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The new digital technology revolution is spurring corporate digital transformation. Presently, the majority of enterprises are still in the digitalization stage. They have yet to pinpoint the key factors and suitable paths for their transformation. Therefore, this study aims to determine which and how factors affect this transformation to improve the current enterprise's digital transformation. We extract key elements affecting corporate digital transformation. Taking 98 representative businesses as examples, we utilize the fuzzy-set qualitative comparative analysis approach (fsQCA) to investigate how different factors combine to achieve digital transformation. The results show that: (1) No single factor can achieve digital transformation for enterprises, as it requires a combination of multiple factors. (2) Four configuration paths can lead to corporate digital transformation. (3) A business can equivalently substitute resource consolidation with strategic planning and human resources to drive digital transformation. This study offers multiple paths for achieving corporate digital transformation to guide businesses in their choice of digital transformation pathways.

In many cases, the 'labeled' outcome is difficult to observe and may require a complicated or expensive procedure, and the predictor information is easy to be obtained. We propose a semi-supervised estimator for the one-dimensional varying coefficient regression model which improves the conventional supervised estimator by using the unlabeled data efficiently. The semi-supervised estimator is proposed by introducing the intercept model and its asymptotic properties are proven. The Monte Carlo simulation studies and a real data example are conducted to examine the finite sample performance of the proposed procedure.

Model averaging based on the least squares estimator or the maximum likelihood estimator has been widely followed, while model averaging based on the generalized method of moments is almost rarely addressed. This paper is concerned with a model averaging method based on the weighted generalized method of moments for missing responses problem. The weight vector for model averaging is obtained via minimizing the leave-one-out cross validation criterion. With some mild conditions, the asymptotic optimality of the proposed method in the sense that it can achieve the lowest squared error asymptotically is proved. Some numerical experiments are conducted to evaluate the proposed method with the existing related ones, and the results suggest that the proposed method performs relatively well.

Linear discriminant analysis (LDA) is one of the most widely used methods in discriminant classification and pattern recognition. However, with the rapid development of information science and technology, the dimensionality of collected data is high or ultrahigh, which causes the failure of LDA. To address this issue, a feature screening procedure based on the Fisher's linear projection and the marginal score test is proposed to deal with the ultrahigh-dimensional binary classification problem. The sure screening property is established to ensure that the important features could be retained and the irrelevant predictors could be eliminated. The finite sample properties of the proposed procedure are assessed by Monte Carlo simulation studies and a real-life data example.

In unsupervised learning, clustering is a common starting point for data processing. The convex or concave fusion clustering method is a novel approach that is more stable and accurate than traditional methods such as k-means and hierarchical clustering. However, the optimization algorithm used with this method can be slowed down significantly by the complexity of the fusion penalty, which increases the computational burden. This paper introduces a random projection ADMM algorithm based on the Bernoulli distribution and develops a double random projection ADMM method for high-dimensional fusion clustering. These new approaches significantly outperform the classical ADMM algorithm due to their ability to significantly increase computational speed by reducing complexity and improving clustering accuracy by using multiple random projections under a new evaluation criterion. We also demonstrate the convergence of our new algorithm and test its performance on both simulated and real data examples.

The COVID pandemic fueled by emerging SARS-CoV-2 new variants of concern remains a major global health concern, and the constantly emerging mutations present challenges to current therapeutics. The spike glycoprotein is not only essential for the initial viral entry, but is also responsible for the transmission of SARS-CoV-2 components via syncytia formation. Spike-mediated cell-cell transmission is strongly resistant to extracellular therapeutic and convalescent antibodies via an unknown mechanism. Here, we describe the antibody-mediated spike activation and syncytia formation on cells displaying the viral spike. We found that soluble antibodies against receptor binding motif (RBM) are capable of inducing the proteolytic processing of spike at both the S1/S2 and S2' cleavage sites, hence triggering ACE2-independent cell-cell fusion. Mechanistically, antibody-induced cell-cell fusion requires the shedding of S1 and exposure of the fusion peptide at the cell surface. By inhibiting S1/S2 proteolysis, we demonstrated that cell-cell fusion mediated by spike can be re-sensitized towards antibody neutralization in vitro. Lastly, we showed that cytopathic effect mediated by authentic SARS-CoV-2 infection remain unaffected by the addition of extracellular neutralization antibodies. Hence, these results unveil a novel mode of antibody evasion and provide insights for antibody selection and drug design strategies targeting the SARS-CoV-2 infected cells.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID‐19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran’s Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results.ResultsWe found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92–0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy.ConclusionsOur study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels.

