Nitrogen transformation and NO production pathways under arsenic and cadmium stress in Chongming Island, China.

Heavy metal(loid) pollution can adversely affect microbial diversity within the soil ecosystem, which are profoundly impacting soil nitrogen (N) cycling and nitrous oxide (NO) emissions. Here, ON labeling techniques based on incubation experiment were used to investigate the N transformation and NO production pathways response to moderately contaminated, heavily contaminated and extremely contaminated of arsenic (As) and cadmium (Cd) levels in paddy soil and coastal wetland. In paddy soil, ammonification rate (PAT) and nitrification rate (PNT) decreased by 15.

Confined cerium oxide clusters induced interface engineering enhance platinum nanoparticles for efficient ethanol oxidation reaction.

Direct ethanol fuel cells (DEFCs) have been extensively studied as promising energy conversion devices due to their non-toxicity, low corrosivity, and high energy and power densities. However, developing highly active and durable catalysts for the ethanol oxidation reaction (EOR) at the anode remains a significant challenge. Herein, we modulate the intermediate affinity on Pt nanoparticles (NPs) to achieve highly efficient EOR performance through precise optimization of the Pt-CeO interface.

Study on Pressure-Bearing Patterns of Gel Plugging Agents in Multi-Scale Fractures.

In fractured reservoirs, fractures serve as both water channeling and oil flow channels. Because of the impact of bottom water coning, the water channeling phenomenon becomes more problematic in the middle and late stages of reservoir development. Furthermore, residual oil is limited to small-scale fractures.

Differential response of heavy metal accumulation in freshwater aquatic organisms to organic matter pathway (δC) and trophic level (δN).

The migration of heavy metals into aquatic ecosystems is a concern for the safety of aquatic organisms and human health. However, the migration of heavy metals from habitats to the food chain in freshwater ecosystems requires extensive exploration. We extensively investigated the levels of heavy metals in multiple media of freshwater ecosystems and explored their migration from freshwater habitats to the food chain.

Built-in Electric Field Within CoSe-FeSe Heterostructure for Enhanced Sulfur Reduction Reaction in Li-S Batteries.

The conversion of LiS to LiS is the most important and slowest rate-limiting step in the complex sulfur reduction reaction (SRR) for Li-S batteries, the adjustment of which can effectively inhibit the notorious "shuttle effect". Herein, a CoSe-FeSe heterostructure embedded in 3D N-doped nanocage as a modified layer on commercial separator is designed (CoSe-FeSe@NC//PP). The CoSe-FeSe heterostructure forms a built-in electric field at the two-phase interface, which leads to the optimized adsorption force on polysulfides and the accelerated reaction kinetics for LiS-LiS evolution.

PharmaBench: Enhancing ADMET benchmarks with large language models.

Accurately predicting ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties early in drug development is essential for selecting compounds with optimal pharmacokinetics and minimal toxicity. Existing ADMET-related benchmark sets are limited in utility due to their small dataset sizes and the lack of representation of compounds used in drug discovery projects. These shortcomings hinder their application in model building for drug discovery.

Automated molecular structure segmentation from documents using ChemSAM.

Chemical structure segmentation constitutes a pivotal task in cheminformatics, involving the extraction and abstraction of structural information of chemical compounds from text-based sources, including patents and scientific articles. This study introduces a deep learning approach to chemical structure segmentation, employing a Vision Transformer (ViT) to discern the structural patterns of chemical compounds from their graphical representations. The Chemistry-Segment Anything Model (ChemSAM) achieves state-of-the-art results on publicly available benchmark datasets and real-world tasks, underscoring its effectiveness in accurately segmenting chemical structures from text-based sources.

Unraveling the molecular mechanisms driving enhanced invasion capability of extravillous trophoblast cells: a comprehensive review.

Precise extravillous trophoblast (EVT) invasion is crucial for successful placentation and pregnancy. This review focuses on elucidating the mechanisms that promote heightened EVT invasion. We comprehensively summarize the pivotal roles of hormones, angiogenesis, hypoxia, stress, the extracellular matrix microenvironment, epithelial-to-mesenchymal transition (EMT), immunity, inflammation, programmed cell death, epigenetic modifications, and microbiota in facilitating EVT invasion.

