Building multiple cross-links or networks is a favorable way of diversifying applications of the hydrogels, which is also available for the organohydrogels prepared via the solvent replacement way. However, the situations become more complicated for organohydrogels due to the presence of replaced solvents. Therefore, the correlations between the multiple cross-links and final performance need to be better understood for the organohydrogels, which is vital for tailoring their inherent properties to expand final application scenarios. Polyacrylamide (PAM)/poly(vinyl alcohol) (PVA)/MXene composite organohydrogels with dual cross-links, namely, the covalently cross-linked PAM chains as the primary network and the physically cross-linked PVA/PAM chains with MXene particles as the secondary cross-links, were developed here for the study. The occurrence of the secondary cross-links plays multiple roles as sacrificial units endowing the system with ultrastretchability with an excellent strain–resistance effect and as temperature-sensitive units endowing the system with thermosensation ability with an outstanding temperature coefficient of resistance. Thus, the optimized sample can be used as a strain sensor with excellent environmental tolerance for detecting human motion as a pressure sensor to probe compression with weak deformation and as a thermal sensor to capture environmental temperature changes. This work provides valuable information on developing organohydrogels with superior performance for multimodal sensors.
Objective To investigate the potential association of cochlear clock genes (CRY1, CRY2, PER1, and PER2), the DNF gene (brain-derived neurotrophic factor), and the NTF3 gene (neurotrophin3) with susceptivity to noise-induced hearing loss (NIHL) among Chinese noise-exposed workers. Methods A nested case–control study was performed with 2056 noise-exposed workers from a chemical fiber factory and an energy company who underwent occupational health examinations in 2019 as study subjects. Propensity score matching was conducted to screen cases and controls by matching sex, age, and the consumption of tobacco and alcohol. A total of 1269 participants were enrolled. Then, general information and noise exposure of the study subjects were obtained through a questionnaire survey and on-site noise detection. According to the results of audiological evaluations, the participants were divided into the case group (n = 432, high-frequency threshold shift > 25 dB) and the matched control group (n = 837, high-frequency threshold shift ≤ 25 dB) by propensity score matching. Genotyping for PER1 rs2253820 and rs2585405; PER2 rs56386336 and rs934945; CRY1 rs1056560 and rs3809236; CRY2 rs2292910 and rs6798; BDNF rs11030099, rs7124442 and rs6265; and NTF3 rs1805149 was conducted using the TaqMan-PCR technique. Results In the dominant model and the co-dominant model, the distribution of PER1 rs2585405 genotypes between the case group and the control group was significantly different (P = 0.03, P = 0.01). The NIHL risk of the subjects with the GC genotype was 1.41 times the risk of those carrying the GG genotype (95% confidence interval (CI) of odds ratio (OR): 1.01–1.96), and the NIHL risk of the subjects with the CC genotype was 0.93 times the risk of those carrying the GG genotype (95%CI of OR: 0.71–1.21). After the noise exposure period and noise exposure intensities were stratified, in the co-dominant model, the adjusted OR values for noise intensities of ≤ 85 was 1.23 (95%CI: 0.99–1.53). In the dominant model, the adjusted OR values for noise exposure periods of ≤ 16 years and noise intensities of ≤ 85 were 1.88 (95%CI: 1.03–3.42) and 1.64 (95%CI: 1.12–2.38), respectively. Conclusion The CC/CG genotype of rs2585405 in the PER1 gene was identified as a potential risk factor for NIHL in Chinese noise-exposed workers, and interaction between rs2585405 and high temperature was found to be associated with NIHL risk.
To explore the fitting effect of the ARIMA, GM(1,1), and RANSAC model in the changes of white blood cells (WBC) in benzene-exposed workers, and select the optimal model to predict the WBC count of workers. Among 350 employees in an aerospace process manufacturing enterprise in Nanjing, workers with 10 years of benzene exposure were selected, and used Excel software to organize the WBC data, and the ARIMA model and RANSAC model were established by R software, and the GM(1, 1) model was established by DPS software, and the magnitude of the mean absolute percentage error (MAPE) of fitting three models to WBC counts was compared. The MAPE based on the ARIMA(2,1,2) model is 6.78%, the MAPE based on the GM(1,1) model is 5.19%, and the MAPE based on the RANSAC model is 6.37%, so the GM( 1,1) model was more suitable for fitting the trend of WBC counts in benzene exposed workers in this study. The GM(1,1) model is suitable for fitting WBC counts in a small sample size and can provide a short-term prediction of WBC counts in benzene-exposed workers and provide basic information for occupational health risk assessment of workers. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-022-24453-z.
Background: Mercury has different levels of toxicity to various organ systems of the human body. Therefore, it is very important to research the molecular differences and functional mechanisms of mercury exposure for the early prevention and treatment of occupational mercury poisoning. Method:The subjects of the population study were on-the-job workers in a thermometer manufacturing plant in Jiangsu Province in 2016. According to the basic information collected, 40 people in the high concentration mercury exposure group and 40 people in the low concentration mercury exposure group (control group) were matched, and the blood of each person was collected. Through bioinformatics analysis of gene expression microarray results, the genes related to mercury exposure were initially screened out. The qRT-PCR was used to verify the initial screening of differential expression genes (DEGs) to identify the differential genes of mercury exposure. Mercury exposure differential genes were verified in 293T model cells, and the molecular functions and mechanisms of mercury exposure differential genes were analyzed by qRT-PCR, Western blot, siRNA transfection and ELISA. Results: Compared with the control group, the expression level of PTEN in the high-concentration mercury exposure group was 21.86% of that in the control group. The result of correlation analysis showed that the relative expression levels of PTEN and RNF2 genes were negatively correlated with the urine mercury value. The expression of PTEN was down-regulated, and the expression of PI3K, AKT and IL-6protein was increased in the mercury-infected 293T cell model. Conclusions:The results showed that mercury exposure could down-regulate the PTEN gene, activate the PI3K/AKT regulatory pathway, increase the expression of inflammatory factors, and thus cause renal inflammation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.