Geographic disparities and predictors of COVID-19 hospitalization risks in the St. Louis Area, Missouri (USA).

BACKGROUND: There is evidence of geographic disparities in COVID-19 hospitalization risks that, if identified, could guide control efforts. Therefore, the objective of this study was to investigate Zip Code Tabulation Area (ZCTA)-level geographic disparities and identify predictors of COVID-19 hospitalization risks in the St. Louis area. METHODS: Hospitalization data for COVID-19 and several chronic diseases were obtained from the Missouri Hospital Association. ZCTA-level data on socioeconomic and demographic factors were obtained from the American Community Survey. Geographic disparities in distribution of COVID-19 age-adjusted hospitalization risks, socioeconomic and demographic factors as well as chronic disease risks were investigated using choropleth maps. Predictors of ZCTA-level COVID-19 hospitalization risks were investigated using global negative binomial and local geographically weighted negative binomial models. RESULTS: COVID-19 hospitalization risks were significantly higher in ZCTAs with high diabetes hospitalization risks (p < 0.0001), COVID-19 risks (p < 0.0001), black population (p = 0.0416), and populations with some college education (p = 0.0005). The associations between COVID-19 hospitalization risks and the first three predictors varied by geographic location. CONCLUSIONS: There is evidence of geographic disparities in COVID-19 hospitalization risks that are driven by differences in socioeconomic, demographic and health-related factors. The impacts of these factors vary by geographical location implying that a 'one-size-fits-all' approach may not be appropriate for management and control. Using both global and local models leads to a better understanding of geographic disparities. These findings are useful for informing health planning to identify geographic areas likely to have high numbers of individuals needing hospitalization as well as guiding vaccination efforts.

Incidence, demographics, and outcomes of nonoperative management of appendicitis in the United States.

BACKGROUND: Appendicitis is the most common intraabdominal surgical emergency in the United States, with over 250,000 cases each year. Several recent studies have evaluated the efficacy of nonoperative management of appendicitis. We measured changes in the treatment of appendicitis in the United States from 1998 to 2014 and evaluated outcomes in the contemporary cohort of appendicitis cases from 2010 to 2014. METHODS: The National Inpatient Sample was queried for cases with a principal diagnosis of appendicitis. Cases with peritoneal abscesses were excluded. We determined trends in management and then compared cases managed nonoperatively versus those managed with early operation for demographics and outcomes including mortality, total charges, and length of stay using univariate analysis, binary logistic regression analysis, and case-control matching. RESULTS: Although early operation remains the dominant treatment for acute appendicitis in the United States, there is an accelerating trend in nonoperative management. Nonoperative management is associated with increased age, number of comorbidities, and inpatient diagnoses. In univariate, multiple regression, and case-control analysis, nonoperative management is associated with decreased total charges but significantly increased risk of mortality. CONCLUSIONS: Elderly patients and patients with medical comorbidities are more likely to be treated nonoperatively for appendicitis than younger patients. Although previously published data support nonoperative management of appendicitis in low-risk surgical patients, we suggest that elderly or medically complex patients may benefit from early operative treatment of appendicitis and are potentially at risk of poor outcomes from nonoperative management.

A Novel Approach to Assessing Professionalism in Preclinical Medical Students Using Multisource Feedback Through Paired Self- and Peer Evaluations.

