Browse Articles

Three-dimensional analysis of facial soft-tissue movement during mastication in children with lip incompetence

A continuous network physiology analysis of brain–heart interactions in epileptic seizures

Abstract The investigation of brain–heart interplay (BHI) has gained significant momentum in recent years, and has emerged as a pivotal area of neurophysiological research. The applications of BHI span cognitive neuroscience, sleep research, and neurological disorders, where the analysis of cortical and autonomic dynamics can provide a mechanistic overview of functional regulation. Epilepsy is known to have an impact on cardiovascular function and autonomic regulation, and the analysis of BHI offers a valuable framework for understanding the dynamics behind autonomic dysfunction in epilepsy. In this work, we use the framework of network physiology (NP) to derive a time-varying time delay stability (TDS) metric to characterize the continuous evolution of the brain–heart network. We further validated the framework on a publicly available dataset of temporal lobe epilepsy (TLE) subjects. The results from the analysis revealed that TDS coupling between brain and heart dynamics changed significantly following an epileptic episode, suggesting instability in the brain–heart network that may reflect altered autonomic and cortical communication in that period. The methodology presented in this work may serve as an informative framework to characterize cortical and autonomic interplay, and could be further explored in the study of disorders characterized by cortical and autonomic dysregulation.

Performance level controlled efficiency of graphene nanoplatelets in cementitious composites

Applying prior knowledge of regulatory signaling to investigate macrophage cAMP dynamics during Mycobacterium tuberculosis infection

Synthesis, characterization, and biocompatibility evaluation of donepezil-loaded magnetite-PLGA nanoparticles in neuroblastoma cells

Abstract This work explores the potential of magnetite polymeric nanoparticles (MPNs) encapsulating Donepezil (DPZ) to evaluate its delivery potential in SH-SY5Y human neuroblastoma cells. The MNPs coated with oleic acid (OA) were synthesized via co-precipitation, resulting in oleic acid-coated magnetite NPs (OAMNPs). These were combined with Poly(lactic-co-glycolic acid) (PLGA) and DPZ to create the nanohybrid, OAMNPs-PLGA-DPZ. The nanohybrid has been characterized utilizing Dynamic light scattering (DLS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Transmission electron microscopy (TEM). Drug loading capacity (LC%) and encapsulation efficiency (EE%) were quantified by Ultraviolet-Visible Spectrophotometry (UV-Vis), and in‑vitro drug release was evaluated at physiological pH 7.4. Finally, the cytotoxicity of OAMNPs-PLGA-DPZ on SH-SY5Y cells was determined using an MTT assay. The crystalline size of OAMNPs-PLGA-DPZ, as revealed by XRD, ranged from 20 to 60 nm, and the wurtzite crystal structure size was 12.95 nm. The FTIR spectra showed that DPZ was successfully encapsulated within the PLGA matrix, and the TEM images revealed the synthesis and production of OAMNP-PLGA-DPZ. Biocompatibility evaluation demonstrated an IC₅₀ of 13.5 ± 2.12 µg/mL as a baseline for the safety profile after 48 h of exposure. Taken together, these findings suggested that OAMNPs‑PLGA‑DPZ represent a foundational drug‑delivery platform with potential applications for neurodegenerative diseases.

Exploratory analysis of biofilm formation and virulence gene expression in Acinetobacter baumannii–Candida albicans co-cultured isolates from urinary tract infections

