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BackgroundPerfluorinated and polyfluoroalkyl substances (PFAS), a large group of emerging pollutants, are ubiquitous in the ecological environment. Their multiple organ toxic effects on human body are reported. Understanding the exposure level of PFAS in cord serum and associated influencing factors can provide scientific evidence for studying maternal and newborn health effects and risk regulation.ObjectiveTo explore the exposure levels of PFAS in cord serum and potential impact factors.MethodsThis study was based on the maternal and infant database and the cord serum sample bank of the Sheyang Mini Birth Cohort Study (SMBCS) established in 2009. A self-designed questionnaire was used to collect information on sociodemographic characteristics, living environment, and lifestyle of mothers during pregnancy. A total of 1097 cord serum samples were measured utilizing ultra-high performance liquid chromatography-Q-Exactive Orbitrap high-resolution mass spectrometry. Multiple linear regression models were used to identify influencing factors related to PFAS exposure level in cord serum.ResultsA total of 38 types of PFAS were detected in the cord serum samples, including 20 perfluorocarboxylic acids (PFCA), 14 perfluorosulfonic acids (PFSA), and 4 other types of PFAS. The detection rates of 14 PFAS compounds were above 50%. The detection rates of perfluoro-1-hexanesulfonic acid (PFHxS), perfluoro-1-octanesulfonic acid (PFOS), perfluorononanoic acid (PFNA), perfluorooctanoic acid (PFOA), perfluorodecanoic acid (PFDA), and perfluoroundecanoic acid (PFUdA) were in the range of 99.18%-100.00%. The median concentrations of PFOA and 6∶2 chlorinated polyfluorinated ether sulfonic acid (6∶2CI-PFESA) were higher than those of the other compounds, which were 3.76 µg·L−1 and 2.61 µg·L−1, respectively. The correlation coefficients among cord serum PFAS were in the wide range of 0.0911-0.8429 (P < 0.05). The associations between PFHxS and perfluoro-1-heptanesulfonic acid (PFHpS) (r=0.8429, P < 0.05), PFOS and PFHpS (r=0.7012, P < 0.05), and PFUdA and perfluorododecanoic acid (PFDoA) (r=0.7875, P < 0.05) were positive. The proportions of PFCA and PFSA in the cord serum samples were 60.1% and 38.4%, respectively. PFOA and 6∶2 Cl-PFESA were the predominant compounds in the cord serum samples, whose proportions were 37.8% and 19.3%, respectively. The concentrations of specific types of cord serum PFAS had varied associations with the following demographic variables of pregnant women: age, parity, education level, gestational age, and occupation. The multiple linear regression analysis found that the concentrations of 8 PFAS (PFHxS, PFHpS, PFNA, PFOS, PFDA, PFUdA, PFDoA, and 6∶2 CI-PFESA) in umbilical cord serum were lower in pregnant women aged 25 years and older than in those under the age of 25 years; compared to pregnant women with education levels at or below junior middle school, those with education levels at or above high school had lower concentrations of perfluoroheptanoic acid (PFHpA); the concentration of PFHpA in cord serum was negatively correlated with household annual income; multiparous women had higher concentrations of PFNA, PFUdA, and PFDoA than primiparous women; compared to mothers engaged in manual labor, the concentration of perfluoro-1-butanesulfonic acid (PFBS) in umbilical cord serum was lower in mothers engaged in mental labor, while the concentrations of PFBS and PFOA were lower and the concentrations of perfluorotridecanoic acid (PFTrDA) and 8∶2 chlorinated polyfluorinated ether sulfonic acid (8∶2CI-PFESA) were higher in mothers of other occupational types; the concentrations of umbilical cord serum PFOA, PFOS, PFUdA, and PFDoA were positively correlated with the gestational age of pregnant women, while N-methylperfluoro-1-octanesulfonamido acetic acid (N-MeFOSAA) was negatively correlated with the gestational age of pregnant women; PFTrDA was negatively correlated with the birth weight of newborns; compared with those with insufficient gestational weight gain, those with adequate gestational weight gain had lower PFDoA, while those with excess gestational weight gain had higher N-MeFOSAA.ConclusionPFAS compounds exposure is common in the mothers and infants in the study area. PFOA and 6∶2 CI-PFESA are the two main compounds in cord serum. Cord serum PFAS are associated with several demographic characteristics of the pregnant women. Future research needs to pay more attention to PFAS alternatives and other emerging contaminants.

To obtain a more comprehensive understanding of the hotspots and research progress of tea beverage at home and abroad, this research paper analyzed the annual publication volume, author co-occurrences, co-citations, research institutions, the number of country publications, journals, and research hotspots of 1247 English literature collected by WOS from 2002 to 2022 using the Web of Science core collection database as the data source and the visual data analysis software CiteSpace v 6.1.6R. The results of the analysis showed that the heat for research on tea beverage at home and abroad continued to rise, and the annual number of publications showed a rising trend year by year. The number of core authors with more than four articles was 584, accounting for 82.4% of the total number of authors. The majority of institutional publications came from Chinese universities, of which the first institution with the highest number of publications was Anhui Agricultural University. The People's Republic of China was the most actively published country, followed by USA and JAPAN. The journals with high publication volume were mainly concentrated in the field of agricultural and food chemistry, and Journal of Agricultural and Food Chemistry was the journal with the highest co-citation frequency, with a total of 988 citations. The "caffeine" "acid" and "catechin" were high-frequency keywords in tea beverage research, with research hotspots focusing on the detection and extraction of active substances in tea beverage, fermented teas, antioxidant and antibacterial activities. In summary, research on tea beverage was still on the rise, but existing studies suffered from a lack of cooperation among authors, limited research areas and convergent research methods, etc. Scholars should strengthen multifaceted cooperation and communication to broaden the breadth and depth of the research, and to jointly promote the development of research in this field. This study provided a reference for a more in-depth understanding of the current status of global tea beverage research in the future.

Background: Neonicotinoid insecticides (NNIs) were reported to be endocrine disruptors and cause adverse health effects in human. However, epidemiological evidence about the effect of prenatal NNIs exposure on birth outcome and hormones remains limited. Objectives: This study aimed to explore the effects of prenatal NNIs exposure on neonatal birth size and endocrine hormones, and assess the potential mediating role of hormones. Methods: The study included 860 mother–child pairs from the Sheyang Mini Birth Cohort Study. 12 parent NNIs (p-NNIs) and 6 metabolites of NNIs (m-NNIs) were measured in maternal urine samples collected on their delivery days, and 5 thyroid hormones and 2 sex hormones were analyzed in cord serum. The concentrations of p-NNIs and its specific metabolite(s) were summed to characterize the role of each class of NNIs. Generalized linear model and weighted quantile sum regression were used to examine the impact of prenatal NNIs exposure on birth size and endocrine hormones, and potential mediating roles of hormones were further explored using mediation analysis. Results: Higher detection frequencies of m-NNIs were observed than those in p-NNIs. A decrease in neonatal head circumference for gestation age z-score was associated with a 10-fold increase in 5-OH-IMI (β = -0.15, 95 %CI: −0.26, −0.03), ∑DIN (β = -0.22, 95 %CI: −0.40, −0.03), ∑IMI (β = -0.20, 95 %CI: −0.35, −0.06) and ∑NNIs (β = -0.23, 95 %CI: −0.42, −0.04). ∑IMI and ∑DIN were the major contributors to the significantly negative mixture effect and no sex-specific effect was observed. Negative associations were observed between ∑DIN and TT3 (β = -0.013, 95 %CI: −0.025, −0.002), ∑IMI and T (β = -0.035, 95 %CI: −0.065, −0.004), respectively. Furthermore, TT3 and T demonstrated 6.7 % and 6.1 % mediating effects on the negative association of prenatal ∑DIN and ∑IMI exposure with head circumference. Conclusions: Our findings suggested the potential endocrine disruptive properties of NNIs and their impacts on head circumference. Endocrine hormones may partly mediate these associations.

