Browse Articles

Artificial intelligence shines a light on hidden global migration flows

Intracellular assembly of artificial enzymes for cytoplasmic enantioselective Mannich reactions

Deep learning based two-way feature depiction model for brain tumor detection

Brain tumors are one of the most fatal disorders that cause one of the highest mortalities in the world. Gliomas are the most common primary brain tumors originating from glial cells in the central nervous system. Traditionally, a tissue sample is extracted and examined for its genetic and characteristic properties. This method is invasive, painful, and takes a longer period to produce results. Various automatic Deep learning (DL) based schemes have been presented for the brain glioma detection, but they lack due to poor explainability, lower generalization, poor feature depiction, class imbalance problem and lower detection rate. This paper presents a deep learning based brain tumor detection using two way feature depiction model (TWFDM) that combines the 2D-Deep Convolution Neural Network (DCNN) and 1D-DCNN. The 2D-DCNN accepts the raw MRI images and the 1D-DCNN accepts the handcrafted local binary pattern (LBP), gray level cooccurrence matrix (GLCM), and Histogram of Oriented Gradient (HOG) features. Furthermore, improved particle swarm optimization (IPSO) is used for feature selection to minimize the computational complexity of the TWFDM system. The proposed TWFDM achieves an overall accuracy of 96.25%, a recall of 96.34%, a precision of 96.31%, and an F1-score of 96.32% on the Brain MRI dataset for four-class classification, representing an important improvement over traditional techniques.

Trend and determinants of underweight among children aged under five years in Rwanda: secondary data analysis using Rwanda Demographic Health Surveys 2005–2020

Electrodeposited self-assembled molecules for perovskite photovoltaics

Ultra flash cold events under global warming

Music-induced cortical plasticity: Protocol for a systematic review

Music engages sensory, motor, cognitive, and emotional systems, making it a powerful model for studying experience-dependent neuroplasticity. Although research on music-related brain changes is expanding, integration of structural, functional, and cerebrovascular findings remains limited, and effects on higher-order cognitive processes remain unclear. This systematic review will primarily synthesize evidence on music-induced cortical adaptations, including structural changes (e.g., gray and white matter alterations), functional modifications in neural networks, and cerebrovascular dynamics. Further, associations with behavioral measures such as attentional control, executive functioning, and language processing will also be examined when these outcomes are directly linked to the neural adaptations across the adult lifespan (≥ 50 years). The protocol was prepared in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) guidelines and has been indexed in International Prospective Register of Systematic Reviews (PROSPERO ID: CRD420251159362). The systematic review will be conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Using controlled vocabularies and medical subject headings (MeSH), a systematic search will be conducted across PubMed, Scopus, Web of Science, PsycINFO, EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), and Google Scholar databases, and supplemented by citation tracking from relevant review articles. Eligible studies will include randomized controlled trials (RCTs), non-randomized controlled trials, quasi-experimental, and observational designs (longitudinal, case-control, cross-sectional studies). The primary outcome will be changes in brain structure, function, and cerebrovascular hemodynamic activity following music intervention. Cognitive measures will be reviewed and consolidated as secondary endpoints. Data extraction, risk of bias and quality assessment will be performed independently by two reviewers using validated instruments, including Cochrane Risk of Bias 2 (RoB 2.0), Risk Of Bias In Non-randomized Studies – of Interventions (ROBINS-I), Risk Of Bias In Non-randomized Studies of Exposures (ROBINS-E), Strengthening the Reporting of Observational Studies in Epidemiology (STROBE), and National Heart, Lung, and Blood Institute (NHLBI) tools. A narrative synthesis will be conducted in accordance with Synthesis Without Meta-analysis (SWiM) guidelines, with meta-analyses undertaken where appropriate. Certainty of evidence will be assessed using Grading of Recommendations Assessment, Development, and Evaluation (GRADE) scale. Collectively, this protocol establishes a rigorous framework to systematically evaluate how music shapes the brain’s structure, function, and vascular systems, and how these changes translate into cognitive and behavioral outcomes.

