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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, shows excellent capabilities in general language understanding and reasoning. Researchers also tested the GPTs on a variety of NLP related tasks and benchmarks and got excellent results. To evaluate the performance of ChatGPT on biomedical related tasks, this paper presents a comprehensive benchmark study on the use of ChatGPT for biomedical corpus, including article abstracts, clinical trials description, biomedical questions and so on. Through a series of experiments, we demonstrated the effectiveness and versatility of Chat-GPT in biomedical text understanding, reasoning and generation.

Rapid and accurate prediction of molecular properties is a fundamental task in drug discovery. In recent years, deep learning-based molecular property prediction methods have received much attention and recent successes have shown that learning the representations of molecular structures by applying graph neural networks (GNNs) can achieve better prediction results. However, most previous approaches typically focus on learning atomic embedding, while in this paper, we propose a novel attention method based on atom pair embedding, and it was applied to two types of prediction task. Firstly, learning of atom pair embedding was done on 2D molecular graphs for predicting a series of ligand properties and secondly, the atom pair embedding was learned on ligand/protein 3D complex structures together with axial attention network to predict protein-ligand interaction. In MolecularNet benchmark datasets, our method achieved better performance than previous state-of-the-art models in ten property prediction tasks and in the task for protein-ligand interaction prediction, our method also obtained superior results on the PDB2016 dataset than a collection of reference models. Our source code will be publicly available upon the acceptance of the manuscript.

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.Eighty-nine active AS patients were enrolled in this multicenter, prospective study. Serum was collected from AS patients at week (W)0, W4, W8, and W12, as well as from 20 osteoarthritis patients and 20 healthy controls after enrollment to detect PCSK9 by ELISA. Based on the ASAS40 response at W12, AS patients were classified as responders and non-responders.PCSK9 was increased in AS patients versus healthy controls (P 0.001) and osteoarthritis patients (P = 0.006). In AS patients, PCSK9 was positively linked with C-reactive protein (CRP) (P = 0.003) and ASDAS-CRP (P = 0.017), but not with other clinical properties (P 0.05). Besides, PCSK9 was negatively correlated with interleukin-4 (P = 0.034), positively associated with Th17 cells (P = 0.005) and interleukin-17A (P = 0.014), but did not relate to Th1 cells, interferon-γ, or Th2 cells (all P 0.05). Additionally, PCSK9 was decreased from W0 to W12 in general AS patients (P 0.001) and responders (P 0.001) but remained unchanged in non-responders (P = 0.129). Moreover, PCSK9 was lower at W4 (P = 0.045), W8 (P = 0.008), and W12 (P = 0.004) in responders versus non-responders. Furthermore, the treatment options did not affect the PCSK9 level (P 0.05).Serum PCSK9 is positively associated with disease activity and Th17 cells, while its short-term decline reflects desirable treatment response in AS patients.

Marine aquaculture in semi-enclosed bays can significantly influence nutrient cycling in coastal ecosystems. However, the impact of marine aquaculture on the dynamics of dissimilatory nitrate reduction processes (DNRPs) and the fate of reactive nitrogen remain poorly understood. In this study, the rates of DNRPs and the abundances of related functional genes were investigated in aquaculture and non-aquaculture areas. The results showed that marine aquaculture significantly increased the denitrification (DNF) and dissimilatory nitrate reduction to ammonium (DNRA) rates and decreased the rate of anaerobic ammonium oxidation (ANA), as compared with non-aquaculture sites. DNF was the dominant pathway contributing to the total nitrate reduction, and its contribution to the total nitrate reduction significantly increased from 66.72% at non-aquaculture sites to 78.50% at aquaculture sites. Marine aquaculture can significantly affect the physicochemical characteristics of sediment and the abundances of related functional genes, leading to variations in the nitrate reduction rates. Although nitrate removal rates increased in the marine aquaculture area, ammonification rates and the nitrogen retention index in the aquaculture areas were 2.19 and 1.24 times, respectively, higher than those at non-aquaculture sites. Net reactive nitrogen retention exceeded nitrogen removal in the aquaculture area, and the retained reactive nitrogen could diffuse with the tidal current to the entire bay, thereby aggravating N pollution in the entire study area. These results show that marine aquaculture is the dominant source of nitrogen pollution in semi-enclosed bays. This study can provide insights into nitrogen pollution control in semi-enclosed bays with well-developed marine aquaculture.