Background: Per- and polyfluoroalkyl substances (PFAS) have been suspected as potential environmental obesogens, with several mechanisms being proposed, including the role of metabolomics. However, current epidemiological studies have yielded inconclusive findings. Objectives: We aimed to estimate the associations of prenatal exposure to PFAS with offspring adiposity measures, and to explore the potential metabolic pathways underlying these associations. Methods: A total of 464 mother–child pairs from the Sheyang Mini Birth Cohort Study (SMBCS) were included in this study. Cord serum concentrations of 12 PFAS and urine metabolite profiles at age 10 were obtained from the SMBCS database. Adiposity-related anthropometric measurements and body composition estimates of children aged 10 were used to assess offspring obesity. Multiple linear regression models and quantile g-computation were conducted to estimate the associations of prenatal exposure to individual and multiple PFAS with obesity at 10 years old. Metabolomics analysis was performed to characterize the biological pathways associated with PFAS exposure or obesity, subsequently identifying the overlapping metabolic pathways underlying the PFAS-obesity relationship. Results: Prenatal exposure to several PFAS was significantly associated with elevated obesity-related markers in 10-year-old children. After stratification by sex, the effects were more pronounced in girls. Quantile g-computation results indicated that exposure to higher levels of PFAS mixtures during pregnancy was associated with increased odds of obesity in girls, with PFNA emerging as the predominant driving compound. Untargeted metabolomics results showed that several amino acid metabolic pathways were characterized as the overlapping pathways underlying the above associations. Conclusions: Taken together, our findings suggested the potential obesogenic effects of prenatal exposure to PFAS and offered insight into the possible metabolic mechanisms underlying PFAS-related offspring obesity.

BackgroundPer- and polyfluoroalkyl substances (PFAS) are a class of persistent organic pollutants that possess potential toxicity to the human body. The production and utilization of diverse emerging PFAS have resulted in widespread human exposure. Therefore, it is imperative to establish a quantitative methodology encompassing a wide range of PFAS for a comprehensive assessment of human exposure to these compounds. ObjectiveTo establish a high-throughput quantitative method for the simultaneous determination of 53 PFAS in human serum based on ultra-high-performance liquid chromatography-Q Exactive high resolution mass spectrometry (UPLC-Q Exactive HRMS). MethodsThe extraction recoveries of hydrophilic-lipophilic balance (HLB) column, weak anionexchange (WAX) column, and 96-well WAX μElution plate were compared to select the SPE column with the highest recovery. The retention time and peak shape of the target compounds were compared between ACQUITY UPLC BEH C18 column and Accucore aQ column, and the more cost-effective column was chosen. The effects of adding different levels of ammonium formate (0, 2, 5 and 10 mmol·L−1) in mobile phase on peak shape and target response were compared to determine the optimal buffer salt concentration. The optimal spray voltage was obtained by comparing −2 kV and −4 kV. The proposed method was validated from the aspects of selectivity, standard curve, limits of detection, precision, accuracy, and matrix effect. The method was applied to 142 umbilical serum samples. ResultsThe best recovery rate (64%-118%) was achieved by using 96-well WAX μElution plate. The optimal separation and peak shape were obtained by utilizing Accucore aQ column with H2O-methanol (containing 5 mmol·L−1 ammonium formate) as the mobile phase. Less in-source collision and better target response were observed when the spray voltage was set to −2 kV. All target analytes had a good linearity, with R2 > 0.99. The limits of detection ranged from 0.01 to 0.50 μg·L−1, and the recovery ranged from 69% to 127% with the precision less than 26%. A total of 31 PFAS were detected in the 142 actual samples, among which 14 PFAS had a detection frequency over 50%. Perfluorooctanoic acid showed the highest median concentration of 4.16 μg·L−1, followed by 6:2 chlorinated polyfluorinated ether sulfonate and perfluorooctane sulfonates (3.50 μg·L−1 and 1.59 μg·L−1, respectively). ConclusionIn this study, we establish a UPLC-Q Excative HRMS method for simutanious determination of 53 PFAS concentrations in serum. This method has the advantages of wide coverage of PFAS, good selectivity, and easy operation, and is suitable for biological detection with a large sample size.

Background: Prenatal exposure to per- and polyfluoroalkyl substances (PFASs) influences neurodevelopment. Thyroid homeostasis disruption is thought to be a possible underlying mechanism. However, current epidemiological evidence remains inconclusive. Objectives: This study aimed to explore the effects of prenatal PFAS exposure on the intelligence quotient (IQ) of school-aged children and assess the potential mediating role of fetal thyroid function. Methods: The study included 327 7-year-old children from the Sheyang Mini Birth Cohort Study (SMBCS). Cord serum samples were analyzed for 12 PFAS concentrations and 5 thyroid hormone (TH) levels. IQ was assessed using the Wechsler Intelligence Scale for Children-Chinese Revised (WISC-CR). Generalized linear models (GLM) and Bayesian Kernel Machine Regression (BKMR) were used to evaluate the individual and combined effects of prenatal PFAS exposure on IQ. Additionally, the impact on fetal thyroid function was examined using a GLM, and a mediation analysis was conducted to explore the potential mediating roles of this function. Results: The molar sum concentration of perfluorinated carboxylic acids (ΣPFCA) in cord serum was significantly negatively associated with the performance IQ (PIQ) of 7-year-old children (β = -6.21, 95 % confidence interval [CI]: −12.21, −0.21), with more pronounced associations observed among girls (β = -9.57, 95 % CI: −18.33, −0.81) than in boys. Negative, albeit non-significant, cumulative effects were noted when considering PFAS mixture exposure. Prenatal exposure to perfluorooctanoic acid, perfluorononanoic acid, and perfluorooctanesulfonic acid was positively associated with the total thyroxine/triiodothyronine ratio. However, no evidence supported the mediating role of thyroid function in the link between PFAS exposure and IQ. Conclusions: Increased prenatal exposure to PFASs negatively affected the IQ of school-aged children, whereas fetal thyroid function did not serve as a mediator in this relationship.

In this study, a series of novel nanofibers based on gelatin (GA) loading with purple potato anthocyanin (PPA) and syringic acid (SA) were obtained by electrospinning technology. The effects of SA on mechanical properties, thermal stability, antioxidant capacity, and antimicrobial activity of the GA/PPA nanofibers were systematically characterized. The scanning electron microscopy observation results revealed a smooth surface on the nanofibers. The incorporation of SA enhanced the viscosity of the electrospun solutions, and it increased the average diameter of nanofibers from 0.17 μm to 0.28 μm. The tensile strength and thermal stability of the obtained nanofibers were enhanced with the addition of a suitable level of SA (1.5%, w/v), which strengthened the intermolecular interaction. The GA/PPA/SA nanofibers presented over 80% antioxidant capacity and strong antibacterial activity against E. coli and S. aureus. Meanwhile, the sensitivity responses of nanofibers to NH3 revealed that GA/PPA/SA II nanofibers (1.5% w/v SA) presented good sensitivity of colorimetric behavior to ammonia. A pork spoilage test was performed to evaluate practical application of the nanofibers, and an obvious color change (dark purple to green) was observed. These results indicated GA/PPA/SA II nanofibers can be utilized as an active and intelligent multipurpose packaging material to preserve and track the freshness of pork.

