequence typing analysis of WGS data. All four isolates produced the diarrheal toxins Hbl, Nhe, and CytK to varying levels, indicative of their potential to cause outbreaks of foodborne diseases. Each of the four isolates exhibited resistance to more than three classes of antibiotics, fulfilling the criterion for multidrug resistance. At an initial concentration of 9 log colony-forming units (CFU)/mL, the intestinal concentration of these four isolates crossed the threshold required to induce widespread diarrhea in the general population. Under rice slurry protection, all tested isolates maintained intestinal concentration beyond the threshold when the initial concentration was increased to &#x2265;8 log CFU/mL. Moreover, the upregulations of genes associated with acid tolerance, bile tolerance and stress response were observed in the surviving MDR B. cereus isolates. Digestion markedly altered the antibiotic resistance profiles of the MDR B. cereus isolates. In the absence of a food matrix, the MDR isolates lost their resistance to imipenem, meropenem, amoxicillin-clavulanic acid, and trimethoprim-sulfamethoxazole post-digestion and was influenced by the initial concentration of the strains. In the presence of food matrix rice slurry, the effects of digestion on the antibiotic resistance of MDR B. cereus isolates can be mitigated, enabling them to maintain their antibiotic resistance to the greatest extent. Most remarkably, after digestion, the isolates Bce055 and Bce166 exhibited newly emergent resistance to cefotetan and trimethoprim-sulfamethoxazole, respectively. Our findings clarify the fate of MDR B. cereus isolates in the gastrointestinal tract and inform the development of prevention and control strategies for foodborne diseases caused by this pathogen.

Drug Resistance, Multiple, Bacterial

Single-cell RNA sequencing provides further insights into the immunostimulatory action of freeze-dried Lactiplantibacillus plantarum on Penaeus vannamei shrimp.

Immunostimulation through dietary interventions opened new avenues in developing disease control and prevention tools for shrimp aquaculture. We have previously shown that feeding with freeze-dried Lactiplantibacillus plantarum (LAB) increased disease resistance of Penaeus vannamei against both Vibrio parahaemolyticus and white spot syndrome virus (WSSV) based on bulk RNA sequencing of shrimp gills. This tissue participates in ion transport and serves as a first line of defense against environmental stressors and pathogenic infections. However, characterization of their cell composition and functions remains limited. Here, we implemented a single-cell RNA sequencing approach to further gather insights into how feeding with freeze-dried LAB modulates host immunity which may not be evident with bulk RNA sequencing approach. A total of five clusters with unique transcriptional signatures were identified, corresponding to pillar cells, septal cells, and sessile hemocytes. Pseudo-bulk analyses at global- and cluster-levels showed differential expression of genes related to host immunity and metabolism. We further revealed how overall transcriptomic changes are not exclusively caused by gene expression changes but may also be driven by cell population dynamics. This study highlighted how single-cell RNA sequencing approach may shed light on the mechanisms of action of immunostimulants which may be masked in bulk transcriptome analyses.

Animals

Transcriptome analysis of the pectoral fin degeneration in half-smooth tongue sole (Cynoglossus semilaevis).

Appendage degeneration is a notable morphological feature of some teleosts with specialized benthic lifestyles. The half-smooth tongue sole (Cynoglossus semilaevis) undergoes severe pectoral fin regression during metamorphosis. However, the molecular basis underlying rapid pectoral fin degeneration remains unclear. Here, we performed time-series transcriptome sequencing on pectoral fins at pre-metamorphosis, metamorphosis peak and post-metamorphosis to characterize the molecular changes associated with pectoral fin degeneration. Transcriptional dynamics and functional enrichment showed that no significant enrichment of classical apoptosis-related transcriptional pathways was detected during pectoral fin degeneration. Instead, sustained downregulation of twist1b, identified as a transcriptomic candidate, together with significant upregulation of ssh1, coupled with enrichment of lysosome and ubiquitin-proteasome system (UPS) pathways, suggested enhanced tissue remodeling during pectoral fin degeneration. Temporal expression clustering revealed heterochronic misalignment in the developmental gene expression: upstream initiator tbx5 was upregulated at early metamorphosis, while downstream maintenance signal fgf10 decreased synchronously. Distal patterning gene hoxd12a exhibited premature expression and rapid decay, losing sustained late-phase expression. Moreover, transient elevation of gli3 during metamorphosis may contribute to restricted distal fin growth. We conclude that pectoral fin degeneration in C. semilaevis is associated with heterochronic disruption of developmental signaling and extensive tissue remodeling. This study provides transcriptomic insights into pectoral fin degeneration in tongue soles and establishes a basis for future functional studies of appendage reduction in teleosts.