Estuarine antibiotic residues are profoundly impacting microbial nitrogen (N) cycling and associated N

A reduced removal of dysfunctional mitochondria is common to aging and age-related neurodegenerative pathologies such as Alzheimer’s disease (AD). Strategies for treating such impaired mitophagy would benefit from the identification of mitophagy modulators. Here we report the combined use of unsupervised machine learning (involving vector representations of molecular structures, pharmacophore fingerprinting and conformer fingerprinting) and a cross-species approach for the screening and experimental validation of new mitophagy-inducing compounds. From a library of naturally occurring compounds, the workflow allowed us to identify 18 small molecules, and among them two potent mitophagy inducers (Kaempferol and Rhapontigenin). In nematode and rodent models of AD, we show that both mitophagy inducers increased the survival and functionality of glutamatergic and cholinergic neurons, abrogated amyloid-β and tau pathologies, and improved the animals’ memory. Our findings suggest the existence of a conserved mechanism of memory loss across the AD models, this mechanism being mediated by defective mitophagy. The computational–experimental screening and validation workflow might help uncover potent mitophagy modulators that stimulate neuronal health and brain homeostasis., Two potent mitophagy inducers, identified and characterized via unsupervised machine learning and a cross-species screening approach, ameliorated the pathology of Alzheimer’s disease in worms and mice.

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

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. Additionally, a CA (correlation analysis) method was used to explore the correlations between landscape indices and concentrations of heavy metals. Results show that the main sources for these dissolved heavy metals are mining activities, fertilizers, pesticides, and natural sources. Specific results of PCA and APCS-MLR suggest that Cu, Zn, Cd, Ba are mainly related to mining activities, Cr and Pb are due to fertilizers and pesticides, and Co and Ni are mainly due to natural sources. Correlations between landscapes and heavy metals revealed significant temporal variations, with the strongest responses of dissolved heavy metals to landscape indices appearing in December and March. The propensity of positive or negative responses of the heavy metals to landscape indices are determined by the sources, and their temporal variations may be related to the seasonal changes of rainfall and plant metabolism.

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. Our results revealed that ARG abundance, richness, and diversity in dry season were higher than those in wet season, and ARG abundance exhibited an increasing trend with latitude. The prevalence of ARGs was significantly driven by human activities, mobile gene elements, microbial communities, antibiotic residuals, physicochemical properties, and climatic variables. Among which, climatic variables and human activities ranked the most important factors, contributing 44% and 36% of the total variance of observed ARGs, respectively. The most important climatic variable shaping ARGs is temperature, where increasing temperature is associated with decreased ARGs. Our results highlight that the prevalence of ARGs in estuarine environments would be co-driven by anthropogenic activities and climate, and suggest the dynamics of ARGs under future changing climate and socioeconomic development.

The concentrations, sources, and risks of heavy metals (Fe, Al, Mn, Cr, Co, Ni, Cu, Zn, As, Cd, W, Pb, and Tl) in sediments in five river-lake ecosystems in the Poyang Lake region were studied. The concentrations of the heavy metals varied spatially, with most of the highest concentrations in the Raohe river-lake ecosystem (RH). All heavy metals except As, Cd, W, and Tl were enriched in sediments possessing high total organic carbon contents or in finer sediments. Based on enrichment factors and statistical methods, it was found that Cd in sediments in the Xiushui (XS), Ganjiang (GJ), Xinjiang (XJ) river-lake ecosystems, and RH; Mn in the XS, GJ, and RH; and W in the XS and GJ were greatly affected by anthropogenic inputs. Moreover, the origins of Cu, Zn, and As require more attention due to the high concentrations found. The high enrichment factor of Cd in the sediments indicated that this metal might cause significant pollution in the environment. The results of the modified potential ecological risk index revealed that the XS, GJ, RH, and XJ were at considerable ecological risk, while the sediments in the Fuhe river-lake ecosystem (FH) were at moderate ecological risk, with Cd contributing the highest proportion of risk. The hazard score fundamentally validated the modified potential ecological risk analysis and revealed a mean toxicity of 57.80% to the benthic organisms in the RH.

