Urinary Metabolites of Polycyclic Aromatic Hydrocarbons of Rural Population in Northwestern China: Oxidative Stress and Health Risk Assessment.

Polycyclic aromatic hydrocarbon (PAH) exposure is suspected to be linked to oxidative damage. Herein, ten PAH human exposure biomarkers [hydroxylated PAH metabolites (OH-PAHs)] and five oxidative stress biomarkers (OSBs) were detected in urine samples collected from participants living in a rural area (n = 181) in Northwestern China. The median molar concentration of ΣOH-PAHs in urine was 47.0 pmol mL-1. The 2-hydroxynaphthalene (2-OHNap; median: 2.21 ng mL-1) was the dominant OH-PAH. The risk assessment of PAH exposure found that hazard index (HI) values were <1, indicating that the PAH exposure of rural people in Jingyuan would not generate significant cumulative risks. Smokers (median: 0.033) obtained higher HI values than nonsmokers (median: 0.015, p < 0.01), suggesting that smokers face a higher health risk from PAH exposure than nonsmokers. Pearson correlation and multivariate linear regression analysis revealed that ΣOH-PAH concentrations were significant factors in increasing the oxidative damage to deoxyribonucleic acid (DNA) (8-hydroxy-2'-deoxyguanosine, 8-OHdG), ribonucleic acid (RNA) (8-oxo-7,8-dihydroguanine, 8-oxoGua), and protein (o, o'-dityrosine, diY) (p < 0.05). Among all PAH metabolites, only 1-hydroxypyrene (1-OHPyr) could positively affect the expression of all five OSBs (p < 0.05), suggesting that urinary 1-OHPyr might be a reliable biomarker for PAH exposure and a useful indicator for assessing the impacts of PAH exposure on oxidative stress. This study is focused on the relation between PAH exposure and oxidative damage and lays a foundation for the study of the health effect mechanism of PAHs.

A fast method for the determination of personal care product chemicals in human urine using dispersive liquid-liquid extraction and ultra high-performance liquid chromatography-tandem mass spectrometry.

RATIONALE: Personal care product chemicals (PCPCs) are the chemicals used in personal care products. Many of them are endocrine disruptors and have potential adverse effects on humans. The concentrations of PCPCs in urine are the main biomarker for assessing human exposure. METHODS: A method was developed for the simultaneous determination of 14 PCPCs in human urine using dispersive liquid-liquid extraction combined with ultra high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). RESULTS: Compared with liquid-liquid extraction, this method had the advantages of time efficiency, sensitivity, and limited organic solvent consumption. It produced good linearity (0.9965-0.9996), limits of detection (2.82-36.36 pg mL-1 ), limits of quantitation (9.39-121.08 pg mL-1 ), matrix effect (-0.90%-2.55%), intra-day precision (relative standard deviations [RSDs] <15%), and inter-day precision (RSDs <19.9%). The method had satisfactory relative recovery at three concentration levels. CONCLUSIONS: A rapid method was developed for the simultaneous quantification of 14 PCPCs in human urine. The practicability of the method was verified with 21 urine from university students. It is expected that this method will provide a powerful reference for the assessment of exposure to PCPCs in large populations.

HE-YOLOv5s: Efficient Road Defect Detection Network.

In recent years, the number of traffic accidents caused by road defects has increased dramatically all over the world, and the repair and prevention of road defects is an urgent task. Researchers in different countries have proposed many models to deal with this task, but most of them are either highly accurate and slow in detection, or the accuracy is low and the detection speed is high. The accuracy and speed have achieved good results, but the generalization of the model to other datasets is poor. Given this, this paper takes YOLOv5s as a benchmark model and proposes an optimization model to solve the problem of road defect detection. First, we significantly reduce the parameters of the model by pruning the model and removing unimportant modules, propose an improved Spatial Pyramid Pooling-Fast (SPPF) module to improve the feature signature fusion ability, and finally add an attention module to focus on the key information. The activation function, sampling method, and other strategies were also replaced in this study. The test results on the Global Road Damage Detection Challenge (GRDDC) dataset show that the FPS of our proposed model is not only faster than the baseline model but also improves the MAP by 2.08%, and the size of this model is also reduced by 6.07 M.

Does mask wearing affect skin health? An untargeted skin metabolomics study.

