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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

Effects of an actuated ankle exoskeleton on walking stability in healthy adults: a controlled laboratory study.

BACKGROUND: Ankle exoskeletons are widely used to reduce the metabolic cost of walking, yet their effects on walking stability during unperturbed gait remain insufficiently understood. Walking stability can be characterized using complementary measures that capture stride-to-stride variability, global temporal organization, and local dynamic stability. Understanding how walking with an actuated ankle exoskeleton system influences these different aspects of gait stability is essential for the safe design and control of wearable robotic devices. METHODS: Eighteen healthy adults walked on a treadmill at a constant speed (1.1&#xa0;m/s) with and without an actuated bilateral ankle exoskeleton in a randomized crossover design. Spatiotemporal variability was quantified using coefficients of variation (CoV) of stride length, step width, and stance ratio. Global gait stability was assessed using detrended fluctuation analysis of stride time. Local dynamic stability was evaluated using maximum Lyapunov exponent calculated for the trunk, hip, upper leg, lower leg, and foot. Paired-samples two-sided t-tests were used to compare conditions. RESULTS: Walking with the ankle exoskeleton resulted in increased stride-to-stride spatiotemporal variability, reflected by higher CoV values for stride length (p&#x2009;<&#x2009;0.001) and stance ratio (p&#x2009;=&#x2009;0.005), while mean stride length and step width remained unchanged. Mean stance ratio was reduced in the exoskeleton condition (p&#x2009;<&#x2009;0.001). Global gait stability did not differ between conditions, indicating preserved long-range temporal gait organization. Local dynamic stability increased at the lower leg (p&#x2009;<&#x2009;0.001) and foot (p&#x2009;=&#x2009;0.019) when walking with the exoskeleton. CONCLUSIONS: Walking with the actuated ankle exoskeleton alters gait control across multiple levels during steady walking. While stride-to-stride variability in stride length and stance ratio increased, global gait stability remained unchanged. Local dynamic stability was increased at the lower leg and foot, suggesting segment-specific effects of ankle-level assistance close to the assisted joint. However, these findings should be interpreted as the combined effect of wearing the exoskeleton and receiving active assistance, rather than the isolated effect of plantarflexion assistance. These&#xa0;results provide insight for the design and control of ankle exoskeletons with respect to stability-related effects during walking.

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

Oblique Lateral Interbody Fusion With Lateral Vertebral Screw Fixation Versus Transforaminal Lumbar Interbody Fusion for Severe Lumbar Stenosis: Results of a Multicenter Randomized Controlled Trial.

BACKGROUND AND OBJECTIVES: The benefits of oblique lateral interbody fusion (OLIF) vs transforaminal lumbar interbody fusion (TLIF) in severe lumbar stenosis (Schizas C/D) remain uncertain. This randomized trial compared clinical, radiographic, and safety outcomes of OLIF and TLIF. METHODS: From November 2018 to December 2021, a prospective, multicenter, randomized controlled trial enrolled 260 adults with single-level severe stenosis and instability. In total, 224 patients were randomized to OLIF or TLIF. Prespecified outcomes followed consolidated standards of reporting trials. Primary outcomes were visual analog scale back/leg pain and Oswestry Disability Index (ODI), with minimal clinically important difference thresholds of ODI &#x2265;12-13 points or &#x2265;30% improvement, and visual analog scale &#x2265;1.5-2.0 points. Radiographic measures included disc height, lumbar and segmental lordosis, and canal cross-sectional area (CSA). Complications were recorded. Ethics approval was obtained from the institutional review board, the trial was registered with ISRCTN.com , and all patients provided written informed consent. RESULTS: In total, 224 patients were randomized, 5 were lost to follow-up (TLIF n = 2, OLIF n = 3). Baseline features were comparable. OLIF was associated with shorter operative time, less blood loss, earlier ambulation, and shorter hospital stay (all P < .05). Both groups achieved significant, clinically meaningful improvements. OLIF showed greater back pain reduction at 3-6 months and 2 years ( P < .05) and superior ODI improvement at 3 and 6 months ( P < .001), although long-term ODI scores were similar. Radiographically, OLIF provided greater restoration of disc height and segmental lordosis (all P < .001) and demonstrated progressive CSA increase (dynamic decompression), whereas TLIF achieved immediate, sustained CSA enlargement. Fusion rates were comparable at 1-2 years. Complication rates were low and similar (7.3% TLIF vs 5.5% OLIF), with most OLIF-specific events transient. CONCLUSION: Both OLIF and TLIF yield improvements in severe lumbar stenosis. OLIF offers perioperative advantages, earlier functional recovery, radiographic restoration, and dynamic canal remodeling, supporting its role as an equivalent alternative for lumbar spinal stenosis with some secondary advantages.