Antibiotics and antibiotic resistance genes (ARGs) are prevalent in estuarine and coastal environments due to substantial terrestrial input, aquaculture effluent, and sewage discharge. In this article, based on peer-reviewed papers, the sources, spatial patterns, driving factors, and environmental implications of antibiotics and ARGs in global estuarine and coastal environments are discussed. Riverine runoff, WWTPs, sewage discharge, and aquaculture, are responsible for the prevalence of antibiotics and ARGs. Geographically, pollution due to antibiotics in low- and middle-income countries is higher than that in high-income countries, and ARGs show remarkable latitudinal variations. The distribution of antibiotics is driven by antibiotic usage and environmental variables (heavy metals, nutrients, organic pollutants, etc.), while ARGs are affected by antibiotics residues, environmental variables, microbial communities, and mobile genetic elements (MGEs). Antibiotics and ARGs alter microbial communities and biogeochemical cycles, as well as pose threats to marine organisms and human health. Our results provide comprehensive insights into the transport and environmental behaviors of antibiotics and ARGs in global estuarine and coastal environments.

Coupling of nitrogen removal processes with nitrification (NRn) are vital synergistic nitrogen elimination mechanisms in aquatic environments. However, the effects of antibiotics on NRn are not well known. In the present work, 20-day continuous-flow experiments combined with 15N tracing techniques and quantitative PCR were performed to simulate the impact of sulfamethoxazole (SMX, a sulfonamide antibiotic) with near in situ concentration on NRn processes in sediments of Yangtze Estuary. Results showed that SMX with near in situ concentration significantly decreased NRn, NRw (uncoupling of nitrogen removal processes with nitrification) and actual nitrogen removal rates via inhibiting nitrogen transformation functional genes (AOB, narG, nirS, nosZ) and anammox 16S rRNA gene, while the coupling links between nitrification and nitrogen removal processes were not broken by the exposure. The proportion of NRn in total nitrogen removal processes decreased by approximately 10% with SMX addition, due to the different inhibition on AOB, denitrifying genes and anammox 16S rRNA gene. N2O production and nitrite accumulation remarkably increased with SMX addition under simultaneous nitrification and denitrification, and they strongly correlated with each other. The more severely inhibition on nirS gene (13.6-19.8%) than Nitrospira nxrB gene (0.3-8.2%) revealed that the increased nitrite accumulation with SMX addition mainly occurred in heterotrophic denitrification, suggesting that the increased N2O production was dominated by the heterotrophic nitrite reduction. Moreover, we estimated that the ratio of external inorganic N eliminated by actual nitrogen removal can upgrade to 6.4-7.4% under circumstances of no inhibition by SMX. This study revealed the effects of SMX with near in situ concentration on NRn processes and illustrated the microbial mechanism on functional genes level. Our results highlighted the inhibitory effects of SMX on NRn may contribute to reactive N retention and N2O production in estuarine and coastal ecosystems.

Conversion of coastal wetland to paddy soil can significantly affect soil biogeochemistry cycling. However, the impacts of coastal wetland reclamation on dissimilatory nitrate reduction processes and nitrogen fate remain poorly understood. In this study, the effects of coastal wetland reclamation on the rates and related functional gene abundances of dissimilatory nitrate reduction processes, N2O emission, and the fate of reactive nitrogen were investigated in Chongming Island, China. Conversion of coastal wetland to paddy soil can significantly increase dissimilatory nitrate reduction rates. Denitrification was the dominant pathway contributing to the total nitrate reduction, while anammox and DNRA played an important role. Conversion of coastal wetland to paddy soil can significantly affect soil physicochemical characteristics and abundances of related functional genes, leading to the variations of nitrate reduction rates. Although the nitrate removal rates increased along the reclamation chronosequences, due to the intensive N fertilizer application and increased nitrification and ammonification rates, more reactive N can be exported in paddy soil than in wetland, and N2O emission was stimulated significantly along reclamation chronosequences. This study can provide valuable insights into the mechanisms of reclamation influences on soil N recycling.

To understand traffic-related metal(loid) status and uptake by dominant plants growing naturally in roadside soils in the Tibetan plateau, China, aboveground parts and root samples of three dominant plant species (Kalidium slenderbranch, Stipa purpurea, Kobresia pygmaea) were collected along the Qinghai–Tibet highway, and were analyzed for concentrations of traffic-related metal(loid)s such as chromium (Cr), zinc (Zn), copper (Cu), cadmium (Cd), arsenic (As), and lead (Pb). The results indicated that concentrations of metal(loid)s in plant tissues varied greatly among plant species and sites. Tissue distribution of metal(loid)s was significantly related to distance and demonstrated variability as an exponential function of traffic proximity. It was deduced that Cd in Kalidium slenderbranch and Cu and Zn in S. purpurea were mainly derived from soil; Kalidium slenderbranch and Kobresia pygmaea absorbed Zn, and S. purpurea absorbed Cd, mainly through stomata, from atmospheric deposition; enrichments of Pb and As in S. purpurea presented similar characteristics to those of Cd and Pb in Kobresia pygmaea and were affected by both soil and atmospheric deposition. After excluding the effects of the traffic, the highest value obtained for metal(loid)-translocation capacity (7.51 for translocation factor, TF) was observed for S. purpurea collected from Tuotuohe, while the lowest value for metal(loid)-uptake capacity (0.015 for bioaccumulation factor, BF) was for Kalidium slenderbranch collected from Golmud. The three plant species showed limited soil-to-root transfer of metal(loid)s, possibly due to the high soil pH along the Qinghai–Tibet highway, but demonstrated great potential for metal(loid) transfer from roots to aboveground parts.