SET binding protein 1 (SETBP1) is essential for human development, and pathogenic germline variants in SETBP1 lead to a recognizable developmental syndrome and variable clinical features. In this study, we assessed a patient with facial dysmorphism, intellectual disability and delayed motor development. Whole genome sequencing identified a novel de novo variation of the SETBP1 (c.2631C > A; p. S877R) gene, which is located in the SKI domain, as a likely pathogenic variant for the proband’s phenotype. RNA sequencing was performed to investigate the potential molecular mechanism of the novel variation in SETBP1. In total, 77 and 38 genes were identified with aberrant expression and splicing, respectively. Moreover, the biological functions of these genes were involved in DNA/protein binding, expression regulation, and the cell cycle, which may advance our understanding of the pathogenesis of SETBP1 in vivo.

Ovarian cancer (OC) is the third most common malignant tumor of women accompanied by alteration of systemic metabolism, yet the underlying interactions between the local OC tissue and other system biofluids remain unclear. In this study, we recruited 17 OC patients, 16 benign ovarian tumor (BOT) patients, and 14 control patients to collect biological samples including ovary plasma, urine, and hair from the same patient. The metabolic features of samples were characterized using a global and targeted metabolic profiling strategy based on Gas chromatography-mass spectrometry (GC-MS). Principal component analysis (PCA) revealed that the metabolites display obvious differences in ovary tissue, plasma, and urine between OC and non-malignant groups but not in hair samples. The metabolic alterations in OC tissue included elevated glycolysis (lactic acid) and TCA cycle intermediates (malic acid, fumaric acid) were related to energy metabolism. Furthermore, the increased levels of glutathione and polyunsaturated fatty acids (linoleic acid) together with decreased levels of saturated fatty acid (palmitic acid) were observed, which might be associated with the anti-oxidative stress capability of cancer. Furthermore, how metabolite profile changes across differential biospecimens were compared in OC patients. Plasma and urine showed a lower concentration of amino acids (alanine, aspartic acid, glutamic acid, proline, leucine, and cysteine) than the malignant ovary. Plasma exhibited the highest concentrations of fatty acids (stearic acid, EPA, and arachidonic acid), while TCA cycle intermediates (succinic acid, citric acid, and malic acid) were most concentrated in the urine. In addition, five plasma metabolites and three urine metabolites showed the best specificity and sensitivity in differentiating the OC group from the control or BOT groups (AUC > 0.90) using machine learning modeling. Overall, this study provided further insight into different specimen metabolic characteristics between OC and non-malignant disease and identified the metabolic fluctuation across ovary and biofluids.

The coronavirus disease (COVID-19) pandemic is a major challenge worldwide. However, the epidemic potential of common human coronaviruses (HCoVs) remains unclear. This study aimed to determine the epidemiological and co-infection characteristics of common HCoVs in individuals with influenza-like illness (ILI) and severe acute respiratory infection (SARI). This retrospective, observational, multicentre study used data collected from patients admitted to nine sentinel hospitals with ILI and SARI from January 2015 through December 2020 in Shanghai, China. We prospectively tested patients for a total of 22 respiratory pathogens using multi-real-time polymerase chain reaction. Of the 4541 patients tested, 40.37% (1833/4541) tested positive for respiratory pathogens and 3.59% (163/4541) tested positive for common HCoVs. HCoV infection was more common in the non-endemic season for respiratory pathogens (odds ratio: 2.33, 95% confidence interval: 1.64–3.31). HCoV-OC43 (41.72%, 68/163) was the most common type of HCoV detected. The co-infection rate was 31.29% (51/163) among 163 HCoV-positive cases, with HCoV-229E (53.13%, 17/32), the HCoV type that was most frequently associated with co-infection. Respiratory pathogens responsible for co-infections with HCoVs included parainfluenza virus, rhinovirus/enterovirus, influenza A virus, and adenovirus. Furthermore, we identified one patient co-infected with HCoV-OC43 and HCoV-NL63/HKU1. The prevalence of common HCoVs remains low in ILI/SARI cases, in Shanghai. However, the seasonal pattern of HCoVs may be opposite to that of other respiratory pathogens. Moreover, HCoVs are likely to co-exist with specific respiratory pathogens. The potential role of co-infections with HCoVs and other pathogenic microorganisms in infection and pathogenesis of ILI and SARI warrants further study.