Wearing masks is used as an effective way to prevent the spread of viruses. However, the effect of wearing masks on skin health requires further assessment. In this study, a non-invasive D-squame sampling method coupled with an untargeted metabolomics analysis by liquid chromatography high-resolution mass spectrometry was developed to identify the changes in the skin metabolome caused by wearing masks. D-squame method was found to have advantages over the commonly used sterile gauze method, especially for the lipids and lipid-like molecules. A total of 356 skin metabolites were putatively identified from the stratum corneum of 10 volunteers, and 17 differential metabolites were significantly downregulated after wearing surgical masks or N95 respirators. The downregulation of metabolites such as phosphatidylethanolamine and sphingomyelin might be related to hypoxia or increased skin moisture caused by wearing masks. Changes in skin metabolomics indicated a potential risk of skin barrier disruption and skin inflammation. Intermittent removal of the masks can effectively alleviate changes in the skin metabolome.

Super-resolution fusion optimization for poultry detection: a multi-object chicken detection method.

Accurate poultry detection is crucial for studying poultry behavior using computer vision and video surveillance. However, in free-range farming environments, detecting chickens can often be challenging due to their small size and mutual occlusion. The current detection algorithms exhibit a low level of accuracy, with a high probability of false and missed detections. To address this, we proposed a multi-object chicken detection method named Super-resolution Chicken Detection, which utilizes super-resolution fusion optimization. The algorithm employs the residual-residual dense block to extract image features and used a generative adversarial network to compensate for the loss of details during deep convolution, producing high-resolution images for detection. The proposed algorithm was validated with the B1 data set and the MC1 multi-object data set, demonstrating that the reconstructed images possessed richer pixel features compared to original images, specifically it improved detection accuracy and reduced the number of missed detections. The structural similarity of the reconstructed images was 99.9%, and the peak signal-to-noise ratio was above 30. The algorithm improved the Average Precision50:95 of all You Only Look Once Version X (YOLOX) models, with the largest improvement for the B1 data set with YOLOX-Large (+6.3%) and for the MC1 data set with YOLOX-Small (+4.1%). This was the first time a super-resolution reconstruction technique was applied to multi-object poultry detection. Our method will provide a fresh approach for future poultry researchers to improve the accuracy of object detection using computer vision and video surveillance.

In free-range farming environments, accurately detecting individual chickens has been a persistent challenge for researchers. Due to mutual occlusion and limitations of camera capturing distance, existing detection algorithms have had low detection accuracy, leading to a high probability of false and missed detections. To address this problem, a multi-object chicken detection method named Super-resolution Chicken Detection (SRCD) was developed. The proposed algorithm utilized super-resolution reconstruction and You Only Look Once Version X object detection networks to achieve accurate chicken detection. Through extensive experimentation with two data sets, SRCD demonstrated its superiority in detecting chickens, reducing missed detections likely related to occlusion and the chickens' distance to the camera. Additionally, the SRCD algorithm enriched the pixel features of the chickens with minimal changes to the original images, resulting in a reconstructed image with high similarity to the original image. As a result, this method provided a practical solution for more accurate detection in small free-range farming environments, improving poultry production efficiency.

Design and Fabrication of an Ag Ultrathin Layer-Based Transparent Band Tunable Conductor and Its Thermal Stability.

Transparent conductors (TC) have been widely applied in a wide range of optoelectronic devices. Nevertheless, different transparent spectral bands are always needed for particular applications. In this work, indium tin oxide (ITO)-free TCs with tunable transparent bands based on the film structure of TiO2/Ag/AZO (Al-doped ZnO) were designed by the transfer matrix method and deposited by magnetron sputtering. The transparent spectra and figure-of-merit (FOM) were effectively adjusted by precisely controlling the Ag layer's thickness. The fabricated as-deposited samples exhibited an average optical transmittance larger than 88.3% (400-700 nm), a sheet resistance lower than 7.7 Ω.sq-1, a low surface roughness of about 1.4 nm, and mechanical stability upon 1000 bending cycles. Moreover, the samples were able to hold optical and electrical properties after annealing at 300 °C for 60 min, but failed at 400 °C even for 30 min.

Integrated metabolomics, transcriptomics, and proteomics analyses reveal co-exposure effects of polycyclic aromatic hydrocarbons and cadmium on ryegrass (Lolium perenne L.).

