Search Results (890)

Persistent high-risk human papillomavirus infection is a critical prerequisite for cervical intraepithelial neoplasia and cervical cancer, yet viral factors alone do not fully explain why most infections clear while a subset persists and progresses. Emerging longitudinal, multi-omics, and mechanistic evidence supports a plausible model in which the cervicovaginal microbiota is not a passive bystander but a functional determinant of mucosal immunity, epithelial barrier integrity, and local metabolic tone. Lactobacillus-dominant community states, particularly those enriched in Lactobacillus crispatus, are generally associated with lower pH, regulated inflammatory signaling, stronger barrier function, and a higher likelihood of HPV clearance. In contrast, anaerobe-enriched dysbiosis is linked to elevated pro-inflammatory cytokines, altered antigen presentation, immune checkpoint signatures consistent with T-cell dysfunction, and metabolic shifts involving lactate depletion and accumulation of short-chain fatty acids and other metabolites that can influence epithelial and immune-cell programs. Importantly, the interaction is bidirectional: hrHPV can remodel the microenvironment by suppressing host defense peptides and perturbing mucosal barriers, thereby reducing Lactobacillus fitness and reinforcing dysbiosis in a feed-forward loop that favors persistence and oncogenic progression. This review integrates functional ecology, longitudinal clinical evidence, immunological and metabolic mechanisms, and translational implications, highlighting opportunities for microbiome-informed risk stratification and adjunctive interventions, as well as key gaps requiring standardized longitudinal multi-omics and rigorously designed clinical trials. Full article

Horizontal nystagmus is still commonly interpreted at the bedside through a pragmatic peripheral-versus-central dichotomy. Although this heuristic is often clinically useful, it may be misleading because distributed brainstem–cerebellar disorders can generate peripheral-appearing phenotypes. This paper presents a narrative clinical–conceptual review proposing that a substantial subset of horizontal nystagmus patterns may be understood more coherently as expressions of dysfunction within a coupled vestibulo-ocular integrative network rather than as direct signatures of a single lesion site. Within this framework, two core dynamical domains are separated conceptually: a vestibular nuclei (VN)-centered velocity-storage process and an NPH-centered gaze-holding integrator. These processes are proposed to operate under cerebellar regulatory influence, with the nodulus–uvula (NU) acting as a plausible regulator of storage gain, temporal persistence, adaptation stability, and oscillatory behavior. Clinically, the velocity-storage domain is expressed through low-frequency vestibulo-ocular reflex behavior and optokinetic after-nystagmus-related dynamics, whereas the gaze-holding domain is expressed through eccentric gaze stability, gaze-evoked nystagmus, and post-saccadic drift. This framework carries a clinically relevant implication: horizontal nystagmus phenotypes may be interpreted more effectively by asking which functional process is predominantly abnormal—gaze holding, storage-related vestibular persistence, or cerebellar regulatory stability—rather than by relying solely on a binary peripheral–central label. On this basis, we outline a clinician-facing workflow linking gaze dependence, periodicity, direction reversals, head-shaking behavior, and Alexander-law mismatch to operational bedside criteria and candidate quantitative readouts. The proposed model is intended as a clinical–conceptual framework rather than a deterministic localization tool. Its main value lies in organizing discordant vestibular findings, strengthening the mechanistic interpretation of bedside and instrumented observations, and identifying testable directions for future validation studies in acute dizziness and ocular motor disorders. Full article