MicroRNAs (miRNAs) are small endogenous single-stranded RNAs that regulate plant growth, development, and environmental stress response posttranscriptionally. Ammopiptanthus nanus, a rare evergreen broad-leaved shrub in the temperate area of Central Asia, can tolerate freezing stress as low as –30 degrees centigrade in winter, and miRNA might be involved in the cold acclimation which enables A. nanus to obtain tolerance to freezing stress. Systematic identification and functional analysis of the miRNAs involved in the cold acclimation in A. nanus may promote understanding of the miRNA-mediated gene regulation network underlying cold acclimation. Here, based on small RNA and degradome sequencing, 256 miRNAs and 1,808 miRNA-target pairs were identified in A. nanus. A total of 39 cold-responsive miRNAs were identified, of which 29 were upregulated and ten were downregulated. These cold-responsive miRNAs may participate in the cold acclimation by regulating redox homeostasis (miR398, miR4415, and miR408), calcium signaling (miR5225 and miR5211), growth and development (miR159 and miR390), and small RNA–mediated gene silencing (miR168 and miR1515). We found that miR4415, a legume-specific miRNA, is involved in the cold acclimation of A. nanus by targeting an L-ascorbate oxidase gene and then regulating the redox state of the apoplast. Our study provides important data for understanding the regulatory role of miRNA in the cold acclimation of A. nanus.

The global spread of SARS-CoV-2 is currently continuing, and the World Health Organization has announced the risk assessment of the viruses as high. In this study, we analyzed virology features of SARS-CoV-2 causing a family cluster outbreak. Among the six family members, five have been laboratory-confirmed infection of SARS-CoV-2 viruses. A total of five SARS-CoV-2 viruses have been isolated from the nasopharyngeal swabs. The complete genome of the viruses exhibited 100% nucleotide identity with each other. Only two nucleotide differences have been observed between genomes of the isolated viruses and the HCoV/Wuhan/ IVDC-HB-01/2019 strain. Therefore, SARS-CoV-2 has been confirmed as the causation of the family cluster infections.

Polype ntafluoropropane glycidyl ether (PPFEE), a new random block hydroxyl-terminated polyfluoroether, was synthesized successfully by cationic ring-opening polymerization of 2-(2,2,3,3,3-pentafluoropropoxymethyl) oxirane, and its molecular structure was confirmed by Fourier transform infrared spectroscopy, nuclear magnetic resonance spectrometry, and gel permeation chromatography. The PPFEE-based polyurethane elastomers featuring fluorine in their side chains were prepared using PPFEE as soft segments, polyisocyanate polyaryl polymethylene isocyanate as hard segments, and dibutyltin dilaurate as catalysts under different curing conditions. The microphase separation, mechanical performance, and thermal behavior of the elastomers were investigated by differential scanning calorimetry, uniaxial tensile test, and thermal gravimetric analysis, respectively. Based on the results, the percentage of hard segments dissolved into the soft segments of elastomers was opposite to the change in breaking strength. The PPFEE-based polyurethane elastomer cured with 20 wt% PAPI at the curing temperature of 50 °C displayed the maximum tensile elongation of 2.26 MPa with an elongation at break of nearly 150%. The increased contents of PAPI can effectively strengthen the tensile strength, and the maximum tensile elongation was 3.04 MPa with an elongation at break of nearly 90% when the content of PAPI was 26 wt%. In addition, the PPFEE-based polyurethane elastomers exhibited excellent resistance to thermal decomposition and a sharp weight loss temperature at around 371 °C. All the results demonstrated that the PPFEE may be a potential polymeric binder as one of the ingredients applied to future propellant formulations.