A general hypergraph learning algorithm for drug multi-task predictions in micro-to-macro biomedical networks.

The powerful combination of large-scale drug-related interaction networks and deep learning provides new opportunities for accelerating the process of drug discovery. However, chemical structures that play an important role in drug properties and high-order relations that involve a greater number of nodes are not tackled in current biomedical networks. In this study, we present a general hypergraph learning framework, which introduces Drug-Substructures relationship into Molecular interaction Networks to construct the micro-to-macro drug centric heterogeneous network (DSMN), and develop a multi-branches HyperGraph learning model, called HGDrug, for Drug multi-task predictions.

A meta-analysis of treatment for early-stage cervical cancer: open versus minimally invasive radical trachelectomy.

Background: In previous systematic reviews, meta-analysis was lacking, resulting in the statistical difference between the data of different surgeries being impossible to judge. This meta-analysis aims to contrast the fertility results and cancer outcomes between open and minimally invasive surgery.

Method: We systematically searched databases including PubMed, Embase, Cochrane, and Scopus to collect studies that included open and minimally invasive radical trachelectomy.

An extensive benchmark study on biomedical text generation and mining with ChatGPT.

Motivation: In recent years, the development of natural language process (NLP) technologies and deep learning hardware has led to significant improvement in large language models (LLMs). The ChatGPT, the state-of-the-art LLM built on GPT-3.5 and GPT-4, shows excellent capabilities in general language understanding and reasoning.

Reclamation of tidal flats to paddy soils reshuffles the soil microbiomes along a 53-year reclamation chronosequence: Evidence from assembly processes, co-occurrence patterns and multifunctionality.

Coastal soil microbiomes play a key role in coastal ecosystem functioning and are intensely threatened by land reclamation. However, the impacts of coastal reclamation on soil microbial communities, particularly on their assembly processes, co-occurrence patterns, and the multiple soil functions they support, remain poorly understood. This impedes our capability to comprehensively evaluate the impacts of coastal reclamation on soil microbiomes and to restore coastal ecosystem functions degraded by reclamation.

PCSK9 promotes T helper 1 and T helper 17 cell differentiation by activating the nuclear factor-κB pathway in ankylosing spondylitis.

Objective: Our previous study reveals that proprotein convertase subtilisin/kexin type 9 (PCSK9) is positively related to inflammatory markers, T helper (Th)-17 cells, and treatment response in ankylosing spondylitis (AS) patients. Subsequently, this study aimed to explore the effect of PCSK9 on Th cell differentiation and its potential molecular mechanism in AS.

Methods: Serum PCSK9 was determined by enzyme-linked immunosorbent assay in 20 AS patients and 20 healthy controls (HCs).

Pharmacophoric-constrained heterogeneous graph transformer model for molecular property prediction.

Informative representation of molecules is a crucial prerequisite in AI-driven drug design and discovery. Pharmacophore information including functional groups and chemical reactions can indicate molecular properties, which have not been fully exploited by prior atom-based molecular graph representation. To obtain a more informative representation of molecules for better molecule property prediction, we propose the Pharmacophoric-constrained Heterogeneous Graph Transformer (PharmHGT).

[Analysis of the positive rate of otitis media in 1-12 years old children based on brain MRI].

To investigate the positive imaging rate of otitis media in children aged 1-12 years by analyzing the positive rate of otitis media suggested by cranial magnetic resonance imaging（MRI） images in children. By collecting the brain MRI images of children aged 1-12 in Department of Otolaryngology, Jinan children's Hospital from January 2014 to December 2020, the overall incidence of otitis media and mastoiditis was firstly determined, and then it was divided into 12 age groups according to age, each age group was split into boy and girl groups according to gender, each group was divided into left, right and bilateral groups, with the changes of otitis media and mastoiditis in the scanning field as the positive standard statistical analysis of the results. Among 12 439 children in the study, 1321 cases were diagnosed with tympanitis, with a positive rate of 10.

Volatile fatty acids changed the microbial community during feammox in coastal saline-alkaline paddy soil.