Phenomenon: Professionalism is integral to the role of the physician. Most professionalism assessments in medical training are delayed until clinical rotations where multisource feedback is available. This leaves a gap in student assessment portfolios and potentially delays professional development. APPROACH: A total of 246 second-year medical students (2013-2015) completed self- and peer assessments of professional behaviors in 2 courses following a series of Team-Based Learning exercises. Correlation and regression analyses were used to examine the alignment or misalignment in the relationship between the 2 types of assessments. Four subgroups were formed based on observed patterns of initial self- and peer assessment alignment or misalignment, and subgroup membership stability over time was assessed. A missing data analysis examined differences between average peer assessment scores as a function of selective nonparticipation. FINDINGS: Spearman correlation demonstrated moderate to strong correlation between self-assessments completed alone (no simultaneous peer assessment) and self-assessments completed at the time of peer assessments (ρ = .59, p < .0001) but weak correlation between the two self-assessments and peer assessments (alone: ρ = .13, p < .013; at time of peer: ρ = .21, p < .0001). Generalized estimating equation models revealed that self-assessments done alone (p < .0001) were a significant predictor of self-assessments done at the time of peer. Course was also a significant predictor (p = .01) of self-assessment scores done at the time of peer. Peer assessment score was not a significant predictor. Bhapkar's test revealed subgroup membership based on the relationship between self- and peer ratings was relatively stable across Time 1 and Time 2 assessments (χ2 = 0.83, p = .84) for all but one subgroup; members of the subgroup with initially high self-assessment and low peer assessment were significantly more likely to move to a new classification at the second measurement. A missing data analysis revealed that students who completed all self-assessments had significantly higher average peer assessment ratings compared to students who completed one or no self-assessments with a difference of -0.32, 95% confidence interval [-0.48, -0.15]. Insights: Multiple measurements of simultaneous self- and peer assessment identified a subgroup of students who consistently rated themselves higher on professionalism attributes relative to the low ratings given by their peers. This subgroup of preclinical students, along with those who elected to not complete self-assessments, may be at risk for professionalism concerns. Use of this multisource feedback tool to measure perceptual stability of professionalism behaviors is a new approach that may assist with early identification of at-risk students during preclinical years.

Predicting cytotoxicity of complex mixtures in high cancer incidence regions of the Huai River Basin based on GC-MS spectrum with partial least squares regression.

Complex mixture exposures, such as those associated with water sources, are an important issue in health risk assessment. This study assessed the cytotoxicity of chemical mixtures extracted from water sources in regions of the Huai River Basin with high cancer incidences and built statistical models of cytotoxicity based on pollution profiles that were measured with gas chromatography-mass spectrometry (GC-MS). Both surface and ground waters were collected from rural water sources of Shenqiu County, Henan Province of China from 2008 to 2011 and extracted with XAD-2 resigns. Cytotoxicity was evaluated with Chinese hamster ovary K1 (CHO-K1) cells and compared against the pollution profiles of the extracts. IC50 of water samples ranged from 0.023 to 0.338L-eq/mL. The pollutants in waters determined by GC-MS are complex and some of the compounds that contributed to cytotoxicity lack toxicity data. A partial least squares (PLS) regression model of cytotoxicity was built based on linear aggregation of predictor variables (i.e., peaks for single compounds in the gas chromatograms). The PLS model contains 2 PLS factors extracted from 141 variables. The model was validated internally with training data permutation and externally with a test sample. The model explained 92% of the cytotoxicity in the training samples and 40% in the test sample. This approach provides a general, rapid method for relating water toxicity to GC-MS chromatograms and for predicting the compounds that contribute most to toxicity.

Real world treatment patterns, healthcare resource use and costs in patients with advanced or metastatic non-small cell lung cancer by EGFR mutation type.