Pharmacogenomics AI offers significant potential for individualized drug therapy; however, its clinical benefits remain unevenly distributed. Models trained predominantly on European-ancestry data consistently underperform in non-European populations, with polygenic risk scores (PRS) showing an estimated 39–73% reduction in predictive accuracy in African-ancestry cohorts across complex traits. These disparities have driven increased interest in moving beyond single-layer genomic approaches. Multi-omics frameworks integrating genomic, transcriptomic, proteomic, and metabolomic data have emerged as a promising strategy to improve prediction across heterogeneous clinical populations, as each molecular layer provides distinct and complementary biological information. Among these layers, metabolomics may represent a particularly transferable component across populations. Metabolite profiles capture the downstream functional output of biological systems influenced by genetic, environmental, dietary, and microbiome-related factors, and may therefore be less reliant on ancestry-stratified allele frequency structures that underlie performance disparities in genomic models. This review synthesizes evidence regarding the mechanistic basis of genomic bias in pharmacogenomics AI, the emerging role of multi-omics integration, especially metabolomics, in improving predictive performance, and the current landscape of computational strategies for bias mitigation, including federated learning, transfer learning, domain adaptation, and synthetic data generation. Collectively, current evidence supports metabolomics-inclusive multi-omics frameworks as a biologically plausible, hypothesis-generating strategy to reduce reliance on ancestry-linked genomic features. However, direct evidence that such frameworks reduce ancestry-related bias in clinical AI outputs remains limited, underscoring the need for globally diverse datasets and prospective multi-population validation. Full article

Anemia represents one of the most frequent systemic complications of inflammatory bowel disease (IBD), with a consistently higher prevalence reported in patients with Crohn’s disease (CD) compared with ulcerative colitis (UC). While chronic inflammation, impaired iron absorption, and intestinal blood loss are recognized contributors, microbiome-mediated mechanisms influencing host iron availability remain insufficiently explored. Emerging evidence indicates that CD-associated dysbiosis is characterized by an increased abundance of siderophore-producing bacteria, particularly members of the Enterobacteriaceae family. Because siderophores are high-affinity iron-chelating molecules capable of competing with host iron acquisition systems and partially escaping lipocalin-2-mediated sequestration, their expansion may contribute to reduced luminal iron bioavailability. In this systematic review, we analyzed comparative microbiome studies published between 2016 and 2026 that directly evaluated microbial differences between CD and UC. CD microbiota consistently demonstrated enrichment in siderophore-associated taxa relative to UC. Based on these findings, we propose that microbiome-driven iron competition may represent an additional mechanistic contributor to the increased prevalence and persistence of anemia observed in CD. Although direct in vivo quantification of siderophore activity in IBD remains limited, the convergence of ecological, functional, and strain-level microbiome evidence supports a biologically plausible interaction between microbial iron-scavenging strategies and host iron metabolism. Full article

Spiking neural networks (SNNs) are well suited for modeling temporally evolving information due to their event-driven and dynamic neuronal mechanisms. Nevertheless, the majority of existing SNN topologies are constructed through algorithmic procedures rather than guided by constraints from biological brain connectivity, which weakens their biological plausibility. In our earlier work, we developed a spiking neural network (SNN) by incorporating topological information from functional brain networks extracted from functional magnetic resonance imaging (fMRI) data of healthy individuals, and named the resulting model fMRISNN. Nevertheless, the fMRI data used in previous work were resting-state fMRI. Compared with resting-state fMRI, task-state fMRI can capture brain-region coordination patterns induced by specific task stimuli, and the resulting functional brain network is therefore more closely related to the corresponding task. Motivated by this advantage, this study replaces the resting-state topology used in previous fMRISNN studies with a task-state, number/digit-related fMRI topology and validates the resulting Task-fMRISNN on handwritten digit recognition. The experimental results demonstrate that the proposed Task-fMRISNN outperforms the Rest-fMRISNN in terms of recognition accuracy, lesion robustness, and noise robustness. In addition, the Task-fMRISNN achieves significantly better performance than several baseline models constructed using algorithmically generated topologies. While deep convolutional neural networks (CNNs) may deliver superior absolute recognition performance, the proposed fMRISNN provides a more compact model structure and shows potential resource-efficiency advantages due to its sparse and event-driven computational characteristics. Full article

Autism spectrum disorder is increasingly linked to altered microglial biology. However, current research models are limited by outdated descriptions of microglial “activation”. Here, we propose that microglial involvement in ASD is best understood as a problem of state mismatch, in which temporally programmed and regionally specialized microglial states fail to align with local developmental demands. We synthesize evidence across genetic models, human transcriptomics, and experimental systems to examine three axes of misalignment: developmental timing, circuit specificity, and functional phenotype. These mismatches produce divergent outcomes, including both excessive and insufficient synaptic pruning, and reflect a decoupling between microglial activation markers and effector capacity. We further evaluate molecular recognition systems governing microglia–synapse interactions, with emphasis on complement signaling and glycan-mediated pathways such as sialic acid–Siglec signaling and polysialylation. While glycosylation is not a universal driver of ASD pathology, it represents a plausible regulatory layer controlling synapse visibility and microglial engagement. This framework reconciles conflicting findings in the literature and positions microglia as dynamic developmental effectors whose misaligned state trajectories contribute to circuit-level dysfunction in ASD. Full article