Abstract Polymicrobial infections with Acinetobacter baumannii (A. baumannii) and Candida albicans ( C. albicans ) are increasingly frequent in urinary tract infections (UTIs). However, experimental data describing their interactions in clinical isolates under co-culture conditions remain limited. In this study, three clinical isolates of both A. baumannii and C. albicans were co-isolated from urine samples with UTIs, then mono-cultured and co-cultured at 24, 48, and 72 h for biofilm quantification by crystal violet assay. The expression levels of bacterial ( ompA, bap, abaI ) and fungal ( ALS3, HWP1, ERG11 ) virulence genes were evaluated by RT-qPCR at 24 and 48 h. Co-culture conditions resulted in increased biofilm biomass compared to monoculture for the tested isolates. In A. baumannii, the virulence genes of bap, abaI, and ompA showed statistically significant increase in expression in co-culture compared to mono-culture after 24 h. In C. albicans , HWP1 is the only virulence gene that shows a statistically significant increase in expression in co-culture compared to monoculture after 48 h. Gene expression patterns varied in patient isolates, suggesting strain heterogeneity. This is an exploratory study that provides evidence of changes in biofilm formation and virulence gene expression in co-culture conditions among clinical isolates of A. baumannii and C. albicans . These findings suggest potential for microbial interactions under polymicrobial conditions, which might affect the diagnosis and treatment of patients with UTIs. Future studies with a larger number of isolates and functional assays are required to clarify the mechanistic regulation and biological relevance of these observations in UTIs.

Satisfaction with telepsychiatry and mental health stigma among health sciences students in Egyptian universities

Abstract Health sciences students have a higher incidence of mental health disorders; however, stigma and barriers have complicated help-seeking. Telepsychiatry may be a solution, but acceptance, satisfaction, and stigma in this population, especially in Egypt, remain unclear. This study aimed to evaluate the levels of satisfaction regarding telepsychiatry, stigma perceived with respect to mental illness, among health sciences students towards mental health services. It also aims to assess sociodemographic factors associated with these outcomes. This was a questionnaire-based cross-sectional study conducted among 799 students from various universities in Egypt. It was conducted between August and November 2025, and the questionnaire involved sociodemographic data, the telepsychiatry satisfaction scale (21 items), and the STIG-9 stigma scale. Data were analyzed using descriptive statistics, chi-square and t-tests, and linear regression, with significance set at p < 0.05. Overall, participants had a mean age of 21.4 years, while 66.8% of participants were female. In total, 24.0% agreed, and 18.4% strongly agreed to being satisfied with telepsychiatry, with a mean total satisfaction score of 67.84/105. The mean STIG‑9 stigma score was 14.44/27. Linear regression identified sociodemographic variables independently associated with satisfaction and stigma; higher stigma was also positively associated with higher satisfaction. In this cohort of Egyptian health sciences students with prior telepsychiatry experience, satisfaction with telepsychiatry was positively associated with perceived stigma. These findings suggest that addressing socio-cultural stigma may support the acceptability of telepsychiatry and improve engagement with digital mental health services in similar student populations.

Glucocorticoid exposure during nutrient deprivation impairs recovery in postmitotic myotubes

Evaluating the copy capacity of polyvinylsiloxane molds in quantitative surface texture analysis of ground stone tools

Abstract Polyvinylsiloxane (PVS) is a molding compound originally developed for dental applications that, over the past 50 years, has also been widely used in archaeology to produce negative surface replicas of artifacts, owing to its excellent detail reproduction and dimensional stability. However, most studies assessing its replication accuracy have focused on bones, teeth, and flint tools, leaving ground stone tools (GSTs) largely unexplored. This study fills this gap by assessing the accuracy of PVS molding on GSTs, whose uneven surfaces and heterogeneous textures present particular challenges for both qualitative and quantitative analyses. We tested the accuracy and precision of PVS copies on a reference collection of GST replicas based on archaeological artifacts from Upper Paleolithic sites, representing four diverse lithologies. Confocal profilometry was used to acquire microtopographic maps of selected areas, enabling in-depth statistical comparisons between original surfaces and corresponding molds, with emphasis on key roughness descriptors. The results show that PVS molds effectively capture fine surface details, making them suitable for rough and irregular surfaces, though minor deviations and parameters overestimation must be considered in quantitative traceological analyses. By evaluating replication accuracy, this study contributes to the refinement of analytical methodologies for GSTs and improves the reliability of functional investigations.