BackgroundParabens, a widely used class of preservatives, are suspected to be potential obesogens as emerging endocrine disrupting chemicals with reproductive and developmental toxicity. ObjectiveTo analyze five urinary parabens (PBs) and estimate the associations of exposure to PBs with adiposity measures in 10-year-old school-age children. MethodsA total of 471 school-age children aged 10 years from the Sheyang Mini Birth Cohort were enrolled in this study. A questionnaire survey was conducted to collect socio-demographic information, physical activity, and dietary intake. Weight, height, and waist circumference of children were measured, and age- and sex-adjusted body mass index (BMI-Z score) was calculated. Spot urine samples were collected during the follow-up visits. Urinary concentrations of five PBs including methyl-paraben (MeP), ethyl-paraben (EtP), propyl-paraben (PrP), butyl-paraben (BuP), and benzyl-paraben (BzP) were detected by gas chromatography-tandem mass spectrometry (GC-MS/MS). Generalized linear models (GLMs) and Bayesian kernel machine regression (BKMR) models were applied to estimate associations of individual/overall urinary PBs concentrations with BMI Z-score and waist circumference. ResultsThe positive rates of selected five urinary PBs were in the range from 78.98% to 98.94%. The urinary PBs concentrations (geometric mean) were in the range of 0.31-5.43 μg·L−1. The children's BMI Z-score and waist circumference (mean ± standard deviation) were (0.56±1.40) and (67.62±10.07) cm respectively. The GLMs results showed that the urinary BzP concentration was negatively associated with waist circumference (b=−0.08, 95%CI: −0.14, −0.02; P=0.01). In sex-stratified analysis, the urinary concentration of BzP was negatively associated with BMI-Z score (b=−0.59, 95%CI: −0.88, −0.30; P

Recently, food grade nanofiber-based materials have received growing attentions in food packaging. In this work, novel active and intelligent packaging nanofibers based on gelatin/ chitosan with curcumin (GA/CS/CUR) were developed via electrospinning technique. Effects of the incorporation of CUR content (0.1 %－0.3 %, m/m) on the microstructure and functional properties of the electrospun nanofibers were investigated. Morphological studies using scanning electron microscopy indicated that loading CUR can affect the average diameter of nanofiber mats, which remained around 160180 nm. The addition of an appropriate level CUR (0.2 %, m/m) led to a stronger intermolecular interaction, and thus enhanced the thermal stability and tensile strength of the obtained nanofibers. Meanwhile, the incorporation of CUR significantly improved antioxidant activity and the antimicrobial activity of GA/CS/CUR nanofibers. Moreover, the sensitivity of nanofibers to ammonia results indicated that GA/CS nanofibers containing 0.2 % CUR (GA/CS/CUR II) presented high sensitivity of colorimetric behavior to ammonia (within 3 min). These results suggest GA/CS/CUR II nanofibers has great potential as a multifunctional packaging to protect and monitor the freshness of protein-rich animal foods, such as meat and seafood.

Background: Prenatal exposure to per- and polyfluoroalkyl substances (PFAS) has been linked to low birth weight but higher childhood weight and obesity. However, little is known regarding the associations between PFAS exposure and dynamic body mass index (BMI) trajectories, particularly from birth through preadolescence. Objective: To evaluate the associations of cord serum PFAS concentrations with BMI trajectories from birth to age 10 years and longitudinal BMI in different periods. Methods: Based on 887 mother–child pairs in the longitudinal prospective birth cohort, we measured 12 PFAS congeners in cord serum and calculated BMI with anthropometric indicators at 9 follow-up time points from birth to age 10 years. The BMI trajectories were identified using group-based trajectory model (GBTM). To estimate the associations of cord serum PFAS levels with BMI trajectories and longitudinal changes in BMI, logistic regression models, linear mixed models, Bayesian kernel machine regression, and quantile-based g-computation models (QGC) were used. Results: The median concentrations of 10 PFAS congeners included in statistical analysis ranged from 0.047 to 3.623 μg/L. Two BMI trajectory classes were identified by GBTM, characterized by high group and low group. In logistic regression models, five PFAS congeners (PFBA, PFHpA, PFHxS, PFHpS, and PFDoDA) were associated with the higher probability of being in high BMI trajectory group (odds ratio, OR: 1.21 to 1.74, p

Cadmium (Cd) is a ubiquitous heavy metal with neurotoxicity. Our previous study reported that Cd could inhibit the proliferation of mouse neural stem cells (mNSCs). However, the underlying mechanisms are obscure. In recent years, the rapid growth of multi-omics techniques enables us to explore the cellular responses that occurred after toxicant exposure at the molecular level. In this study, we used a combination of metabolomics and transcriptomics approaches to investigate the effects of exposure to Cd on mNSCs. After treatment with Cd, the metabolites and transcripts in mNSCs changed significantly with 110 differentially expressed metabolites and 2135 differentially expressed genes identified, respectively. The altered metabolites were mainly involved in glycerophospholipid metabolism, arginine and proline metabolism, arginine biosynthesis, glyoxylate and dicarboxylate metabolism. Meanwhile, the transcriptomic data demonstrated perturbed membrane function and signal transduction. Furthermore, integrated analysis of metabolomic and transcriptomic data suggested that glycerophospholipid metabolism might be the major metabolic pathway affected by Cd in mNSCs. More interestingly, the supplementation of lysophosphatidylethanolamine (LPE) attenuated Cd-induced mitochondrial impairment and the inhibition of cell proliferation and differentiation in mNSCs, further supporting our analysis. Overall, the study provides new insights into the mechanisms of Cd-induced neurotoxicity.

Purpose: To compare the safety, feasibility, and effectiveness of transvaginal natural orifice transluminal endoscopic sacrocolpopexy (vNOTES-SC) and laparoendoscopic single-site sacrocolpopexy (LESS-SC) for pelvic organ prolapse (POP). Method: Ninety-four patients with POP who underwent vNOTES-SC or LESS-SC from October 2016 to November 2018 were included. The propensity score matching method was used for 1:1 matching between the two surgery groups. After matching, the general perioperative indicators, surgical complications, and the subjective and objective therapeutic effects of the two groups 3 years post-surgery were analyzed. Results: After matching, 36 patients in each group were included, exhibiting balanced and comparable baseline data and an average follow-up of 48.6 ± 7.44 months. The operation time and postoperative hospitalization days were significantly reduced in the vNOTES-SC group (P 0.05). Additionally, no significant differences were detected in de novo stress urinary incontinence (16.7% vs. 13.9%), de novo overactive bladder (de novo OAB, 8.3% vs. 0.0%), urination disorder (2.8% vs. 0.0%), defecation disorder (0.0% vs. 2.8%), lumbosacral pain (0.0% vs. 2.8%), or mesh complication (2.8% vs. 5.6%) incidences between the vNOTES-SC and LESS-SC groups (P > 0.05). Prolapse recurrence was not reported in either group. The quantitative description of pelvic organ position (POP-Q), Pelvic Floor Impact Questionnaire-7 (PFIQ-7), and Patient Global Impression of Improvement scale (PGI-I) scores showed improvement after the operation, but no significant differences were observed between the two groups (P > 0.05). Conclusion: The 3-year follow-up revealed that vNOTES-SC and LESS-SC had similar complications and efficacy rates. Compared with LESS-SC, vNOTES-SC resulted in shorter operation time and fewer postoperative hospitalization days (corresponding to the enhanced recovery after surgery [ERAS] concept), along with better cosmetic results without a scar. Therefore, our study findings suggest that clinicians should choose the surgery method based on the specific situation, and we recommend choosing vNOTES-SC when both surgeries are suitable.

Abstract Introduction Despite its public health importance, the causes of small vessel disease (SVD) are not fully understood. The presence of SVD in monogenic twins indicates the involvement of genetic factors in the pathogenesis of this disease. The purpose of this study was to investigate the association of methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms with SVD risk. Methods Patients with SVD and matched controls were recruited from Tianjin Union Medical Center and Tianjin Huanhu Hospital. Clinical and laboratory data were collected. Plasma total homocysteine (tHcy) and folate levels were measured, and MTHFR rs1801133 (C677T) and rs1801131 (A1298C) single‐nucleotide polymorphisms were genotyped. We analyzed potential associations among SVD and MTHFR polymorphisms, tHcy, and folate levels. Results Patients with SVD displayed significantly decreased plasma folate levels (Z = –3.537, p

Cholesterol homeostasis disorder and hypertriglyceridemia, as common metabolic conditions, have rarely been reported to affect the immune responses to the hepatitis B vaccine. Our study found that higher high-density lipoprotein (HDL) level showed a significant relationship with positive anti-HBs results (cOR = 1.479, 95% CI: 1.150, 1.901, p = 0.002; aOR = 1.304, 95% CI: 1.006, 1.691, p = 0.045), especially in individuals aged 18- to 40-year-old, female, smoking more than 100 cigarettes in life, and drinking more than 12 times every year. Lower low-density lipoprotein (LDL) level was associated with a negative anti-HBs result among participants aged 18- to 40-year-old, and participants who were obese. Higher level of HDL and lower level of LDL may be protective factors of better immune effect of hepatitis B vaccine. More research should be conducted to investigate the influence of the cholesterol level on the immune responses to the hepatitis B vaccine, and more in-depth research should be performed to uncover the mechanism.