AIMS: This study described treatment patterns, healthcare resource utilization (HRU) and costs among advanced or metastatic non-small cell lung cancer (a/mNSCLC) patients with different epidermal growth factor receptor (EGFR) mutation types. MATERIALS AND METHODS: This retrospective study leveraged NeoGenomics NeoNucleus linked with IQVIA PharMetrics Plus between 01 January 2016 to 30 April 2021 (study period). Patients with evidence of a/mNSCLC between 01 July 2016 to 31 March 2021 (selection window) with EGFR test results indicating exon 19 deletion (exon19del), exon 21 L858R (L858R), or exon 20 insertion (exon20i) mutations were included; date of first observed evidence of a/mNSCLC was the index date. Treatment patterns, all-cause HRU and costs during ≥1 month follow-up were reported for each cohort (exon19del, L858R, and exon20i). RESULTS: A total of 106 exon19del, 75 L858R, and 13 exon20i patients met the study criteria. The prevalence of hospitalization was highest in the exon20i cohort (76.9%), followed by L858R (62.7%) and exon19del (55.7%) cohorts. A higher proportion of patients had evidence of hospice/end-of-life care in the exon20i (30.8%) and L858R (29.3%) cohorts relative to the exon19del cohort (22.6%). The exon20i cohort had higher median total healthcare costs per patient per month ($27,069) relative to exon19del ($17,482) and L858R ($17,763). EGFR tyrosine kinase inhibitors (TKI) were the most frequently observed treatment type for exon19del and L858R cohorts, while chemotherapy was the most observed treatment in exon20i cohort. LIMITATIONS: The sample size for the study cohorts was small, thus no statistical comparisons were conducted. CONCLUSIONS: This is one of the first real-world studies to describe HRU and costs among a/mNSCLC patients by specific EGFR mutation type. HRU and costs varied between EGFR mutation types and were highest among exon20i cohort, potentially reflecting higher disease burden and unmet need among patients with this mutation.

Patients with non-small cell lung cancer (NSCLC) in an advanced or metastatic stage (a/mNSCLC) where cancer has spread to other parts of the body have high chance of dying within five years. Treatment and management of a/mNSCLC also incurs significant healthcare resource utilization (HRU) and costs. Patients with a/mNSCLC may have their epidermal growth factor receptor (EGFR) gene mutated with different variations. Our study described what a/mNSCLC patients were treated with, their HRU and healthcare costs separately for the following three types of EGFR mutations: exon 19 deletion (exon19del), exon 21 L858R (L858R), or exon 20 insertion (exon20i). Our study found that patients with exon19del or L858R mutation were commonly treated with EGFR tyrosine kinase inhibitors (TKIs), while exon20i patients were mostly treated with chemotherapy due to lack of targeted treatment for exon20i during the time when the study was conducted. HRU and healthcare costs were highest for patients with exon20i, which shows that patients with exon20i face high burden and have a need for new treatment options.

Excess healthcare resource utilization and costs for commercially insured patients with pulmonary arterial hypertension: A real-world data analysis.

This retrospective study was conducted to evaluate all-cause healthcare resource utilization (HCRU) and costs in commercially insured patients living with pulmonary arterial hypertension (PAH) and explore end-of-life (EOL)-related HCRU and costs. Data from the IQVIA PharMetrics® Plus database (October 2014 to May 2020) were analyzed to identify adults (≥18 years) with PAH (PAH cohort) and those without PH (non-PH cohort). Patients were required to have data for ≥12 months before (baseline) and ≥6 months after (follow-up) the first observed PH diagnosis (index date) for PAH cohort or pseudo index date for non-PH cohort. A PAH EOL cohort was similarly constructed using a broader data window (October 2014 to March 2022) and ≥1 month of follow-up. Annualized all-cause HCRU and costs during follow-up were compared between PAH and non-PH cohorts after 1:1 matching on propensity scores derived from patient characteristics. EOL-related HCRU and costs were explored within 30 days and 6 months before the death date and estimated by a claims-based algorithm in PAH EOL cohort. The annual all-cause total ($183,616 vs. $20,212) and pharmacy ($115,926 vs. $7862; both p < 0.001) costs were 8 and 14 times higher, respectively, in the PAH cohort versus matched non-PH cohort (N = 386 for each). In PAH EOL cohort (N = 28), the mean EOL-related costs were $48,846 and $167,524 per patient within 30 days and 6 months before the estimated death, respectively. Hospitalizations contributed 58.8%-70.8% of the EOL-related costs. The study findings indicate substantial HCRU and costs for PAH. While pharmacy costs were one of the major sources, hospitalization was the primary driver for EOL-related costs.