Abstract Background The sequencing platform BGISEQ-500 is based on DNBSEQ technology and provides high throughput with low costs. This sequencer has been widely used in various areas of scientific and clinical research. A better understanding of the sequencing process and performance of this system is essential for stabilizing the sequencing process, accurately interpreting sequencing results and efficiently solving sequencing problems. To address these concerns, a comprehensive database, SEQdata-BEACON, was constructed to accumulate the run performance data in BGISEQ-500. Results A total of 60 BGISEQ-500 instruments in the BGI-Wuhan lab were used to collect sequencing performance data. Lanes in paired-end 100 (PE100) sequencing using 10 bp barcode were chosen, and each lane was assigned a unique entry number as its identification number (ID). From November 2018 to April 2019, 2236 entries were recorded in the database containing 65 metrics about sample, yield, quality, machine state and supplies information. Using a correlation matrix, 52 numerical metrics were clustered into three groups signifying yield-quality, machine state and sequencing calibration. The distributions of the metrics also delivered information about patterns and rendered clues for further explanation or analysis of the sequencing process. Using the data of a total of 200 cycles, a linear regression model well simulated the final outputs. Moreover, the predicted final yield could be provided in the 15th cycle of the early stage of sequencing, and the corresponding R2 of the 200th and 15th cycle models were 0.97 and 0.81, respectively. The model was run with the test sets obtained from May 2019 to predict the yield, which resulted in an R2 of 0.96. These results indicate that our simulation model was reliable and effective. Conclusions Data sources, statistical findings and application tools provide a constantly updated reference for BGISEQ-500 users to comprehensively understand DNBSEQ technology, solve sequencing problems and optimize run performance. These resources are available on our website http://seqBEACON.genomics.cn:443/home.html.

Background: Widespread exposure to parabens has been a concern, especially among pregnant women. Only one study reported that parabens are associated with glucose levels among pregnant women. However, studies on parabens exposure and gestational diabetes mellitus (GDM) are lacking. Objectives: This study investigated whether exposure to parabens in early pregnancy is related to GDM. Methods: We conducted a prospective study of 1087 pregnant women from a single tertiary medical center between 2014 and 2015 in Wuhan, China. Parabens [methyl paraben (MeP), ethylparaben (EtP), propylparaben (PrP), butylparaben (BuP), and benzylparaben (BzP)] concentrations were measured in spot urine samples collected between 8 and 16 gestational weeks. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Groups Consensus Panel (IADPSG) recommendations. We used the Poisson regression with a robust error variance with generalized estimating equations (GEE) estimation analyses to evaluate associations between parabens exposure and GDM risk. Results: A total of 103 (9.5%) women were diagnosed with GDM. We evaluated the associations of GDM risk with urinary MeP, EtP, and PrP (detection rate: >90%), but not with BuP and BzP due to the relatively low detection rate (

Previous studies have proven the endocrine-disrupting properties and health hazards of parabens, triclosan, and benzophenones, but their relationship with blood pressure during pregnancy remains unknown. Therefore, we investigated the associations of repeated measures of urinary parabens, triclosan, and benzophenones with blood pressure during pregnancy and evaluated whether the associations were modified by fetal sex. From a prospective birth cohort in Wuhan, China, we collected urine samples from 644 pregnant women in the first, second, and third trimesters between 2014 and 2015. Five parabens, triclosan, and three benzophenones were quantified in all urine samples. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured in each trimester after urine sampling. Mixed linear models were used to estimate the associations between urinary chemical levels and blood pressure during pregnancy among all pregnant women and subgroups stratified by fetal sex. In the women carrying male fetuses, urinary triclosan and selected benzophenone concentrations were associated with a slight change of SBP during pregnancy. In the women carrying female fetuses, no chemical was associated with SBP, while urinary concentration of triclosan was inversely associated with DBP, though the magnitude was small. Urinary paraben levels weren't associated with blood pressure during pregnancy. Our results suggest that triclosan and selected benzophenone exposure might be associated with blood pressure during pregnancy in a potential fetal sex-different manner. Replicated research studies in pregnant women with higher triclosan and benzophenone exposure levels are needed in the future.

