Hybrid deep learning based prediction for water quality of plain watershed.

Establishing a highly reliable and accurate water quality prediction model is critical for effective water environment management. However, enhancing the performance of these predictive models continues to pose challenges, especially in the plain watershed with complex hydraulic conditions. This study aims to evaluate the efficacy of three traditional machine learning models versus three deep learning models in predicting the water quality of plain river networks and to develop a novel hybrid deep learning model to further improve prediction accuracy. The performance of the proposed model was assessed under various input feature sets and data temporal frequencies. The findings indicated that deep learning models outperformed traditional machine learning models in handling complex time series data. Long Short-Term Memory (LSTM) models improved the R2 by approximately 29% and lowered the Root Mean Square Error (RMSE) by about 48.6% on average. The hybrid Bayes-LSTM-GRU (Gated Recurrent Unit) model significantly enhanced prediction accuracy, reducing the average RMSE by 18.1% compared to the single LSTM model. Models trained on feature-selected datasets exhibited superior performance compared to those trained on original datasets. Higher temporal frequencies of input data generally provide more useful information. However, in datasets with numerous abrupt changes, increasing the temporal interval proves beneficial. Overall, the proposed hybrid deep learning model demonstrates an efficient and cost-effective method for improving water quality prediction performance, showing significant potential for application in managing water quality in plain watershed.

Microplastics and biochar interactively affect nitrous oxide emissions from tobacco planting soil.

Biochar application to amend acidified tobacco-soils can enhance tobacco quality and reduce nitrous oxide (N2O) emissions. Microplastics from agricultural mulch are commonly found in cash-crop farmland soils and, together with biochar, affect soil N2O emissions. In this study, we applied three types of microplastics (polyethylene, PE; polylactic acid, PLA; polybutylene adipate terephthalate, PBAT) and rice biochar alone or in combination to acidified tobacco planting soil in central China to investigate their effects on soil N2O emissions, soil chemical properties, nitrogen-cycle-related functional genes, and microbial functional diversity during a 35-day laboratory incubation period. Significant increases in N2O emissions were observed with PE and PLA, which raised emissions by 15.96 % and 21.52 %, respectively. Additionally, different microplastics affected soil N2O emissions through distinct regulatory pathways. Co-application of microplastics and biochar suppressed N2O emissions compared to microplastics alone. Biochar mitigates N2O emissions mainly by increasing the abundance of the nosZ gene. It can remediate soil contaminated by microplastics and reduce their negative impacts on the soil environment. This study provides deeper insight into the effects of microplastics on soil nitrogen cycling and biochar-mitigated remediation of microplastic-contaminated soil.

Specific CpG sites methylation is associated with hematotoxicity in low-dose benzene-exposed workers.

Benzene is a broadly used industrial chemicals which causes various hematologic abnormalities in human. Altered DNA methylation has been proposed as epigenetic biomarkers in health risk evaluation of benzene exposure, yet the role of methylation at specific CpG sites in predicting hematological effects remains unclear. In this study, we recruited 120 low-level benzene-exposed and 101 control male workers from a petrochemical factory in Maoming City, Guangdong Province, China. Urinary S-phenylmercapturic acid (SPMA) in benzene-exposed workers was 3.40-fold higher than that in control workers (P < 0.001). Benzene-induced hematotoxicity was characterized by reduced white blood cells counts and nuclear division index (NDI), along with an increased DNA damage and urinary 8-hydroxy-2'-deoxyguanosine (all P < 0.05). Methylation levels of TRIM36, MGMT and RASSF1a genes in peripheral blood lymphocytes (PBLCs) were quantified by pyrosequencing. CpG site 6 of TRIM36, CpG site 2, 4, 6 of RASSF1a and CpG site 1, 3 of MGMT methylation were recognized as hot CpG sites due to a strong correlation with both internal exposure and hematological effects. Notably, integrating hot CpG sites methylation of multiple genes reveal a higher efficiency in prediction of integrative damage compared to individual genes at hot CpG sites. The negative dose-response relationship between the combined methylation of hot CpG sites in three genes and integrative damage enabled the classification of benzene-exposed individuals into high-risk or low-risk groups using the median cut-off value of the integrative index. Subsequently, a prediction model for integrative damage in benzene-exposed populations was built based on the methylation status of the identified hot CpG sites in the three genes. Taken together, these findings provide a novel insight into application prospect of specific CpG site methylation as epi-biomarkers for health risk assessment of environmental pollutants.