In order to indicate the effect of volatile fatty acids (VFAs) on the characteristics of feammox and dissimilatory iron reducing bacteria (DIRB) in paddy soils, different VFAs were selected with paddy soils for anaerobic cultivation. Five treatments were set up, respectively, only adding N and both adding N and C (formate + NH (Fo-N), acetate + NH (Ac-N), propionate + NH (Pr-N), and butyrate + NH (Bu-N)) treatments. The concentration of Fe(II), Fe(III), NH, and VFAs was assessed within 45 d, and the bacterial community was determined after cultivation.

Serum PCSK9 is positively correlated with disease activity and Th17 cells, while its short-term decline during treatment reflects desirable outcomes in ankylosing spondylitis patients.

Objective: Proprotein convertase subtilisin/kexin type 9 (PCSK9) participates in the autoimmune disease pathology by regulating T helper (Th) cell differentiation, NF-κB pathway, toll-like receptor 4, etc. This study intended to investigate the association of serum PCSK9 with disease activity, Th cells, and treatment response in ankylosing spondylitis (AS) patients.

Methods: Eighty-nine active AS patients were enrolled in this multicenter, prospective study.

Pre-Training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding.

The latest biological findings observe that the motionless "lock-and-key" theory is not generally applicable and that changes in atomic sites and binding pose can provide important information for understanding drug binding. However, the computational expenditure limits the growth of protein trajectory-related studies, thus hindering the possibility of supervised learning. A spatial-temporal pre-training method based on the modified equivariant graph matching networks, dubbed ProtMD which has two specially designed self-supervised learning tasks: atom-level prompt-based denoising generative task and conformation-level snapshot ordering task to seize the flexibility information inside molecular dynamics (MD) trajectories with very fine temporal resolutions is presented.

Antibiotics sulfamethoxazole alter nitrous oxide production and pathways in estuarine sediments: Evidenced by the N-O isotopes tracing.

Estuarine antibiotic residues are profoundly impacting microbial nitrogen (N) cycling and associated NO production, but the response of NO production pathways to antibiotics remains poorly understood. Here, N-O labeling technique combined with molecular methods were used to investigate the impacts of sulfamethoxazole on the contribution of ammonia oxidation (nitrifier nitrification, nitrifier denitrification, and nitrification-coupled denitrification) and heterotrophic denitrification (HD) to NO production in estuarine sediments. Results showed that environmental concentration of sulfamethoxazole (4 ng/g) promoted the total NO production by 17.

Risk assessment of heavy metals in a typical mangrove ecosystem - A case study of Shankou Mangrove National Natural Reserve, southern China.

Mangroves bear enormous ecosystem value, while the ecosystems are facing increasing environmental pressures. In this study, 73 samples of soil sediments in mangroves, paddy fields, grasslands, forests, and shrimp ponds were collected from Shankou Mangrove National Nature Reserve (SKMNNR), Guangxi Zhuang Autonomous Region, China. The pollution status and ecological risks of heavy metal elements of Cr, Ni, Cu, Zn, As, Cd, Pb, V, and Co were determined using the enrichment factor (EF), geoaccumulaton index (I), and potential ecological risk index (PERI).

Metagenomics highlights the impact of climate and human activities on antibiotic resistance genes in China's estuaries.

Estuarine environments faced with contaminations from coastal zones and the inland are vital sinks of antibiotic resistance genes (ARGs). However, little is known about the temporal-spatial pattern of ARGs and its predominant constraints in estuarine environments. Here, we leveraged metagenomics to investigate ARG profiles from 16 China's estuaries across 6 climate zones in dry and wet seasons, and disentangled their relationships with environmental constraints.

The temporal response of dissolved heavy metals to landscape indices in the Le'an river, China.

Heavy metals in watersheds are a serious concern due to their toxicity, abundance, and persistence in the environment, especially in mining areas. Source analyses and exploration of other related factors are one of the most important methods to help with effective prevention and control of heavy metal pollution in watersheds. In this study, the concentrations of Cr, Co, Ni, Cu, Zn, As, Cd, Sb, Ba and Pb were measured in the Le'an River, and PCA (principal component analysis) and APCS-MLR (absolute principal component scores - multivariate linear regression) methods were used to identify the sources of the dissolved heavy metals.

Robust weakly supervised learning for COVID-19 recognition using multi-center CT images.

The world is currently experiencing an ongoing pandemic of an infectious disease named coronavirus disease 2019 (i.e., COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).