Background: Urinary para-nitrophenol (PNP), an exposure biomarker of ethyl parathion (EP) and methyl parathion (MP) pesticides, was still pervasively detected in the general population even after global restriction for years. And the concern whether there is an association of PNP level with child development of the nervous system is increasing. The current study aimed to evaluate the maternal urinary PNP concentrations during late pregnancy and the associations of PNP levels with cognitive and motor function of their children at the age of 2 years. Methods: 323 mother-child pairs from the Sheyang Mini Birth Cohort Study were included in the current study. Gas chromatography-tandem mass spectrometry was used to measure concentrations of PNP, the specific metabolite of EP and MP, in maternal urine samples during pregnancy. Developmental quotients (DQs) scores measured with Gesell Developmental Scales were employed to evaluate cognitive and motor function of children aged 2 years. Generalized linear models were performed to analyze the associations of PNP concentrations in pregnant women’s urine samples with cognitive and motor function of their children. Results: Maternal PNP was detected in all urine samples with a median of 4.11 μg/L and a range from 0.57 μg/L to 109.13 μg/L, respectively. Maternal urinary PNP concentrations showed a negative trend with DQ of motor area [regression coefficient (β) = − 1.35; 95 % confidence interval (95 %CI): − 2.37, − 0.33; P

In the Dempster-Shafer theory, how to quantitatively evaluate the quality of information is an essential issue and also an open issue. Many of measures of uncertainty have been proposed in previous work, whereas some measures among them had been proved to have a few shortcomings. The validity and rationality of the measures proposed in recent years have been explored and analyzed preliminarily, and then an empirical measure of uncertainty with exponential function form which is directly based on the framework of the evidence theory is proposed to overcome the shortcomings. Several numerical examples have been presented to illustrate the validity and rationality of the empirical measure.

Background: Carbamate pesticides are widely used in agriculture and cause widespread human exposure. The health effect of carbamates on physical development remains unclear. The current study aimed to explore the carbamate’s health effect on physical development. Methods: Prenatal, 3-year-old, 7-year-old urinary carbofuranphenol concentration was measured by gas chromatography tandem mass spectrometry and adjusted by creatinine. Anthropometric indices were measured by standard method and z-score standardized. Generalized linear models (GLM) were using to assess associations between exposure measurements and anthropometric indices. The generalized estimate equation (GEE) was applied to analyze the association between multiperiod exposure and anthropometric indices, and time-interaction terms were used to exam health effect consistency of exposure in each period. Gender-stratified analysis were conducted according to results of gender-interaction terms to identify gender-specific effects. Results: The gender-interaction term of prenatal exposure with height z-score was significant (β = -0.057; 95% CI: −0.113, −0.001; p = 0.045). The 3-year-old carbofuranphenol level showed negative associations with weight z-score (β = -0.019; 95% CI: −0.038, −0.000; p = 0.040), height z-score (β = -0.015; 95% CI: −0.028, −0.001; p = 0.026), chest circumference (β = -0.086; 95% CI: −0.171, −0.001; p = 0.046), and waist circumference (β = -0.128; 95% CI: −0.230, −0.026; p = 0.014). No statistically significant trend was found for prenatal and 7-year-old carbofuranphenol levels. In GEEs, carbofuranphenol level was negatively associated with weight z-score (β = -0.103; 95% CI: −0.195, −0.011; p = 0.027), height z-score (β = -0.087; 95% CI: −0.152, −0.022; p = 0.008), and chest circumference (β = -0.472; 95% CI: −0.918, −0.026; p = 0.037). Boy’s height z-score was inversely associated with carbamate exposure (β = -0.140; 95% CI: −0.227, −0.053; p = 0.001). Conclusions: Prenatal and postnatal carbamate exposure may affect physical developmental process.

Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.Then,the advantages of the heuristic algorithm were illustrated from its applications in machine learning,including the parameter and structure optimization of neural network and other machine learning algorithms,feature optimization,ensemble pruning,prototype optimization,weighted voting ensemble and kernel function learning.Finally,the heuristic algorithms and their development directions in the field of machine learning were given according to the actual needs.

Keystroke biometrics is a well-investigated dynamic behavioral methodology that utilizes the unique behavioral patterns of users to verify their identity when tapping keys. However, the performance of keystroke biometrics is unreliable due to its high error rate and low robustness. In this paper, we propose differential evolution and adversarial noise-based user authentication (DEANUA), which is a verification scheme for enhancing reliability by reducing the error rate and improving robustness. We investigate the current mainstream features and build a more comprehensive feature set that composed of 146 features. Then, we use a differential evolution method to select an optimized feature set. With the support vector regression method on this feature set, we achieve an equal error rate (EER) of 0.12660% and also a 31.25% energy consumption reduction rate. In this paper, the model is trained with the training samples collected from one situation, but the model is used in various situations. Thus, the robustness of the model is inadequate. We constructed the adversarial noise samples to simulate users' behavioral characteristics in different situational contexts. We use the adversarial noise samples to test the models in a strict experimental environment, which raises the EER by 83.59%, to 10.9299%. Then, we enhance the model with adversarial noise samples to obtain an EER of 8.70932%, which is a reduction of 20.32%.

Social engineering has been increasingly used during the past few years. Social engineering attacks have resulted in great financial losses. Research on social engineering models and frameworks is still in its elementary stage. An appropriate social engineering framework can interpret all the attack components and their relationships clearly, which will contribute to the defense of social engineering attacks. In this tutorial paper, existing social engineering models and frameworks are summarized and a new social engineering framework is proposed involving the concept of the session and dialogue. An entire social engineering attack is defined as a social engineering session (SES). A social engineering dialogue (SED) refers to a specific attack phase, which is included in a SES. A SES contains several well-organized SEDs. Then, the attack graph is used to formalize the proposed social engineering framework. The SED is treated as an atomic attack during the whole SES. The human weaknesses that an attacker can exploit are described as vulnerabilities, the information, and trust that an attacker owns as permissions. Finally, three real-world social engineering cases are analyzed using the proposed framework and attack graph. The analyses illustrate the usability of the proposed framework and provide a better understanding of various social engineering attacks.

The main challenge of user personality recognition is low accuracy resulting from small sample size and severe sample distribution imbalance. This paper analyzes the impact of imbalanced data distribution and positive and negative sample overlap on the machine learning classification model. The classification model is based on the data resampling technique, which can improve the classification accuracy. These problems can be solved once the data are effectively resampled. We present a personality prediction method based on particle swarm optimization (PSO) and synthetic minority oversampling technique+Tomek Link (SMOTETomek)resampling (PSO-SMOTETomek), which, apart from effective SMOTETomek resampling of data samples, is able to execute PSO feature optimization for each set of feature combinations. Validated by simulation, our analysis reveals that the PSO-SMOTETomek method is efficient under a small dataset, and the accuracy of personality recognition is improved by up to around 10%. The results are better than those of previous similar studies. The average accuracies of the plain text dataset and the non-plain text dataset are 75.34% and 78.78%, respectively. The average accuracies of the short text dataset and the long text dataset are 75.34% and 64.25%, respectively. From the experimental results, we found that short text has a better classification effect than long text. Plain text data can still have high personality discrimination accuracy, but there is no relevant external information. The proposed model is able to facilitate the design and implementation of a personality recognition system, and the model significantly outperforms existing state-of-the-art models.