Differences of RUNX2 gene promoter methylation and transcription level in ankylosing spondylitis.

BACKGROUND AND OBJECTIVE: Ankylosing spondylitis is a refractory immune disease that seriously affects the life and work of patients. Epigenetic modifications, especially DNA methylation, have become a research hotspot in complex diseases. We aim to explore the changes in runt-related transcription factor 2 (RUNX2) gene promoter methylation and transcription level in AS. METHOD: We detected the RUNX2 gene promoter methylation in 83 AS patients and 83 healthy controls (HCs), then inspected the mRNA difference of RUNX2 between 30 AS patients and 30 HCs by the quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: The RUNX2 gene promoter was hypomethylated in AS patients compared to HCs (p < .001). The research involved 4 CpG regions and 74 CpG sites of RUNX2, of which CpG-2, CpG-4 regions, and 18 CpG sites have been differentially methylated. The CpG-4 island methylation was negatively correlated with C-reactive protein (p < .05) in AS patients. In the qRT-PCR validation phase, the mRNA level of RUNX2 in AS patients was significantly higher than HCs (p < .05), and in AS patients who were treated with biologics, the methylation level of CpG-2 island showed a negative correlation to mRNA (p < .05). ROC results indicated that RUNX2 methylation and its transcription level have good potential to distinguish AS patients from HCs. CONCLUSION: The RUNX2 gene promoter was hypomethylated in AS patients. Meanwhile, the qRT-PCR verified the up-regulated expression on the transcription level, suggesting the abnormal methylation of RUNX2 contributes to the pathogenesis of AS.

PRICKLE1 gene methylation and abnormal transcription in Chinese patients with ankylosing spondylitis.

BACKGROUND: Ankylosing spondylitis (AS) is a common inflammatory arthritis without a reliable biomarker. The role of methylation and mRNA expression of PRICKLE1 promoter in the pathogenesis of ankylosing spondylitis remains unclear. METHODS: A two-stage case-control design was used to detect the characteristics of methyl group and transcriptome of PRICKLE1 gene in Ankylosing spondylitis. The methylation degree of PRICKLE1 gene promoter region was tested by phosphate-sequencing, and further analyzed whether there was significant difference in methylation level of PRICKLE1 gene. The expression levels of PRICKLE1 mRNA in 50 AS patients and 50 healthy controls were detected by real-time quantitative PCR (RT-qPCR). RESULTS: Compared with healthy control group, the intensity of methylation in 4 ponds of PRICKLE1 in patients with Ankylosing spondylitis was low, and the mRNA levels were overexpressed (P = 0.017). ROC results showed that the sensitivity of PRICKLE1 was 68.67% and specificity was 71.43%. CONCLUSION: There is a significant change in the concentration of serum PRICKLE1 mRNA​in patients with Ankylosing spondylitis, and the degree of gene methylation is significantly reduced, suggesting that PRICKLE1 gene maybe involved in the pathogenesis of Ankylosing spondylitis, which may be useful for predicting the occurrence of AS and finding new early screening indicators.

DNA methylation and transcription of the FOXO3a gene are associated with ankylosing spondylitis.

To explore the association between methylation level and transcript level of Forkhead box O3a (FOXO3a) gene with ankylosing spondylitis (AS) susceptibility. Methylation levels of the FOXO3a promoter were measured in 84 AS patients and 83 healthy controls. A total of 77 patients and 66 healthy subjects were included in subsequent mRNA level testing. DNA methylation levels of 107 CpG sites on 6 CpG islands in the FOXO3a gene were investigated. This study indicated that CpG-4 and CpG-5 islands were markedly hypomethylated in AS patients. The methylation level of CpG-4 island in AS patients was negatively correlated with erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and Ankylosing Spondylitis Disease Activity Score (ASDAS). Moreover, FOXO3a mRNA levels were significantly decreased in AS patients and were obviously negatively correlated with the methylation levels of CpG-2 and CpG-5 islands in AS patients without treatment. The sensitivity and specificity of differential methylated CpG sites of FOXO3a were 74.7 and 85.4%, respectively. Besides, FOXO3a mRNA had a sensitivity of 80.0% and a specificity of 68.8%. DNA methylation and transcription of FOXO3a might be related to AS susceptibility and play a crucial role in the diagnosis of AS, but many open questions remain.

