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First photos from Artemis II: see stunning ‘Earthset’ and more
OR7A10 GPCR engineering boosts CAR-NK therapy against solid tumours
Machine learning–based risk stratification identifies heart failure with preserved ejection fraction as an independent predictor of adverse outcomes in hypertrophic cardiomyopathy
Scientists invented a fake disease. AI told people it was real
Investigating non-linear volume-outcome relationships in total knee arthroplasty based on a sample of more than 60,000 hospital cases from Germany, 2020–2023
Perceived human-robot relational structures: a pictogram-based questionnaire to assess ideal and assumed relationships
Abstract Evaluations in human-robot interaction (HRI) have traditionally focused on surface-level impressions such as likability and anthropomorphism, often neglecting the underlying relational structures that define mutual contributions and shared goals. Understanding these relational dynamics is crucial for fostering effective and sustainable human-robot collaborations. Here, we developed and validated a novel pictogram-based questionnaire grounded in social psychology to capture relational structures, conducting three scenario-based online surveys. We examined ideal and assumed relational structures in human-human and human-robot contexts across varying robot appearances, roles, and utterances. We distinguish between ideal relational structures (what users would like to establish; Surveys A and B) and assumed (expected) relational structures (what users believe would emerge under the described conditions; Survey C). Our results reveal that ideal relational structures vary by human relationship type, and that a robot’s communicative behavior significantly influences perceived relational structures, often more than physical appearance. These findings suggest that assessing relational perceptions can inform the design of robots better aligned with user expectations, enhancing long-term engagement and collaboration in HRI.
Unlocking shale gas potential in the Sembar Formation through multi-analytical assessment and basin modeling, Central Indus Basin, Pakistan
Identification of hub genes and molecular networks involved in alveolar bone resorption based on bioinformatics analysis
Abstract Periodontitis is the leading cause of tooth loss, with alveolar bone resorption serving as its fundamental pathological feature. Identifying key regulatory genes and molecular mechanisms is essential for enhancing preventive and therapeutic strategies. Nevertheless, reliable biomarkers and comprehensive regulatory networks have yet to be elucidated. This study aims to systematically identify candidate alveolar bone resorption hub genes (ABRHUB) and their regulatory networks through bioinformatics analysis. Our objective is to establish a bioinformatics foundation for generating hypotheses about the mechanisms underlying periodontitis progression and to identify potential targets for future experimental validation. The GSE16134 dataset extracted from the GEO database was utilized to screen differentially expressed genes in patients with periodontitis and explore the significance of alveolar bone resorption in the prevention and treatment of this condition. Furthermore, these genes were intersected with modular genes screened by weighted gene co-expression network analysis (WGCNA) as well as osteoclast-related genes obtained from molecular characterization databases, and co-expression differential genes (co-DEGs) were obtained. The co-DEGs were subjected to in-depth analysis using various machine learning algorithms. The validation set GSE10334 and qRT-PCR analysis were utilized for double validation, ultimately confirming ABRHUB. The diagnostic value and immune relevance of ABRHUB were further evaluated, and the potential miRNAs and lncRNAs associated with these key genes were predicted using relevant databases. A significant correlation exists between alveolar bone resorption and periodontitis. Through differential analysis of multiple databases and the integration of machine learning techniques, we identified four key ABRHUB genes: NEDD9, P2RX5, CSF1R and NPR3. Subsequently, we validated these genes using the GSE10334 validation set and quantitative reverse transcription polymerase chain reaction (qRT-PCR) analyses, and constructed diagnostic and risk models to elucidate the potential utility of ABRHUB in predicting alveolar bone resorption. Furthermore, the calibration curves we established further validated the accuracy of the model predictions. Ultimately, based on these ABRHUB genes, we constructed a lncRNA-miRNA-mRNA molecular regulatory network, providing a significant bioinformatics foundation for future studies. Four genes associated with osteoclast function, namely NEDD9, P2RX5, CSF1R and NPR3, may serve as potential candidate biomarkers for alveolar bone resorption. Notably, the down-regulation of miR-1260b, miR-1224-5p, miR-3156-5p and miR-4286 may contribute to the progression of periodontitis by promoting the expression of NEDD9, P2RX5 and CSF1R.
Experimental and numerical evaluation of a novel swirling reversed circular flow jet impingement for photovoltaic thermal module
Association of physical activity with motoric cognitive risk syndrome among the middle-aged and older adults in China
Analyzing bamboo-based enterprises in Injibara, Amhara Region, Northwest Ethiopia
Massive budget cuts for US science proposed again by Trump administration
Psychological profiles of mindfulness and tourist fatigue: a latent profile analysis in a digital travel context
A comparison of dental professionals’ and patients’ perceptions in assessing smile esthetics
A transverse picoNewton force revealed in anisotropic Womersley flow
Abstract The fluid-dynamic quantity that regulates endothelial mechanotransduction remains unsettled. Wall Shear Stress (WSS) characterizes boundary traction but does not represent the volumetric inertial structure of arterial blood flow. Meanwhile, blood exhibits direction-dependent stress under physiological shear, suggesting that the classical Womersley solution of the Navier-Stokes equation may omit constitutive mechanisms relevant to near-wall dynamics. Here, I derive an anisotropic extension of Womersley flow by introducing a tensorial viscosity into the incompressible Navier–Stokes equations. By evaluating the nonlinear interaction of velocity and vorticity within a near-wall control volume, I demonstrate that anisotropic viscosity produces a non-trivial spectral signature in the transverse forcing, maintaining power across higher-order harmonics. While macroscopic geometric drivers dominate the bulk flow at the fundamental cardiac frequency, they are subject to significant inertial damping as the harmonic frequency increases. In contrast, the anisotropy-induced Lamb vector, sustained by the sharp gradients of the oscillatory boundary layer, evades this macroscopic attenuation. These findings define a geometry-independent baseline for multidirectional pulsatile dynamics and provide a theoretical basis for future spectral investigations of endothelial mechanobiology under high-frequency, near-wall inertial stimuli.
Longitudinal stability of cognitive impairments in post-COVID-19 syndrome assessed with the tablet-based Oxford Cognitive Screen-Plus
Abstract In a previous cross-sectional study using the tablet-based Oxford Cognitive Screen-Plus (OCS-Plus), deficits in delayed memory, attention, and executive functioning were identified in working-age patients with post-COVID-19 syndrome (PCS) following infection in 2020 or early 2021. Initial assessment occurred approximately five months after infection. To examine short-term longitudinal trajectories, patients were reassessed several months later. Eighty-one patients with PCS (mean age 46.6 years, 64% female) completed OCS-Plus assessments at baseline and after a median follow-up of 4.4 months. Cognitive change was analysed using Wilcoxon signed-rank tests and equivalence testing (± 1 SD of reference scores) to assess clinical relevance. Associations between cognitive change and changes in depression and fatigue were examined using bootstrap-corrected multiple regression. No significant change in cognitive performance was observed between baseline and follow-up across any cognitive domain (all p > 0.3). Equivalence testing indicated that observed differences fell within predefined bounds of clinical insignificance (all p < 0.01). Changes in depressive symptoms and fatigue were not associated with changes in cognitive performance. Across the observed follow-up period, domain-level cognitive performance remained stable, with no evidence of short-term spontaneous improvement. These findings suggest short-term longitudinal stability of cognitive impairments in PCS within the limits of screening-based assessment and the follow-up interval studied, supporting the value of continued cognitive monitoring in affected individuals.