Browse Articles

Steric effect of intermediates induces formation of three-dimensional covalent organic frameworks

Park use patterns and park satisfaction before and after citywide park renovations in low-income New York City neighborhoods

Abstract Urban parks may promote health through physical activity, stress management, and social connectedness. However, poor-quality parks in disrepair are underutilized, limiting these benefits. This study evaluated the impact of a citywide park renovation program known as the Community Parks Initiative (CPI) on changes in park use patterns and park satisfaction among residents living in low-income New York City neighborhoods. Repeated cross-sectional surveys were administered to residents living near 31 parks undergoing CPI renovations (545 pre-renovation and 201 post-renovation respondents) and near 21 parks in socio-demographically matched control neighborhoods (345 pre-renovation and 129 post-renovation respondents). Surveys measured self-reported past-month park visits, typical park visit duration, and satisfaction with park quality and facilities. Using a difference-in-differences (DID) approach, generalized estimating equations were fit to compare changes over time in park use and satisfaction among residents living near parks receiving renovations compared to those living near control parks. Models were adjusted for age, body mass index, income, public housing, marital status, and children in household. Residents in neighborhoods receiving park renovations reported a larger increase in minutes spent at the park on weekdays [DID = 30.0 min (95% CI 10.3, 49.7)] and total minutes spent at the park in the last 30 days [DID = 466.3 min (95% CI 63.0, 869.6)] compared to controls. Residents of renovated park neighborhoods also reported larger increases in park satisfaction relative to residents of control neighborhoods, with the largest improvements in the percent of residents satisfied with overall park quality [DID = 38.4% (95% CI 25.2, 51.6)] and maintenance of grounds and facilities [DID = 40.9% (95% CI 27.7, 54.1)]. This study provides evidence that park renovations are an important urban planning strategy to support community health through increased park use and improved park perceptions.

N-Homocysteinylation of lysine residues in α-Synuclein enhances aggregation propensity and cytotoxicity in SH-SY5Y cells

Hyperlaxity and low bone mass predispose young female gymnasts to develop scoliosis suspected status

Adolescent sexuality education, sexual debut, and associated factors in Nigerian public secondary schools

Abstract Adolescents in Nigeria face significant sexual and reproductive health risks, yet the effectiveness of existing sexuality education programs remains uncertain. Addressing these gaps is critical to improving adolescent health outcomes. This study assessed sexuality education, sexual debut, and associated factors among public secondary school adolescents in Ekiti State, Nigeria. A cross-sectional study was conducted among 380 adolescents selected through multistage sampling. Data were collected using a validated semi-structured questionnaire covering sociodemographic variables, sexuality education (assessed with 13 questions exploring past sex-related discussions, sexually transmitted infection, contraceptive, and puberty), as well as engagement in sexual intercourse. Pearson chi-square and binary logistic regression were used to identify the predictors of engagement in sexual intercourse. Approximately 36.8% (n = 140) of respondents had a good level of sexuality education. Less than one-third, 27.1% (n = 103) had ever discussed sex-related matters with their parents or guardian. About 22.1% (n = 84) had engaged in sexual intercourse, with 41.7% (n = 35) having their sexual debut before the age of 15. Predictors of engagement in sexual intercourse included being ≥ 18 years old (AOR 12.881, 95% CI 3.615–45.892), male gender (AOR 2.573, 95% CI 1.353–4.892), senior secondary school enrollment (AOR 4.201, 95% CI 1.654–10.671), polygamous family background (AOR 2.508, 95% CI 1.007–6.316), having four or more siblings (AOR 3.778, 95% CI 2.043–6.986), and higher level of sexuality education (AOR 1.829, 95% CI 1.006–6.986). A huge proportion of adolescents who engage in sexual intercourse begin early; therefore, it is crucial to target interventions to address their needs at this stage. The limited parental involvement in sexuality education must be addressed to provide adolescents with safe, accurate, and socio-culturally sensitive comprehensive sexuality education. We suggest increasing advocacy to encourage parents and guardians to openly educate their children about sexuality.