Cadmium (Cd) and polycyclic aromatic hydrocarbons (PAHs) are prominent soil contaminants found in industrial sites, and their combined effects on plants are not yet fully understood. To investigate the mechanisms underlying the co-exposure of Cd and PAHs and identify key biomarkers for their co-effects, an integrated analysis of metabolomics, transcriptomics, and proteomics was conducted on ryegrass leaves cultivated in soil. In nontarget metabolomics analysis, nine differentially expressed metabolites that were specifically induced by the compound exposure were identified. When combined with the analysis of differentially expressed genes and proteins, it was determined that the major pathways involved in the response to the co-stress of Cd and PAHs were linoleic acid metabolism and phenylpropanoid biosynthesis. The upregulation of 12,13-dihydroxy-9Z-octadecenoic acid and the downregulation of sinapyl alcohol were identified as typical biomarkers, respectively. Compared to scenarios of single exposures, the compound exposure to Cd and PAHs disrupted the oxidation of linoleic acid, leading to alterations in the profiles of linoleate metabolites. Additionally, it intensified hydroxylation, carboxylation, and methylation processes, and interfered with reactions involving coenzyme A, thus inhibiting lignin production. As a result, oxidative stress was elevated, and the cell wall defense system in ryegrass was weakened. The findings of this study highlight the ecological risks associated with unique biological responses in plants co-exposed to Cd and PAHs in polluted soils.

Prenatal exposure to multiple environmental chemicals and birth size.

BACKGROUND: Epidemiological studies addressing the combined effects of exposure to chemical mixtures at different stages of pregnancy on birth size are scarce. OBJECTIVE: To evaluate the association between prenatal exposure to chemical mixtures and birth size. METHODS: Our previous study repeatedly measured the urinary concentrations of 34 chemical substances among 743 pregnant women and identified three distinct clusters of exposed population and six dominant principal components of exposed chemicals in each trimester. In this study, we assessed the associations of these exposure profiles with birth weight, birth length, and ponderal index using multivariable linear regression. RESULTS: We found that compared with women in cluster 1 (lower urinary chemical concentrations), women in cluster 2 (higher urinary concentrations of metals, benzothiazole, benzotriazole, and some phenols), and women in cluster 3 (higher urinary concentrations of phthalates) were more likely to give birth to children with higher birth length [0.23 cm (95% CI: -0.03, 0.49); 0.29 cm (95%CI: 0.03, 0.54), respectively]. This association was observed only in 1st trimester. In addition, prenatal exposure to PC3 (higher benzophenones loading) was associated with reduced birth length across pregnancy [-0.07 cm (95% CI: -0.18, 0.03) in 1st and 2nd trimester; -0.13 cm (95% CI: -0.24, -0.03) in 3rd trimester]. Exposure to PC6 (higher thallium and BPA loading in 2nd trimester) was associated with increased birth length [0.15 cm (95% CI: 0.05, 0.26)]. Compared with other outcomes, associations of both clusters and PCs with birth length were stronger, and these associations were more pronounced in boys. IMPACT STATEMENT: Exposure to multiple chemicals simultaneously, the actual exposure situation of pregnant women, was associated with birth size, indicating that chemical mixtures should be taken more seriously when studying the health effects of pollutants.

Discovery of 35 novel classes of per- and polyfluoroalkyl substances in representative commercial fluorinated products in China.

Per- and polyfluoroalkyl substances (PFAS) have received increasing scientific and regulatory attention due to their global distribution and health hazards. However, little is known about the PFAS composition of fluorinated products commercially available in China. In this study, a sensitive and robust analytical method was proposed for the comprehensive characterization of PFAS in aqueous film-forming foam and fluorocarbon surfactants in the domestic market based on liquid chromatography-high resolution mass spectrometry in full scan acquisition mode followed by parallel reaction monitoring mode. Consequently, a total of 102 PFAS from 59 classes were elucidated, of which 35 classes are reported for the first time, including 27 classes of anionic, seven classes of zwitterionic, and one class of cationic PFAS. The anionic-type products are mainly C6 fluorotelomerization-based (FT-based) PFAS. Perfluorooctanoic acid and perfluorooctane sulfonate are negligible, while some known electrochemical fluorination-based long-chain precursors in zwitterionic products are worthy of concern because of their high abundance and potential degradation. New precursors detected in zwitterionic products are FT-based PFAS, for example, 6:2 FTSAPr-AHOE and 6:2 FTSAPr-diMeAmPrC. The structural elucidation of PFAS in commercial products facilitates a better assessment of human exposure and environmental release.