Ecological risk assessment based on soil adsorption capacity for heavy metals in Taihu basin, China.

Due to the toxicity, bioaccumulation, non-biodegradability and perseverance of heavy metals, their risk assessment is essential for soil quality management. The Hakanson potential ecological risk index (RI), which considers the effects of heavy metal concentration and toxicity, has been widely used in soil ecological risk assessment. However, RI overlooks the influence of soil properties on the mobility and availability of heavy metals in risk assessment. To fill this gap, this study sought to develop an improved ecological risk index (IRI), which incorporates soil adsorption into RI, and applied it to evaluate the ecological risk of heavy metals in the soil of the Taihu basin, China. The soil adsorption models based on the Gradient Boosting Decision Tree (GBDT) was used to predict the soil adsorption capacity of five heavy metals (i.e. cadmium, chromium, copper, lead, zinc). The soil adsorption capacity in 1446 sites in the Taihu basin was predicted by the GBDT models and was assigned as the weight of IRI. The risk assessment results of the five metals in the Taihu basin showed that 40% of the sites were at a moderate risk level and 60% of the sites were at a slight risk level based on the RI. The value of IRI in the basin ranged from 11.1 to 75.5, with a mean value of 28.1. IRI differed from RI in spatial distribution due to the influence of soil adsorption. The comparative analysis between the metal contents in sediments and surrounding soils confirmed the tremendous influence of soil adsorption on ecological risks, indicating that soil adsorption should be taken into consideration in soil risk assessment.

Endoplasmic Reticulum Aminopeptidase 1 Is Involved in Anti-viral Immune Response of Hepatitis B Virus by Trimming Hepatitis B Core Antigen to Generate 9-Mers Peptides.

Endoplasmic reticulum aminopeptidase 1 (ERAP1) is a processing enzyme of antigenic peptides presented to major histocompatibility complex (MHC) class I molecules. ERAP1-dependent trimming of epitope repertoire determines an efficacy of adoptive CD8+ T-cell responses in several viral diseases; however, its role in hepatitis B virus (HBV) infection remains unknown. Here, we show that the serum level of ERAP1 in patients with chronic hepatitis B (CHB) (n = 128) was significantly higher than that of healthy controls (n = 44) (8.78 ± 1.82 vs. 3.52 ± 1.61, p < 0.001). Furthermore, peripheral ERAP1 level is moderately correlated with HBV DNA level in patients with CHB (r = 0.731, p < 0.001). HBV-transfected HepG2.2.15 cells had substantially increased ERAP1 expression and secretion than the germline HepG2 cells (p < 0.001). The co-culture of ERAP1-specific inhibitor ERAP1-IN-1 pretreated HepG2.2.15 cells or ERAP1 knockdown HepG2.2.15 cells with CD8+ T cells led to 14-24% inhibition of the proliferation of CD8+ T cells. Finally, liquid chromatography tandem mass spectrometry (LC-MS/MS) test demonstrated that ERAP1-IN-1 blocks completely the production of a 9-mers peptide (30-38, LLDTASALY) derived from Hepatitis B core antigen (HBcAg). The predictive analysis by NetMHCpan-4.1 server showed that human leukocyte antigen (HLA)-C*04:01 is a strong binder for the 9-mers peptide in HepG2.2.15 cells. Taken together, our results demonstrated that ERAP1 trims HBcAg to produce 9-mers LLDTASALY peptides for binding onto HLA-C*04:01 in HepG2.2.15 cells, facilitating the potential activation of CD8+ T cells.

Analysis of ecosystem service drivers based on interpretive machine learning: a case study of Zhejiang Province, China.

A systematic understanding of the driving mechanisms of ecosystem services (ESs) and the relationships among them is critical for successful ecosystem management. However, the impact of driving factors on the relationships between ESs and the formation of ecosystem service bundles (ESBs) remains unclear. To address this gap, we developed a modeling process that used random forest (RF) to model the ESs and ESBs of Zhejiang Province, China, in regression and classification mode, respectively, and the Shapley Additive Explanations (SHAP) method to interpret the underlying driving forces. We first mapped the spatial distribution of seven ESs in Zhejiang Province at a 1 × 1 km spatial resolution and then used the K-means clustering algorithm to obtain four ESBs. Combining the RF models with SHAP analysis, the results showed that each ES had key driving factors, and the relationships of synergy and trade-off between ESs were determined by the driving direction and intensity of the key factors. The driving factors affect the relationships of ESs and consequently affect the formation of ESBs. Thus, managing the dominant drivers is key to improving the supply capacity of ESs.