Tai Chi’s synergistic modulation on autonomic nervous activity and central autonomic networks in functional constipation patients: a randomized controlled trial

Author Correction: RhoA determines lineage fate of mesenchymal stem cells by modulating CTGF–VEGF complex in extracellular matrix

Simple fabrication and comprehensive evaluation of novel nanocomposite for effective methylene blue dye removal from aqueous media

Comprehensive search for assessment indicators that influence the level of handwriting difficulties among children in educational settings

Abstract Handwriting difficulties are a major public health problem among school-aged children worldwide, as they seriously interfere with their academic performance and well-being. Teachers’ assessments of handwriting difficulties determine whether a child should be subsequently referred for medical or professional assistance. However, very few studies focused on teachers’ perception of handwriting difficulties and the relationship between such perception and direct assessments of children’s relevant abilities. As a result, the direction of support in educational settings remains vague and less focused. In this study, we investigate the relationship between teachers’ perceptions of children’s handwriting difficulties and children’s abilities relevant to their handwriting skills in three main areas: (1) handwriting process, (2) legibility of written letters, and (3) the cognitive and motor functions. The findings suggest that the presence of handwriting difficulties is related to clumsiness of foundational motor skills and the severity of handwriting difficulties is related to lack of carefulness. In addition, somatosensory and visuomotor integration were found to important indicators that characterize handwriting difficulties. These results can provide guidance to teachers and professionals who support children with handwriting difficulties, with individualized and optimal strategies.

Thermodynamic modeling adsorption behavior of a well-known gelation crosslinker on sandstone rocks

Meta-analysis and in-silico functional characterization of the SNCA variant rs356220 in Parkinson’s disease

Abstract The progression of Parkinson’s disease (PD) is influenced by genetic factors, particularly the Synuclein-Alpha (SNCA) gene, which encodes the alpha-synuclein (α-syn) protein involved in dopaminergic neuron degeneration. This study aimed to explore the relationship between rs356220 and PD risk and to understand its functional impact through computational analysis. We thoroughly reviewed nine databases regarding the association between this variant and PD risk. Firstly, a meta-analysis of 9 articles, consisting of 10 studies with 11,638 cases and 37,393 controls was conducted, that identified the C allele of rs356220 as a protective factor against PD (Odds Ratio (OR) 0.91, 95% Confidence Interval (CI): 0.88–0.94, P = 3.82E−08)). Subsequently, we characterized the functional impact of this non-coding variant in the pathophysiology of PD. In-silico process flow included transcription factor binding site (TFBS) analysis, pathway enrichment analysis, and protein interaction analysis. The TFBS analysis suggested that the C allele may influence multiple factors, while subsequent Pathway and Protein Network analyses identified proteins that enhance SNCA expression. Our investigation therefore reveals that rs356220 influences the dynamics of the α-syn protein through interactions with BAD, CANX, SLC18A1, and IRF1, potentially advancing the progression of PD. This research emphasizes the need for holistic study approaches to explore the intricacies of complex disorders like PD.

Cold induced expression of a novel levansucrase gene sacB1 enhances exopolysaccharide production and stress resilience in Leuconostoc mesenteroides

