High-resolution spatio-temporal estimation of street-level air pollution using mobile monitoring and machine learning.

High spatio-temporal resolution street-level air pollution (SLAP) estimation is essential for urban air quality management, yet traditional methods face significant challenges in capturing the detailed spatial and temporal variability of pollution. Methods relying on fixed monitoring networks provide limited spatial coverage, while those utilizing mobile monitoring campaigns, despite their flexibility, often suffer from data sparsity and temporal incompleteness. To address these limitations, we propose a Two-Step Machine Learning Gap-Filling Framework employing a Multi-task Graph-based XGBoost (MTGXGB) model to enhance SLAP resolution.

A comprehensive multicriteria decision analysis framework for shallow geothermal energy suitability evaluation in Yinchuan Area, China.

Shallow geothermal energy (SGE) is a green, clean, and renewable energy source that is widely used for heating and cooling. However, hydrogeology conditions, thermophysical properties, geological environment conditions, and other factors influence the implementation of SGE projects. Making a suitability evaluation before implementing the SGE projects is necessary.

Investigating the biological significance of the TCM principle "promoting urination to regulate bowel movements" through the influence of the intestinal microbiota and their metabolites on the renal-intestinal axis.

Treatment methods in traditional Chinese medicine (TCM) are foundational to their theoretical, methodological, formulaic, and pharmacological systems, significantly contributing to syndrome differentiation and therapy. The principle of "promoting urination to regulate bowel movements" is a common therapeutic approach in TCM. The core concept is "promoting the dispersion and drainage of water dampness, regulating urination to relieve diarrhea," yet its scientific underpinning remains unclear.

Association between serum copper concentration and body composition in children with spinal muscular atrophy: a cross-sectional study.

Background And Objectives: The role of serum copper in modulating body composition in patients with spinal muscular atrophy (SMA) remains uncertain. This study aimed to illustrate the correlation between serum copper concentration and body composition in children with SMA.

Methods And Study Design: This study was conducted at a pediatric medical center in China from July 2019 to August 2022.

Sensitive and Deep Coverage Phosphoproteome Detection Method Reveals Spleen as a More Sensitive Organ than Liver in Early Detection of Liver Fibrosis-Related Signaling Protein Dysregulation.

Although cathepsin S is transported from the spleen to the liver, where it cleaves collagen XVIII to produce endostatin and plays a critical role in the onset of early liver fibrosis, the relationship between liver fibrosis and spleen function remains underexplored. Given the roles of phosphorylation in disease, understanding its regulatory mechanism in early liver fibrosis is crucial. Despite advances in mass spectrometry enhancing phosphoproteomics, its application is limited by small clinical samples and subtle protein changes.

Evaluating generalizability of oncology trial results to real-world patients using machine learning-based trial emulations.

Randomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to real-world oncology patients. Although restrictive eligibility criteria contribute to this issue, the role of selection bias related to prognostic risk remains unclear. In this study, we developed TrialTranslator, a framework designed to systematically evaluate the generalizability of RCTs for oncology therapies.

Quantitative redox proteomics links thioredoxin to heavy ion resistance in Deinococcus radiodurans.

Heavy ion radiotherapy is an effective treatment for tumors, but its therapeutic efficacy is limited in cancer cells with radiation resistance. Deinococcus radiodurans, well known for its extremely resisting various stresses, was used to explore radioresistant mechanism. We used quantitative redox proteomics to track the dynamic changes in the global redox state after C irradiation.

Screening and identification of viruses in termites: behavior-regulating roles of RcBsV and RcBV.

Background: Termites live underground in a social setting having continuous contact with microorganism. However, there is no comparative study on virus diversity and relative abundance between termites, castes and body parts in termites. To address this gap, pseudergates of Cryptotermes declivis, workers of the Odontotermes formosanus, and workers, soldiers and alates of the Reticulitermes chinensis were used as experimental materials to perform virome sequencing, virus annotations and their relative abundance analysis.

Metalloporphyrinic metal-organic frameworks for enhanced photocatalytic degradation of a mustard gas simulant.

Four metalloporphyrinic metal-organic frameworks (MOFs) were successfully synthesized and exhibited enhanced activities for the photooxidation of a sulfur mustard simulant, 2-chloroethyl ethyl sulfide (CEES). Among them, a Sn-porphyrin functionalized 2D MOF, namely CSLA-21-NH(Sn), showed a half-life of 1.5 min for CEES oxidation under blue LED, featuring as one of the fastest photocatalysts for CEES degradation.