Surface water samples were collected from 20 sampling sites throughout the Ganjiang River during pre-monsoon, monsoon, and post-monsoon seasons, and the concentrations of dissolved trace elements were determined by inductively coupled plasma-mass spectrometry (ICP-MS) for the spatial and seasonal variations, risk assessment, source identification, and categorization for risk area. The result demonstrated that concentrations of the elements exhibited significant seasonality. The high total element concentrations were detected at sites close to the intensive mining and urban activities. The concentrations of the elements were under the permissible limits as prescribed by related standards with a few exceptions. The most of heavy metal pollution index (HPI) values were lower than the critical index limit, indicating the basically clean water used as habitat for aquatic life. As was identified as the priority pollutant of non-carcinogenic and carcinogenic concerns, and the inhabitants ingesting the surface water at particular site might be subjected to the integrated health risks for exposure to the mixed trace elements. Multivariate statistical analyses confirmed that Zn, As, Cd, and Tl were derived from mining and urban activities; V, Cd, and Pb exhibited mixed origin; and Co, Ni, and Cu mainly resulted from natural processes. Three categorized risk areas corresponded to high, moderate, and low risks, respectively. As a whole, the upstream of the Ganjiang River was identified as the high-risk area relatively.

Sediment is the one of most important storage of heavy metal. Microbiotas in sediment can be used as the effective indicators of heavy metals. The goal of this study was to understand the bacterial communities responding to heavy metal enrichment in sediments and prioritize some factors that affected significantly to bacterial community. Sediments were sampled from five river-lake systems in the Poyang Lake in dry season, and the bacterial community was analyzed using Illumina high-throughput sequencing. Relationships between sediment environment and the diversity and structure of bacterial communities were determined by correlation analysis and redundancy analysis (RDA). The result indicated that Cd and Sb were identified as the heavy metals of the great risk in sediments. Sediments from five river-lake systems shared 31.83% core operational taxonomic units (OTUs) of bacterial communities. Proteobacteria (33.54% of total sequences) and Actinobacteria (15.04%) were the dominant phyla across all sites. High enrichment of heavy metals (MRI and mCd) resulted in low diversity of bacterial communities (Simpson index). The RDA revealed pH, OC, mCd, and Efs of As, Pb, Cd were major factors related to bacterial community structure changes. The dominant phylum Actinobacteria was regarded as tolerant bacteria, while the dominant phylum Proteobacteria was named as resistant bacteria in sediment with high anthropogenic Cd enrichment.

Vibrio metschnikovii is a food-borne pathogen found in seafood worldwide. We studied the global proteome responses of V. metschnikovii under cold stress by nano-flow ultra-high-performance liquid chromatography coupled to a quadrupole Orbitrap mass spectrometer. A total of 2066 proteins were identified, among which 288 were significantly upregulated and 572 were downregulated. Functional categorization of these proteins revealed distinct differences between cold-stressed and control cells. Quantitative reverse transcription polymerase chain reaction analysis was also performed to determine the mRNA expression levels of seventeen cold stress-related genes. The results of this study should improve our understanding of the metabolic activities of cold-adapted bacteria and will facilitate a better systems-based understanding of V. metschnikovii.