Background: Cancer pain affects approximately 44.5% of all patients with malignancy and up to 55–65% of those with advanced or metastatic disease; a substantial proportion remain inadequately controlled with conventional pharmacological approaches alone. Peripheral nerve stimulation (PNS), a minimally invasive neuromodulatory strategy, has emerged as a potential opioid-sparing analgesic option for the perioperative management of oncologic surgical patients. Objectives: This narrative review synthesizes current evidence on the application, mechanisms, clinical efficacy, safety, and integration of temporary and permanent PNS systems in cancer patients, with specific focus on cancer-specific pain syndromes, key clinical studies, opioid-sparing immunological implications, evidence quality, and directions for future research. Methods: As a narrative review, this work was structured in accordance with the Scale for the Assessment of Narrative Review Articles (SANRA) to ensure methodological transparency. A focused, non-systematic literature search of PubMed/MEDLINE, Embase, and the Cochrane Library was performed from database inception through March 2026, supplemented by hand-searching of reference lists and targeted retrieval of clinical practice guidelines. Sources were selected on the basis of relevance to PNS or closely analogous peripheral neurostimulation modalities in oncologic, perioperative, or chronic pain contexts. Evidence was synthesized narratively, with each cited study graded using the Oxford Centre for Evidence-Based Medicine (OCEBM) 2011 Levels of Evidence framework to enable transparent calibration of confidence. Results: Available preliminary and largely extrapolated evidence supports PNS as a promising but not yet established useful adjunct in oncologic perioperative care; because cancer-specific data rest substantially on a single pilot study (n = 12), one retrospective review (n = 15), and extrapolation from non-cancer populations, these conclusions should be regarded as hypothesis-generating. Randomized controlled trial data from non-cancer cohorts demonstrate opioid consumption reductions of approximately 80–90% in the PAINfRE trial, while the post-amputation trial demonstrated ≥50% pain-relief responder rates and reductions in pain interference, with clinically meaningful improvements in pain and function. Oncologic-specific pilot and retrospective evidence confirms feasibility and a 58–67% success rate across diverse cancer pain subtypes. Conclusions: The opioid-sparing properties of PNS carry additional biological plausibility for preserving perioperative antitumor immune function. High-quality prospective trials specifically designed for oncologic surgical populations remain needed to establish evidence-based recommendations. Full article

The pyrolysis of polypropylene (PP) microplastics offers a potential route to convert plastic waste into fuel-range hydrocarbon mixtures and chemical feedstocks. However, the elementary radical pathways underlying the formation of medium-chain hydrocarbon fragments remain insufficiently resolved. In this study, a representative isotactic PP oligomer model (C₄₅H₉₂) was evaluated using a comparative density functional theory (DFT) framework. The main mechanistic analysis was based on M06-2X, ωB97X-D, and M11 calculations combined with the def2-TZVP basis set, whereas LANL2DZ was retained only as a lower-cost comparative level during reaction-pathway exploration. Thermochemical profiles were evaluated over a temperature range of 298–923 K. Three selected pathways involving mid-chain homolytic cleavage, intramolecular hydrogen transfer (backbiting), radical rearrangement, and β-scission were examined. Within the selected reaction set, Route 1 exhibited a comparatively more favorable thermochemical profile than Routes 2 and 3 and provided a mechanistically plausible sequence toward medium-chain hydrocarbon fragments. The −TΔS contribution strongly influenced the calculated Gibbs free-energy profiles because fragmentation increases the number of molecular species under the ideal-gas thermochemical approximation. Accordingly, the ΔG values were interpreted comparatively and were not treated as direct evidence of spontaneous fragmentation under condensed-phase pyrolysis conditions or as quantitative predictions of experimental product selectivity. Differences among the evaluated functionals further indicate that the relative description of radical intermediates and transition-state regions is method-dependent. These results provide a molecular-level framework for future studies integrating quantum-chemical calculations, microkinetic modeling, and experimental product characterization. Full article