Animals

Application of musculoskeletal ultrasound in postoperative rehabilitation assessment and monitoring after rotator cuff repair: A systematic review.

BACKGROUND: The development of rehabilitation protocols after rotator cuff repair has long lacked objective benchmarks. Traditional time&#x2011;based regimens are limited by considerable inter&#x2011;individual variability and an increased risk of re&#x2011;tear. Musculoskeletal ultrasound allows dynamic assessment of tendon healing and muscle morphology, yet evidence for directly linking its use to rehabilitation decisions remains scarce. OBJECTIVE: To systematically synthesize the evidence on the use of musculoskeletal ultrasound monitoring to inform rehabilitation decision&#x2011;making after rotator cuff repair. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta&#x2011;Analyses (PRISMA) guidelines, we searched PubMed, China National Knowledge Infrastructure (CNKI), and Wanfang Data from January 2020 to April 2026. Original studies were included if they involved patients who had undergone rotator cuff repair, used musculoskeletal ultrasound (including gray&#x2011;scale ultrasound, elastography, etc.) to evaluate the rotator cuff tendons or shoulder muscles, and reported at least one parameter related to rehabilitation decision-making or functional outcomes. RESULTS: Eleven studies were included. Shear wave velocity (SWV), cross&#x2011;sectional area (CSA), and echo intensity (EI) were the most frequently reported ultrasound parameters. Available evidence indicated that SWV increased progressively after surgery, with an overall increase of approximately 22% to 25% from one week to 12 months postoperatively. This dynamic trajectory may serve as a reference baseline for judging rehabilitation progress. An abnormally elevated SWV in the early postoperative period was associated with an increased risk of re&#x2011;tear, suggesting that a more conservative rehabilitation strategy should be adopted. Tendon stiffness measured at 12 weeks after surgery independently predicted long&#x2011;term return to sport. Regarding muscle parameters, changes in CSA and EI were positively correlated with shoulder function scores, and the combination of these two parameters effectively identified patients with rehabilitation bottlenecks. CONCLUSION: Musculoskeletal ultrasound parameters are associated with the initiation of active movement, adjustment of exercise load, prediction of return&#x2011;to&#x2011;sport prognosis, and identification of retear risk. Among these, SWV shows particular promise as an objective monitoring parameter for supporting rehabilitation assessment after rotator cuff repair. Future randomized controlled trials are needed to determine whether ultrasound-informed assessment can improve rehabilitation outcomes compared with traditional time-based regimens, and to establish standardized measurement protocols and clinically applicable reference values. Key findings of this review are summarized in S1 File.

Humans

Longitudinal Relations among Perceived Economic Stress, Teacher-Student Relationships, and Cybervictimization: Exploring Within-Person Links.

Family economic hardship has been identified as a risk factor for adolescents' cybervictimization. Nevertheless, existing studies have primarily focused on objective economic conditions, and little is known about the within-person association between perceived economic stress and adolescents' cybervictimization and the mediating mechanisms underlying this association. To fill these gaps, the random intercept cross-lagged model was employed to examine the dynamic relations among perceived economic stress, teacher-student relationships, and cybervictimization. The data were obtained from a sample of 2407 Chinese adolescents (Mage = 12.75, SD = 0.58, 50.23% girls at baseline) recruited from seven schools and assessed at three time points over one year. At the between-person level, there were no significant associations among perceived economic stress, teacher-student relationships, and cybervictimization. At the within-person level, perceived economic stress positively predicted later cybervictimization over time, and this effect was unidirectional. The bidirectional relations between perceived economic stress and teacher-student relationships remained stable over time. Cybervictimization significantly and negatively predicted subsequent teacher-student relationships across time, indicating a unidirectional predictive effect. Additionally, perceived economic stress indirectly predicted cybervictimization through teacher-student relationships. The findings highlight the importance of distinguishing within-person from between-person processes and shed light on the longitudinal role of teacher-student relationships in the association between perceived economic stress and cybervictimization.

Humans

Non-linear predictive modeling and comprehensive meta-analysis of rectal temperature in Santa In&#xea;s 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 In&#xea;s 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&#xa0;&#xb0;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 In&#xea;s literature. This non-linear approach offers a biologically superior tool for identifying the onset of thermal distress.

Animals

Modelling peak microbial pollution events caused by combined sewer overflows in a source-to-sea system.