Humans

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

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

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

Human endogenous retroviruses leading to autoimmune diseases.

Human endogenous retroviruses (HERVs) comprise approximately 8% of the human genome and were long regarded as inert remnants of ancestral retroviral infections. Increasing evidence indicates that HERVs are active genomic elements capable of influencing transcriptional programs, modulating immune responses, and contributing to disease pathogenesis. Under physiological conditions, HERV expression is tightly controlled by epigenetic mechanisms; however, infections, chronic inflammation, aging, and diverse environmental stimuli can promote HERV reactivation. HERV-derived RNAs and proteins engage innate immune sensors and trigger antiviral-like responses through mechanisms of viral mimicry, leading to activation of type I interferon and other inflammatory pathways. HERV dysregulation has been associated with disease-relevant immune pathways. This review summarizes recent advances linking HERVs to autoimmune disease pathogenesis and discusses their potential translational relevance as biomarkers and therapeutic targets.

Humans

Ecological momentary assessment studies on food craving among healthy adults: A systematic review.

Ecological Momentary Assessment (EMA) can capture the dynamic nature of food craving in free-living conditions, addressing limitations of laboratory and retrospective reporting methods. This systematic review synthesized findings from EMA studies to characterize 1) methodological features, 2) the temporal dynamics of food craving, and 3) the relationship between craving and eating behaviors. A systematic search of PubMed and PsycINFO databases was conducted following PRISMA guidelines. The review included 23 studies that utilized EMA designs to assess food craving repeatedly in daily life among healthy adults. Most studies employed EMA protocols that prompted participants to respond at pre-specified time points and utilized single-item craving measures. Most craving measures (71%) lacked specificity regarding the type of food craved. Results revealed a consistent positive within-person association between hunger and food craving. Conversely, associations between stress/negative affect and craving were inconsistent, varying by individual traits and context. Momentary food craving appeared to predict subsequent eating outcomes. Evidence suggested food craving may be a dynamic, transient state that co-fluctuates with hunger, functioning as a proximal antecedent to food intake. However, reliance on non-specific food craving measures and EMA protocols prompting at fixed schedules limits the granular understanding of craving mechanisms. Future research requires refining food craving measurement and incorporating randomized prompting within predefined windows, or participant-initiated sampling triggered by specific events (e.g., eating occasion), to better characterize food craving dynamics in relation to eating behaviors.

Humans

Comparative in silico analysis of Apis mellifera immune responses to Varroa destructor and Tropilaelaps mercedesae: Common and mite-specific molecular signatures.

