Browse Articles

Dynamic response characteristics, load-bearing efficiency in multimaterial tunnel assemblies subjected to recurrent intense fluid loading

HyMSS-GAD: a hybrid multi-stage framework for multi-view graph anomaly detection with structural, contextual, and geometric reasoning

Pharmacophore-driven kinase profiling applied to the PKIS2 chemogenomic dataset

Abstract We present a data-driven and unsupervised approach for extracting 3D pharmacophore hypotheses, without prior ligand selection, from a chemogenomic kinase dataset (406 kinases and 645 compounds, PKIS2). A metric called NEM for Normalized Enrichment Measure is introduced for each pharmacophore, which quantifies change in the proportion of active compounds consistent with the pharmacophore compared to the original dataset. Based on this metric, we can identify pharmacophores associated with specific kinases and, conversely, determine all kinases that share similar metric values. This approach enables the characterization of polypharmacological profiles linked to individual pharmacophore hypotheses. We further evaluate the consistency of our results with various biological datasets, including ChEMBL, DrugBank, LINCS, KINOMEscan, and Kinobeads, showing agreement across representative case studies. This study highlights the potential of our approach for elucidating relationships between pharmacophores and kinase selectivity profiles, providing a scalable framework for exploring kinase–ligand interaction landscapes.

Nanoformulation of pomegranate peel extract enhances anti-psoriatic efficacy in a rat model

Abstract Psoriasis is a chronic inflammatory disease affecting 2% of the global population. Current treatments (e.g., corticosteroids and phototherapy) face limitations such as adverse effects and poor bioavailability, necessitating safer, more effective alternatives. Pomegranate ( Punica granatum L.) peel, rich in bioactive compounds with antioxidant and anti-inflammatory properties, holds therapeutic potential but suffers from low stability and solubility. Here, we developed pomegranate peel extract nanoparticles (PGNPs) to overcome these limitations and evaluated their efficacy in psoriasis management. Pomegranate peel extract (PGE) was prepared and transformed into PGNPs via acid hydrolysis. Nanoparticles were characterized for size, stability, and bioactivity. In vitro assays assessed cytotoxicity, antioxidant (DPPH), and anti-inflammatory (hemolysis inhibition) effects. In vivo efficacy was tested in imiquimod-induced psoriatic rats ( n  = 20) divided into negative control (group I), untreated psoriasis (group II), PGE-treated (200 mg/kg, group III), and PGNPs-treated (100 mg/kg, group IV). Outcomes included oxidative stress markers (MDA, SOD, CAT, and GSH), cytokines (IL-6, IL-17, IFN-γ, and IL-10), and histopathology. PGNPs exhibited superior stability (size: 87–91 nm; zeta potential: +41–44 mV) and lower cytotoxicity than PGE (15.2% vs. 31.2% at 1000 µg/mL). In vitro, PGNPs showed higher antioxidant (96.63% DPPH scavenging) and anti-inflammatory (94.66% hemolysis inhibition) activity. In vivo, PGNPs reduced psoriatic lesions more effectively than PGE, normalizing oxidative stress (MDA: 7.26 vs. 12.22 nmol/g tissue) and inflammatory cytokines (IL-17: 102.20 vs. 123.40 pg/g tissue; IFN-γ: 204.40 vs. 216.80 pg/g tissue). Histopathology confirmed enhanced skin regeneration with PGNPs. PGNPs demonstrated enhanced bioavailability, stability, and therapeutic efficacy over crude extract, significantly mitigating psoriasis-like inflammation in rats. These findings highlight PGNPs as a promising nanotherapy for psoriasis, warranting further clinical exploration.