Combined exposure to 3-chloro-4-dichloromethyl-5-hydroxy-2(5H)-furanone and microsytin-LR increases genotoxicity in Chinese hamster ovary cells through oxidative stress.

The disinfection byproducts 3-chloro-4-dichloromethyl-5-hydroxy-2(5H)-furanone (MX) and microcystins-LR (MC-LR), which are common contaminants in drinking water, often occur together in water sources in areas with high gastrointestinal tract cancer risks. While often studied alone, combination effects of these compounds are unknown. Here, we examine combined genotoxic responses to mixtures of MX and MC-LR using the Ames test, a cytokinesis-block micronuclei assay, and the comet assay with analysis for interactions by fractional analysis. We also evaluated a possible mechanism of genotoxicity by examining effects of the compounds on markers of oxidative stress. MX and MC-LR administrated jointly at noncytotoxic concentrations demonstrated significant interactions in the Ames test, the micronuclei assay, and the comet assay showing responses greater than those expected for additivity. Moreover, coexposure to MX and MC-LR significantly increased luciferase antioxidant response element activity, intracellular superoxide dismutase, catalase, glutathione, and reactive oxygen species production. In comparison with exposure to either compound alone, the mixtures of MX and MC-LR caused a less than additive effect on oxidative stress. Taken together, these results indicate that MC-LR exacerbates MX genotoxicity in low-dose combined exposure. This interaction may be enhanced by oxidative stress in the combined exposures.

Pollution trees: identifying similarities among complex pollutant mixtures in water and correlating them to mutagenicity.

There are relatively few tools available for computing and visualizing similarities among complex mixtures and in correlating the chemical composition clusters with toxicological clusters of mixtures. Using the "intersection and union ratio (IUR)" and other traditional distance matrices on contaminant profiles of 33 specific water samples, we used "pollution trees" to compare these mixtures. The "pollution trees" constructed by neighbor-joining (NJ), maximum parsimony (MP), and maximum likelihood (ML) methods allowed comparison of similarities among these samples. The mutagenicity of each sample was then mapped to the "pollution tree". The IUR-distance-based measure proved effective in comparing chemical composition and compound level differences between mixtures. We found a robust "pollution tree" containing seven major lineages with certain broad characteristics: treated municipal water samples were different from raw water samples and untreated rural drinking water samples were similar with local water sources. The IUR-distance-based tree was more highly correlated to mutagenicity than were other distance matrices, i.e., MP/ML methods, sampling group, region, or water type. IUR-distance-based "pollution trees" may become important tools for identifying similarities among real mixtures and examining chemical composition clusters in a toxicological context.

Change of water consumption and its potential influential factors in Shanghai: a cross-sectional study.

BACKGROUND: Different water choices affect access to drinking water with different quality. Previous studies suggested social-economic status may affect the choice of domestic drinking water. The aim of this study is to investigate whether recent social economic changes in China affect residents' drinking water choices. METHODS: We conducted a cross-sectional survey to investigate residents' water consumption behaviour in 2011. Gender, age, education, personal income, housing condition, risk perception and personal preference of a certain type of water were selected as potential influential factors. Univariate and backward stepwise logistic regression analyses were performed to analyse the relation between these factors and different drinking water choices. Basic information was compared with that of a historical survey in the same place in 2001. Self-reported drinking-water-related diarrhoea was found correlated with different water choices and water hygiene treatment using chi-square test. RESULTS: The percentage of tap water consumption remained relatively stable and a preferred choice, with 58.99% in 2001 and 58.25% in 2011. The percentage of bottled/barrelled water consumption was 36.86% in 2001 and decreased to 25.75% in 2011. That of household filtrated water was 4.15% in 2001 and increased to 16.00% in 2011. Logistic regression model showed strong correlation between one's health belief and drinking water choices (P < 0.001). Age, personal income, education, housing condition, risk perception also played important roles (P < 0.05) in the models. Drinking-water-related diarrhoea was found in all types of water and improper water hygiene behaviours still existed among residents. CONCLUSIONS: Personal health belief, housing condition, age, personal income, education, taste and if worm ever founded in tap water affected domestic drinking water choices in Shanghai.