Corrigendum: IL-9 inhibits viral replication in coxsackievirus B3-induced myocarditis.

[This corrects the article DOI: 10.3389/fimmu.2016.

Phylogenetic and divergence analysis of Pentatomidae, with a comparison of the mitochondrial genomes of two related species (Hemiptera, Pentatomidae).

Pentatomidae, the most diverse family of Pentatomoidea, is found worldwide. Currently, the phylogenetic relationships among Pentatomidae tribes remain unstable, and subfamily divergence has not been estimated. Here, we sequenced and analyzed the complete mitochondrial genomes of two species of Lelia, and studied the phylogenetic relationships among Pentatominae tribes.

Federated Multiple Imputation for Variables that Are Missing Not At Random in Distributed Electronic Health Records.

Large electronic health records (EHR) have been widely implemented and are available for research activities. The magnitude of such databases often requires storage and computing infrastructure that are distributed at different sites. Restrictions on data-sharing due to privacy concerns have been another driving force behind the development of a large class of distributed and/or federated machine learning methods.

Deep learning-based approaches for multi-omics data integration and analysis.

Background: The rapid growth of deep learning, as well as the vast and ever-growing amount of available data, have provided ample opportunity for advances in fusion and analysis of complex and heterogeneous data types. Different data modalities provide complementary information that can be leveraged to gain a more complete understanding of each subject. In the biomedical domain, multi-omics data includes molecular (genomics, transcriptomics, proteomics, epigenomics, metabolomics, etc.

Improved high-current-density hydrogen evolution reaction kinetics on single-atom Co embedded in an order pore-structured nitrogen assembly carbon support.

Single-atom catalysis is a subcategory of heterogeneous catalysis with well-defined active sites. Numerous endeavors have been devoted to developing single-atom catalysts for industrially applicable catalysis, including the hydrogen evolution reaction (HER). High-current-density electrolyzers have been pursued for single-atom catalysts to increase active-site density and enhance mass transfer.

Differences between phytophagous and predatory species in Pentatomidae based on the mitochondrial genome.

Pentatomidae includes many species of significant economic value as plant pests and biological control agents. The feeding habits of Pentatomidae are closely related to their energy metabolism and ecological adaptations. In this study, we sequenced the mitochondrial genomes of 12 Asopinae species using the next-generation sequencing to explore the effect of dietary changes on mitochondrial genome evolution.

SADI: Similarity-Aware Diffusion Model-Based Imputation for Incomplete Temporal EHR Data.

Missing values are prevalent in temporal electronic health records (EHR) data and are known to complicate data analysis and lead to biased results. The current state-of-the-art (SOTA) models for imputing missing values in EHR primarily leverage correlations across time points and across features, which perform well when data have strong correlation across time points, such as in ICU data where high-frequency time series data are collected. However, this is often insufficient for temporal EHR data from non-ICU settings (e.

Bridging the Gap: Rademacher Complexity in Robust and Standard Generalization.

Training Deep Neural Networks (DNNs) with adversarial examples often results in poor generalization to test-time adversarial data. This paper investigates this issue, known as adversarially robust generalization, through the lens of Rademacher complexity. Building upon the studies by Khim and Loh (2018); Yin et al.

DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation.

Designing faithful yet accurate AI models is challenging, particularly in the field of individual treatment effect estimation (ITE). ITE prediction models deployed in critical settings such as healthcare should ideally be (i) accurate, and (ii) provide faithful explanations. However, current solutions are inadequate: state-of-the-art black-box models do not supply explanations, post-hoc explainers for black-box models lack faithfulness guarantees, and self-interpretable models greatly compromise accuracy.

Spatial accessibility and equity of community healthcare: unraveling the impact of varying time and transport mode.

Background: Achieving a higher level of accessibility and equity to community healthcare services has become a major concern for health service delivery from the perspectives of health planners and policy makers in China.

Methods: In this study, we introduced a comprehensive door-to-door (D2D) model, integrating it with the open OD API results for precise computation of accessibility to community hospitals over different transport modes. For the D2D public transit mode, we computed the temporal variation and standard deviation of accessibility at different times of the day.