Urinary Levels of 14 Metal Elements in General Population: A Region-Based Exploratory Study in China.

Metal pollution may lead to a variety of diseases; for this reason, it has become a matter of public concern worldwide. However, it is necessary to use biomonitoring approaches to assess the risks posed to human health by metals. In this study, the concentrations of 14 metal elements in 181 urine samples obtained from the general population of Gansu Province, China, were analyzed using inductively coupled plasma mass spectrometry. Eleven out of fourteen target elements had detection frequencies above 85%, namely, Cr, Ni, As, Se, Cd, Al, Fe, Cu and Rb. The concentrations of most metal elements in the urine of our subjects corresponded to the medium levels of subjects in other regional studies. Gender exerted a significant influence (p < 0.05) on the concentrations of Tl, Rb and Zn. The concentrations of Ni, As, Pb, Sr, Tl, Zn, Cu and Se showed significant differences among different age groups and the age-related concentration trends varied among these elements. There were significant differences in the urine concentrations of Zn and Sr between those subjects in the group who were frequently exposed to soil (exposed soil > 20 min/day) and those in the group who were not, indicating that people in regular contact with soil may be more exposed to metals. This study provides useful information for evaluating the levels of metal exposure among general populations.

Hydrogen sulfide suppresses H2O2-induced proliferation and migration of HepG2 cells through Wnt/ß-catenin signaling pathway.

Both H2S and H2O2 affect many cellular events, such as cell differentiation, cell proliferation and cell death. However, there is some controversy about the roles of H2S and H2O2, since the detailed mechanisms they are involved remain unclear. In this study, low concentration of H2O2 (40 µM) increased the viability of hepatocellular carcinoma cells HepG2, while both H2S and high concentration of H2O2 decreased the cell viability in a dose-dependent manner. Wound healing assay indicated that 40 µM H2O2 promoted migration of HepG2 cells, which was suppressed by exogenous H2S. Further analysis revealed that administration of exogenous H2S and H2O2 changed the redox status of Wnt3a in HepG2 cells. Altered expression of proteins including Cyclin D1, TCF-4, and MMP7, which are downstream of the Wnt3a/ß-catenin signaling pathway, were found after treatment with exogenous H2S and H2O2. Compared with H2S, low concentration of H2O2 showed opposite effects on these protein expression levels in HepG2 cells. These results suggest that H2S suppressed H2O2-induced proliferation and migration of HepG2 through regulating Wnt3a/ß-catenin signaling pathway.

Remix: Towards the transferability of adversarial examples.

Deep neural networks (DNNs) are susceptible to adversarial examples, which are crafted by deliberately adding some human-imperceptible perturbations on original images. To explore the vulnerability of models of DNNs, transfer-based black-box attacks are attracting increasing attention of researchers credited to their high practicality. The transfer-based approaches can launch attacks against models easily in the black-box setting by resultant adversarial examples, whereas the success rates are not satisfactory. To boost the adversarial transferability, we propose a Remix method with multiple input transformations, which could achieve multiple data augmentation by utilizing gradients from previous iterations and images from other categories in the same iteration. Extensive experiments on the NeurIPS 2017 adversarial dataset and the ILSVRC 2012 validation dataset demonstrate that the proposed approach could drastically enhance the adversarial transferability and maintain similar success rates of white-box attacks on both undefended models and defended models. Furthermore, extended experiments based on LPIPS show that our method could maintain a similar perceived distance compared to other baselines.

Multiple metal exposure and metabolic syndrome in elderly individuals: A case-control study in an active mining district, Northwest China.

