[Contamination Characteristics and Ecological Risk of Antibiotics in Contaminated Sites of Typical Pharmaceutical Factories in China].

To understand the contamination characteristics and ecological risk of antibiotics in contaminated fields of pharmaceutical plants， samples of the surface soil， soil column， wastewater treatment process water， ground water， and residue dregs were collected from two typical antibiotic pharmaceutical plants in South and North China. A total of 87 commonly used antibiotics were quantified using ultrasound extraction-solid phase extraction and ultra-high performance liquid chromatography-mass spectrometry. The results showed that a total of 31 antibiotics of five classes were detected in all types of samples， and the maximum concentrations at each sampling point in the surface soil， soil column， residue dregs， wastewater treatment process water， and groundwater were 420 ng·g-1， 595 ng·g-1， 139 ng·g-1， 1 151 ng·L-1， and 6.65 ng·L-1， respectively. Most of the antibiotics were found in the surface soil， showing a decreasing trend with the depth of the soil column. The ecological risk assessment indicated that sulfamethazine， sulfaquinoxaline， tetracycline， chlorotetracycline， and D-sorbitol were at higher risk. Improving the efficiency of antibiotic removal from pharmaceutical wastewater and preventing production shop leaks are effective measures of controlling antibiotic contamination into and around fields in pharmaceutical plants.

Synergistic impact of co-exposures to whole blood metals on chronic kidney disease in general US adults: a cross­sectional study of the National Health and Nutrition Examination Survey 2011-2020.

The impact of exposure to metals on chronic kidney disease (CKD) has only been investigated in two-way or single metal interactions in previous studies. We investigated the associations between five single metals in blood and their mixed exposure and CKD by using the machine learning approach. Relevant data were extracted from the National Health and Nutrition Examination Survey (NHANES 2011-2020), and the level of five metals in blood detected by inductively coupled plasma mass spectrometry was considered as exposures, namely, cadmium (Cd), lead (Pb), total mercury (Hg), manganese (Mn), and selenium (Se). The correlations between individual metal and metal mixtures and CKD were then evaluated by survey-multivariable logistic regression (SMLR), generalized weighted quantile sum (WQS), and Bayesian kernel machine regression (BKMR). Altogether, our study included 12,412 participants representing 572.6 million non-institutionalized US adults. Several single metals with the high quartile of exposure showed a positive association with the CKD ratio including Cd [(AOR = 1.873, 95% CI: 1.537, 2.284), Q4], Pb [(AOR = 1.559, 95% CI: 1.295, 1.880), Q4], and total Hg [(AOR = 1.169, 95% CI: 1.018, 1.343), Q2], while Mn [(AOR = 0.796, 95% CI: 0.684, 0.927), Q2] and Se [(AOR = 0.805, 95% CI: 0.664, 0.976), Q4] were negatively associated with the CKD ratio. In light of the positive fit of the WQS regression model, a significantly positive correlation was found between mixed metals and CKD (AOR = 1.373, 95% CI: 1.224, 1.539) after full covariate adjustment, and a similar finding was also detected in the BKMR model. Our study revealed that each single metal including Cd, Pb, and total Hg might have a positive association with CKD while this association was negative for both Mn and Se. The five metals might have a positive joint effect on CKD.

Joint effect of whole blood metals exposure with dyslipidemia in representative US adults in NHANES 2011-2020.

With little knowledge on the joint effects of metal exposure on dyslipidemia, we aimed to investigate the relationship between exposure to metal and dyslipidemia among US adults based on the National Health and Nutrition Examination Survey (NHANES). Based on the five NHANES waves (2011-2020), we selected five metals in blood as exposure, namely, cadmium (Cd), lead (Pb), total mercury (Hg), manganese (Mn), and selenium (Se), which were detected by inductively coupled plasma mass spectrometry. Survey-multivariable logistic regression, generalized weighted quantile sum (WQS), and Bayesian kernel machine regression (BKMR) were performed to determine whether dyslipidemia was associated with single metals or mixed metals. Our study included 12,526 participants aged from 20 to 80, representing 577.1 million non-institutionalized US adults. We found a positive association between several metals including Pb [adjusted odds ratio (AOR) = 1.332, 95%CI: 1.165, 1.522], total Hg (AOR = 1.264, 95%CI: 1.120, 1.427), Mn (AOR = 1.181, 95%CI: 1.046, 1.334), and Se (AOR = 1.771, 95%CI: 1.576, 1.992) and dyslipidemia. According to the WQS approach, metal mixtures were positively associated with dyslipidemia (AOR: 1.310, 95%CI: 1.216, 1.411) after a full-model adjustment. As is shown in the BKMR model, mixed metals tended to be positively associated with dyslipidemia ratios in a significant manner. Females, non-Hispanic White populations, people aged over 60, and those who did a little physical activity had a greater risk for dyslipidemia. Our findings suggest metals including Cd, Pb, Hg, Mn, and Se and their combinations may adversely affect dyslipidemia among US adults. Due to the cross-sectional nature of the study, it is possible that reverse causation may exist.