Work autonomy mediates associations between medical AI readiness and well being in a three wave nurse study

VPS13C/PARK23 initiates lipid transfer and membrane remodeling for efficient lysosomal repair

Abstract Perturbations in lysosome integrity are tightly linked to neurological disorders and ageing, but the underlying pathogenic mechanisms are incompletely understood. Using an unbiased proteomic approach, we here identified the bridge-like lipid transport protein VPS13C/PARK23 as a key component of a global early response pathway to lysosome damage. VPS13C readily binds lysosomes under mechanical or osmotic tension in anticipation of membrane lesions. The latter trigger a conformational change in the protein’s C -terminus, involving its ATG2C domain acting as sensor of damage-induced lipid packing defects. We show that ER-lysosome contacts formed by VPS13C provide critical binding platforms for OSBP/ORPs to enable efficient ER wrapping of damaged lysosomes. A chemical approach to assess directional ER-to-lysosome lipid transport revealed that VPS13C is essential for large-scale lipid delivery to acutely damaged lysosomes to facilitate their repair. Our findings offer new mechanistic insights into how loss-of-function mutations in VPS13C may enhance the risk of Parkinson’s disease.

Calculation method and predictive analysis of flexural capacity of reinforced concrete beams strengthened with carbon fiber-reinforced polymer sheets applied to the side surfaces

In response to the situation where it is not allowed to stick CFRP cloth at the bottom of a concrete beam and stick it on both sides of the beam, this article analyzes the factors that affect the ultimate flexural bearing capacity of reinforced concrete beams reinforced with CFRP on the side, and provides a calculation method for the flexural bearing capacity of reinforced concrete beams reinforced with CFRP on the side; At the same time, for the convenience of calculation, this paper explores the comprehensive consideration of the tensile force of carbon fiber cloth pasted on the side and the corresponding correction factor η f of the force arm, and analyzes it by fitting a quadratic trend function with the ratio of CFRP pasting height to beam height ( h f / h ). Based on this, the calculation methods for the bending capacity of carbon fiber cloth pasted on the bottom surface according to the “Code” and the bending capacity of carbon fiber cloth pasted on the bottom surface according to the quadratic trend function are proposed. Research has shown that using CFRP to reinforce reinforced concrete beams on the side can effectively improve the flexural bearing capacity. After comparative analysis, the calculation results of three calculation methods are in good agreement with the experimental values; The correction coefficient η f increases with the increase of the ratio of the bonding height to the beam height ( h f / h ). When the ratio of the bonding height to the beam height ( h f / h ) exceeds 0.25, the value of the correction coefficient η f increases significantly; Especially when the ratio of the pasting height to the beam height ( h f / h ) exceeds 0.5, it is recommended to calculate the flexural bearing capacity of carbon fiber cloth pasted on the bottom surface according to the proposed quadratic trend function for η f ; At the same time, it is recommended to consider the reduction of the cross-sectional area of carbon fiber cloth as compensation when determining the flexural bearing capacity of reinforced concrete beams with carbon fiber cloth pasted on the side according to the calculation of the beam bottom. In order to reduce errors, the utilization coefficient of ψ f is no longer limited. Theoretical analysis shows that there are critical values for the bonding height and thickness of carbon fiber cloth used for reinforcement. When these exceed the critical value, the effect on enhancing load-bearing capacity becomes insignificant or even declines.

Motor ability-aware adaptive pose estimation with hierarchical uncertainty modeling and cross-ability learning