The prevalence of metabolic syndrome (MetS) is increasing at an alarming rate worldwide, particularly among elderly individuals. Exposure to various metals has been linked to the development of MetS. However, limited studies have focused attention on the elderly population living in active mining districts. Participants with MetS (N = 292) were matched for age (±2 years old) and sex with a healthy subject (N = 292). We measured the serum levels of 14 metals in older people aged 65-85 years. Conditional logistic regression, restricted cubic spline model, multiple linear regression, and Bayesian Kernel Machine Regression (BKMR) were applied to estimate potential associations between multiple metals and the risk of MetS. Serum levels of Sb and Fe were significantly higher than the controls (0.58 µg/L vs 0.46 µg/L, 2167 µg/L vs 2042 µg/L, p < 0.05), while Mg was significantly lower (20035 µg/L vs 20,394 µg/L, p < 0.05). An increased risk of MetS was associated with higher serum Sb levels (adjusted odds ratio (OR) = 1.61 for the highest tertile vs. the lowest tertile, 95% CI = 1.08-2.40, p-trend = 0.018) and serum Fe levels (adjusted OR = 1.55 for the highest tertile, 95% CI = 1.04-2.33, p-trend = 0.032). Higher Mg levels in serum may have potential protective effects on the development of MetS (adjusted OR = 0.61 for the highest tertile, 95% CI = 0.41-0.91, p-trend = 0.013). A joint exposure analysis by the BKMR model revealed that the mixture of 12 metals (except Tl and Cd) was associated with increased risk of MetS. Our results indicated that exposure to Sb and Fe might increase the risk of MetS in an elderly population living in mining-intensive areas. Further work is needed to confirm the protective effect of Mg on MetS.

Derivatization of N-Acyl Glycines by 3-Nitrophenylhydrazine for Targeted Metabolomics Analysis and Their Application to the Study of Diabetes Progression in Mice.

N-Acyl glycines (NAGlys) are an important class of metabolites in the detoxification system of the human body. They have been used in the diagnosis of several metabolic diseases. Liquid chromatography-mass spectrometry (LC-MS) is the most frequently used NAGlys detection platform. Here, we describe a simple and sensitive method of NAGlys detection by LC-MS in plasma and urine samples. This approach is based on the use of a derivatization reagent, 3-nitrophenylhydrazine. The reaction is quick in aqueous solution, and no quenching step is needed. To expand the coverage of NAGlys when standards are not available, NAGlys were first identified based on high-resolution LC-MS. Quantification was subsequently carried out on triple quadrupole LC-MS. This approach allowed a much broader measurement of NAGlys (41 NAGlys in total), especially when authentic standards are unavailable. Comprehensive analysis of NAGlys with this new method was applied in plasma and urine samples of db/db diabetic and non-diabetic db/m+ control mice. The majority of detected NAGlys were altered with high differentiation ability in plasma and urine samples from diabetic and non-diabetic mice. These identified NAGlys hold the potential to be diagnostic biomarkers for type II diabetes and diabetic complications.

Sex Detection of Chicks Based on Audio Technology and Deep Learning Methods.

The sex detection of chicks is an important work in poultry breeding. Separating chicks of different sexes early can effectively improve production efficiency and commercial benefits. In this paper, based on the difference in calls among one-day-old chicks of different sexes, a sex detection method based on chick calls is designed. Deep learning methods were used to classify the calls of chicks and detect their sex. This experiment studies three different varieties of chicks. The short-time zero-crossing rate was used to automatically detect the endpoints of chick calls in audio. Three kinds of audio features were compared: Spectrogram, Cepstrogram and MFCC+Logfbank. The features were used as the input in neural networks, and there were five kinds of neural networks: CNN, GRU, CRNN, TwoStream and ResNet-50. After the cross-comparison experiment of different varieties of chicks, audio features and neural networks, the ResNet-50 neural network trained with the MFCC+Logfbank audio features of three yellow chick calls had the highest test accuracy of 83% when testing Three-yellow chicks' calls. The GRU neural network trained with the Spectrogram audio features of native chick calls had the highest test accuracy of 76.8% when testing Native chicks' calls. The ResNet-50 neural network trained with Spectrogram audio features of flaxen-yellow chick calls had the highest test accuracy of 66.56%when testing flaxen-yellow chick calls. Multiple calls of each chick were detected, and the majority voting method was used to detect the sex of the chicks. The ResNet-50 neural network trained with the Spectrogram of three yellow chick calls had the highest sex detection accuracy of 95% when detecting the three yellow chicks' sex. The GRU neural network trained with the Spectrogram and cepstrogram of native chick calls and the CRNN network trained with the Spectrogram of native chick calls had the highest sex detection accuracy of 90% when detecting the native chicks' sex. The Twostream neural network trained with MFCC+Logfbank of flaxen-yellow chick calls and the ResNet-50 network trained with the Spectrogram of flaxen-yellow chick calls had the highest sex detection accuracy of 80% when detecting the flaxen-yellow chicks' sex. The results of the cross-comparison experiment show that there is a large diversity between the sex differences in chick calls of different breeds. The method is more applicable to chick sex detection in three yellow chicks and less so in native chicks and flaxen-yellow chicks. Additionally, when detecting the sex of chicks of a similar breed to the training chicks, the method obtained better results, while detecting the sex of chicks of other breeds, the detection accuracy was significantly reduced. This paper provides further perspectives on the sex detection method of chicks based on their calls and help and guidance for future research.

