Search Results (860)

Background/Objectives: Although genetic studies have linked immune phenotypes with anxiety, broad Mendelian randomization (MR) screens require explicit multiple-testing control. We reappraised 1753 reported immune-cell-trait-to-anxiety inverse-variance-weighted (IVW) association records available in the analysis tables and assessed the chromosome 20 signal that includes CD40. Methods: The reported records were derived from the 731-trait Sardinian flow-cytometry GWAS of Orrù et al. and were evaluated across one UK Biobank and three FinnGen anxiety phenotypes; outcome-specific Benjamini–Hochberg false-discovery-rate (FDR) correction was applied to the available analysis table. The leading locus was examined using bulk and single-cell expression quantitative trait locus annotations, two-sample MR, summary-data-based MR (SMR), HEIDI tests, and regional colocalization results. Results: Of 1753 tests, 120 were nominally significant, and 21 were retained after outcome-specific FDR correction (14 for UK Biobank anxiety and 7 for FinnGen all anxiety; none for generalized or phobic anxiety). B-cell and regulatory/CD4 T-cell traits were common among retained associations, and several B-cell traits mapped to variants at the CD40 locus. For FinnGen all anxiety disorders, monocyte instruments gave a positive estimate (beta = 0.00418, p = 9.25 × 10⁻⁴), whereas three naïve B-cell instruments gave a negative estimate (beta = −0.0520, p = 2.64 × 10⁻⁴). Monocyte SMR was null (p = 0.542). Naïve B-cell SMR was nominally significant (p = 0.00537), but HEIDI could not be calculated. Regional colocalization was weak in both cell contexts (PP.H4 = 0.0205 and 0.00272). Conclusions: The post-selection locus follow-up prioritizes a chromosome 20 immune locus but does not establish CD40-mediated regulation of anxiety. Because the upstream screen was not regenerated from source GWAS files and complete per-instrument F-statistics were unavailable, all findings are exploratory. CD40 remains a testable candidate for ancestry-matched fine-mapping and cell-state-specific validation. Full article

Background: Prostate cancer (PCa) is a leading cause of cancer-related mortality worldwide, highlighting the need for improved prognostic tools. The integration of artificial intelligence (AI) and machine learning (ML) with multi-omics data offers new opportunities for biomarker discovery and risk stratification. Methods: We integrated bulk transcriptomic data from GSE116918 (training, n = 248) and three cross-cohort consistency evaluation cohorts (TCGA-PRAD, GSE70769, GSE46602), focusing on 1087 epithelial–mesenchymal transition (EMT)-associated genes. Using consensus clustering, weighted gene co-expression network analysis (WGCNA), and 91 machine learning algorithm combinations (including Random Forest, Lasso, and CoxBoost), we constructed a prognostic signature. SHAP analysis was used for model interpretability. Single-cell RNA sequencing (scRNA-seq, GSE268307, 10,672 cells) and spatial transcriptomics (10× Genomics Visium FFPE) provided hypothesis-generating evidence; spatial analysis was based on one tissue section. Results: A three-gene signature (INHBA, FAP, ITGBL1) effectively stratified patients into high- and low-risk groups, with the high-risk group showing significantly worse metastasis-free survival (HR = 1.61, 95% CI: 1.39–1.87; 4-year AUC = 0.93 in the training cohort; external AUCs ranged from 0.62 to 0.77). CytoTRACE inferred high differentiation potential of COMP+ fibroblasts, and Monocle3 inferred a transcriptional transition from COMP+ toward NELL2+ fibroblasts. BayesPrism deconvolution suggested that high inferred COMP+ fibroblast abundance was associated with poor prognosis and advanced T stage. NicheNet analysis prioritized BMP7 as a key upstream ligand, with downstream targets enriched in TGF-β signaling and stem cell pluripotency pathways. Conclusions: This study presents a machine learning-based multi-omics framework for prostate cancer risk stratification. The three-gene signature provides a new exploratory prognostic model while inferring a COMP+ to NELL2+ transcriptional transition. These findings may inform future hypothesis-driven studies of treatment sensitivity, pending experimental validation, and demonstrate the value of AI-driven multi-omics integration for precision oncology. Full article