Trimethylamine-N-oxide (TMAO), a diet-derived cometabolite linked to cardiometabolic disease, has been associated with elevated dietary status, particularly in people with kidney failure and adults with dietary modulations. However, the influence of the current diet on TMAO levels in free-living children has not been adequately described. This study was to explore associations of food compositions and dietary diversity with urinary TMAO and its precursor concentrations. Urinary TMAO and its precursor concentrations of 474 healthy children from the Sheyang Mini Birth Cohort were quantified by ultra-performance liquid chromatography–Q Exactive high-resolution mass spectrometer (UPLC-Q Exactive HRMS). Individual food compositions from 24 h dietary recall data were classified into 20 groups and diversity scores were calculated according to the guidelines of the Food and Agriculture Organization of the United Nations (FAO). Associations of urinary TMAO and its precursors with food compositions and dietary diversity scores were assessed by generalized linear regression models. In models adjusted for potential confounders, urinary TMAO was significantly associated with intakes of fish (β, regression coefficient = 0.155, p < 0.05) and vegetables (β = 0.120, p < 0.05). Eggs intake showed positive associations with TMAO’s precursors (trimethylamine: β = 0.179, p < 0.05; choline: β = 0.181, p < 0.05). No association between meat intake and TMAO was observed, whereas meat and poultry intakes were related to the levels of acetyl-L-carnitine and L-carnitine (β: 0.134 to 0.293, p < 0.05). The indicators of dietary diversity were positively correlated to TMAO concentration (β: 0.027 to 0.091, p < 0.05). In this free-living children-based study, dietary factors were related to urinary TMAO and its precursors, especially fish, meat, and eggs. As such, dietary diversity was positively related to the level of TMAO.

Background: Early-life carbamate exposure during developmental period has been linked with adverse health effects and attracted attention. Methods: Three hundred and three children at age of seven were included in the current study. Urinary carbofuranphenol concentrations were measured using gas chromatography-tandem mass spectrometry. Verbal, performance and full-scale intelligence quotients (IQV, IQP, and IQFS) were assessed using Wechsler Intelligence Scale for Children-Chinese Revised. Generalized linear models were used to explore the associations between carbofuranphenol levels and IQs. Generalized estimating equations were used to explore long-term health effect and sensitive time window. Results: Carbofuranphenol was detected in 96.6% of the seven-year-old urinary samples, the geometric mean, median, and inter quartile range of the carbofuranphenol concentrations were 0.67 μg/L, 0.30 μg/L, and 0.09–3.72 μg/L, respectively, which were similar with the level of three-year-old children from the SMBCS cohort. Seven-year-old carbofuranphenol level was negatively associated with IQP [β = −0.044; 95% confidence interval (CI): −0.087, −0.001; p = 0.045]. Three-year-old carbofuranphenol level was negatively associated with IQP (β = −0.100; 95% CI: −0.186, −0.014; p = 0.022) and IQFS (β = −0.087; 95% CI: −0.173, −0.001; p = 0.047). Carbamate exposure of maternal and children at both three and seven years old had negative associations with IQP (β = −0.089; 95% CI: −0.171, −0.007; p = 0.034), and IQFS (β = −0.064; 95% CI: −0.127, −0.000; p = 0.049) of children at age of seven. Conclusion: Results of the present study verify that children in an agricultural region of China were widely exposed to carbamate pesticides. Carbamate exposure in utero and at three and seven years may adversely impact children’s neurodevelopment.

Background: Diabetes mellitus is considered a common comorbidity of COVID-19, which has a wide spectrum of clinical manifestations ranging from asymptomatic infection to severe respiratory symptoms and even death. However, the impact of COVID-19 on blood glucose has not been fully understood. This meta-analysis aimed to summarize available data on the association between glycemic parameters and severity of COVID-19.Methods: PubMed, EMBASE, and Cochrane Library were searched from December 1, 2019 to May 15, 2020. Observational studies investigating blood glucose or glycated hemoglobin A1c (HbA1c) according to the severity of COVID-19 were considered for inclusion. Two independent researchers extracted data from eligible studies using a standardized data extraction sheet and then proceeded to cross check the results. Data were pooled using a fixed- or random-effects model to calculate the weighted mean differences (WMDs) and 95% confidence intervals (CIs).Results: Three studies reported blood glucose and HbA1c according to the severity of COVID-19 and were included in this meta-analysis. The combined results showed that severe COVID-19 was associated with higher blood glucose (WMD 2.21, 95% CI: 1.30–3.13, P < 0.001). In addition, HbA1c was slightly higher in patients with severe COVID-19 than those with mild COVID-19, yet this difference did not reach significance (WMD 0.29, 95% CI: −0.59 to 1.16, P = 0.52).Conclusions: This meta-analysis provides evidence that severe COVID-19 is associated with increased blood glucose. This highlights the need to effectively monitor blood glucose to improve prognosis in patients infected with COVID-19.

Background: Long-chain per- and polyfluoroalkyl substances (PFASs) and their short-chain alternatives have been produced and used extensively in China. However, it is unclear whether these compounds contribute to the risk of gestational diabetes mellitus (GDM) in women residing in contaminated areas. Objective: The study was performed to explore the association between PFASs varying in chain length and the risk of developing GDM. Method: A nested case-control study was conducted in a prospective cohort of 2,460 pregnant women between July 1, 2017, and January 31, 2019 in Shanghai, China. Twelve PFASs of interest were measured using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF MS) in the sera of pregnant women at 16–20 weeks. GDM was diagnosed by an oral glucose tolerance test administered over 24–28 gestational weeks. The cases and controls were matched by maternal age. The relationship between maternal serum PFAS level and GDM risk was determined by conditional logistic and linear regression analyses. Results: A total of 165 GDM cases and 330 controls were enrolled in the study cohort. The frequencies of detection of PFHpA, PFDS, and PFOSA were all ≤80%. Hence, they were excluded from any further risk analysis. Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) were detected at relatively high serum levels (medians 6.57 ng/mL and 8.07 ng/mL, respectively). The serum levels of perfluorobutanesulfonic acid (PFBS) and perfluorododecanoic acid (PFDoA) were significantly higher in the GDM group than they were in the control group (P = 0.02 and P

Higher melamine exposure may increase the risk of kidney stone formation and kidney injury in infants, but little is known about the potential nephrotoxic effects of environmental low-dose melamine and its derivative exposure on kidney function of adults in the general population. Our objective was to assess associations between urinary concentrations of melamine and its derivative, cyanuric acid, and kidney function through analyzing the data from the National Health and Nutrition Examination Survey (NHANES) 2003–2004. Information on 298 participants aged ≥20 years was utilized. Urinary melamine and cyanuric acid levels were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) were calculated to reflect kidney function. Covariate-adjusted creatinine standardization concentrations accounting for sex, race, age, race/ethically, and body mass index, was employed to control potential confounding of kidney function. Multivariable linear regression models were conducted to estimate associations of covariate-adjusted creatinine standardization urinary melamine and cyanuric acid concentrations with eGFR and UACR. Log-binomial regression models were performed to estimate risks of impaired kidney function and hypertension associated with urinary melamine and cyanuric acid levels. The geometric mean values of urinary melamine and cyanuric acid concentrations were 1.51 μg/L [95% confidence interval (CI): 1.21 μg/L, 1.89 μg/L] and 5.86 μg/L (95% CI: 5.34 μg/L, 6.44 μg/L), respectively. The median value of estimated daily intake (EDI) for melamine was 0.06 (ranging from undetectable to 1.11) μg/kg body weight/day calculated by urinary concentration and creatinine excretion accounting for sex and body weight. Adults in the fourth quartile of melamine and cyanuric acid exposure had 0.142 mL/min/1.73 m2 (95% CI: −0.271, −0.014) and 0.106 mL/min/1.73 m2 (95% CI: −0.020, 0.006) lower eGFR for melamine and cyanuric acid, respectively, compared to participants in the first quartile of exposure with adjustment for potential confounders. To our best knowledge, this is the first study to report associations between melamine and its derivative and kidney function of the U.S. adults from NHANES 2003–2004. The suggestive evidence revealed that individuals with high melamine exposure had lower eGFR than those with low melamine exposure, although no significant association between melamine and cyanuric acid exposure and markers of kidney function was observed. These findings should be interpreted with caution regarding the possible reverse causality.