Prevalence and risk of COVID-19 in patients with rheumatic diseases: a systematic review and meta-analysis.

OBJECTIVES: COVID-19 pandemic has already had a tremendous impact on the process of human society; the survival of mankind and the healthy living environment deterioration with the influence will last for many years. This meta-analysis aims to assess the risk of COVID-19 in patients with rheumatic diseases. METHODS: PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and Chinese Biomedical Database (CBM) were systematically searched with no language restriction up to July 5, 2021. The pooled rates were synthesized by fixed effect model or random effect model depending on heterogeneity. RESULTS: A total of 83 articles were included in this meta-analysis. The incidence of COVID-19 in patient with rheumatic diseases was 0.0190 (95% CI: 0.0136-0.0252), and the hospitalization rate, intensive care unit admission rate, mechanical ventilation rate, and case fatality rate of patients with rheumatic diseases infected with COVID-19 were 0.4396 (95% CI: 0.3899-0.4898), 0.0635 (95% CI: 0.0453-0.0836), 0.0461 (95% CI: 0.0330-0.0609), and 0.0346 (95% CI: 0.0218-0.0493), respectively. CONCLUSIONS: Our research shows that patients with rheumatic diseases have great risk of COVID-19. Differences in COVID-19 incidence, hospitalization rates, and mortality rates in regions were statistically significant. We still need to pay attention to the risk of COVID-19 in patients with rheumatic diseases. KEY POINTS: • Although the risk of COVID-19 in patients with rheumatic diseases has been discussed in previous meta-analysis, their research directions were inconsistent, and few studies focus on prevalence or serious outcomes of COVID-19 in patient with rheumatic diseases, while the quality of these articles was variable. • The incidence of COVID-19 and serious clinical outcomes in patients with rheumatic diseases were still high along with differential risks in most regions. • The use of glucocorticoids and conventional synthetic disease-modifying antirheumatic drugs did not affect the hospitalization rate and mortality in rheumatism patients with COVID-19.

Telomere length in patients with osteoarthritis: a systematic review and meta-analysis.

BACKGROUND: Telomere length (TL) as a biomarker of aging was associated with many age-related diseases. The relationship between TL and osteoarthritis (OA), the most common form of joint diseases, had been investigated in a number of studies, but with the result inconsistent. AIMS: The purpose of this study was to systematically evaluate the relationship between TL and OA. METHODS: Until January 1, 2021, PubMed, Web of Science and Cochrane Library were comprehensively retrieved for relevant literatures. Quality of included literature was assessed using the Newcastle-Ottawa Scale (NOS) assessment scale. The pooled standard mean difference (SMD) with 95% confidence interval (CI) of Leukocytes TL was calculated using random-effect model. Subgroup analysis and meta-regression were used to investigate the potential source of heterogeneity. RESULTS: Six original studies containing 678 OA patients and 1457 healthy controls were included in this meta-analysis. All six included studies were case-control designed. Pooled results showed that patients with OA had a shorter TL in peripheral blood leukocytes (PBLs) compared with healthy controls, (SMD = - 0.32, 95% CI - 0.57 to - 0.06, Z = - 2.45, P = 0.014). Subgroup and meta-regression analysis showed that sex ratio and body mass index (BMI) were possible sources of heterogeneity. Publication bias was not observed. CONCLUSION: The TL of PBLs in patients with OA was shorter than that of healthy controls, suggesting that PBLs TL may be closely associated with the pathogenesis and progression of OA.

Influence of prefoldin subunit 4 on the tolerance of Kluyveromyces marxianus to lignocellulosic biomass-derived inhibitors.