Background: Previous studies have suggested that phthalates might disrupt fetal steroidogenesis. However, the evidence of the effects of prenatal phthalate exposure across pregnancy on fetal glucocorticoids was insufficient. Objective: We investigated the associations between urinary phthalate metabolites across pregnancy and cord blood glucocorticoids in a prospective birth cohort. Methods: Our study included 553 mother-infant pairs from a prospective birth cohort conducted in Wuhan, China. Maternal urine samples were collected at 14, 24 and 36 weeks of gestation (mean). Urinary phthalate metabolites and cord blood glucocorticoids (cortisol and cortisone) were measured. Generalized estimating equation models were conducted to explore the relationships of phthalate metabolite concentrations at each trimester and glucocorticoid levels. Results: Among the participants, mono‑benzyl phthalate (MBzP) in the first trimester was associated with higher cortisol/cortisone ratio concentrations, and mono‑(2‑ethyl‑5‑carboxypentyl) phthalate (MECPP) and mono‑(2‑ethyl‑5‑oxohexyl) phthalate (MEOHP) measured in the third trimester were associated with decreased cortisone. Moreover, the associations between phthalates and glucocorticoids varied by sex. Among the female infants, each 10-fold increase in several maternal urinary phthalate metabolite concentrations in 1st and 3rd trimester was associated with the increased glucocorticoid levels with percent changes ranged from 16.2%–55.9%. However, among male infants, each 10-fold increase in maternal urinary MECPP, mono‑(2‑ethyl‑5‑hydroxyhexyl) phthalate (MEHHP) and MEOHP in 3rd trimester was associated with 20.8%–36.3% decreased cortisol and cortisone levels, respectively. Conclusion: We have shown that prenatal phthalate exposure during early and late trimester disrupted the infant steroidogenesis and these associations might be modified by infant sex. To the best of our knowledge, this is the first study to evaluate phthalate exposure at three trimesters during pregnancy in relation to infant glucocorticoids. Keywords: Phthalate, Glucocorticoid, Prenatal exposure, Trimester-specific

Background: Benzotriazoles (BTRs) and benzothiazoles (BTHs) are emerging contaminants with high production volume worldwide, which exhibit potential health risk to human. To date, little is known about the exposure of BTRs and BTHs (BTs) on human, especially in the context of pregnancy. Objectives: We aimed to characterize the exposure profiles, temporal variability, and potential predictors of urinary BTs during pregnancy. Methods: Between 2014 and 2015, we recruited 856 pregnant women in Wuhan who provided urine samples at three trimesters (13.1 ± 1.1, 23.7 ± 3.2, and 35.7 ± 3.4 gestational weeks). We measured the urinary concentrations of five BTRs (1‑H‑benzotriazole, 1‑hydroxy‑benzotriazole, xylyltriazole, tolyltriazole, 5‑chloro‑1‑H‑benzotriazole) and five BTHs (benzothiazole, 2‑hydroxy‑benzothiazole, 2‑methylthio‑benzothiazole, 2‑amino‑benzothiazole, 2‑thiocyanomethylthio‑benzothiazole) to characterize the exposure profiles of BTs. We calculated the intra-class correlation coefficients (ICCs) to assess the temporal variability and investigated potential predictors of urinary BTs by using the mixed models. Results: Most of the targeted BTs were detected in over 50% of urine samples, except for 5‑chloro‑1‑H‑benzotriazole (9.3%) and 2‑thiocyanomethylthio-benzothiazole (1.4%). The predominant BTRs in urine was 1‑hydroxy‑benzotriazole [Geometric Mean (GM): 0.77 ng/mL]. Benzothiazole was the major derivative in urine samples with a GM concentration of 1.6 ng/mL. Correlations among BTHs (r = 0.04–0.39) were higher than that among BTRs (r = 0.02–0.14). The exposure pattern was constant at low level and co-exposure to all the targeted compounds was infrequent during pregnancy. Urinary concentrations of BTRs exhibited considerable within-subject variation (ICCs: 0.12–0.56) during pregnancy. Relatively high temporal reliability was observed for urinary concentrations of BTHs with ICCs ranging from 0.42 to 0.85. It was found that parity, household income, pregnancy occupational status, sampling season and menstrual cycle were associated with urinary concentrations of BTs in pregnant women (P

Endocrine-disrupting chemicals (EDCs) are widespread environmental chemicals that are often considered as risk factors with weak activity on the hormone-dependent process of pregnancy. However, the adverse effects of EDCs in the body of pregnant women were underestimated. The interaction between dynamic concentration of EDCs and endogenous hormones (EHs) on gestational age and delivery time remains unclear. To define a temporal interaction between the EDCs and EHs during pregnancy, comprehensive, unbiased, and quantitative analyses of 33 EDCs and 14 EHs were performed for a longitudinal cohort with 2317 pregnant women. We developed a machine learning model with the dynamic concentration information of EDCs and EHs to predict gestational age with high accuracy in the longitudinal cohort of pregnant women. The optimal combination of EHs and EDCs can identify when labor occurs (time to delivery within two and four weeks, AUROC of 0.82). Our results revealed that the bisphenols and phthalates are more potent than partial EHs for gestational age or delivery time. This study represents the use of machine learning methods for quantitative analysis of pregnancy-related EDCs and EHs for understanding the EDCs’ mixture effect on pregnancy with potential clinical utilities.