Predicting peak microbial pollution events in downstream coastal bathing waters caused by combined sewer overflows (CSOs) is essential for protecting public health. In urban areas, wastewater effluents, CSOs, and surface runoff can contribute to elevated microorganism loads to downstream waters. These pressures are likely to be intensified by growing population density and more frequent heavy rainfalls due to climate change. This study developed a process-based model to simulate Escherichia coli (E. coli) emissions, transport, and fate from the initial sources to coastal beaches. A three-year retrospective simulation (2017-2019) shows that E. coli concentrations in CSO discharges varied widely across the catchment (4.6 - 7.3 (log10&#xa0;CFU 100&#xa0;ml-1)). 99th percentile E. coli concentrations (4.0 (log10&#xa0;CFU 100&#xa0;ml-1)) at the inland water outlet were dominated by local CSO emissions, whereas 90th percentile E. coli concentrations (3.6 (log10&#xa0;CFU 100&#xa0;ml-1)) reflected cumulative upstream contributions from both CSO and effluent emissions. With the simulation accuracy of 89%, the model reliably reproduced the E. coli dynamics on the downstream beach and showed strong performance in representing peak concentrations based on Complementary Cumulative Distribution Function (CCDF) analysis. The process-based model enables quantitative tracking of source contributions and identification of pollution hotspots, providing support for mitigation measures. The study lays down a source-to-sea modelling framework for representing pollution transport across the aquatic continuum and provides a transferable tool for microbial pollution forecasting and climate adaptation planning.

Climate projection

Dissociating behavioral, neural and experiential effects of prefrontal HD-tDCS during conflict resolution.

Inconsistent evidence regarding the cognitive effects of transcranial direct current stimulation (tDCS) highlights the need for more comprehensive approaches to assess its impact. This study aimed to investigate the effects of high-definition tDCS (HD-tDCS) on conflict resolution by combining behavioral, neural, and subjective experience measures. Sixty participants were randomly assigned to anodal, cathodal, or sham HD-tDCS groups and completed a 30-min flanker task. EEG was recorded during the first and last blocks (without stimulation), while stimulation was applied during the intermediate blocks of the task. Using a multidimensional methodological approach including Drift-Diffusion Modeling (DDM), EEG spectral analysis, Lempel-Ziv complexity, and Temporal Experience Tracing (TET), we assessed the cognitive, neural, and phenomenological effects of stimulation. Behavioral results indicated no significant improvements in reaction times or accuracy across the stimulation groups. Similarly, DDM parameters showed no effect of HD-tDCS on latent cognitive processes. However, EEG data revealed a significant reduction in neural complexity in the anodal group during resting-state, suggesting a stabilization or reorganization of neural dynamics. Subjective experience analysis identified two distinct clusters of task-related feelings, though time spent in these experiential states did not differ between groups. Interestingly, sensation of stimulation was significantly higher for anodal stimulation than sham when analyzed as a single dimension. Despite null behavioral effects, this study provides important insights into the neural and subjective responses to HD-tDCS and highlights the value of integrating complementary multidimensional approaches to better characterize brain stimulation effects. These findings contribute to the ongoing debate about the efficacy of tDCS in cognitive enhancement.

Humans

DNM1L depletion leads to accelerated heteroplasmy shifting of m.10191C allele through ATG7-dependent pathways.

Nucleotide composition bias in mitochondrial DNA (mtDNA) makes the heavy strand prone to form a DNA secondary structure called a guanine quadruplex (G4). This secondary structure has been shown to inhibit polymerase processivity in vitro. We previously identified pathogenic mtDNA variants that lead to increased G4-forming propensity, including a T to C mutation at m.10191 (m.10191&#xa0;T&#xa0;>&#xa0;C) that causes Leigh syndrome. Cells treated with G4 binding agent (G4BA) berberine show a reduction in m.10191C pathogenic heteroplasmy levels. To help better understand the underlying mechanism behind berberine-induced heteroplasmy shift, we examined the relationship between mitochondrial fission and berberine-mediated shift. Here we show that knockdown of the fission factor DNM1L leads to an accelerated heteroplasmy shift towards the healthy mtDNA allele, lowering m.10191C by 10% in 3&#xa0;weeks, compared to the 5&#xa0;weeks required for berberine alone. The specific mechanism involves ATG7, as knockdown of ATG7 is able to partially delay this accelerated heteroplasmy shift. Taken together, we show that DNM1L knockdown is able to accelerate berberine-induced m.10191C heteroplasmy shifting through an autophagy-related mechanism.

Humans