Despite safety advantages over conventional polyurethanes, one of the biggest drawbacks of polyhydroxyurethanes (PHUs) are their comparatively weak mechanical properties derived from their limited molecular weights via poly(addition). Improvement of mechanical properties of a neat, moisture-curable PHU, synthesized from typical diamine and dicarbonate precursors, was attained by blending both fumed silica and amino-functionalized silica, independently. Varying filler loadings, and both amine-terminated and cyclic carbonate-terminated PHU prepolymers (synthesized in bulk using telechelic amino-terminated poly(propylene glycol), number average molecular weight M_n~2000 g mol⁻¹) and diglycerol dicarbonate, resulted in a much-improved formulation in terms of hardness, modulus, and tensile properties. The amine-terminated prepolymer cross-linked with 3-glycidyloxypropyltrimethoxysilane (GLYMO) and 3.5 wt% of fumed silica had the highest hardness, 2.01 MPa, and the highest modulus, 5.07 MPa, according to nanoindentation tests, and we obtained E of 0.0280 MPa, σ_u of 0.118 MPa, and ε_u of 13.2%, all of which were unobtainable for the benchmark PHU as it was mechanically too weak to perform the tests. All samples were successfully cross-linked, and we found that those reinforced with amino-functionalized silica were weaker than their fumed silica counterparts due to the formation of aggregates, which were confirmed using SEM and TEM imaging. Full article

Marine low-permeability gas-bearing sandstones are commonly characterized by thin sand–mud interbeds, poor reservoir properties, limited seismic bandwidth, and heterogeneous pore structures and fluid distributions, which make stable fluid prediction from conventional prestack seismic attributes difficult. This study proposes an uncertainty-weighted robust frequency-scanning amplitude variation with offset (AVO) inversion method, termed URFS-AVO, for gas-bearing sandstone identification in the Xihu Sag, East China Sea. Under a fluid-matrix decoupled AVO framework, a frequency-dependent P-to-P (PP) reflection-coefficient equation related to the fluid bulk modulus is combined with matching-pursuit Wigner–Ville distribution (MP-WVD) spectral decomposition to obtain local time–frequency spectra from prestack angle gathers. Moving narrow frequency windows are then used to estimate local fluid-dispersion attributes within the effective seismic bandwidth. Rather than extracting the maximum response, URFS-AVO fuses multi-window estimates using local inversion uncertainty and frequency-domain consistency. Tests based on the Chapman pore–microcrack model and the generalized propagator matrix show that the proposed attribute is sensitive to gas-bearing variations. Compared with maximum-window frequency-scanning AVO (FS-AVO), URFS-AVO produces a more focused target-layer response and suppresses unstable background fluctuations, especially under noisy conditions. Application to marine prestack seismic data from the Xihu Sag shows that high URFS-AVO responses are generally consistent with gas-bearing intervals interpreted from well logs. The method provides a stable seismic constraint for fluid prediction in marine low-permeability gas-bearing sandstone reservoirs. Full article

Microplastics are emerging as ubiquitous contaminants in agricultural soils, while nickel (Ni), although catalogued as a potentially toxic element, is an essential micronutrient and a cofactor of urease. In a pot experiment, this study examined how three microplastics (polyethylene, PE; poly(ethylene terephthalate), PET; and polystyrene, PS) affect nickel availability and the properties of two calcareous agricultural soils from central Greece. The microplastics were applied at two levels (1.5 and 3.0% by weight), and the samples were analysed at four time points (3, 6, 9, and 12 months, n = 3). Total (aqua regia) and available (DTPA) nickel, pH, electrical conductivity, organic matter, bulk density (BD), water-holding capacity (WHC), and microbial respiration (qCO₂) were measured, and the data were evaluated by one-way ANOVA with Tukey HSD tests. Total nickel remained stable (about 15.1–15.4 mg/kg; non-significant), whereas the available fraction changed systematically. In Soil 1 (12 months, 1.5%), PE raised DTPA-Ni by +24.9%, PET by +19.8% and PS by −1.7%, while at 3.0% the increases reached +39.8% and +31.7%. In parallel, PE lowered bulk density by up to −16.1%, PET raised water holding capacity by up to +28.9%, and PS raised microbial respiration by up to +38.3%, producing distinct, polymer-specific responses. The changes intensified with time and dose and were milder in the more strongly buffered Soil 2. Microplastics redistribute the biologically active, rather than the total, pool of nickel, a finding that supports reappraising Ni as a nutritional micronutrient and monitoring its available fraction. Because no plants were grown, the nutritional interpretation is advanced as a hypothesis for future testing rather than as a demonstrated agronomic benefit, and the applied microplastic doses (1.5–3.0% w/w) exceed most reported field levels and were chosen to resolve mechanisms under accelerated conditions. Full article