Background: Mitochondria are sensitive to environmental toxicants due to the limited repair capacity. Exposure to benzotriazoles (BTRs) and benzothiazoles (BTHs) may contribute to adverse health outcomes through oxidative stress, which may interfere with mitochondrial function. However, the mitochondrial effects of exposure to BTs (BTRs and BTHs) have not yet been elucidated, particularly in human investigations. Objectives: We examined the associations between trimester-specific urinary BTRs and BTHs concentrations and cord blood mitochondrial DNA copy number (mtDNAcn) in a prospective birth cohort. Methods: The present study included 742 mother-infant pairs who participated in a birth cohort between 2014 and 2015 in Wuhan and had data on urinary concentrations of BTRs and BTHs and mtDNAcn in cord blood. Concentrations of BTs were repeatedly measured in maternal urine samples at different trimesters using high performance liquid chromatography-tandem mass spectrometry. Relative mtDNAcn in umbilical cord blood was analyzed by quantitative real-time polymerase chain reaction. Generalized estimating equations were used to evaluate the associations between BTs exposure across gestation and mtDNAcn in cord blood. Results: In the present study, we observed a positive association between urinary 2-methylthio-benzothiazole (2-MeS-BTH) concentrations in the first trimester and cord blood mtDNAcn, with marginal significance [percent changes (%Δ) = 3.97, 95% confidence interval (CI): −0.05, 8.16, p = 0.05], while urinary 2-amino-benzothiazole concentrations in the third trimester were significantly negatively associated with cord blood mtDNAcn (%Δ = −5.89, 95% CI: −10.32, −1.24). Similar patterns of associations were demonstrated between urinary 1-H-benzotriazole (1-H-BTR) and xylyltriazole concentrations in the third trimester and cord blood mtDNAcn (%Δ = −4.18 to −3.23). In sex-specific analysis, we identified that maternal urinary 1-H-BTR in the first trimester and 2-MeS-BTH in the third trimester were positively associated with cord blood mtDNAcn among male infants but not female (P for interaction = 0.05 for 1-H-BTR, P for interaction = 0.05 for 2-MeS-BTH, respectively). Conclusions: We found evidence that prenatal exposure to BTRs and BTHs were associated with cord blood mtDNAcn alternation, and these associations were modified by infant gender. Further investigations are needed to corroborate these findings.

Background: Benzotriazoles (BTRs) and benzothiazoles (BTHs) are emerging contaminants with potential insulin modulation activities. Pregnancy exposure to BTs (BTRs and BTHs) may be a risk factor for the development of gestational diabetes mellitus (GDM). However, epidemiological studies are limited. Objectives: We prospectively investigated the associations of exposure to BTs at early pregnancy with the blood glucose levels and the risks of GDM. Methods: A prospective cohort of 1770 pregnant women who were free of diabetes at baseline was established between 2013 and 2015 in Wuhan, China. Urine samples collected at 13.1 ± 1.1 weeks of gestation were analyzed to estimate the exposure level of BTs. The diagnosis of GDM was based on a 75 g oral glucose tolerance test (OGTT) conducted at 26.4 ± 2.4 weeks of gestation. We examined the associations between urinary concentration of BTs and blood glucose levels by linear regression models. The associations of urinary BTs concentrations with the relative risk (RR) of GDM were evaluated by generalized estimating equations with Poisson regression. Effect modifications by fetus sex and pre-pregnancy body mass index (BMI) were further evaluated in the sensitivity analysis. Results:A total of 147 (8.31%) pregnant women were diagnosed with GDM. Median concentrations of urinary BTs did not differ significantly between pregnant women with and without GDM. It was found that urinary levels of benzothiazole and 2-hydroxy-benzothiazole (2-OH-BTH) were positively associated with 2-hour blood glucose (p for trend

Background: Bisphenol A (BPA) may cause some adverse effects on human health by mimicking estrogen activities. In vitro and animal studies have observed the non-monotonic associations between BPA and natural estrogens, but the evidence in human study is lacking, particularly at multiple points in time during pregnancy. Objective: We aimed to examine the relationships between BPA and estrogens in the three trimesters among Chinese pregnant women and their gender variations. Methods: This study included 851 participants from a birth cohort conducted in Wuhan, China between 2014 and 2015. We measured concentrations of BPA and three estrogens (estrone (E1), 17β-estradiol (E2) and estriol (E3)) in urine samples collected in the three trimesters of pregnancy (mean for each visit: 13.0, 23.6, and 35.9 weeks’ gestation). We calculated the estimated daily intakes using urinary BPA concentrations and compared them with the tolerable intake value to assess potential health risks. We used multivariate linear regression models stratified by trimester and gender to explore trimester-specific and gender-specific associations of BPA with E1, E2, and E3. Results: We found the decreased levels of estrogens (β