Abstract The current human pose estimation systems suffer from large decreases in accuracy as they are applied to people of different motor abilities. Current approaches to human pose estimation rely heavily upon a standardized anatomy that does not allow for the quantification of uncertainty. In this paper we propose an extensive framework for the human pose estimation problem that is composed of three sub-modules. The first module, called MADSRNet, dynamically alters the structure of skeletons to represent varying motor abilities by utilizing gated fusion and dynamic graph construction. The second module, called HUGPose, utilizes heteroscedastic regression to provide hierarchical uncertainty estimates at the joints, limbs, and body level. Finally, the third module, called CADCL, utilizes both contrastive learning and domain adversarial training to enable the transfer of knowledge across different motor abilities. We evaluate our proposed framework on the DiverseMotor-PE dataset and obtain state-of-the-art results (41.2 mm MPJPE), which represents a 14.7% improvement compared to the best baseline (ViTPose). The difference in mean per-level MPJPE for typical individuals and those with severe motor impairments is reduced from 12.1 mm to 10.3 mm. The expected calibration error of the uncertainty estimates is 1.58%. The motor ability aware design of our framework is able to make accurate predictions for humans regardless of their motor ability. This work contributes to the development of inclusive human pose estimation systems and promotes equitable access to healthcare and assistive technologies.

CDIN1-Codanin-1 complex defective in congenital dyserythropoietic anaemia type I is an RNA nuclease

Abstract Congenital Dyserythropoietic Anaemia type I (CDA-I) is a rare inherited disorder of erythropoiesis, in which erythroid cells display a unique nuclear phenotype referred to as ‘spongy’ heterochromatin. The molecular basis of CDA-I remains unknown, with most cases of CDA-I caused by mutations in CDAN1 , encoding Codanin-1, or CDIN1 , encoding for Codanin-1-interacting nuclease 1 (CDIN1). To date, very little is known about the function of CDA-I disease proteins and the mechanism by which their associated mutations cause disease. Here, we demonstrate that endogenous CDIN1 interacts with Codanin-1, to form a stable complex. Structural and functional analysis of this complex reveals that the CDIN1-Codanin-1 complex is an RNA nuclease. We shed light on the key mechanistic features of the complex using biochemical and biophysical approaches, complemented by all-atom molecular dynamics (MD) structural simulations. We identify various functional consequences of founder patient mutations on the RNA nuclease activity of CDIN1, providing a framework for understanding the pathophysiology and developing therapeutic strategies for CDA-I.

Editorial Note: Expression and function of the miR-143/145 cluster in vitro and in vivo in human breast cancer

Public knowledge and attitudes toward respiratory syncytial virus vaccination in Hong Kong: a territory-wide population-based study

Abstract Respiratory syncytial virus (RSV) represents a significant global health burden, particularly for high-risk groups such as children and older adults. This study aims to assess the willingness of the public in Hong Kong to receive a fully funded RSV vaccine and identify associated factors. An online survey was conducted in August 2024 across Hong Kong to gather territory-wide data on sociodemographic characteristics, constructs of the health belief model (HBM), knowledge about RSV, and the willingness to receive a fully funded RSV vaccine. A total of 2,099 respondents participated, with 1,356(64.6%) expressing a willingness to receive the fully funded RSV vaccine. Factors associated with a higher likelihood of vaccine willingness included higher perceived susceptibility, higher perceived severity, higher perceived benefit, higher cues to action, higher self-efficacy, lower perceived barriers, and did not receive government subsidies. Parallel mediation analysis revealed that knowledge about RSV significantly influenced vaccine willingness, with HBM constructs mediating 77.8% of this effect. All HBM constructs showed positive mediation effects, except for perceived barriers, which demonstrated a negative effect. Promotion on the knowledge about RSV may enhance acceptability of RSV vaccine. Multivariable regression revealed that government subsidy recipients were less likely to accept vaccination, while higher perceived barriers were associated with reduced willingness. The findings highlight the urgent need for targeted public health interventions and policies to enhance awareness and correct misconceptions about RSV, particularly its lack of specific antiviral treatments and the critical role of vaccination in prevention.