Wearable assistive exoskeletons require lightweight, compact, and backdrivable transmission systems with low output impedance to ensure safe and comfortable human–robot interaction. These efficient, modular actuators benefit from reduction mechanisms that minimize axial bulk while providing high motion regularity. While existing transmissions perform well on some of these metrics, their practical implementation is often constrained by geometric complexity, low backdrivability, limited reduction ratios, or standard component sizes. This paper presents a novel combination of a Rolling Element Eccentric (REE) stage and a planetary gearbox, specifically designed for wearable exoskeleton actuation. The proposed architecture integrates a bearing-based REE drive concentrically within the sun gear of a planetary transmission, reducing mechanical complexity and friction and improving regularity. Moreover, the design exploits additively manufactured bearings, enabling substantial weight reduction, reduced encumbrance, and increased design freedom without reliance on standard bearing dimensions. A prototype reducer has been designed and fabricated using additive manufacturing techniques. It was experimentally evaluated and compared with state-of-the-art transmission designs. These investigations demonstrated low friction, minimal backlash, good torsional stiffness, and sufficient backdrivability, despite the high reduction ratio, while maintaining a compact, flat form factor. The experimental results indicate that the proposed rolling element eccentric planetary transmission is a viable and effective solution for lightweight, efficient, axially compact (independently of the implemented reduction ratio), and backdrivable actuators in assistive wearable robotics. Full article

Neuropsychiatric systemic lupus erythematosus (NPSLE) is a severe manifestation of lupus marked by cognitive and mood disorders, yet the molecular mechanisms underlying hippocampal dysfunction remain poorly understood. To address this, we performed bulk RNA sequencing on hippocampal tissue from 17-week-old female MRL/Lpr mice and MRL^+/+ controls, followed by an integrative multi-layered analytical workflow. Differential gene expression analysis identified 223 significant differentially expressed genes, with a predominant downregulation of myelin-related transcripts. Gene set enrichment analysis confirmed coordinated suppression of oligodendrocyte differentiation, neuron ensheathment, and Wnt signaling programs. Weighted gene co-expression network analysis identified a disease-associated module enriched in myelination and glial developmental pathways, with hub genes spanning structural, transcriptional, and adhesion-related functions. Cell-type deconvolution revealed a selective reduction in mature oligodendrocytes, while oligodendrocyte precursor cells remained largely unaffected, consistent with impaired lineage maturation rather than global loss. RT-qPCR and Western blot validated the repression of key myelin-related genes and MBP protein in MRL/Lpr hippocampi. Collectively, these findings challenge an inflammation-centric interpretation of NPSLE hippocampal pathology, highlighting instead an additional contribution of impaired oligodendrocyte maturation. This transcriptomic resource establishes a molecular foundation for future mechanistic and histological investigations. Full article

The galaxy size–mass relation (SMR) is a key scaling relation used to constrain the physical processes that build galaxy structure, yet it is almost always measured in a single rest-frame optical band, where the light traces the bulk of the old stellar mass. Tracing younger populations with flux-weighted ages of ∼100–500 Myr and low-metallicity stars, the rest-frame near-ultraviolet opens a new stellar window on this scaling relation. Because each process redistributes the light of young and old stars differently, the same mechanism shifts the slope and zero point of the SMR by different amounts in the two wavelength regimes. Here we review and synthesize the effects of main physical processes on the form of the SMR for star-forming and quiescent galaxies in the rest-UV and optical. For each process, we start from its underlying physics, the galaxy stellar masses it affects, and the light it adds/removes/rearranges, anchoring the predictions to observations and simulations. We validate the predicted imprints with forward Monte Carlo modelling. The two-wavelength view breaks several degeneracies that single-band analyses cannot, most notably between minor mergers, dry major mergers, and adiabatic expansion. These results motivate joint rest-UV and optical SMR measurements with current and upcoming wide-field imaging surveys. Full article