Global distribution of deep-sea natural products shows environmental and phylogenetic undersampling with potential for biodiscovery

Abstract Natural products from marine and terrestrial organisms provide an important resource for medicinal chemistry and drug discovery. Defined as occurring at depths greater than 200 m, most of the ocean, by area and volume, is comprised of deep-sea environments. These contrasting ecosystems exhibit a wide range of temperature, pressure, and environmental chemistry conditions that harbour high phylogenetic diversity. Here we analyse the global distribution of Marine Natural Products (MNPs) from deep-sea organisms, which reveals chronic undersampling of the deep ocean as a reservoir of new and diverse chemical structures and bioactivity. The sources of 2909 compounds and extracts, compiled from published records, show a sampling bias towards benthic and shallower deep-sea habitats, with relatively few from areas beyond national jurisdictions and a concentration of records along geomorphological features that have been the focus of marine scientific interest such as seamounts and hydrothermal vents. The phylogenetic distribution of deep-sea MNPs is dominated by non-metazoan sources (76% of records) and Ascomycota fungi in particular (55%). Polyketides are the most prevalent metabolites in deep-sea MNPs, and cytotoxic and antibacterial properties are the most commonly reported bioactivities. Our analyses highlight a need for systematic sampling and consistent data reporting to explore potential relationships, if any, between, bioactivity, new chemical structures, phylogeny and deep-sea environmental conditions, which could guide targeted biodiscovery in our planet’s largest biome and enable better assessment of the benefits of protecting deep-sea biodiversity from human impacts.

Artificial seed mediated micropropagation of Mucuna pruriens L. (DC) and its novel antibiofilm potential against MDR ESKAPE pathogens

Eco-friendly nanocomposite SA/Al2O3/Ag2Mo2O7 microbeads for fast and sustainable photo-induced adsorption of methylene blue dye from industrial wastewater

Abstract The increasing release of hazardous synthetic dye waste poses a serious threat to the environmental and human health. In this study, a novel ternary nanocomposite was designed as an innovative photo-responsive adsorbent by embedding poly silver molybdate (Ag 2 Mo 2 O 7 ) and alumina nanoparticles (Al 2 O 3 ) into a sodium alginate (SA) polymeric matrix. Designed to efficiently eliminate methylene blue (MB) dye from contaminated water and overcome the separation bottleneck of traditional powdered materials. The SA/Al 2 O 3 /Ag 2 Mo 2 O 7 microbeads were synthesized via a facile and eco-friendly ionotropic gelation method. Structural and morphological characterization of the prepared nanocomposite was authenticated via X-ray diffraction (XRD) and transmission electron microscopy (TEM), confirmed the successful formation of the ternary nanocomposite with particle size ranging from 10 to 12 nm. The incorporation of Ag 2 Mo 2 O 7 and Al 2 O 3 within the alginate polymer matrix significantly enhanced the photo-induced adsorption performance compared to bulk sodium alginate (SA) microbeads. Notably, 1.2 g/L of the microbeads achieved a remarkable 91.78% removal efficiency for methylene blue (MB) dye (77.5 mg/g) within just 40 min under visible light irradiation. In comparison, the nanocomposite demonstrates a significantly higher elimination compared to individual Ag 2 Mo 2 O 7 and Al 2 O 3 , which exhibited only 60.69% and 56.89%, respectively. Kinetic studies revealed that the removal process obeyed the pseudo-second-order model, while the equilibrium data closely followed the Freundlich isotherm. Thermodynamic parameters confirmed that the photo-induced adsorption process is spontaneous and endothermic. Furthermore, the reusability of the SA/Al 2 O 3 /Ag 2 Mo 2 O 7 microbeads was tested through five adsorption–desorption cycles, consistently removing more than 73.89% of MB dye. These results demonstrate the practical application of this photo-responsive nanocomposite as an easily recoverable and efficient solution for eliminating toxic cationic dyes from industrial wastewater.