This study characterizes AP-20-A, a lytic podovirus infecting Sinorhizobium meliloti, isolated from agricultural chernozem. Its 49.4 kbp genome shows negligible intergenomic similarity with known rhizobiophages (<2%). Core structural proteins—the major capsid protein (MCP) and terminase large subunit (TerL)—show closest homology to podoviruses infecting Paenibacillus, rather than to alphaproteobacterial viruses, suggesting cross-phylum horizontal gene transfer. This exchange is ecologically plausible, as Paenibacillus and Sinorhizobium co-exist in the rhizosphere. Over 63% of predicted proteins are functionally uncharacterized, with structural homologs detected in bacteria, archaea, and eukaryotes. We report the first identification in a rhizobiophage of a Tad2-like domain, predicted to block the bacterial Thoeris type II anti-phage defense. AP-20-A infected 56% of native S. meliloti strains; agrocenose isolates showed higher resistance than phytocenose isolates, evidence of local co-evolution. Among susceptible strains, 60% entered putative pseudolysogeny (with one strain exhibiting growth stimulation), whereas a symbiotically elite inoculant strain was completely lysed within hours. Some host strains carry additional AbiE systems; whether these independent defense–counterdefense layers interact during infection remains unknown. We conclude that resident phages represent a selective force that can disrupt inoculant establishment, underscoring the need to integrate soil virome assessment into agricultural microbiome management. Full article

This study investigates physics-informed and data-driven hybrid modeling strategies for an automotive-grade electrohydraulic (EH) semi-active damper system. Although deep sequence learning architectures such as Long Short-Term Memory (LSTM) networks and Transformers can provide high predictive accuracy, purely data-driven approaches may struggle to preserve physical consistency and maintain robustness under unseen operating conditions. These limitations become more pronounced for EH dampers, whose hysteretic characteristics exhibit highly nonlinear and non-proportional variations under different current and frequency excitations, unlike the more scalable behavior commonly observed in magnetorheological (MR) dampers. To address these challenges, two physics-informed integration strategies are investigated. The first strategy combines physical and data-driven models through parallel loss-function synthesis. The second strategy introduces a learnable physics layer (PINN-Hybrid), in which the coefficients of the extended hyperbolic tangent formulation are adaptively learned within the neural network architecture. In this framework, the physical model acts as a structural regularization mechanism that guides the learning process while preserving the flexibility of data-driven sequence modeling. The proposed models are evaluated under abrupt valve-control operating conditions. Comparative results indicate that the proposed physics-informed architectures improve hysteresis continuity, physical plausibility, and robustness compared with purely data-driven approaches, particularly in low-velocity and transition regions. The proposed framework therefore demonstrates the potential of physics-informed learning strategies for reliable real-time modeling of nonlinear automotive EH damper systems. Full article

In recent years, China’s urban underground rail transit has developed rapidly, and the development of underground space has become increasingly complex, exposing the system to multiple operational risks such as structural instability, excessive deformation, equipment failures and emergencies. Existing studies often evaluate individual hazards or isolated stakeholder risks, while insufficient attention has been paid to how sudden events interact and propagate as disaster chains. To address this gap, this study develops a disaster-chain network framework for operational risk management in underground rail transit. Twenty sudden disaster risk events are first identified through literature review, expert consultation, system investigation, and HAZOP (Hazard and Operability) analysis. A database of 595 historical events is then used to construct co-occurrence and adjacency matrices. And the Jaccard index is used only to quantify association strength, while temporal order, HAZOP-based causal screening, and expert verification are introduced to distinguish plausible triggering relationships from simple correlations. Network indicators, including degree, betweenness, modified clustering coefficient, path length, connectivity, and edge vulnerability, are applied to identify critical nodes and propagation paths. The results indicate that functional failure of civil structures, fire, and crowd stampede are the dominant risk nodes. The proposed framework provides a transparent and replicable basis for prioritizing monitoring, emergency response, and link-cutting mitigation measures. The findings are intended as system-specific decision support rather than universal risk rankings and should be updated when new local operational data become available. Full article