Thyroid-disrupting effects caused by exposure to alternative flame retardants from groundwater contamination in rural central China.

Accumulating evidence reveals that exposure to alternative flame retardants (AFRs) results in defective thyroid functions. AFRs are detectable in various environmental media in developed cities in China. However, few studies have reported the contamination levels of AFR in groundwater in rural areas, indicating an urgent need to investigate exposure of AFRs and perform health risk assessment for populations that use groundwater as the main source of drinking water. This study investigated the concentrations of AFRs in groundwater in rural areas of central China. Moreover, Nthy-ori-3-1 cells were used to determine the thyroid cytotoxicities and thyroid-interfering effects of a single AFR as well as the mixtures of AFRs based on the AFR contamination levels in real-world. The results revealed that all classes of AFRs were detectable in rural areas in central China. Dechlorane plus, hexabromocyclododecane, bromophenols (BPs), novel brominated flame retardants (NBFRs) and organophosphate flame retardants (OPFRs) exhibited spatial contamination patterns, with an average concentrations (median) of 157.89 ± 88.61 (185.47) pg/L, 0.09 ± 0.29 (not detectable) ng/L, 5.20 ± 5.92 (3.43) ng/L, 3338.11 ± 3758.78 (2836.72) pg/L, and 79.35 ± 97.19 (53.62) ng/L, respectively. The half maximal effective concentrations (EC50) of BPs, OPFRs, and NBFRs ranged 98.4-4012 µM, 42.0-2506 µM, and 10.1-203.7 µM, respectively. Several AFRs exhibited more cytotoxic effects than did traditional brominated flame retardants. It is intriguing that several single AFRs and mixtures at environmentally-relevant exposure levels promoted the viability of Nthy-ori-3-1 cells. Taken together, our study demonstrates that AFRs are present in the groundwater in rural areas in central China and AFRs exhibit thyroid disrupting effects.

Path Analysis Reveals the Direct Effect of PCB28 Exposure on Cognitive Dysfunction in Older Chinese Females.

Background: Research indicates that exposure to polychlorinated biphenyls (PCBs) can cause neurobehavioral impairments in neonates and adults, but the way specific PCBs' congeners impact cognition functions at a low exposure level in a real-life co-exposure system remains poorly understood. This study aimed to investigate the association of PCBs burden with cognition function among elderly adults. Methods: Based on the Weitang Geriatric Diseases study (2014−2015), the current study measured the plasma concentrations of six indicator-PCBs by GC-MS/MS and assessed the cognitive dysfunction (CoD) via an Abbreviated Mental Test in 266 participants (ages 61−90). Sequential logistic regression was used to analyze the effects of PCBs on cognition functions. Female participants aged less than or equal to 80 years were selected, and path analysis was used to determine the direct or indirect impacts of co-exposure PCBs on CoD by structural equation modeling. Results: After sequential adjustments to potential confounding factors and correction by the Bonferroni, no statistically significant correlation between PCBs exposure and CoD was found in participants (p > 0.05). However, in the co-exposure system, after controlling for co-exposures and confounders, exposure to PCB28 had a direct effect on CoD in females aged between 61 and 80, with a factor load of 0.670. Conclusions: After adjusting for the co-exposures and confounders, exposure to PCB28 can directly increase the risk of cognitive impairment in older Chinese females.

[Eutrophication of water bodies and pollutions of microcystins in water and sediments in X County in the Huai River Basin].

OBJECTIVE: The purpose of the study is to investigate the status of eutrophication, the polluted situation of algae and microcystins in different water bodies of X County in the Huai River Basin. METHOD: Superficial water and sediment samples were taken from S River, Y River and a representative ditch in May 2010 (median-water period) and August (high water period ). Chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), chlorophyll a (Chl a) and algal density were detected by the recommended methods of national standard microcystin-LF/LR/LW/RR/YR in water (dissolved form), algal cells and sediments were detected by solid phase extraction and HPLC. RESULTS: Water pollutions in rivers and ditches of X County were serious, and total nitrogen and total phosphorus significantly exceed to the national standard for surface water quality. Most indexes of the water quality ranged from grade III to worse than grade V of national standard. Total nitrogen (4.78 mg/L) was most serious pollutions in the mainstream of S river, the water quality in high water period was better than in median-water period (P < 0.05). However, water quality in inner river Y and ditch in high water period was worse than in median-water period. Maximum chlorophyll a in ditch water reached 648.4 mg/ m3. The percent of cyanobacteria in various water bodies was less than 10% in median-water period, increased sharply to 40% and became dominant species in high water period. The maximum percentage of cyanobacteria was 44% in ditch. Microcystin-RR was the main toxin detected in water (dissolved form), algal cells and sediments. Maximum MC-RR in water and sediments reached 17.731 microg/L and 0.802 microg/g, respectively. The detected frequencies and concentrations of MC-LF/LR/LW/YR in most samples were low. CONCLUSION: Water bodies in X County were between middle eutrophication and hyper-eutrophication. Microcystin-RR of sediments in high water period were significant higher than in median-water period (P < 0.05).

Disrupted and Restored Patient Experience With Transition to New Electronic Health Record System.

Transitioning from one electronic health record (EHR) system to another is of the most disruptive events in health care and research about its impact on patient experience for inpatient is limited. This study aimed to assess the impact of transitioning EHR on patient experience measured by the Hospital Consumer Assessment of Healthcare Providers and Systems composites and global items. An interrupted time series study was conducted to evaluate quarter-specific changes in patient experience following implementation of a new EHR at a Midwest health care system during 2017 to 2018. First quarter post-implementation was associated with statistically significant decreases in Communication with Nurses (-1.82; 95% CI, -3.22 to -0.43; P = .0101), Responsiveness of Hospital Staff (-2.73; 95% CI, -4.90 to -0.57; P = .0131), Care Transition (-2.01; 95% CI, -3.96 to -0.07; P = .0426), and Recommend the Hospital (-2.42; 95% CI, -4.36 to -0.49; P = .0142). No statistically significant changes were observed in the transition, second, or third quarters post-implementation. Patient experience scores returned to baseline level after two quarters and the impact from EHR transition appeared to be temporary.

Quantifying the Impacts of Pre- and Post-Conception TSH Levels on Birth Outcomes: An Examination of Different Machine Learning Models.

Background: While previous studies identified risk factors for diverse pregnancy outcomes, traditional statistical methods had limited ability to quantify their impacts on birth outcomes precisely. We aimed to use a novel approach that applied different machine learning models to not only predict birth outcomes but systematically quantify the impacts of pre- and post-conception serum thyroid-stimulating hormone (TSH) levels and other predictive characteristics on birth outcomes. Methods: We used data from women who gave birth in Shanghai First Maternal and Infant Hospital from 2014 to 2015. We included 14,110 women with the measurement of preconception TSH in the first analysis and 3,428 out of 14,110 women with both pre- and post-conception TSH measurement in the second analysis. Synthetic Minority Over-sampling Technique (SMOTE) was applied to adjust the imbalance of outcomes. We randomly split (7:3) the data into a training set and a test set in both analyses. We compared Area Under Curve (AUC) for dichotomous outcomes and macro F1 score for categorical outcomes among four machine learning models, including logistic model, random forest model, XGBoost model, and multilayer neural network models to assess model performance. The model with the highest AUC or macro F1 score was used to quantify the importance of predictive features for adverse birth outcomes with the loss function algorithm. Results: The XGBoost model provided prominent advantages in terms of improved performance and prediction of polytomous variables. Predictive models with abnormal preconception TSH or not-well-controlled TSH, a novel indicator with pre- and post-conception TSH levels combined, provided the similar robust prediction for birth outcomes. The highest AUC of 98.7% happened in XGBoost model for predicting low Apgar score with not-well-controlled TSH adjusted. By loss function algorithm, we found that not-well-controlled TSH ranked 4th, 6th, and 7th among 14 features, respectively, in predicting birthweight, induction, and preterm birth, and 3rd among 19 features in predicting low Apgar score. Conclusions: Our four machine learning models offered valid predictions of birth outcomes in women during pre- and post-conception. The predictive features panel suggested the combined TSH indicator (not-well-controlled TSH) could be a potentially competitive biomarker to predict adverse birth outcomes.

Triage Modeling for Differential Diagnosis Between COVID-19 and Human Influenza A Pneumonia: Classification and Regression Tree Analysis.

Background: The coronavirus disease 2019 (COVID-19) pandemic has lasted much longer than an influenza season, but the main signs, symptoms, and some imaging findings are similar in COVID-19 and influenza patients. The aim of the current study was to construct an accurate and robust model for initial screening and differential diagnosis of COVID-19 and influenza A. Methods: All patients in the study were diagnosed at Fuyang No. 2 People's Hospital, and they included 151 with COVID-19 and 155 with influenza A. The patients were randomly assigned to training set or a testing set at a 4:1 ratio. Predictor variables were selected based on importance, assessed by random forest algorithms, and analyzed to develop classification and regression tree models. Results: In the optimal model A, the best single predictor of COVID-19 patients was a normal or high level of low-density lipoprotein cholesterol, followed by low level of creatine kinase, then the presence of <3 respiratory symptoms, then a highest temperature on the first day of admission <38°C. In the suboptimal model B, the best single predictor of COVID-19 was a low eosinophil count, then a normal monocyte ratio, then a normal hematocrit value, then a highest temperature on the first day of admission of <37°C, then a complete lack of respiratory symptoms. Conclusions: The two models provide clinicians with a rapid triage tool. The optimal model can be used to developed countries/regions and major hospitals, and the suboptimal model can be used in underdeveloped regions and small hospitals.

[Formation and changes of regulated trihalomethanes and haloacetic acids in raw water of Yangtze River, Huangpu River and different treatment processes and pipelines network].

OBJECTIVES: To investigate the pollutant levels of regulated disinfection by-products trihalomethanes (THMs) and haloacetic acids (HAAs) in raw water from the Huangpu River, the Yangtze River and different treatment processes and finished water, and to explore the changes tendency in transmission and distribution pipeline network. METHODS: A total of 65 ml water samples with two replicates were collected from different raw water, corresponding treatment processes, finished water and six national surveillance points in main network of transmission and distribution, water source for A water plant and B, C water plant was the Huangpu River and the Yangtze River, respectively. Regulated THMs and HAAs above water samples were detected by gas chromatography. RESULTS: The total trihalomethanes (THM(4)) concentration in different treatment processes of A water plant was ND-9.64 µg/L, dichlorobromomethane was the highest (6.43 µg/L). The THM(4) concentration in B and C water plant was ND to 38.06 µg/L, dibromochloromethane (12.24 µg/L) and bromoform (14.07 µg/L) were the highest in the B and the C water plant respectively. In addition to trichloroacetic acid in A water plant from the raw water, the other HAAs came from different treatment processes. The total haloacetic acids (HAA(6)) concentration of different treated processes in A water plant was 3.21 - 22.97 µg/L, mobromoacetic acid (10.40 µg/L) was the highest. Dibromoacetic acid was the highest both in B (8.25 µg/L) and C (8.84 µg/L) water plant, HAA(6) concentration was ND to 27.18 µg/L. The highest and the lowest concentration of THM(4) were found from the main distribution network of C and A water plant respectively, but the concentration of HAA(6) in the main water pipes network of A water plant was the highest, and the lowest in C water plant. The THMs concentration was 21.11 - 31.18 µg/L in C water plant and 6.72 - 8.51 µg/L in A water plant. The concentration of HAA(6) was 25.02 - 37.31 µg/L in A water plant and 18.69 - 23.32 µg/L in C water plant. The highest concentrations of brominated disinfection by-products in B and C water plant were 54.57 µg/L and 45.38 µg/L respectively, those were higher than A water plant (18.98 µg/L), and higher than the chlorinated disinfection by-products in B and C water plants (30.23 µg/L and 30.60 µg/L). CONCLUSIONS: The THM(4) concentrations of finished water treated from Huangpu River was lower than finished water from the Yangtze River, while the HAAs concentrations in finish water from Huangpu River was higher than the two water plants of Yangtze River. The fluctuations of THMs and HAAs concentration in distribution network were low during transmission and distribution process.