Single-cell RNA sequencing of hematopoietic and non-hematopoietic cells defines a distinct signature in atopic and NRG1 mouse lung

Transcriptomic meta-analysis identifies dysregulated pathways and potential therapeutic targets in Vestibular Schwannoma

Vestibular schwannoma (VS) is a benign Schwann cell–derived tumor that frequently causes progressive hearing loss and vestibulocochlear dysfunction, substantially impacting quality of life. The molecular mechanisms underlying VS pathobiology remain poorly defined, and reliable biomarkers or targeted therapies are lacking. This study aimed to delineate the molecular landscape of VS through a transcriptome-wide meta-analysis. We performed a genome-wide random-effects meta-analysis of four independent Affymetrix microarray datasets from the Gene Expression Omnibus (GEO) database. Differential expression analyses were conducted with and without covariate adjustment. Gene Ontology enrichment and DrugBank-based drug–gene interaction analyses were subsequently applied to characterize biological pathways and assess translational potential. Across the meta-analysis, more than 3,200 differentially expressed genes were identified in the covariate-free model. After applying a more stringent threshold (|metaLFC| > 1 and FDR < 0.05), 1,095 genes remained differentially expressed, with high concordance between the covariate-free and covariate-adjusted models. Downregulated genes included extracellular matrix and stromal components ( MFAP5 , FABP4 , DCN ), and sensory- and synapse-related transcripts ( SLC22A3 , LGI1 ). Upregulated genes included immune- and inflammation-associated genes ( TREM2 , CCL3 , CCL4 , L1CAM ) and proliferative regulators ( CCND1 , RAB31 , MOXD1 ). Functional enrichment highlighted extracellular matrix remodeling, immune modulation, sensory signaling, and cell cycle pathways. Notably, many of the most strongly dysregulated genes have not previously been associated with VS. Drug–gene interaction analysis identified multiple dysregulated genes with known pharmacological targets, suggesting potential translational relevance. This transcriptome-wide meta-analysis provides a comprehensive overview of gene expression patterns in VS, highlighting alterations related to extracellular matrix organization, sensory and synaptic processes, immune-associated signaling, and cell cycle–related pathways. The study highlights novel disease-associated genes and pathways and may help prioritize candidates for further investigation, including those with potential relevance for therapeutic targeting.

Alteration of epidermal lipid metabolism by 2-linoleoylglycerol in a 3D skin model

AI-driven diagnosis of mpox using deep learning models

Mpox lesions can resemble other dermatological conditions, motivating image-based screening, yet published studies remain difficult to compare owing to differences in dataset construction, augmentation policy, and evaluation design. This study provides a leakage-aware benchmark for binary mpox classification using a unified dataset assembled from MSLD v1.0 and v2.0. Seven pretrained backbones and a weighted ensemble were compared under group-stratified five-fold cross-validation with original-only test evaluation, validation-based threshold selection, and temperature scaling. The weighted ensemble achieved mean accuracy 0.8729, F1-score 0.8334, and AUC 0.9388; ConvNeXt-Tiny was the strongest single model (F1 0.8159, AUC 0.9284). These grouped original-only results are intentionally conservative relative to augmentation-heavy or single-split designs and should be interpreted as deflated but more trustworthy reference values. Post hoc calibration analysis, content-level near-duplicate auditing, and a test-time augmentation ablation are provided to substantiate the methodological claims. The contribution is methodological: a transparent benchmark emphasizing reproducible dataset curation, grouped evaluation, and calibrated comparison, while highlighting the limitations of current public skin-image data. Accordingly, these results should be interpreted as a reproducible reference benchmark rather than a clinically validated diagnostic tool, and external clinical validation remains necessary before deployment.