Occurrence and profile characteristics of environmental phenols in human urine from a rural area in Northwestern China.

Many environmental phenols, such as bisphenols, benzophenones and parabens, are known as endocrine disruptors and can adversely affect human health. However, the knowledge of human exposure to common environmental phenols in Chinese rural areas is insufficient. In this context, 181 urine samples were collected from participants in a rural area in Northwest China and were analyzed for nine bisphenols, three benzophenones and four parabens. Bisphenol A (BPA), bisphenol S, benzophenone-1 (BP-1), benzophenone-3 (BP-3), 4-hydroxybenzophenone, methylparaben (MeP), ethylparaben and propylparaben (PrP) were detected in more than 50% of the urine samples, with median concentrations of 0.938 ng/mL, 0.0111 ng/mL, 0.191 ng/mL, 1.30 ng/mL, 0.0320 ng/mL, 25.9 ng/mL, 4.31 ng/mL and 1.94 ng/mL, respectively. A significant positive correlation was observed between BP-1 and BP-3, as well as between MeP and PrP, indicating metabolic transformation and combined use, respectively. The concentrations of MeP and PrP in females were significantly higher than those in males, suggesting that females were exposed to more MeP and PrP than males. Urinary concentrations of BPA, BP-3, MeP and PrP could be influenced by age. Other demographic information, such as annual household income, education and occupation was not associated with the exposure level of the targeted phenols in adults. The estimated daily intakes of the analytes except BPA were all below their respective tolerable/acceptable daily intake levels. This study profiles the demographic differences in the exposure to environmental phenols in general populations from rural areas and provides information on risk assessments.

Fabrication of Chitosan-Loaded Multifunctional Wool Fabric for Reactive Dye Digital Inkjet Printing by Schiff Base Reaction.

Improving the development of high-value multifunctional wool fabrics was essential to satisfy diverse needs. Considering the various characteristics of chitosan macromolecules, herein, a padding-cross-linking process was adopted and then multifunctional wool fabrics with outstanding printing effects, shrink resistance, and antibacterial properties were fabricated. The test results showed that chitosan macromolecules loaded successfully on the wool fiber surface by Schiff base reaction. Wool fabrics changed from hydrophobic to hydrophilic due to the existence of chitosan macromolecules. The color strength (K/S value) of the reactive dye inkjet-printed wool fabric was greatly increased from 20.48 to 26.6. The area shrinkage of final samples was 2.53%, which was exceedingly lower than that of the original wool (10.96%). Moreover, the chitosan macromolecules with reactive amino groups endowed wool fabrics with certain antibacterial properties against E. coli and S. aureus. Generally, this study provided guidance for manufacturing multifunctional digital inkjet-printed wool products in mass production.

The association of serum phthalate metabolites with biomarkers of ovarian reserve in women of childbearing age.