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) is the most prevalent and biologically aggressive subtype of renal cell carcinoma, characterized by pronounced immunogenicity and extensive remodeling of the tumor microenvironment. Chronic inflammation and dysregulated cytokine signaling contribute substantially to tumor progression. Signal transducer and activator of transcription 3 (STAT3) represents a central molecular hub integrating cytokine- and hypoxia-driven pathways. This review aims to summarize current evidence on the cytokine–STAT3 signaling axis in ccRCC and to evaluate its translational relevance for biomarker development. Methods: A narrative review of the literature was conducted using PubMed, Scopus, and Web of Science databases. Experimental, translational, and clinical studies addressing cytokine signaling, STAT3 activation, tumor microenvironment interactions, and biomarker development in ccRCC were evaluated. Particular attention was given to studies analyzing cytokine profiles in tumor tissue, plasma, and urine, as well as their associations with STAT3 activation and clinicopathological parameters. Results: Accumulating evidence indicates that ccRCC exhibits a complex, compartment-specific cytokine signature involving interleukins, chemokines, and tumor necrosis factor (TNF)-related cytokines. Among these mediators, IL-6, IL-8, and selected chemokines such as CXCL10 appear particularly relevant due to their associations with tumor progression, immune modulation, and clinical outcome. Many of these mediators converge on persistent STAT3 activation, which promotes tumor cell survival, angiogenesis, immune suppression, and metastatic potential. Tissue-based analyses demonstrate correlations between altered cytokine expression and STAT3 activation, while urinary cytokine profiles reflect tumor-associated inflammatory processes in a non-invasive manner. Plasma cytokines appear to capture broader systemic inflammatory responses. Conclusions: The cytokine–STAT3 axis represents a biologically plausible signaling network associated with tumor progression and immune modulation in ccRCC. By integrating evidence from cytokine profiling in tumor tissue, plasma, and urine with current knowledge of STAT3 signaling, this review highlights the importance of compartment-specific inflammatory signatures in understanding ccRCC biology and their potential relevance for biomarker discovery. Integrative approaches combining cytokine profiling with functional assessment of STAT3 activation may improve disease characterization and support the development of diagnostic and prognostic biomarkers, although rigorous clinical validation remains necessary. Full article

The larger research problem is to get combustion engines more effective and flexible and reduce or even eliminate greenhouse gas emissions. Here we concentrate more on a smaller-scale and focused research problem about the significance of air feeding in engine operation. Therefore, the need for modeling a charge air system is obvious. The interaction and co-operation between the charge air systems and combustion engines is a central issue in this article. A literature review was carried out on related topics, and it reveals a research gap in this area. A simulation model of a charge air system based on first principles is developed. It is based on physical and systemic modeling, and it is constructed including control loops reducing and controlling the pressures in the charge air chain. The simulation models of this auxiliary system and engine are successfully combined, and functioning together is demonstrated. The composed models represent real research laboratory equipment in the University of Vaasa Energy Laboratory under construction. The research laboratory equipment and the whole research environment are described. Simulation scenarios are presented both with the charge air system alone and with the combined model, including also the engine part. The significance of the developed models is discussed, and the path towards a digital twin experiment environment is outlined. As a conclusion, we can claim that the combined simulation model is successfully constructed and shown to operate in a stable and physically plausible manner. The digital twin concept can be tested completely only when the research laboratory is constructed and ready and the test runs begin to produce measurement data for the digital part. Then also the simulation models can be tuned to a better accuracy level, and the operation as a digital twin will be verified. Full article