BACKGROUND: Kluyveromyces marxianus is a potentially excellent host for microbial cell factories using lignocellulosic biomass, due to its thermotolerance, high growth rate, and wide substrate spectrum. However, its tolerance to inhibitors derived from lignocellulosic biomass pretreatment needs to be improved. The prefoldin complex assists the folding of cytoskeleton which relates to the stress tolerance, moreover, several subunits of prefoldin have been verified to be involved in gene expression regulation. With the presence of inhibitors, the expression of a gene coding the subunit 4 of prefoldin (KmPFD4), a possible transcription factor, was significantly changed. Therefore, KmPFD4 was selected to evaluate its functions in inhibitors tolerance. RESULTS: In this study, the disruption of the prefoldin subunit 4 gene (KmPFD4) led to increased concentration of intracellular reactive oxygen species (ROS) and disturbed the assembly of actin and tubulin in the presence of inhibitors, resulting in reduced inhibitor tolerance. Nuclear localization of KmPFD4 indicated that it could regulate gene expression. Transcriptomic analysis showed that upregulated gene expression related to ROS elimination, ATP production, and NAD+ synthesis, which is a response to the presence of inhibitors, disappeared in KmPFD4-disrupted cells. Thus, KmPFD4 impacts inhibitor tolerance by maintaining integration of the cytoskeleton and directly or indirectly affecting the expression of genes in response to inhibitors. Finally, overexpression of KmPFD4 enhanced ethanol fermentation with a 46.27% improvement in productivity in presence of the inhibitors. CONCLUSION: This study demonstrated that KmPFD4 plays a positive role in the inhibitor tolerance and can be applied for the development of inhibitor-tolerant platform strains.

Predicting Heavy Metal Adsorption on Soil with Machine Learning and Mapping Global Distribution of Soil Adsorption Capacities.

Studying heavy metal adsorption on soil is important for understanding the fate of heavy metals and properly assessing the related environmental risks. Existing experimental methods and traditional models for quantifying adsorption, however, are time-consuming and ineffective. In this study, we developed machine learning models for the soil adsorption of six heavy metals (Cd(II), Cr(VI), Cu(II), Pb(II), Ni(II), and Zn(II)) using 4420 data points (1105 soils) extracted from 150 journal articles. After a comprehensive comparison, our results showed that the gradient boosting decision tree had the best performance for a combined model based on all the data. The Shapley additive explanation method was used to identify the feature importance and the effects of these features on the adsorption, based on which six independent models were developed for the six metals to achieve better model performance than the combined model. Using these independent models, the global distribution of heavy metal adsorption capacities on soils was predicted with known soil properties. Reversed models, including one combined model for all the six metals and six independent models, were also built using the same data sets to predict the heavy metal concentration in water when the adsorbed amount is known for a soil/sediment.

Spatial heterogeneity modeling of water quality based on random forest regression and model interpretation.

A systematic understanding of the spatial distribution of water quality is critical for successful watershed management; however, the limited number of physical monitoring stations has restricted the evaluation of spatial water quality distribution and the identification of features impacting the water quality. To fill this gap, we developed a modeling process that employed the random forest regression (RFR) to model the water quality distribution for the Taihu Lake basin in Zhejiang Province, China, and adopted the Shapley Additive exPlanations (SHAP) method to interpret the underlying driving forces. We first used RFR to model three water quality parameters: permanganate index (CODMn), total phosphorus (TP), and total nitrogen (TN), based on 16 watershed features. We then applied the built models to generate water quality distribution maps for the basin, with the CODMn ranging from 1.39 to 6.40 mg/L, TP from 0.02 to 0.23 mg/L, and TN from 1.43 to 4.27 mg/L. These maps showed generally consistent patterns among the CODMn, TN, and TP with minor differences in the spatial distribution. The SHAP analysis showed that the TN was mainly affected by agricultural non-point sources, while the CODMn and TP were affected by agricultural and domestic sources. Due to differences in sewage collection and treatment between urban and rural areas, the water quality in highly populated urban areas was better than that in rural areas, which led to an unexpected positive relationship between water quality and population density. Overall, with the RFR models and SHAP interpretation, we obtained a continuous distribution pattern of the water quality and identified its driving forces in the basin. These findings provided important information to assist water quality restoration projects.

Association of FOXO3a gene polymorphisms and ankylosing spondylitis susceptibility in Eastern Chinese Han population.

OBJECTIVE: To investigate the association of FOXO3a polymorphisms and ankylosing spondylitis (AS) susceptibility in Eastern Chinese Han population. METHODS: FOXO3a polymorphisms rs12206094, rs12212067, rs2253310, rs3800232, and rs4946933 were genotyped in 650 AS patients and 646 controls by the improved Multiple Ligase Detection Reaction. RESULTS: The distribution of genotype in rs12212067 polymorphism was significantly different between AS patients and controls (P = 0.020), especially in male population (P = 0.009). There was significant difference of the genotype frequency distribution at rs3800232 between patients and controls in male population. The results of binary regression analysis showed that the rs12212067 GG genotype and rs3800232 TT genotype were obviously correlated with elevated AS risk, and the associations were still significant after being adjusted by age and gender (all P < 0.05). Interestingly, rs12212067 and rs3800232 genotypes were associated with disease activity of patients. Additionally, haplotype block rs12212067G- rs3800232T (OR = 1.403, 95%CI = 1.011-1.949) was further shown to confer promoting effect on developing AS. CONCLUSION: Among Eastern Chinese Han population, FOXO3a polymorphism rs12212067 and rs3800232 may contribute to increased risk of developing AS, but well-designed multicenter studies are needed to further confirm these preliminary findings in the future.