Objective: Prenatal exposure to heavy metals, pesticides and phenols has been suggested to interfere with neurodevelopment, but the neurotoxicity of their mixtures is still unclear. We aimed to elucidate the associations of maternal urinary concentrations of selected chemical mixtures with intelligence quotient (IQ) in children. Methods: Maternal urinary concentrations of selected heavy metals, pesticide metabolites, and phenols were quantified in pregnant women who participated in the Sheyang Mini Birth Cohort Study (SMBCS) from June 2009 to January 2010. At age 7 years, child’s IQ score was assessed using the Chinese version of Wechsler Intelligence Scale for Children (C-WISC) by trained pediatricians. Generalized linear regression models (GLM), Bayesian kernel machine regression (BKMR) models and elastic net regression (ENR) models were used to assess the associations of urinary concentrations individual chemicals and their mixtures with IQ scores of the 7-year-old children. Results: Of 326 mother-child pairs, single-chemical models indicated that prenatal urinary concentrations of lead (Pb) and bisphenol A (BPA) were significantly negatively associated with full intelligence quotient (FIQ) among children aged 7 years [β = −2.31, 95% confidence interval (CI): −4.13, −0.48; p = 0.013, sex interaction p-value = 0.076; β = −1.18, 95% CI: −2.21, −0.15; p = 0.025; sex interaction p-value = 0.296, for Pb and BPA, respectively]. Stratified analysis by sex indicated that the associations were only statistically significant in boys. In multi-chemical BKMR and ENR models, statistically significant inverse association was found between prenatal urinary Pb level and boy’s FIQ scores at 7 years. Furthermore, BKMR analysis indicated that the overall mixture was associated with decreases in boy’s IQ when all the chemicals’ concentrations were at their 75th percentiles or higher, compared to at their 50th percentiles. ENR models revealed that maternal urinary Pb levels were statistically significantly associated with lower FIQ scores (β = −2.20, 95% CI: −4.20, −0.20; p = 0.031). Conclusions: Prenatal exposure to selected chemical mixtures may affect intellectual performance at 7 years of age, particularly in boys. Pb and BPA were suspected as primary chemicals associated with child neurodevelopment.

Konjac glucomannan (KGM) hydrogel has favorable gel-forming abilities, but its insufficient swelling capacity and poor control release characteristics limit its application. Therefore, in this study, oxidized hyaluronic acid (OHA) was used to improve the properties of KGM hydrogel. The influence of OHA on the structure and properties of KGM hydrogels was evaluated. The results show that the swelling capacity and rheological properties of the composite hydrogels increased with OHA concentration, which might be attributed to the hydrogen bond between the KGM and OHA, resulting in a compact three-dimensional gel network structure. Furthermore, epigallocatechin gallate (EGCG) was efficiently loaded into the KGM/OHA composite hydrogels and liberated in a sustained pattern. The cumulative EGCG release rate of the KGM/OHA hydrogels was enhanced by the increasing addition of OHA. The results show that the release rate of composite hydrogel can be controlled by the content of OHA. These results suggest that OHA has the potential to improve the properties and control release characteristics of KGM hydrogels.

Background/Aims: Metformin treatment is reported to be associated with a lower incidence of and mortality from pancreatic cancer (PC) in type 2 diabetes patients. Activated pancreatic stellate cells (PSCs) are key stroma cells responsible for pancreatic fibrogenesis and PC progression. However, little research is about the influence of metformin on PSCs. Given the potential beneficial effects of metformin on PC, pancreatic tumour stroma is an important target for new therapeutics. We observed the effects of metformin on PSCs. We investigated the effects of metformin on human PSCs proliferation and the production of extracellular matrix (ECM) proteins. Methods: Cells were cultured with different concentrations of metformin (0-10 mmol/L). Cell proliferation was determined by immunofluorescence staining for nuclear Ki67 labelling. ECM production was studied by quantitative real-time polymerase chain reaction, immunoblotting and immunofluorescence microscopy. Adenosine monophosphate–activated protein kinase (AMPK), an important regulatory molecule responsible for metformin action, and the organic cation transporter member 1 (OCT1), which is believed to be the most important transporter for the pharmacological action of metformin, were investigated for their possible involvements in metformin-induced proliferation and ECM production. Results: Our results showed that metformin inhibited PSCs proliferation and decreased the production of ECM proteins by activation of AMPK phosphorylation. Silencing of OCT1 expression resulted in a reduction in the effects of metformin on PSCs activity. Conclusions: Collectively, the data indicate that OCT1 may contribute to uptake metformin and regulate PSCs activity. OCT1 is a target of metformin in regulating PSCs activity.

Abstract Background Osteopontin (OPN) plays an important role in inflammatory processes and insulin resistance. Polycystic ovary syndrome (PCOS) is a reproductive metabolic disease associated with insulin resistance and metabolic abnormalities, including high levels of liver fat content (LFC). The objective of this study was to explore whether circulating OPN independently contributes to elevated LFC in non-obese PCOS patients. Methods This study included 61 non-obese PCOS patients and 56 age-matched healthy women from Shanghai, China. After an overnight fast, all participants underwent anthropometric measurements, oral glucose tolerance tests, lipid profile and sex hormone measurements. Quantitative measurement of LFC by ultrasonography was performed. OPN concentrations were measured using ELISA. An independent samples t-test and the Mann-Whitney U test were performed to compare variables between the two groups; one-way ANOVA and Kruskal-Wallis test were performed to compare four subgroups of patients. Correlations were determined by Spearman’s correlation tests. Stepwise multiple linear regression analyses were performed to assess for independent contributors. A receiver operating characteristic curve with the maximum Youden index was calculated for the optimal cut-off value. Results In non-obese PCOS women, circulating OPN levels were increased in the subgroups with a higher body mass index (BMI) and free androgen index (FAI), and the LFC levels were increased in the elevated OPN subgroups. Moreover, increased OPN was associated with increased FAI and LFC in PCOS women, and the association between OPN and LFC was independent of triglyceride, HOMA-IR and FAI after adjusting for PCOS status in all participants. OPN combined with FAI and hsCRP may better predict NAFLD than WHR in this study cohort. However, there was no significant difference in circulating OPN levels between non-obese PCOS and normal control women. Conclusions Increased OPN levels may be related to FAI and elevated LFC in non-obese women with PCOS.

Phishing has become one of the biggest and most effective cyber threats, causing hundreds of millions of dollars in losses and millions of data breaches every year. Currently, anti-phishing techniques require experts to extract phishing sites features and use third-party services to detect phishing sites. These techniques have some limitations, one of which is that extracting phishing features requires expertise and is time-consuming. Second, the use of third-party services delays the detection of phishing sites. Hence, this paper proposes an integrated phishing website detection method based on convolutional neural networks (CNN) and random forest (RF). The method can predict the legitimacy of URLs without accessing the web content or using third-party services. The proposed technique uses character embedding techniques to convert URLs into fixed-size matrices, extract features at different levels using CNN models, classify multi-level features using multiple RF classifiers, and, finally, output prediction results using a winner-take-all approach. On our dataset, a 99.35% accuracy rate was achieved using the proposed model. An accuracy rate of 99.26% was achieved on the benchmark data, much higher than that of the existing extreme model.