Background: Phthalates are a family of endocrine disruptors with short elimination half-lives in the human body. To date, few epidemiological studies have examined repeated measures of maternal urinary phthalates and the combined effects of prenatal exposure to multiple phthalates on children's neurocognitive development. Objectives: We aimed to investigate the association between children's neurocognitive development at 2 years of age and prenatal phthalate exposure, as assessed by repeated measurements during pregnancy, and to further examine the effects of co-exposure to multiple phthalates using cumulative risk assessment. Method: Within a prenatal cohort in Wuhan, China, we measured five high-molecular-weight (HMW) phthalates and three low-molecular-weight (LMW) phthalate metabolites' concentrations in three urine samples collected in the 1st, 2nd, and 3rd trimester of pregnancy from each mother. We assessed neurocognitive development by Bayley Scales of Infant and Toddler Development (BSID) at 2 years of age (n = 476) to obtain the children's mental development index (MDI) and psychomotor development index (PDI). Results: Higher exposure levels to LMW phthalates compared to HMW phthalates were observed in our population. Ln-transformed averaged concentration of mono-n-butyl phthalate (MnBP), a metabolite of the LMW phthalate di-n-butyl phthalate (DnBP) during pregnancy, was associated with decreased PDI scores in all children (β = −1.90, 95% CI: −3.43, −0.37). Similarly, the averaged sum concentration of ∑dibutyl phthalate (∑DBP) was associated with decreased PDI scores in all children (β = −1.89, 95% CI: −3.63, −0.15). A negative trend of association between exposure to HMW phthalates and PDI scores was observed in girls, while a positive association was found in boys. In cumulative risk assessment analyses, we consistently observed that the hazard quotient of DnBP (the parent compound of MnBP) was inversely associated with PDI scores in all children, whereas the hazard quotient of di-2-ethylhexyl phthalate (DEHP), an HMW phthalate, was positively associated with PDI scores in boys only. Conclusions: This study is the first to use repeated measurement of maternal urinary phthalates in all three trimesters to assess prenatal exposure in relation to children's neurodevelopment. Our study suggested a negative association between prenatal exposure to MnBP and children's psychomotor development, and potentially sex-specific associations between HMW phthalates and neurocognitive development among boys and girls. These findings warrant further confirmation. Keywords: Phthalate metabolites, Child neurodevelopment, Prenatal exposure, Trimester-specific, Cumulative risk assessment

Background: The association of bisphenol A (BPA) and gestational diabetes mellitus (GDM) has been investigated in only a small number of studies, and research on the associations between BPA substitutes and GDM is scarce.Objective: We aimed to investigate the associations of four bisphenols [bisphenol A (BPA), bisphenol S (BPS), bisphenol F (BPF), and bisphenol AF (BPAF)] levels in urine sample with the risk of gestational diabetes mellitus (GDM) and plasma glucose levels.Methods: A total of 1,841 pregnant women from a cohort study were recruited at their first prenatal examination between 2013 and 2015 in Wuhan, China. Concentrations of four bisphenols (BPA, BPS, BPF, BPAF) were measured in first-trimester urine samples using Ultra-high performance liquid chromatography system coupled to a Triple Quadrupole mass spectrometer (UHPLC-TQMS). An oral glucose tolerance test (OGTT) was performed at 24–28 gestational weeks and GDM was diagnosed post hoc using International Association of Diabetes and Pregnancy Study Groups criteria. We used multivariable logistic regression models to examine the associations of urinary bisphenols with the risk of GDM, and multiple linear regression models to determine the associations between bisphenols exposure and plasma glucose levels.Results: Urinary BPAF was associated with increased odds of GDM among women with normal pre-pregnancy BMI [adjusted odds ratio (aOR) = 1.70 (95% CI: 1.08, 2.67) for the highest group compared to the lowest group], and the association remained significant after additional adjustment for other bisphenols [aOR = 1.68 (95% CI: 1.03, 2.72)]. No significant associations were observed for other bisphenols and GDM. Consistent with the result of GDM, women in the highest BPAF category had a mean of 0.05 mmol/L (95% CI: 0.01, 0.09) higher fasting plasma glucose (FPG) levels than women in the lowest category. For BPA and plasma glucose, non-linear associations were observed between urinary BPA and FPG and the sum of the PG z-score among women who were overweight (p for non-linear association < 0.05). We also found that the per-unit increase in natural log transformed specific gravity adjusted BPS [ln (SG-adj BPS)] was associated with a 0.03 mmol/L (95% CI: 0.01, 0.04) increase in FPG levels and the associations might be modified by fetal sex (p for interaction < 0.05). Among women with female fetus, a per-unit increase in ln (SG-adj BPS) was associated with a 0.04 mmol/L (95% CI: 0.02, 0.06) increase in FPG, a 0.11 mmol/L (95% CI: 0.04, 0.17) increase in 1 h-PG and a 0.19 mmol/L (95% CI: 0.08, 0.30) increase in the sum of PG z-score.Conclusions: Our results provide evidence that BPAF and BPS might be potential risk factors of GDM, which require to be studied further.