Chemical intuition on bond-dissociation energies as an emergent ability of universal machine-learning interatomic potentials

A-eye: Automated 3D MRI segmentation and morphometric feature extraction for eye and orbit atlas construction

In this study we introduce automated 3D segmentation of the healthy human adult eye and orbit from Magnetic Resonance Images, to improve ophthalmic diagnostics and treatments. Past efforts have primarily focused on small sample sizes and varied imaging modalities. Here, we leverage a large-scale dataset of T1-weighted MRI of 1245 subjects and the deep learning-based nnU-Net for MR-Eye segmentation tasks. The results showcase robust and accurate 3D segmentation of lens, globe, optic nerve, rectus muscles, and orbital fat. We also present the automated estimation of key ophthalmic morphometry biomarkers such as axial length and volumetry, while benchmarking correlations between body mass index and eye structure volumes. Quality control protocols are introduced through the pipeline to ensure the reliability of the segmented large-scale data, further enhancing the applicability of our algorithm in clinical research. As a major outcome we provide the first large-scale unbiased eye atlases (female, male, and combined) towards standardization of spatial normalization tools for MR-Eye.

Dopamine modified hyaluronic acid and chitosan/gallic acid grafted chitosan based hydrogel with antibacterial and antioxidant property for wound dressing

Six ways to put the public at the heart of science and policy

Multitrophic interaction networks mediate biodiversity effects on ecosystem multifunctionality

Abstract Biodiversity loss threatens the multifunctionality of ecosystems on which human well-being ultimately depends. Multitrophic species interactions may be key to explaining the ecological consequences of biodiversity loss, but research explicitly linking species interactions and ecosystem multifunctionality remains rare. To fill this gap, we synthesize data from a large-scale biodiversity experiment established in 2009 in subtropical China that manipulates tree species richness (1-24 species). We integrate 11 types of antagonistic and mutualistic species interaction networks, and 34 ecosystem functions associated with a diverse set of species and trophic levels. Our analysis highlights that characterizing the structure of species interaction networks is invaluable for assessing interaction-mediated biodiversity effects and underlying mechanisms. Positive effects of network size align with expected benefits of multitrophic diversity for ecosystem multifunctionality. Positive effects of niche overlap among interacting species and negative effects of highly connected species (i.e. high linkage density) reveal additional, interaction-mediated drivers. The effects of niche overlap suggest benefits of functionally similar species, and the effects of linkage density underscore the importance of specialized interactions in promoting ecosystem multifunctionality. These findings emphasize that ecosystem service provisioning does not only rely on biodiversity across trophic levels, but to a similar degree on how species interact.

NOX2 inhibition attenuates oxidative stress and eNOS uncoupling in pulmonary arteries of rats following simulated air diving

Simulated diving and decompression can impair endothelial function, but the upstream oxidant sources and their relationship with endothelial nitric oxide synthase (eNOS) coupling in the pulmonary circulation remain unclear. We investigated whether NADPH oxidase 2 (NOX2) is associated with oxidative stress, tetrahydrobiopterin (BH4) depletion, altered eNOS coupling, and pulmonary endothelial dysfunction after simulated air diving. Eighteen male Sprague–Dawley rats were assigned to three groups: control, decompression stress, and decompression stress with the NOX2 inhibitor GSK2795039 (100 mg/kg, intraperitoneal) administered before pressurization. Decompression stress was induced by hyperbaric exposure to 600 kPa for 1 h followed by decompression to ambient pressure; pulmonary arteries were collected 1 h after decompression. We evaluated NOX2 expression, oxidative stress indices, BH4 content, eNOS phosphorylation and dimer/monomer ratio, nitric oxide metabolites (nitrate plus nitrite), markers associated with endothelial activation, and vasoreactivity. Compared with controls, decompression stress increased NOX2 expression, reactive oxygen species and lipid peroxidation, decreased superoxide dismutase activity, reduced BH4 and nitric oxide metabolites. It also caused a shift in eNOS towards a lower dimer/monomer ratio, increased endothelin-1 and adhesion molecules, and impaired endothelium-dependent relaxation, though endothelium-independent relaxation remained intact. GSK2795039 pretreatment attenuated oxidative stress, improved BH4 availability, restored nitric oxide metabolites, and decreased markers of endothelial activation, partially improving endothelium-dependent relaxation. These findings suggest that NOX2-associated oxidative stress contributes to reduced BH4 availability and eNOS coupling imbalance, leading to pulmonary endothelial dysfunction after decompression.