Background: Impaired glucose tolerance (IGT) is the principal prediabetic stage preceding type 2 diabetes mellitus (T2D), yet islet-specific biomarkers capable of tracking progressive molecular changes from normal glucose tolerance (NGT) through IGT to T2D remain unestablished. We sought to identify a multi-gene biomarker panel with monotonically increasing expression and causal support across the full glycemic continuum. Methods: Two human islet transcriptomic datasets (GSE76895, GSE164416; n = 181: NGT 50, IGT 56, T2D 75) were integrated following ComBat batch correction. Candidate biomarkers were identified at the intersection of limma differential expression and weighted gene co-expression network analysis (WGCNA), then refined through a five-algorithm machine learning consensus (LASSO, random forest, XGBoost, SVM-RFE, elastic net). Progressive expression was assessed by the Jonckheere–Terpstra (J–T) trend test. Two-sample Mendelian randomization (MR) with eQTLGen cis-eQTL instruments, Steiger directionality testing, and Bayesian colocalization provided causal inference. A diagnostic model was internally validated via 1000-iteration bootstrap resampling. Cell-type specificity was verified using single-cell RNA sequencing (GSE200044; 127,919 cells). Results: A 12-gene biomarker panel (ALDOB, DKK3, PCOLCE2, KCNE4, INHBA, IRF8, ITGB2, LAPTM5, MYOF, RAMP3, RUNX2, S100A4) was identified, with all members passing Bonferroni-corrected J–T trend testing across the NGT–IGT–T2D axis (p ≤ 2.4 × 10⁻³). Notably, a direct IGT-versus-NGT transcriptome-wide comparison (11,948 genes) yielded no significant DEGs after FDR correction, indicating that prediabetic islet signals are subtle and detectable only through progressive trend analysis on preselected candidates. Nevertheless, the mean IGT-stage effect size of the 12 hub genes reached 41.9% of the T2D value, with KCNE4 achieving 94.0% (nominal p = 1.75 × 10⁻⁴), identifying it as the earliest-altered biomarker. Two-sample MR using whole-blood eQTLs suggested protective effects of genetically proxied MYOF (OR 0.999, FDR = 1.68 × 10⁻⁴) and RUNX2 (OR 0.998, FDR = 1.68 × 10⁻⁴) on T2D risk, with Steiger testing supporting an expression-to-disease direction (p < 10⁻³⁶). However, Bayesian colocalization indicated independent causal variants at both loci (PP.H3 > 0.76, PP.H4 < 0.001), substantially weakening the causal interpretation and suggesting that the MR associations may reflect linkage disequilibrium rather than shared causal biology. The panel achieved a bootstrap-corrected AUC of 0.833 (apparent 0.879) with PR-AUC of 0.951. Single-cell validation confirmed upregulation of 7 hub genes in β cells and revealed cell-type-specific patterns invisible in bulk data, including bidirectional INHBA regulation between β and α cells and progressive α-cell proportion expansion (28.97% → 46.41%). Pathway enrichment converged on three mechanistic axes: extracellular matrix remodeling, immune activation, and autoimmune-like responses, with direct enrichment of the type 1 diabetes pathway (hsa04940). Conclusions: This study establishes a 12-gene progressive islet biomarker panel spanning the NGT–IGT–T2D continuum, supported by machine learning robustness, genetic causal evidence, diagnostic modeling, and single-cell biological validation. KCNE4 emerges as a candidate early-warning biomarker for prediabetes, while MYOF and RUNX2 represent causally supported compensatory targets, collectively providing a multilayered foundation for T2D risk stratification and precision intervention. From a clinical perspective, the identification of progressive islet biomarkers at the prediabetic stage provides molecular support for early lifestyle intervention, reinforcing that timely detection and behavioral modification remain the most effective strategies to prevent T2D progression. Full article

Organic solar cells are widely recognized for their flexibility, light weight and semitransparency, all relevant for niche applications. A significant challenge in their development lies in the accurate prediction of their power conversion efficiency depending on the combination of the donor and acceptor selected in the bulk heterojunction. To address this issue, we developed a robust machine learning (ML) framework designed to establish correlations between molecular structure and device performance. A feature selection strategy, incorporating SHapley Additive exPlanations and Boruta algorithms, was employed to extract the most informative descriptors. Among the regression models that were systematically evaluated on a curated dataset comprising 1575 experimentally characterized donor–acceptor pairs, histogram-based gradient boosting demonstrated superior predictive performance, giving an R² score of 0.79, with a low root mean square error of 2.16. Subsequently, the optimized model was used to predict new donor–acceptor pairs with PCEs above 20% and identify prospective candidates for further experimental validation. Full article