Abstract Background Manganese (Mn) is an essential element for humans, but exposure to high levels has been associated with adverse developmental outcomes. Early epidemiological studies evaluating the effect of Mn on fetal growth are inconsistent. Methods We investigated the association between maternal urinary Mn during pregnancy and the risk of low birth weight (LBW). Mn concentrations in maternal urine samples collected before delivery were measured in 816 subjects (204 LBW cases and 612 matched controls) recruited between 2012 and 2014 in Hubei Province, China. Results The median Mn concentration in maternal urine was 0.69 μg/g creatinine. Compared to the medium tertile of Mn levels, an increased risk of LBW was observed for the lowest tertile (≤0.30 μg/g creatinine) [adjusted odds ratio (OR) = 1.28; 95 % confidence interval (CI) = 0.67, 2.45], and a significantly increased risk of LBW was observed for the highest tertile (≥1.16 μg/g creatinine) [adjusted OR = 2.04; 95 % CI = 1.12, 3.72]. A curvilinear relationship between maternal urinary Mn and risk of LBW was observed, showing that the concentration at 0.43 μg/g creatinine was the point of inflection. Similar associations were observed among the mothers with female infants and among the younger mothers

A novel imidazoline derivative, 2-methyl-4-phenyl-1-tosyl-4, 5-dihydro-1H-imidazole (IMI), was prepared and investigated as corrosion inhibitor for P110 carbon steel in 1.0 M HCl solution by weight loss measurements, potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) tests. The inhibition efficiency increased with the rising concentration of IMI inhibitor. The test results and fitting data indicated that the IMI behaved as a mixed-type inhibitor and obeys the Langmuir adsorption isotherm. Scanning electron microscopy (SEM) was carried out to investigate the surface of carbon steel specimens, showing great protection from aggressive solution. Finally, inhibition mechanism of IMI on metal surface was further discussed.

OBJECTIVES:Determine the ability of the Cobas 4800 assay to detect high-risk human papillomavirus (HrHPV) and high-grade cervical lesions when using cervico-vaginal samples applied to liquid medium and solid media cards compared to a direct cervical sample. METHODS:Two cervico-vaginal specimens (pseudo self-collected) were obtained from 319 women. One was applied to an iFTA Card (FTA) then the brush placed in liquid-based medium (LSELF); the other was applied to a new solid media: POI card (POI). The clinical performance of Cobas4800 assay using the three aforementioned specimens was compared to direct collected endocervical specimens in liquid media (LDOC). RESULTS:The overall agreements of HrHPV detection were 84.2% (LSELF vs. LDOC), 81.0% (FTA vs. LDOC), and 82.3% (POI vs. LDOC). LSELF, FTA and POI identified 98.0%, 79.6%, and 97.5% positive cases of LDOC. Sensitivity to identify CIN2+ were 98.4% (LSELF), 73.8% (FTA), 95.1% (POI), and 93.4% (LDOC) respectively. FTA had 78.1% and 90.4% agreement with the LSELF samples for all HrHPV and HPV16/18 detection respectively, while POI had 91.6% for both. CONCLUSIONS:Cobas4800 HPV test combined with cervico-vaginal specimens applied to both liquid media and POI solid card are accurate to detect HrHPV infection and high-grade cervical lesions as compared with direct endocervical samples in liquid media.