Parasitic mites Varroa destructor and Tropilaelaps mercedesae represent major threats to global honey bee (Apis mellifera) health and productivity, yet comparative molecular insights into host responses remain limited. To address this, we systematically compiled published studies (2015-2025) reporting genes associated with honey bee interactions with V. destructor (11 studies, 87 genes), T. mercedesae (4 studies, 35 genes), and hygienic behavior (6 studies, 44 genes). Gene identifiers were harmonized to the Amel_HAv3.1 genome assembly, yielding three non-redundant sets: 64 Varroa-associated, 34 Tropilaelaps-associated, and 44 hygienic behavior-associated genes. Venn analysis identified 10 overlapping genes (including A0A088A8D5, A0A088ADL8, ABAE_APIME, Def1, Def2, Gapdh, HYTA_APIME, Imd, LOC726783, and Vg), suggesting conserved defense mechanisms, while 41 and 24 genes were uniquely associated with Varroa and Tropilaelaps, respectively. Enrichment analyses revealed Varroa-responsive genes were enriched in immune processes, chitin catabolism, and signaling pathways (Toll/Imd, MAPK, Wnt). Tropilaelaps-associated genes were enriched for antibacterial defense and stress response, with Toll/Imd signaling as the sole significantly enriched pathway. Overlapping genes reinforced core innate immunity activation. Protein-protein interaction network centrality analysis identified key hub genes: Def1, HYTA_APIME, ABAE_APIME, PPO, Imd, PGRP-LC, Vg for Varroa; and ACPH1_APIME, MRJP1, Vg, LOC726783 for Tropilaelaps. Results demonstrate that, despite differences in mite biology, honey bees show a conserved immune response against both parasites, centered on antibacterial defense, humoral immunity, and activation of the Toll/Imd pathway. Although limited by the in-silico nature and research asymmetries reflecting Tropilaelaps' emergence, this curated resource establishes a comprehensive framework for elucidating shared and distinct molecular defense mechanisms. Ultimately, this approach prioritizes diagnostic markers and candidate genes for functional validation and breeding strategies to enhance colony resilience against mite&#x2011;driven disease globally.

Animals

Mapping antibody sequences and effector functions across spatial niches.

Antibodies are fundamental to human health but can also drive pathology. Each antibody has a molecular specificity, encoded by their clonally heritable B cell receptor (BCR). Recent advances in spatial transcriptomics coupled with repertoire sequencing have enabled capturing antibody-secreting cells (ASCs) and their clonal BCR within their tissue microenvironment. However, our understanding of antibody production niches remains limited. Furthermore, where antibodies are produced can be distinct from where antibodies exert their effector function. Here, we propose a conceptual spatial framework to distinguish between 'antibody production niches', defined by the ASC, BCR, and niche composition, versus 'antibody functional niches', composed of the antibody, antigen, and effector landscape. We then examine the possibilities and challenges to map and link antibody-encoding sequences and antibody effector functions using current and emerging technologies. Combined, we argue that integrating spatial sequence data with the antibody functional context is essential to decode the architecture of antibody-mediated immunity.

Humans

Microglial modulation in general anesthesia: molecular.

General anesthetics profoundly alter brain function and consciousness, yet the mechanisms underlying these effects remain incompletely understood. Although traditional studies have primarily focused on neuronal targets, accumulating evidence suggests that microglia dynamically respond to anesthetic exposure and may participate in anesthesia-associated neurophysiological changes. Beyond their established immune functions, microglia are increasingly implicated in synaptic remodeling, metabolic regulation, neuronal activity surveillance, and neuron-glia communication. Recent studies indicate that different classes of anesthetic agents modulate microglial activity through diverse and context-dependent mechanisms involving inflammatory signaling, purinergic pathways, calcium dynamics, mitochondrial metabolism, and neural circuit interactions. These responses are associated with postoperative neurocognitive disorders, altered synaptic plasticity, and anesthesia-related changes in brain states. In this review, we summarize current evidence regarding the effects of volatile anesthetics, intravenous anesthetics, and analgesics on microglial function and discuss the molecular, functional, and circuit-level mechanisms underlying anesthesia-associated neuron-microglia interactions. We further highlight the dynamic and heterogeneous nature of microglial responses during anesthesia and discuss current limitations in the field, including the lack of temporally resolved and cell-specific approaches. Understanding these processes may provide insights into anesthesia-associated neurocognitive dysfunction and support the development of neuroimmune-targeted strategies in anesthesiology.

General anesthesia

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans