Source-oriented health risk assessment of groundwater nitrate by using EMMTE coupled with HHRA model.

Conventional concentration-oriented approaches for nitrate risk diagnosis only provide overall risk levels without identifying risk values of individual sources or sources accountable for potential health risks. Therefore, a hybrid model combining the end-member mixing model tool on Excel™ (EMMTE) with human health risk assessment (HHRA) was developed to assess the source-oriented health risks for groundwater nitrate, particularly in the Poyang Lake Plain (PLP) region. The results indicated that the EMMTE and the Bayesian stable isotope mixing model (MixSIAR) exhibited remarkable consistency in source apportionment of groundwater nitrate. The source contribution of groundwater nitrate in PLP was related to land use types, hydrogeological conditions, and soil properties. Notably, manure and sewage sources, contributing up to 53.4 %, represented the largest nitrate pollution sources, with a significant contribution of soil nitrogen and nitrogen fertilizers. The non-carcinogenic risk for four potential sources was below the acceptable threshold of 1. Given the factors including rainfall dilution and economic development, attention should be directed towards mitigating the health risks posed by manure and sewage. This study can verify the efficacy of EMMTE in source apportionment and offer valuable insights for decision-makers to regulate the largest sources of nitrate contamination and enhance groundwater management efficiency.

Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater.

Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors. The results showed that at least 82.86 % of non-carcinogenic risks and 97.41 % of carcinogenic risks were unacceptable for people of all ages, especially infants and children. According to the relationships among HMs, pollution sources, and health risks, As and natural sources were defined as high-risk HMs and sources, respectively. The interactions among Holocene thickness, oxidation-reduction potential, and dissolved organic carbon emerged as the primary drivers of spatial variability in high-risk factors, with their combined explanatory power reaching up to 74%. This proposed framework provides a scientific reference for future studies and a practical reference for environmental authorities in developing effective pollution management measures.

A portable optical pulsatile flowmetry demonstrates strong clinical relevance for diabetic foot perfusion assessment.

We present a robust, cost-effective (<2000 USD), and portable optical diffuse speckle pulsatile flowmetry (DSPF) device with a flexible handheld probe for deep tissue blood flow measurement in the human foot as well as a first-in-man observational clinical study using the proposed optical device for tissue ischemia assessment and peripheral artery disease (PAD) diagnosis. Blood flow in tissue is inherently pulsatile in nature. However, most conventional methods cannot measure deep tissue-level pulsatile blood flow noninvasively. The proposed optical device can measure tissue-level pulsatile blood flow ∼6 mm underneath the skin surface. A new quantitative tissue perfusion index (TPIDSPF) based on frequency domain analysis of the pulsatile blood flow waveform is defined to assess tissue ischemia status. Through a clinical study involving 66 subjects, including healthy individuals and diabetes patients with and without PAD, TPIDSPF demonstrated strong correlations of 0.720 with transcutaneous tissue partial oxygen pressure (TcPO2) and 0.652 with toe-brachial index (TBI). Moreover, among the three methods, TPIDSPF demonstrated the highest area under the curve for PAD diagnosis among diabetes patients, with a notable value of 0.941. The promising clinical results suggest that the proposed optical method has the potential to be an effective clinical tool for identifying PAD among the diabetic cohort.

Distribution, bioavailability, and human health risk assessment of arsenic in groundwater-soil-rice system in the Jianghan Plain, Central China.

Many studies have reported high arsenic concentrations in the groundwater and soil of the Jianghan Plain (JHP), an important rice production base in China. However, no comprehensive study on the occurrence and risk of As in groundwater-soil-rice systems in this region has been conducted. In this study, As concentrations in groundwater, soil, rice straw, and rice grain samples were analyzed. Arsenic concentrations were found to range from BDL to 42.88 µg/L (median 0.34 µg/L) in phreatic water, BDL to 41.77 µg/L (median 8.64 µg/L) in soil pore water, 10.20 to 21.90 mg/kg (mean 16.52 mg/kg) in soil, 0.204 to 2.860 mg/kg (mean 0.847 mg/kg) in rice straw, and 0.131 to 0.951 mg/kg (mean 0.449 mg/kg) in rice grain. Arsenic uptake by rice from soils was evaluated according to bioavailable As defined by chemical extraction and diffusive gradients in thin films. The results indicated that owing to the low content of highly mobile As fractions, the less mobile As fraction (mainly bound with amorphous Fe/Al (hydr)oxides) also contributed to bioavailable As, suggesting that amorphous Fe/Al bound As should be considered in analyzing bioavailable As. In terms of the geoaccumulation index and the Chinese paddy soil standard (GB15618-2018) limit (25 mg/kg), As pollution in water and soils in the study area is at a low level and can be considered relatively safe. However, the target hazard quotients and cancer risk assessment indicated that As pollution is at a dangerous level with potential human health risk. According to the bioconcentration factor, the bioavailability of soil is higher in JHP compared with other rice-growing areas owing to the unique hydrogeological conditions and irrigation using groundwater with high As content. Rice planting areas in JHP should be set as far away from large rivers as possible, and groundwater with high As concentrations must be pre-treated prior to irrigation.

Predictors of phthalate metabolites in urine and follicular fluid and correlations between urine and follicular fluid phthalate metabolite concentrations among women undergoing in vitro fertilization.

BACKGROUND: Phthalate metabolites in follicular fluid (FF) may negatively affect normal folliculogenesis; however, the predictors of phthalate metabolite concentrations in urine and FF and relationships between urine and FF phthalate metabolite concentrations among women undergoing in vitro fertilization (IVF) are poorly understood. OBJECTIVE: To investigate predictors of phthalate metabolites in urine and FF and correlations between urine and FF phthalate metabolite concentrations among women undergoing IVF. METHOD: We recruited 305 women seeking infertility treatment at a reproductive center in Wuhan, China, from October to November 2016. Information regarding demographic characteristics, personal care product use and plastic material contact was obtained through direct interviews. Concentrations of 8 phthalate metabolites in urine and FF samples were measured using high-performance liquid chromatography and tandem mass spectrometry. Associations regarding metabolite concentrations in urine and FF samples were analysed by Spearman's correlation and linear regression. Generalized linear regression was used to examine potential predictors of phthalate metabolite concentrations in urine and FF. RESULTS: Weak to moderate associations between urine and FF samples were found for monoethyl phthalate (MEP) and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) (correlation coefficient: MEP, 0.350; MEOHP, 0.377); no associations were observed for other metabolites. The predictive powers of urinary metabolite concentrations in determining FF metabolite concentrations were uniformly low, with R2 ≤ 0.113. Body mass index (BMI) and educational level were inversely associated with the urinary concentrations of certain metabolites. Higher household income, intake of bottled drinks within 48 h, and use of shower gel and soap were frequently associated with higher urinary metabolite concentrations. BMI, higher household income and use of disposable plastic cups within 48 h were associated with higher metabolite concentrations in FF. CONCLUSION: Phthalate metabolite concentrations in urine and FF vary according to sociodemographic characteristics and lifestyle factors. Phthalate metabolite concentrations in urine may not be appropriate for estimating ovary phthalate exposure.