Enhancement of perchloroethene dechlorination by a mixed dechlorinating culture via magnetic nanoparticle-mediated isolation method.

Highly enriched active dechlorinating cultures are important in advancing microbial remediation technology. This study attempted to enrich a rapid perchloroethene (PCE) dechlorinating culture via magnetic nanoparticle-mediated isolation (MMI). MMI is a novel method that can separate the fast-growing and slow-growing population in a microbial community without labelling. In the MMI process, PCE dechlorination was enhanced but the subsequent trichloroethene (TCE) dechlorination was inhibited, with TCE cumulative rate reached up to 80.6% within 70 days. Meanwhile, the microbial community was also changed, with fast-growing genera like Dehalobacterium and Petrimonas enriched, and slow-growing Methanosarcina almost ruled out. Relative abundances of several major genera including Petrimonas and Methanosarcina were positively related to TCE dechlorination rate and the relative abundance of Dehalococcoides. On the other hand, Dehalobacterium was negatively related to TCE dechlorination rate and Dehalococcoides abundance, suggesting potential competition between Dehalobacterium and Dehalococcoides. The regrowth of Methanosarcina coupled well with the recovery of TCE dechlorination capacity, which implied the important role of methanogens in TCE dechlorination. Via MMI method, a simpler but more active microbial consortium could be established to enhance PCE remediation efficiency. Methanogens may act as the indicators or biomarkers for TCE dechlorination, suggesting that methanogenic activity should also be monitored when enriching dechlorination cultures and remediating PCE contaminated sites. CAPSULE: A rapid perchloroethene dechlorinator was gotten via magnetic nanoparticles and dechlorination of trichloroethene coupled well with growth of Methanosarcina.

Single nucleotide polymorphisms of TRAF2 and TRAF5 gene in ankylosing spondylitis: a case-control study.

Objective To investigate the role of eight locus polymorphisms of tumor necrosis factor receptor-associated factor 2 (TRAF2) and TRAF5 gene and their interaction in the susceptibility to ankylosing spondylitis (AS) in Chinese Han population. Methods Eight single nucleotide polymorphisms (SNPs) of TRAF2 (rs3750511, rs10781522, rs17250673, rs59471504) and TRAF5 (rs6540679, rs12569232, rs4951523, rs7514863) gene were genotyped in 673 AS patients and 687 controls. Results The SNPs of TRAF2 and TRAF5 do not indicate a correlation with the susceptibility of AS in Chinese Han population. Genotype frequencies of rs3750511 were statistically significant in females between patients and controls. The allele frequencies of rs10781522 and genotype frequencies of rs3750511 were statistically significant between groups of different diseases activity. One three-locus model, TRAF2 (rs10781522, rs17250673) and TRAF5 (rs12569232), had a maximum testing accuracy of 52.67% and a maximum cross-validation consistency (10/10) that was significant at the level of P = 0.0001, after determined empirically by permutation testing. As to environmental variables, only marginal association was found between sleep quality and AS susceptibility. Conclusion TRAF2 rs3750511 polymorphism may be associated with the susceptibility and severity of AS. Besides, the interaction of TRAF2 and TRAF5 genes may be associated with AS susceptibility, but many open questions remain.

Association of CTLA-4 (+49 A/G) polymorphism with susceptibility to autoimmune diseases: A meta-analysis with trial sequential analysis.

OBJECTIVES: In recent years, more and more studies have been focusing on the association between Cytotoxic T lymphocyte antigen-4 (CTLA-4) (+49 A/G) gene polymorphism and autoimmune diseases. However, the results of previous studies are still controversial. The meta-analysis is aiming at determining the association in CTLA-4 (+49 A/G) gene rs231775 polymorphism and ankylosing spondylitis (AS), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE). METHODS: We searched PubMed, Web of Science, Chinese National Knowledge Infrastructure (CNKI) and Chinese Biomedical Database (CBM) up to November 2020, use random or fixed-effect models to perform meta-analysis to compare alleles and other genetic models, including homozygous, heterozygous, recessive and dominant models. The odds ratio (OR) with a 95% confidence interval (95% CI) was used to assess the correlation between CTLA-4 (+49 A/G) gene polymorphism and the genetic affectability of AS, RA, and SLE. Meanwhile, we used sequential trial analysis (TSA) to analyze the reliability of the results. Finally, we searched the relevant data of genome-wide association studies (GWAS) to further verify the accuracy of the experimental results. RESULTS: 47 studies with 11,893 cases and 12,032 healthy controls were included. The rs231775 G allele was relevant to high risk of autoimmune disease over all people (P < 0.05). The G allele of rs231775 was significantly related to RA susceptibility (P < 0.05), but not with AS or SLE. Subgroup analysis by ethnicity indicated that rs231775 G allele was closely related to RA in Caucasian populations and Mongolian populations (P < 0.05). A strong connection within rs231775 G allele and AS affectability was uncovered in Caucasian populations (P < 0.05). The analysis of the TSA shows that the meta-analysis can draw the conclusion. CONCLUSION: CTLA-4 (+49 A/G) gene rs231775 G allele increases the risk of autoimmune diseases in Caucasian populations. And it also increases the risk of RA in Caucasian and Mongolian populations. More sample size and more elaborately designed studies are needed to elucidate the relationship in CTLA-4 (+49 A/G) gene rs231775 G allele and autoimmune diseases, especially AS, SLE.

An improved weighted index for the assessment of heavy metal pollution in soils in Zhejiang, China.

Soil heavy metal pollution assessment is an important procedure in soil quality and ecological risk management, for which different mathematical models have been developed. However, these models have often failed to consider the characteristics of both heavy metals and the polluted sites. In this study, we analyzed the concentrations of seven heavy metals in soils in Zhejiang Province, China, and developed an improved weighted index (IWI) model to evaluate pollution levels. In contrast to traditional models, weights were assigned to different heavy metals using statistical tools, including hierarchical cluster analysis and principal component analysis. Of the 89 sites, 61.8% were considered unpolluted with IWI values < 1; 32.58% were slighted polluted with IWI values from 1 to 2, and only 2.25% of the sites were seriously polluted with IWI values > 3. The IWI results agree well with two traditional integrated index models, but can be also applied to much wider heavy metal concentration ranges. Possible pollution sources were then proposed based on the IWI model. The IWI overcame several shortcomings of the traditional indices and could be very beneficial for assessing heavy metal pollution in soil. Overall, this study developed a new model for soil pollution assessment and soil ecological risk management and comprehensively evaluated the current pollution status of soil surrounding potable surface water sources in Zhejiang Province, China.

Microbial Quality of Ready-to-Eat Foods Sold in School Cafeterias in Chongqing, China.

ABSTRACT: The microbiological quality of ready-to-eat (RTE) foods from school cafeterias in Chongqing, People's Republic of China, was evaluated and compared with a guideline published by a provincial health commission. These RTE foods were divided into five types based on their preparation processes and potential risks: 1, general cooked and hot-held foods; 2, cooked meats; 3, heated aquatic products; 4, fresh fruits or vegetables; and 5, cooked foods with postcooking handling (e.g., cutting, cooling, or addition of ingredients or condiments). Food types 1 through 3 (subjected to thermal processes and hot-held) were microbiologically safer than types 4 and 5 (prepared by nonthermal process or with postcooking processes). None of the samples of types 1 through 3 were unsatisfactory based on their aerobic plate counts (APC) and total coliforms (TC), whereas 43.1% of type 4 and 8.3 and 71.7% of type 5 samples were unsatisfactory due to high counts of TC and high APC and TC, respectively. Two, 12, and 50 samples of types 2, 4, and 5, respectively, were unacceptable due to high levels of Staphylococcus aureus. Bacillus cereus and Vibrio parahaemolyticus were detected, but levels were below the unacceptable limits. None of the samples were positive for Salmonella, Listeria monocytogenes, or Escherichia coli O157. The bacterial profile can be used by policy makers and epidemiologists for microbiological risk assessments, which may be conducive to developing interventions to control hazards, improve food hygiene, and develop safety management systems for school cafeterias in China.