Haptic feedback in violin education as a case study of robotic exoskeleton-mediated motor learning

Abstract This study explores the use of an upper-limb wearable exoskeleton for teaching violin technique to novices through haptic-assisted training. The educational potential of this technology was evaluated using a framework that integrated quantitative kinematic metrics and qualitative assessments, comparing a group receiving haptic feedback ( N  = 12) with a control group that did not ( N  = 12) in a mixed between-within-subjects design. Results from a double-blind expert panel indicated that participants trained with the exoskeleton outperformed the control group during recall measurements. In addition, spatial and spatiotemporal - but not temporal - kinematic metrics related to bowing technique improved significantly during training, with gains persisting during recall, and these outcomes were supported by self-reported user assessments. However, subtle features of the technology also became apparent, including interference with natural shoulder movements, exposing areas for refinement. In conclusion, this study suggests that haptic-assisted training with an exoskeleton can enhance specific motor skills in violin playing, highlighting promising directions for future research in educational technology and providing a quantitative framework for assessing motor skill development in haptic-assisted learning, which can further support the development and validation of educational technologies. However, given the absence of long-term retention measurements and the limited generalizability associated with the small sample size, the findings of this pilot study should be interpreted with caution.

Novel proteolytic post-translational modification in voltage-gated potassium channel KCNQ2

Abstract KCNQ2 is a member of the voltage-gated potassium (Kv) channel family and regulates neuronal activity through potassium ion efflux. Pathogenic variants of KCNQ2 induce aberrant neuronal activity and cause two types of epilepsy: self-limited familial neonatal epilepsy (SLFNE) and developmental and epileptic encephalopathies (DEE). However, the molecular mechanism by which these pathogenic variants influence KCNQ2 expression remains unclear. Here, we show N-terminal and C-terminal fragments derived from mouse KCNQ2 (KCNQ2 S−N and KCNQ2 S−C , respectively), whose amounts differed significantly across variants compared with wild type, whereas those of full-length KCNQ2 (KCNQ2 F ) remained unchanged. Of particular interest, two variants at the same codon, Y284C and Y284D, which are associated with distinct clinical phenotypes—self-limited familial neonatal epilepsy (SLFNE) and developmental and epileptic encephalopathy (DEE), respectively—exerted opposite effects on the fragment: Y284C increased the amounts of both KCNQ2 fragments, whereas Y284D decreased it compared with the wild type. As both KCNQ2 S−N and KCNQ2 S−C were localized in the plasma membrane, both fragments were suggested to be post-translational products resulting from a cleavage of full-length KCNQ2. This novel post-translational cleavage was observed in neuronal cells and appears to be evolutionarily conserved. Although the role of this post-translational modification in epilepsy remains unknown, it may be elucidated through future studies.

Advanced stacked modeling techniques for material porosity estimation via high-resolution computed tomography imaging

Cut instance mixing: A domain-specific data augmentation method applied to gastrointestinal lesion detection

Abstract Early detection of gastrointestinal lesions such as intestinal metaplasia (IM), dysplasia, and polyps remains challenging due to their subtle appearance and the scarcity of well-annotated medical image datasets. To address this limitation, we introduce Cut Instance Mixing (CIM), a domain-specific data augmentation method designed to generate anatomically plausible lesion-containing images through the identification of biologically relevant regions of interest and seamless lesion blending using Poisson image editing and gradient-based mixing. CIM was evaluated across three distinct endoscopic datasets (IM, dysplasia, and polyps) using a ResNet50 classifier and five-fold cross-validation. The proposed method consistently outperformed state-of-the-art augmentation techniques. In IM classification, CIM with α = 0.8 achieved the highest performance (AUC: 0.879, Accuracy: 0.823), surpassing MixUp, CutMix and random copy-paste. In dysplasia detection, CIM reached near-perfect results (AUC: 0.997, Accuracy: 0.966), and demonstrated strong generalization on an external polyp dataset (AUC: 0.830, Accuracy: 0.769). Grad-CAM analyses further confirmed that CIM preserves clinically relevant features, improving model attention on lesion regions. These findings demonstrate that CIM enables the generation of realistic and biologically coherent synthetic samples, effectively mitigating data imbalance and enhancing classification robustness. The method is architecture-agnostic and broadly applicable to tasks requiring anatomically consistent augmentation, providing a promising direction for improving deep learning systems in gastrointestinal imaging.