Single-use plastic residues persist in agricultural and peri-urban soils of the Ecuadorian Andes. Regionally sourced starch-based films are a plausible local replacement for short-lifetime petroleum plastics, yet field-relevant degradation data for tropical high-altitude soils remain scarce. This study evaluated the soil biodegradability of bioplastic films produced from Colocasia esculenta (malanga blanca) and Manihot esculenta (yuca) across three contrasting soils from Chimborazo, Ecuador (ESPOCH, San Andrés and Río Chimborazo; 2825–3249 m a.s.l.) as a function of their physicochemical properties and bibliographically inferred microbial context. The films were prepared by citric acid starch extraction, glycerol plasticization and carboxymethylcellulose reinforcement; the gravimetric weight loss was tracked on days 0, 11, 18, 27, 40 and 47 on n = 20–21 film replicates per soil × feedstock combination, with the soils characterized by their pH, electrical conductivity and organic matter. After 47 days, the malanga films reached 42.3 ± 13.6%, 22.9 ± 10.7% and 54.1 ± 19.3% mean (±standard deviation, SD) weight loss in the ESPOCH, San Andrés and Río Chimborazo soils, respectively; the yuca films reached 24.4 ± 6.5%, 21.1 ± 6.8% and 49.4 ± 18.7%. The between-soil differences were statistically significant at 47 days according to the analysis of variance (ANOVA) (malanga: F = 22.17, p < 0.001; yuca: F = 34.08, p < 0.001; Tukey’s Honestly Significant Difference (HSD)), with the results corroborated by the Kruskal–Wallis method (H = 29.16 and 37.05; both p < 0.001), given the partial departure from normality identified by the Shapiro–Wilk test. The ordering of degradation departed from the bulk organic matter ranking, indicating that microbial community composition, rather than organic matter quantity alone, was the proximal driver. These findings extend the scarce evidence base on cassava/taro film degradation under high-Andean conditions. Full article

Background: Renal ischemia–reperfusion injury (RIRI) is a major cause of acute kidney injury (AKI) and contributes to delayed graft function and progression toward chronic kidney disease. In addition to oxidative stress and inflammation, RIRI induces profound metabolic derangements, particularly suppression of tubular fatty-acid β-oxidation (FAO), leading to energetic stress, lipid accumulation, and maladaptive repair. Peroxisome proliferator–activated receptor-α (PPARα) is a key regulator of tubular FAO, but whether Schisandrin B (Sch B) mitigates RIRI through restoration of a PPARα-associated metabolic program remains unclear. Objective: To determine whether Sch B alleviates RIRI in association with restoration of tubular FAO and attenuation of lipid accumulation and fibrotic remodeling. Methods: A unilateral murine renal I/R model and an HK-2 hypoxia/reoxygenation (H/R) model were used. Mice received Sch B (20 or 40 mg/kg/day) before I/R, and a subset was co-treated with the PPARα antagonist GW6471. Renal function, tubular injury, fibrosis, lipid accumulation, and FAO-related proteins were assessed by serum biochemistry, histopathology, Oil Red O staining, transmission electron microscopy, immunohistochemistry, immunofluorescence, and Western blotting. Bulk RNA-seq and public single-cell RNA-seq datasets were integrated to characterize metabolic pathway remodeling and cell-type-associated PPARα changes. Molecular docking and molecular dynamics simulations were performed to explore the potential interaction between Sch B and PPARα. Results: Sch B significantly improved renal function, reduced tubular injury, and attenuated interstitial collagen deposition after I/R. Sch B also reduced lipid droplet accumulation, preserved mitochondrial ultrastructure, and restored the expression of FAO-related proteins, including CPT1A, CPT2, and ACADM. In vivo and in vitro, Sch B decreased α-SMA, COL1A1, and vimentin expression, indicating attenuation of EMT-associated/profibrotic remodeling. Integrated transcriptomic analyses supported marked metabolic reprogramming after I/R, with enrichment of FAO- and PPAR-related pathways and reduced PPARα expression predominantly in tubular compartments. Sch B was associated with restoration of tubular PPARα expression, while docking and molecular dynamics analyses supported a plausible Sch B–PPARα interaction in silico. GW6471 blunted the beneficial effects of Sch B on fibrosis-related and FAO-related readouts. Conclusions: Sch B alleviates RIRI and limits subsequent fibrotic remodeling in association with restoration of a PPARα-related tubular FAO program, reduced lipid accumulation, and preservation of tubular metabolic homeostasis. These findings identify metabolic reprogramming as an important component of Sch B-mediated renoprotection, although the precise mode by which Sch B regulates PPARα requires further investigation. Full article