Gestational exposure to manganese (Mn), an essential trace element, is associated with fetal and childhood physical growth. However, it is unclear which period of growth is more significantly affected by prenatal Mn exposure. The current study was conducted to assess the associations of umbilical cord-blood Mn levels with birth outcomes and childhood continuous physical development. The umbilical cord-blood Mn concentrations of 1179 mother–infant pairs in the Sheyang mini birth cohort were measured by graphite furnace atomic absorption spectrometry (GFAAS). The association of cord-blood Mn concentrations with birth outcomes, and the BMI z-score at 1, 2, 3, 6, 7 and 8 years old, were estimated separately using generalized linear models. The relationship between prenatal Mn exposure and BMI z-score trajectory was assessed with generalized estimating equation models. The median of cord-blood Mn concentration was 29.25 μg/L. Significantly positive associations were observed between Mn exposure and ponderal index (β, regression coefficient = 0.065, 95% CI, confidence interval: 0.021, 0.109; p = 0.004). Mn exposure was negatively associated with the BMI z-score of children aged 1, 2, and 3 years (β = −0.383 to −0.249, p < 0.05), while no significant relationships were found between Mn exposure and the BMI z-score of children at the age of 6, 7, and 8 years. Prenatal Mn exposure was related to the childhood BMI z-score trajectory (β = −0.218, 95% CI: −0.416, −0.021; p = 0.030). These results indicated that prenatal Mn exposure was positively related to the ponderal index (PI), and negatively related to physical growth in childhood, which seemed most significant at an early stage.

Abstract Although the regular consumption of resveratrol has been known to improve glucose homeostasis and reverse insulin resistance in type 2 diabetes mellitus (T2DM), the reported results are inconsistent. Thus, we aimed to assess the effects of resveratrol on glycemic control and insulin sensitivity among patients with T2DM. We searched for relevant articles published until June 2017 on PubMed-Medline, Embase, Cochrane Library, and Web of Science. Randomized controlled trials in T2DM patients administered with resveratrol as intervention were included. After study selection, quality assessment and data extraction were performed independently by two authors, and STATA and RevMan software were used for statistical analysis. Nine randomized controlled trials involving 283 participants were included. Meta-analysis showed that resveratrol significantly improved the fasting plasma glucose ( −0.29 mmol/l, 95% CI: −0.51, −0.06, p < 0.01) and insulin levels (−0.64 U/mL, 95% CI: −0.95, −0.32, p < 0.0001). The drug also reduced homeostasis model assessment of insulin resistance (HOMA-IR) index, systolic blood pressure, and diastolic blood pressure among participants with T2DM. The changes in hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol were negligible. Subgroup analysis comparing the resveratrol supplementation doses of < 100 mg/d versus ≥ 100 mg/d revealed a significant difference in fasting plasma glucose. In particular, the latter dose presented more favorable results. This meta-analysis provides evidence that supplementation of resveratrol may benefit management of T2DM.

Abstract Measurement of endogenous hormones in early life is important to investigate the effects of hormonally active environmental compounds. To assess the possible hormonal effects of different feeding regimens in different sample matrices of infants, 166 infants were enrolled from two U.S hospitals between 2006 and 2009. The children were classified into exclusive soy formula, cow milk formula or breast milk regimens. Urine, saliva and blood samples were collected over the first 12 months of life. Estradiol, estrone, testosterone, luteinizing hormone (LH), follicle-stimulating hormone (FSH) and sex hormone-binding globulin (SHBG) levels were measured in the three matrices. Lower estradiol and LH levels were found in urine and saliva samples of soy formula-fed boys compared to cow formula-fed boys. Higher LH level was found in urine samples of soy formula-fed girls compared to cow formula-fed girls. However, we found neither a neonatal testosterone rise in the boys nor a gender-specific difference in testosterone levels, which suggests that urinary testosterone levels may not accurately reflect blood levels during mini-puberty. Nevertheless, our study shows that blood, urine and saliva samples are readily collectible and suitable for multi-hormone analyses in children and allow examination of hypotheses concerning endocrine effects from dietary compounds.

Cross-domain relation extraction has become an essential approach when target domain lacking labeled data. Most existing works adapted relation extraction models from the source domain to target domain through aligning sequential features, but failed to transfer non-local and non-sequential features such as word co-occurrence which are also critical for cross-domain relation extraction. To address this issue, in this paper, we propose a novel tripartite graph architecture to adapt non-local features when there is no labeled data in the target domain. The graph uses domain words as nodes to model the co-occurrence relation between domain-specific words and domain-independent words. Through graph convolutions on the tripartite graph, the information of domain-specific words is propagated so that the word representation can be fine-tuned to align domain-specific features. In addition, unlike the traditional graph structure, the weights of edges innovatively combine fixed weight and dynamic weight, to capture the global non-local features and avoid introducing noise to word representation. Experiments on three domains of ACE2005 datasets show that our method outperforms the state-of-the-art models by a big margin.

Currently, most text style transfer methods encode the text into a style-independent latent representation and decode it into new sentences with the target style. Due to the limitation of the latent representation, previous works can hardly get satisfactory target style sentence especially in terms of semantic remaining of the original sentence. We propose a “Mask and Generation” structure, which can obtain an explicit representation of the content of original sentence and generate the target sentence with a transformer. This explicit representation is a masked text that masks the words with the strong style attribute in the sentence. Therefore, it can preserve most of the semantic meaning of the original sentence. In addition, as it is the input of the generator, it also simplified this process compared to the current work who generate the target sentence from scratch. As the explicit representation is readable and the model has better interpretability, we can clearly know which words changed and why the words changed. We evaluate our model on two review datasets with quantitative, qualitative, and human evaluations. The experimental results show that our model generally outperform other methods in terms of transfer accuracy and content preservation.

While there have been significant advances in detecting emotions in text, in the field of utterance-level emotion recognition (ULER), there are still many problems to be solved. In this paper, we address some challenges in ULER in dialog systems. (1) The same utterance can deliver different emotions when it is in different contexts. (2) Long-range contextual information is hard to effectively capture. (3) Unlike the traditional text classification problem, for most datasets of this task, they contain inadequate conversations or speech. (4) To better model the emotional interaction between speakers, speaker information is necessary. To address the problems of (1) and (2), we propose a hierarchical transformer framework (apart from the description of other studies, the “transformer” in this paper usually refers to the encoder part of the transformer) with a lower-level transformer to model the word-level input and an upper-level transformer to capture the context of utterance-level embeddings. For problem (3), we use bidirectional encoder representations from transformers (BERT), a pretrained language model, as the lower-level transformer, which is equivalent to introducing external data into the model and solves the problem of data shortage to some extent. For problem (4), we add speaker embeddings to the model for the first time, which enables our model to capture the interaction between speakers. Experiments on three dialog emotion datasets, Friends, EmotionPush, and EmoryNLP, demonstrate that our proposed hierarchical transformer network models obtain competitive results compared with the state-of-the-art methods in terms of the macro-averaged F1-score (macro-F1).

Uterine prolapse complicating pregnancy is rare. Two cases are presented here: one patient had uterine prolapse at both her second and third pregnancy, and the other developed only once prolapse during pregnancy. This report will analyze etiology, clinical characteristics, complication, and treatment of uterine prolapse in pregnancy. Routine gynecologic examination should be carried out during pregnancy. If uterine prolapse occurred, conservative treatment could be used to prolong the gestational period as far as possible. Vaginal delivery is possible, but caesarean section seems a better alternative when prolapsed uterus cannot resolve during childbirth.

In previous work, imbalanced datasets composed of more benign samples (the majority class) than the malicious one (the minority class) have been widely adopted in Android malware detection. These imbalanced datasets bias learning toward the majority class, so that the minority class examples are more likely to be misclassified. To solve the problem, we propose a new oversampling method called fuzzy–synthetic minority oversampling technique, which is based on fuzzy set theory and the synthetic minority oversampling technique method. As the sample size of the majority class increases relative to that of the minority class, fuzzy–synthetic minority oversampling technique generates more synthetic examples for each minority class examples in the fuzzy region, where the minority examples have a low degree of membership to the minority class and are more likely to be misclassified. Using the new synthetic examples, the classifiers build larger decision regions that contain more minority examples, and they are no longer biased to the majority class. Compared with synthetic minority oversampling technique and Borderline–synthetic minority oversampling technique methods, fuzzy–synthetic minority oversampling technique achieves higher accuracy on both the minority class and the entire datasets.