Mechanistic investigation of ammonium nitrogen adsorption on low-temperature pyrolysis cotton stalk biochar based on DFT calculations

Construction of automatic air monitoring point siting model based on convolutional neural network and K-means clustering

Analysis of the performance of a virtual gauge-based method in hydrological modeling of basins with no precipitation stations

Phytochemical responses of Dracocephalum kotschyi Boiss. to water deficit stress and different fertilizers

A qualitative study exploring critical care survivors’ and their clinicians’ shared experiences of navigating a fragmented care system

Abstract Recovery following a critical illness is challenging. Follow-up clinic provision is standard of care, but the effectiveness of services remain unclear, with some data demonstrating limited or potential detrimental effects. While the patients’ perspective has been described previously, no studies combine with clinician experience. We explored this combined experience to understand modifiable factors in effective delivery of critical care follow-up services. We conducted a single-centre qualitative interview study in a large UK adult critical care service as part of an evaluation of a pilot follow-up service. Semi-structured interviews with sixteen patients and seven clinicians were analysed using reflexive thematic analysis. Patients experienced uncertainty, fragmented care, and psychological distress as immediate, ongoing challenges marked by a lack of guidance and support. Clinicians described the same broad issues but perceived them somewhat differently, as reflecting the inherent unpredictability of recovery, and caused by delayed presentation of needs, and the constraints imposed by complex care systems. By combining patient and clinician perspectives, our study identifies mismatches in expectations, timing of support, and perceived responsibility. Our data highlight the need for systemic improvements in follow-up care and the importance of integrated social and healthcare services to ensure that patients receive timely and comprehensive support.

Associations between early-life adversity, coping strategies, and adult mental health, brain, and cognition

Abstract Early adversity is associated with later mental health, brain, and cognitive outcomes, but the pathways are complex and may involve coping strategies and individual vulnerabilities. We investigated associations between early adversity, coping strategies, neuroticism, and adult mental health, cognition, and global brain volumes. Path analysis was applied to behavioural and imaging data from the UK Biobank dataset ( N  = 472,450, Mdn age = 58, SD age = 8.03, 54.46% of women). All assessed early adverse experiences were associated with greater anxiety symptoms, while all except physical neglect were associated with increased depressive symptoms. Physical neglect was the only adversity associated with poorer cognitive performance, and no adversity showed a direct association with global grey- or white-matter or cerebrospinal fluid volumes. Several indirect pathways were observed: specific coping strategies and neuroticism significantly mediated links between early adversity and adult mental health, cognition, and cerebrospinal fluid volume. These findings are consistent with prior work linking early adversity to adult mental health and brain measures, and highlight coping behaviours and neuroticism as mediating factors. Strengthening adaptive coping may mitigate some detrimental associations, but causal inference is limited by the cross-sectional study design.

Analyzing the impact of gender-specific vaccination strategies and behavioral dynamics on HPV transmission

Investigation of the propagation behavior of hydraulic fractures and its influencing mechanisms in fractured reservoirs based on a hydromechanical coupling numerical model

RETRACTED ARTICLE: Flavokawain C suppresses nephroblastoma growth by inducing autophagy-mediated downregulation of FABP4 via AMPK/mTOR pathway

Mutation type, tyrosine kinase function in normal cell and tyrosine kinase inhibitor activity in cancers

Beyond decoration: free-standing lace embroidery for 3D shaped surgical mesh implants

Abstract Conventional mesh pockets manufactured from flat textiles by cutting and sewing often display wrinkles, excess material, and suboptimal fit on curved surfaces. This study demonstrates that free-standing lace embroidery enables the production of near-net-shape hemispherical mesh pockets with predefined pore geometries using standard embroidery machines. These pockets are scalable to different implant sizes and shapes. Experimental evaluations, including tensile and drop testing as well as 3D surface scanning, confirmed that the pockets are mechanically robust and exhibit excellent conformity with minimal wrinkling. These results highlight the potential of embroidery as a versatile platform for developing patient-specific surgical mesh implants.

Reliability prediction of crane brakes based on the bayesian method