Polystyrene (PS) thermal degradation involves localized molecular bond-cleavage events that are not directly equivalent to the apparent kinetic parameters obtained from bulk thermal analysis. In this study, a finite hydrogen-terminated PS oligomeric model was examined using density functional theory at the M06-2X/LANL2DZ level, whereas the non-isothermal degradation behavior of a PS sample was independently evaluated by thermogravimetric analysis under nitrogen. The computational analysis considered frontier molecular orbital distributions and site-specific thermodynamic descriptors associated with homolytic C–C cleavage and radical-mediated β-scission reactions. The calculated HOMO–LUMO gap of 742.62 kJ mol⁻¹ indicated a comparatively large orbital-energy separation within the selected oligomeric model, while the localization of the frontier orbitals over aromatic and benzylic regions revealed a spatially heterogeneous electronic distribution. Homolytic C–C cleavage exhibited bond dissociation energies ranging from 414.09 to 481.24 kJ mol⁻¹, demonstrating that the thermodynamic requirement for radical generation depends on the local molecular environment of the evaluated structure. The Gibbs free-energy changes calculated for the selected radical β-scission reactions ranged from 55.44 to 189.41 kJ mol⁻¹. These quantities represent model-dependent reaction thermodynamics and should not be interpreted as activation barriers because transition states were not calculated. Thermogravimetric analysis showed systematic increases in Tonset and Tmax with increasing heating rate, consistent with kinetic delay and thermal-lag effects under non-isothermal conditions. The Kissinger method yielded a global apparent activation energy of 186.61 kJ mol⁻¹, whereas the residual-mass-corrected Flynn–Wall–Ozawa and Kissinger–Akahira–Sunose methods produced average apparent activation energies of 180.81 and 178.49 kJ mol⁻¹, respectively, over α = 0.05–0.95. Across the same conversion interval, the FWO apparent activation energy increased from 143.10 to 221.71 kJ mol⁻¹, while the KAS values increased from 140.10 to 220.23 kJ mol⁻¹, indicating an evolving macroscopic degradation response with greater uncertainty toward high conversion. The computational and experimental datasets were therefore interpreted as complementary but non-equivalent scale-dependent descriptions: DFT compares the relative thermodynamics of selected molecular reactions within a finite isolated oligomer, whereas TGA characterizes the global apparent kinetic behavior of the condensed polymer sample. No direct numerical correspondence was established between the molecular reaction energies and the TGA-derived apparent activation energies, and no individual cleavage reaction was assigned to a specific conversion interval. Extrapolation of these results to high-molecular-weight, polydisperse, additive-containing, cross-linked, or environmentally aged PS microplastics should therefore be made with caution. Full article

Liquefaction and dynamic separation of moisture-sensitive solid bulk cargoes may remain latent for much of a voyage and then manifest as a sustained heel, leaving a comparatively short interval for emergency action. This study develops an exploratory reliability-based analysis of accident chronology using a source-traceable registry of 35 casualties and incidents. Eighteen cases provided post-heel information suitable for the principal emergency time reserve analysis; the observations comprised exact, approximate, reconstructed, interval-censored, and right-censored times. Descriptive statistics calculated from the selected central values and censoring bounds yielded a mean emergency time reserve TR of 200.99 min, a median of 192.20 min, and a range of 67.50–335.10 min. In likelihood-based fitting that retained censoring, the Weibull model achieved the lowest AIC (212.51) and BIC (215.18), with Kolmogorov–Smirnov D = 0.097 (p = 0.989). The fitted lower-tail quantiles were Q10 = 105.40 min and Q25 = 147.99 min, substantially shorter than the descriptive mean. Robustness was examined using nonparametric estimators, Akaike-weighted model averaging, source-confidence weighting, leave-one-out analysis, and alternative interval assumptions. The contribution is a reproducible framework for converting heterogeneous casualty narratives into uncertainty-qualified lower-tail time-reserve evidence and non-prescriptive bridge–team decision support. The framework is not a physical stability model and cannot replace ship-specific GM/GZ calculations, approved loading and stability information, or the master’s judgement. Full article