Cross-scenario evaluation of explainable machine learning for non-invasive summer occupancy detection across five building scenarios

Abstract Accurate identification of indoor occupant presence is crucial for intelligent building energy management. Traditional monitoring methods are often invasive and lack standardized quantitative indicators. Therefore, this study proposes a non-invasive occupant presence state prediction method based on machine learning. Six machine learning algorithms—Logistic Regression, Decision Tree, k-Nearest Neighbor (KNN), Random Forest, CatBoost, and XGBoost—were evaluated across five building scenarios (hospitals, classrooms, dormitories, offices, and dwelling houses) using core environmental features including air temperature, relative humidity, sound pressure level, illuminance, CO 2 concentration, formaldehyde (HCHO), PM 2.5 , PM 1.0 , and PM 10 . A temporally ordered walk-forward evaluation framework was adopted to prevent data leakage, with VIF screening and RFECV for feature selection. The best-performing models achieved mean accuracies ranging from 0.61 (dwelling) to 0.88 (office), with the optimal algorithm varying by scenario. SHAP-based interpretability analysis identified CO 2 concentration, illuminance as the most consistently influential predictors, with PM 2.5 , temperature, and sound contributing in scenario-specific patterns. A leave-one-feature-out sensitivity analysis showed that removing CO 2 caused the largest performance drop in the hospital scenario. This study provides a comparative analysis of explainable machine-learning predictors across five single-room building scenarios under a temporally aligned protocol, providing comparative observations that may inform subsequent multi-room and closed-loop studies of smart building management.

Enhancing perovskite solar cells efficiency via dual surface passivation

Effective defect passivation is essential for achieving high performance in perovskite solar cells (PSCs). Dimensional engineering provides a powerful strategy to suppress non-radiative recombination in both the bulk and surface regions of PSCs. In this work, we present a novel interfacial passivation approach for the perovskite/hole transport layer interface using a dual-cation passivation layer composed of guanidinium bromide (GuaBr) and n-phenylethylammonium bromide (n-PEABr). This dual-cation strategy delivers an open-circuit voltage of 1.23 V and a power conversion efficiency (PCE) of 25.11%, significantly outperforming devices based on single-cation passivation. The combined cations induce the formation of a mixed 1D/2D perovskite structure, resulting in a more uniform and hydrophobic surface compared with unpassivated films. Moreover, stability tests conducted under ambient conditions (80% relative humidity) and continuous light-soaking reveal markedly enhanced device stability. The results demonstrate the superior passivation effectiveness of phenylethylammonium compared with previously reported methods. In particular, this approach surpasses the 23% PCE achieved using octylammonium passivation, achieving efficiencies exceeding 25%. Overall, the excellent defect passivation and favorable optical and electrical properties of phenylethylammonium play a key role in significantly improving both the efficiency and stability of PSCs.

High expression of VISTA on M-MDSCs is associated with immunosuppression and predicts poor prognosis in acute myeloid leukemia

Research on the protection and restoration technology of glazed components in ancient architecture

In traditional Chinese architecture, glazed tile components are a significant decorative element that are frequently utilized on walls and roofs. However, glazed tile components typically show variable degrees of deterioration and damage owing to long-term exposure to the natural environment. This study examines and evaluates the preservation quality and primary forms of deterioration of historic architectural glazed tile components. The damage development process of glazed tile components under the combined influences of temperature, humidity fluctuations, and acidic environments was discovered through characterization of material morphological changes and corrosion products. Tetraethyl orthosilicate (TEOS) and hydroxyl-terminated polydimethylsiloxane (PDMS−OH) were chosen as reinforcement materials for common problems including pulverization of the glazed tile body. The glazed tile body was reinforced using ethanol as a solvent. The best material formulation for glazed tile body reinforcement was chosen by evaluating the performance of reinforcement systems with various ratios using a thorough index analysis. Concurrently, scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) were used to examine the reinforcing process. This work suggests modifying the matrix material’s particle size to improve mechanical characteristics and structural stability for glazed tile components that are extensively damaged and challenging to repair with reinforcement. The study’s findings can serve as a theoretical foundation and technical guide for the scientific preservation and repair of glazed tile elements found in historic buildings.