Abstract Exopolysaccharides (EPS) play critical roles in microbial survival, stress adaptation, and biofilm formation across diverse environments. In food-associated bacteria such as Leuconostoc mesenteroides, understanding the regulation of EPS production under environmental stress is important for both spoilage control and industrial applications. However, the mechanisms linking cold stress to EPS biosynthesis remain poorly understood. Here, we show that sucrose and low temperature (8 °C) trigger a metabolic shift from dextran-only to combined dextran and levan biosynthesis in four meat-borne Leuc. mesenteroides strains. Two high EPS-producing strains (HEPRs) possess the sacB_1 gene, which encodes a previously uncharacterized levansucrase absent from low EPS-producing strains (LEPRs) that only carry the levS gene. This is the first study to describe the role of sacB_1 in cold-induced EPS production. Notably, sacB_1 was also identified in Leuc. mesenteroides strains isolated from plant-based fermentations such as kimchi and birch sap, but the HEPR strains analyzed here are the only known meat-derived isolates to carry this gene. Genomic analyses revealed highly conserved biosynthetic clusters for dextran, heteropolysaccharide, and levan. Gene expression profiling showed that levS and sacB_1 were upregulated at 8 °C, while dsrD expression was favoured at 25 °C. Cold-induced sucrose metabolism, characterized by high expression of levS, sacB_1, and dsrD, enhanced cell viability under oxidative stress. Furthermore, heterologous expression of sacB_1 in Leuc. mesenteroides and Lactococcus lactis improved resilience under cold and high-aeration conditions, confirming the protective role of levan. These findings advance the understanding of temperature-dependent EPS regulation in LAB and highlight sucrase diversity as a key factor in microbial adaptation to environmental stress.

Early Triassic super-greenhouse climate driven by vegetation collapse

Abstract The Permian–Triassic Mass Extinction (PTME), the most severe crisis of the Phanerozoic, has been attributed to intense global warming triggered by Siberian Traps volcanism. However, it remains unclear why super-greenhouse conditions persisted for around five million years after the volcanic episode, with one possibility being that the slow recovery of plants limited carbon sequestration. Here we use fossil occurrences and lithological indicators of climate to reconstruct spatio-temporal maps of plant productivity changes through the PTME and employ climate-biogeochemical modelling to investigate the Early Triassic super-greenhouse. Our reconstructions show that terrestrial vegetation loss during the PTME, especially in tropical regions, resulted in an Earth system with low levels of organic carbon sequestration and restricted chemical weathering, resulting in prolonged high CO 2 levels. These results support the idea that thresholds exist in the climate-carbon system whereby warming can be amplified by vegetation collapse.

Deep learning strategies for semantic segmentation of pediatric brain tumors in multiparametric MRI

A parallel program for the simulation of flooding

Abstract Accurate flood simulations are essential for effective prevention but they can be computationally slow and expensive, especially in large-scale scenarios. This can limit their use in time-critical situations. To solve this problem, this study aims to enhance the speed of numerical methods while maintaining accuracy in flood simulation results. A parallel algorithm is developed by applying the automatic domain updating method to solve the shallow water equations using a well-balanced, positivity-preserving first-order finite volume scheme. The parallel algorithm was designed with an index array to store the coordinates of cells in the computational domain that exclude unnecessary cells. The index array is divided and assigned to different cores, enabling parallel processing of each sub-domain. The developed parallel program was tested by simulating the water flow, compared with the results obtained in the literature, and applied to the Xe-Pian Xe-Namnoy dam break simulation in Laos. The computational times obtained by the proposed parallel program were compared with those of the serial program, which used only the automatic domain updating method without the parallel technique. The results show that the parallel program outperforms the serial program by reducing the computational time.

Efficient federated graph aggregation for privacy-preserving GNN-based session recommendation

Abstract Graph Neural Networks (GNN) have attracted increasing attention due to their efficient performance in recommendation systems. However, applying GNNs in session-based recommendations with emerging federated learning (FL) for a privacy-preserving recommendation is challenging. Firstly, constructing a global graph in a centralized manner is forbidden due to the privacy-preserving constraints of FL. Secondly, local graphs in each device contain minimal information on the global graph, causing the inefficient merging of sub-graphs by aggregating local models. Thirdly, the session data in these separated devices are usually extraordinarily non-Independent and Identically Distributed (non-IID), which harms the model performance. In this paper, we bridge the practical gaps between FL and GNN-based session recommendations for the first time by introducing a novel adaptive federated learning method named Federated Graph Aggregation (FedGA). FedGA is beyond the reach of prior adaptive FL methods by incorporating Divergence Resistant Aggregation (DRA) and Conditional Second-Moment Estimation (C-SME), yielding an efficient aggregator where local models trained by the unseen local graph embedding can be efficiently merged. Thanks to the above-proposed strategies, FedGA optimizes models without being interfered with by the aggressive learning rates generated by existing adaptive methods under extreme non-IIDness. In addition, we perform the theoretical analysis of the proposed method, and the results demonstrate that our method achieves a similar rate of convergence as other adaptive FL methods. We validate our method on both open datasets and real-world production data. Results show that our method obtains state-of-the-art performance compared to existing adaptive FL methods while retaining the comparable performance of the centralized methods.