Using land use types in multiple spatial scales (entire basin, buffer zones, and slopes) as well as statistical and spatial analysis, relationships between land use types and concentrations of dissolved trace metals were determined in the Le'an River Basin, China. The result showed that farmland and urban land were determined as the source of the pollutants, while forestland and grassland were identified as the sink of the pollutants. The temporal differences of relationships between land use types and concentrations of dissolved trace metals mainly due to the discrepancy of rainfall characteristics. Land use type close to river was a better indicator for the effectiveness of concentrations of trace metals, especially at scale of 0-200 m. Forestland and grassland on lower slopes greatly affected the water quality, and the former had no significant or weak influences on higher slopes. Urban land had the greater positive correlations with concentrations of dissolved trace metals on higher slopes, which are mainly due to frequent mining activity. Further analysis suggested that the buffer zones with low slope needed to be seriously taken into consideration for effective land use management in similar basin.

The condition about the heavy metal contamination of wetland soil has become a hot research topic in wetland science. The research on heavy metal contamination is of great importance for coastal wetland management and for monitoring the intensity of human activities. This paper aims to provide information on the concentration levels of heavy metals within different land use types in a coastal wetland in China. Topsoil (0– 20cm) about different land use types was sampled in Tianjin Palaeocoast and Wetland National Natural Reserve (TJPWNR), China. The chemical properties of the soil and the concentrations of heavy metals in the different sample areas within TJPWNR were investigated in 2007. To investigate the level of pollution, total concentrations of heavy metals such as As, Cd, Cu, Pb, Zn, and Cr were analyzed by applying the method of inductively coupled plasma atomic absorption spectrometry to assess and compare contamination levels of the sampling spots. The average concentrations of As, Cu, Pb, Zn, Cr, and Cd in the surface soil were respectively 19.846, 36.147, 32.656, 100.1, 86.43 and 0.207 mg/kg. Compared with those from other typical wetlands in coastal China, the heavy metal is at a mediate level, which is consistent with the fact that the Tianjin coastal wetland is highly exploited and suffers extreme impacts from human activities. An overall common trend in heavy metal accumulation was shown to have the following decreasing order, with few exceptions: FS>VCS>HIS>WS. Our research demonstrates that the mean concentrations of heavy metals are higher in areas of intensive human activities and farmland than those in wetland soil and vegetation community soil, which suggests that human activities cause larger effects; no significant differences were observed for other heavy metals. The comprehensive contamination indices indicate low contamination levels in the four land use types. The results of this analysis suggest that land use types can play significant role in heavy metal contamination.

A compound system involving three matrices (water, sediment, and paddy soil) was conceived to determine the potential sources of metal(loid)s (Ti, Fe, Co, Ni, Cu, Zn, As, Cd, Pb, and U) and synthetically evaluate their pollution levels in the Le’an River basin. The result indicated that the established background values (BVs) of paddy soil and sediment in the compound system were obviously higher than those of the upper continental crust (UCC) and soils from Jiangxi Province, a difference which was especially marked for sediment. The concentrations of Cu, Zn, As, Cd in the system had high coefficients of variation (CVs), and metal(loid)s in sediment showed higher levels than those in paddy soil, except for Pb. Cd and Cu in the system had the highest Ef levels, which probably pose a high risk to organisms and the health of local residents. There were significantly linear relationships between the site rank index (SRI) for water and that for sediment or paddy soil, revealing that matrices in the system interacted with each other. Principal component analysis (PCA) and absolute principal component scores and multiple linear regression model (APCS-MLR) results demonstrated that Cu, Zn, As, Cu, Pb, and U enrichments in the system were mainly affected by mining activities and were predominately deposited in sediment. Point pollution sources rather than non-point pollution sources such as mining activities, contributed most of the anthropogenic metal(loid)s to sediment. Both SRI and Hierarchical cluster analysis (HCA) results visually showed that S5, S8, S9, S10, S11, and S12 severe pollution grouped together and scattered through areas with extensive mining activities, while other sites with moderate pollution were spread along the main stream of the Le’an River.

Vibrio parahaemolyticus is a common foodborne bacterial pathogen, which survives in cold environments and is sometimes difficult to culture. Fatty acid analysis under cold stress was conducted for several V. parahaemolyticus strains using gas chromatography/mass spectrometry, and the results were compared with those of the controls. All the fatty acid profiles obtained were visualized by multidimensional scaling (MDS) and self-organized map (SOM). It was observed that the fatty acid profiles of V. parahaemolyticus substantially changed under cold stress. The percentage of methyl palmitate remarkably decreased and that of methyl palmitoleate (except for two strains) and methyl oleate increased. These findings demonstrate the role of fatty acids in cold stress. The changes in the fatty acid profiles illustrated by MDS and SOM could differentiate strains under cold stress from the controls and can potentially lead to a method of detecting injured cold-stressed V. parahaemolyticus .