Intrusion detection systems play an important role in preventing security threats and protecting networks from attacks. However, with the emergence of unknown attacks and imbalanced samples, traditional machine learning methods suffer from lower detection rates and higher false positive rates. We propose a novel intrusion detection model that combines an improved conditional variational AutoEncoder (ICVAE) with a deep neural network (DNN), namely ICVAE-DNN. ICVAE is used to learn and explore potential sparse representations between network data features and classes. The trained ICVAE decoder generates new attack samples according to the specified intrusion categories to balance the training data and increase the diversity of training samples, thereby improving the detection rate of the imbalanced attacks. The trained ICVAE encoder is not only used to automatically reduce data dimension, but also to initialize the weight of DNN hidden layers, so that DNN can easily achieve global optimization through back propagation and fine tuning. The NSL-KDD and UNSW-NB15 datasets are used to evaluate the performance of the ICVAE-DNN. The ICVAE-DNN is superior to the three well-known oversampling methods in data augmentation. Moreover, the ICVAE-DNN outperforms six well-known models in detection performance, and is more effective in detecting minority attacks and unknown attacks. In addition, the ICVAE-DNN also shows better overall accuracy, detection rate and false positive rate than the nine state-of-the-art intrusion detection methods.

Machine learning plays an important role in building intrusion detection systems. However, with the increase of data capacity and data dimension, the ability of shallow machine learning is becoming more limited. In this paper, we propose a fuzzy aggregation approach using the modified density peak clustering algorithm (MDPCA) and deep belief networks (DBNs). To reduce the size of the training set and the imbalance of the samples, MDPCA is used to divide the training set into several subsets with similar sets of attributes. Each subset is used to train its own sub-DBNs classifier. These sub-DBN classifiers can learn and explore high-level abstract features, automatically reduce data dimensions, and perform classification well. According to the nearest neighbor criterion, the fuzzy membership weights of each test sample in each sub-DBNs classifier are calculated. The output of all sub-DBNs classifiers is aggregated based on fuzzy membership weights. Experimental results on the NSL-KDD and UNSW-NB15 datasets show that our proposed model has higher overall accuracy, recall, precision and F1-score than other well-known classification methods. Furthermore, the proposed model achieves better performance in terms of accuracy, detection rate and false positive rate compared to the state-of-the-art intrusion detection methods.

Three-dimensional nanofibers cryogels (NFCs) with both thermally-tolerant and mechanically-robust properties have potential for wide application in biomedical or food areas; however, creating such NFCs has proven to be extremely challenging. In this study, konjac glucomannan (KGM)/poly (lactic acid) (PLA)-based novel NFCs were prepared by the incorporation of the mussel-inspired protein polydopamine (PDA) via a facile and environmentally-friendly electrospinning and freeze-shaping technique. The obtained KGM/PLA/PDA (KPP) NFCs were characterized by field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and compressive and tensile test. The results showed that the hierarchical cellular structure and physicochemical properties of KPP NFCs were dependent on the incorporation of PDA content. Moreover, the strong intermolecular hydrogen bond interactions among KGM, PLA and PDA also gave KPP NFCs high thermostability and mechanically-robust properties. Thus, this study developed a simple approach to fabricate multifunctional NFCs with significant potential for biomedical or food application.

Mitochondria are essential organelles and important targets for environmental pollutants. The detection of mitochondrial biogenesis and generation of reactive oxygen species (ROS) and p53 levels following low-dose methylmercury (MeHg) exposure could expand our understanding of underlying mechanisms. Here, the sensitivity of immortalized human neural progenitor cells (ihNPCs) upon exposure to MeHg was investigated. We found that MeHg altered cell viability and the number of 5-ethynyl-2′-deoxyuridine (EdU)-positive cells. We also observed that low-dose MeHg exposure increased the mRNA expression of cell cycle regulators. We observed that MeHg induced ROS production in a dose-dependent manner. In addition, mRNA levels of peroxisome-proliferator-activated receptor gammacoactivator-1α (PGC-1α), mitochondrial transcription factor A (TFAM) and p53-controlled ribonucleotide reductase (p53R2) were significantly elevated, which were correlated with the increase of mitochondrial DNA (mtDNA) copy number at a concentration as low as 10 nM. Moreover, we examined the expression of microRNAs (miRNAs) known as regulatory miRNAs of p53 (i.e., miR-30d, miR-1285, miR-25). We found that the expression of these miRNAs was significantly downregulated upon MeHg treatment. Furthermore, the overexpression of miR-25 resulted in significantly reducted p53 protein levels and decreased mRNA expression of genes involved in mitochondrial biogenesis regulation. Taken together, these results demonstrated that MeHg could induce developmental neurotoxicity in ihNPCs through altering mitochondrial functions and the expression of miRNA.

Bisphenol-A (BPA) is a potential endocrine disruptor impacting metabolic processes and increasing the risk of obesity. To determine whether urine BPA level is associated with overweight/obesity in school-age children, we examined 1,326 students in grades 4-12 from three schools (one elementary, one middle, and one high school) in Shanghai. More than 98% of eligible students participated. Total urine BPA concentration was measured and anthropometric measures were taken by trained research staff. Information on risk factors for childhood obesity was collected for potential confounders. Age- and gender-specific weight greater than 90(th) percentile of the underlying population was the outcome measure. After adjustment for potential confounders, a higher urine BPA level (≥2 µg/L), at the level corresponding to the median urine BPA level in the U.S. population, was associated with more than two-fold increased risk of having weight >90(th) percentile among girls aged 9-12 (adjusted odds ratio (aOR) = 2.32, 95% confidence interval: 1.15-4.65). The association showed a dose-response relationship with increasing urine BPA level associated with further increased risk of overweight (p = 0.006 for trend test). Other anthropometric measures of obesity showed similar results. The same association was not observed among boys. This gender difference of BPA effect was consistent with findings from experimental studies and previous epidemiological studies. Our study suggests that BPA could be a potential new environmental obesogen. Widespread exposure to BPA in the human population may also be contributing to the worldwide obesity epidemic.

To elucidate the structure–antioxidant activity relationships of chitosan gallate (CG), a series of CG derivatives with different degrees of substitution (DS’s) and molecular weights (MWs) were synthesized from chitosan (CS) and gallic acid (GA) via a free radical graft reaction. A higher MW led to a lower DS of CG. The structures of CG were characterized by FT-IR and 1H NMR, and results showed that GA was mainly conjugated to the C-2 and C-6 positions of the CS chain. The antioxidant activity (the DPPH radical scavenging activity and reducing power) were enhanced with an increased DS and a decreased MW of CG. A correlation between antioxidant activities and the DS and MW of CG was also established. In addition, a suitable concentration (0~250 μg/mL) of CG with different MWs (32.78~489.32 kDa) and DS’s (0~92.89 mg·GAE/g CG) has no cytotoxicity. These results should provide a guideline to the application of CG derivatives in food or pharmacology industries.

User identity linkage (UIL) refers to identifying user accounts belonging to the same identity across different social media platforms. Most of the current research is based on text analysis, which fails to fully explore the rich image resources generated by users, and the existing attempts touch on the multimodal domain, but still face the challenge of semantic differences between text and images. Given this, we investigate the UIL task across different social media platforms based on multimodal user-generated contents (UGCs). We innovatively introduce the efficient user identity linkage via aligned multi-modal features and temporal correlation (EUIL) approach. The method first generates captions for user-posted images with the BLIP model, alleviating the problem of missing textual information. Subsequently, we extract aligned text and image features with the CLIP model, which closely aligns the two modalities and significantly reduces the semantic gap. Accordingly, we construct a set of adapter modules to integrate the multimodal features. Furthermore, we design a temporal weight assignment mechanism to incorporate the temporal dimension of user behavior. We evaluate the proposed scheme on the real-world social dataset TWIN, and the results show that our method reaches 86.39% accuracy, which demonstrates the excellence in handling multimodal data, and provides strong algorithmic support for UIL. [ABSTRACT FROM AUTHOR]