Phthalates (PAEs) are widely used plasticizers drawing increasing concern due to reproductive toxicity. However, studies on serum PAEs metabolites (mPAEs) and their associations with human ovarian function remain very scarce. In this study, from April 2019 to August 2020, a total of 297 women of childbearing age were recruited in Tianjin, China. Eleven mPAEs were analyzed in serum samples and eight mPAEs were detected at frequencies > 65% with median concentrations of 0.43-15.3 ng/mL. In multinomial logistic analysis, an increase in serum mono (2-isobutyl) phthalate (miBP) was associated with decline in antral follicle count (AFC) (OR=1.26, 95% CI: 0.99, 1.61) and 5-mono-(2-ethyl-5-hydroxyhexyl) phthalate (mEHHP) was significantly associated with AFC increase (OR=1.43, 95% CI: 1.06, 1.92), which were aligned with the associations found between mPAEs and AMH through generalized linear regression. In multiple linear regression models, per 10% increase in serum mono (2-ethylhexyl) phthalate (mEHP), mono (2-ethyl-5-oxohexyl) phthalate (mEOHP) (oxo-mEHP), and principal component 1 featured for high concentrations of mono-n-butyl phthalate (mBP), miBP and mEHP were associated with 0.15 (95% CI: -0.29, -0.02), 0.01 (95% CI: -0.01, 0.00) and 0.01 (95% CI: -0.02, 0.00) ln-unit decrease in estradiol (E2) levels, respectively, while mono-[(2-carboxymethyl) hexyl] phthalate (mCMHP) (carboxymethyl-mEHP) was positively associated with 0.05 ln-unit increase of E2 (95% CI: 0.02, 0.08). The observed negative associations between mPAEs and the Anti-Müllerian hormone (AMH) also aligned with the change in AFC. Generalized linear regression also revealed nonlinear associations between mono-ethyl phthalate (mEP), mCMHP and follicle-stimulating hormone (FSH). Overall, serum mEHP and its metabolites were negatively associated with E2. miBP was negatively associated with AFC. The nonlinear associations between mPAEs and FSH, and AMH need further study.

Spatial distribution and ecological risks of polychlorinated biphenyls in a river basin affected by traditional and emerging electronic waste recycling in South China.

With development of e-waste related legislation in China, formal recycling activities are designated in some areas while informal ones are illegally transferred to emerging areas to avoid supervision. However, the resulting environmental impact and ecological risks are not clear. Here, we investigated the discharge of polychlorinated biphenyls (PCBs) to soil and aquatic environments by e-waste recycling activities in the Lian River Basin, China. The study area included a designated industrial park in the traditional e-waste recycling area (Guiyu, known as the world's largest e-waste center), several emerging informal recycling zones, and their surrounding areas and coastal area. A total of 27 PCBs were analyzed, and the highest concentration was found in an emerging site for soil (354 ng g-1) and in a traditional site for sediment (1350 ng g--1) respectively. The pollution levels were significantly higher in both the traditional and emerging recycling areas than in their respective upstream countryside areas (p = 0.0356 and 0.0179, respectively). Source analysis revealed that the traditional and emerging areas had similar PCB sources mainly associated with three PCB technical mixtures manufactured in Japan (KC600) and the USA (Aroclor 1260 and Aroclor 1262). The PCB pollution in their downstream areas including the coastal area was evidently affected by the formal and informal recycling activities through river runoff. The ecological risk assessments showed that PCBs in soils and sediments in the Lian River Basin could cause adverse ecotoxicological consequences to humans and aquatic organisms.

Phthalates in dormitory dust and human urine: A study of exposure characteristics and risk assessments of university students.

Phthalate diesters (PAEs) are prevalent and potentially toxic to human health. The university dormitory represents a typical and relatively uniform indoor environment. This study evaluated the concentrations of phthalate monoesters (mPAEs) in urine samples from 101 residents of university status, and the concentrations of PAEs in dust collected from 36 corresponding dormitories. Di-(2-ethylhexyl) phthalate (DEHP, median: 68.0 µg/g) was the major PAE in dust, and mono-ethyl phthalate (47.9 %) was the most abundant mPAE in urine. The levels of both PAEs in dormitory dust and mPAEs in urine were higher in females than in males, indicating higher PAE exposure in females. Differences in lifestyles (dormitory time and plastic product use frequency) may also affect human exposure to PAEs. Moreover, there were significant positive correlations between the estimated daily intakes of PAEs calculated by using concentrations of PAEs in dust (EDID) and mPAEs in urine (EDIU), suggesting that PAEs in dust could be a significant source of human exposure to PAEs. The value of EDID/EDIU for low molecular weight PAEs (3-6 carbon atoms in their backbone) was lower than that of high molecular weight PAEs. The contribution rate of various pathways to PAE exposure illustrated that non-dietary ingestion (87.8 %) was the major pathway of human exposure to PAEs in dust. Approximately 4.95 % of university students' hazard quotients of DEHP were >1, indicating that there may be some health risks associated with DEHP exposure among PAEs. Furthermore, it is recommended that some measures be taken to reduce the production and application of DEHP.