Patulous Eustachian Tube (PET) is a rare otologic disorder, which is caused by abnormal patency of the Eustachian tube. Rapid weight loss is a recognized predisposing factor for PET potentially because of the reduction in peritubal adipose tissue that contributes to normal tubal closure. Although there is increasing awareness of this association, the best treatment of PET is still debated with several conservative, medical and surgical operations reported in the literature. This narrative review summarizes the available evidence regarding conservative, medical, minimally invasive, and surgical management of PET, with particular consideration of PET associated with rapid weight loss. Relevant literature was identified through searches of PubMed/MEDLINE, Embase, Web of Science, and the Cochrane Library, with attention to studies using standardized diagnostic criteria and outcome measures. Conservative approaches, including hydration, nasal saline instillation, and behavioral modifications such as cessation of habitual sniffing, have been associated with symptomatic improvement and considered as initial options because of their accessibility and low procedural burden. Medical therapies, such as topical irritants, estrogen-based preparations, and mucosal-thickening agents, may provide temporary symptom relief, although their long-term effects require further evaluation. Among interventional strategies, silicone (Kobayashi) plug insertion has demonstrated encouraging symptom improvement and reductions in symptom scores in selected patients with refractory PET. Minimally invasive techniques, including autologous fat injection, cartilage augmentation, and soft tissue bulking procedures, have also demonstrated encouraging outcomes. Trans-tympanic interventions, including ventilation-tube insertion and catheter-based techniques, provided additional options with variable reported outcomes. Management of PET remains heterogeneous and largely individualized. Conservative and medical therapies are considered reasonable first-line options, while surgical and minimally invasive approaches may be considered for selected patients with persistent symptoms. Full article

Belt conveyors are essential to continuous ore and bulk-material transport, yet the diagnostic signatures of slippage, belt breakage, deviation and overheating tend to appear as coupled changes across multiple variables rather than isolated in a single signal. This study presents a multi-model and explainable diagnostic framework using belt speed, motor temperature, motor current, drum temperature and belt tension. A balanced dataset containing 1500 observations from five operating states was analyzed under a unified protocol. Eleven classifiers were compared using identical stratified partitioning and cross-validation, and a perturbation-based validation set was introduced to test whether near-ceiling baseline scores would hold under sensor noise and boundary-state drift. The measurements were preserved without alteration, and the perturbation set was treated explicitly as a sensitivity analysis. The baseline test confirmed strong class separability; the robustness-validation setting, in contrast, gave a more conservative picture of model behavior and revealed differences invisible in the ordinary hold-out split. Logistic regression reached accuracy = 0.800, macro-F1 = 0.798 and weighted AUC = 0.946 under perturbation. SHAP analysis showed that motor current, belt tension, motor temperature and belt speed were the dominant contributors, while drum temperature played a much weaker role. The results suggest that conveyor fault diagnosis should be reported with model comparison, robustness analysis and feature-level explanation together, particularly when ordinary ROC curves approach one and the practical value of a model must be weighed against uncertainty. Full article

The study investigates the effects of high-energy laser treatment on titanium-based alloys, TiAlV, TiNbZr, and TiNbSnTa, materials of high interest for medical applications such as implants and dental devices due to their exceptional strength-to-weight ratio, corrosion resistance, and biocompatibility. In this research, a unique high-energy laser was used for Ti-based surface activation. The laser exposure induced significant changes in both surface morphology and chemistry while preserving the bulk properties of the substrate. The modified surfaces were evaluated for their impact on cytocompatibility and antibacterial activity. It was found that viability of U-2 OS cells incubated with laser-treated Ti-based substrates was not negatively affected and was comparable to or slightly higher than that of control samples, indicating very good cytocompatibility of the prepared materials. Further, antibacterial evaluation against E. coli and S. epidermidis demonstrated that laser-treated samples had improved activity, especially against S. epidermidis, relative to untreated controls. Thus, these results demonstrate that high-energy laser treatment can simultaneously enhance the biocompatibility and antibacterial properties of titanium alloys, highlighting its potential as a versatile surface modification strategy for advanced biomedical devices. Full article