Oxidative stress gene expression in ulcerative colitis: implications for colon cancer biomarker discovery

Abstract There is a complex interrelationship between colorectal cancer (CRC) and ulcerative colitis (UC). This study aimed to identify key molecules and pathways involved in the co-occurrence of CRC and UC, as well as the role of oxidative stress in disease progression, through bioinformatics analysis of public RNA sequencing databases. We downloaded datasets from public repositories and conducted gene set enrichment analysis (GSEA), screening for oxidative stress-related differentially expressed genes (OXSRDEGs) to evaluate their diagnostic potential. Subsequently, we performed Gene Ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) analyses, followed by immune infiltration analysis using the single-sample gene-set enrichment analysis (ssGSEA) and CIBERSORT algorithms. By constructing a multivariate Cox prognostic model using Kaplan–Meier curves and least absolute shrinkage and selection operator (LASSO) regression analysis, we assessed the model’s prognostic capability. Furthermore, we utilized the STRING database and Cytoscape to establish a protein–protein interaction (PPI) network and constructed an mRNA-transcription factor (TF) and mRNA-miRNA interaction networks. The molecular functions and signaling pathways enriched in OXSRDEGs were determined. The robust diagnostic efficacy of OXSRDEGs was verified. This analysis suggests that immune cells may collaborate with OXSRDEGs to impact the onset and progression of diseases. A total of 6 OXSRDEGs with prognostic significance were identified, and the multifactorial Cox regression model constructed demonstrated a strong clinical predictive capacity. The mRNA-transcription factor (TF) and mRNA-miRNA interaction networks revealed that OXSRDEGs are regulated by multiple miRNAs and many transcription factors. Common biomarkers of oxidative stress in the pathogenesis, disease progression, gene expression, and transcription of ulcerative colitis and colorectal cancer have been identified, presenting potential therapeutic targets. The model may be beneficial in prognostic prediction and guiding treatment decisions.

Optimization of biological activities of Agaricus species: an artificial intelligence-assisted approach

The importance of distinguishing between natural and managed tree cover gains in the moist tropics

Polar code construction by estimating noise using bald hawk optimized recurrent neural network model

Abstract Polar codes are making significant progress in error-correcting coding due to their ability to reach the limit of the Shannon capacity of communication channels, indicating great advancements in the field. Decoding errors are common in real communication channels with noise. The main objective of this study is to develop a recurrent neural network decoder for robust polar code construction with the Bald Hawk Optimization (RNN-based Decoder with BHO) model that can estimate the error in information bits. This research presents a practical and significant innovation by combining recurrent neural networks (RNNs) for noise estimation in polar coding with a Bald Hawk optimization approach. Moreover, this synthesis of RNN-based noise estimation with Bald Hawk optimization makes the polar coding system more flexible and adaptive, allowing for more accurate noise estimation during decoding. In terms of frame errors, the Bit Error Rate (BER), Binary Phase Shifting Key-BER (BPSK-BER), and Frame Error Rate (FER) achieve the lowest error values of 0.0000087, 0.01519, and 0.000182, respectively. Similarly, in a 4 dB SNR context, the BER, BPSK-BER, and FER achieve values of 0.0000073, 0.02065, and 0.000108, respectively. The results shows that the proposed RNN-based decoder with BHO model outperforms the existing decoders.