[Determination of several herbicides, fungicides and estrogens in water from various treatment processes of different water plants in Shanghai by solid phase extraction-gas chromatography/mass spectrometry].

OBJECTIVE: To establish the solid phase extraction-gas chromatography/mass spectrometry (GC/MS) method for qualitative and quantitative determination of several herbicides, fungicides and estrogens in drinking water. METHODS: Duplicate 1 L water samples were collected from various treatment processes of different water plants. Target pollutants were extracted by XAD-2 resin from water samples and were eluted by 30% acetone-methanol. GC/MS was employed for qualitative and quantitative analysis of target pollutants. RESULTS: The linear ranges of standard curves of 6 target compounds including atrazine, alachlor, 4-cumyphenol, thiabendazole, ß-estradiol and ethylestradiol were 0.1 - 10 µg/ml and the R(2) values were 0.9915 - 0.9995. The detection limits, the recovery rates, and the relative standard deviation (RSD) were separately 0.01 - 0.40 µg/L, 74.0% - 112.0% and 2.3% - 14.8%. Atrazine (0.11 - 0.13 µg/L), 4-cumyphenol (0.20 - 0.35 µg/L), thiabendazole (0.92 - 1.46 µg/L), ß-estradiol (1.02 - 1.32 µg/L) and ethylestradiol (0.96 - 1.66 µg/L)were all detected in raw water, post-coagulation water, post-sedimentation water and finished water using Huangpu River as water source. Alachlor was not detected in any water samples in Huangpu River. The 6 target compounds were not detected in any water samples from the water plants using Yangtse River as water source. CONCLUSION: The methods with high sensitivity and satisfying selectivity are suitable to simultaneously qualitative and quantitative determination of target pollutants in drinking water. Concentrations of above-mentioned pollutants in drinking water coming from Huangpu River are obviously higher than in drinking water coming from Yangtze River. Thiabendazole, ß-estradiol and ethylestradiol at the level of µg/L exist in drinking water coming from Huangpu River and more attention should be paid to surveillance of future.

[Study on in vitro isolation and culture method of neural stem cells from fetal rat neocortex].

OBJECTIVE: To establish method for isolation and culture of neural stem cells from fetal rat neocortex in vitro. METHODS: Neocortexes of fetal SD rats were isolated on gestational day 14. Mechanical triturations were used to improve cell dissociation status and conditions of serum-free media were optimized. Three test methods including neural stem cell marker protein (nestin and SOX2), proliferation and clonogenic ability and the multilineage differentiation potential were employed to identify neural stem cells. RESULTS: Nestin of cells cultured with this method was expressed with strong positive, and more than 99% cells were SOX2-positive. BrdU was incorporated into the cells, and the amounts of the cells were 10.55 times as much as the initial cell number after 3 days of culture. The ratios of clonal neurosphere were (33.00 +/- 4.40)% after 6 days of culture. Staining with specific protein markers in the corresponding cells confirmed that neural stem cells could form neurons (MAP2), astrocytes (GFAP) and oligodendrocytes (O4) after differentiation induction. CONCLUSION: Neural stem cells obtained with this method had high purity and cell output, potent self-renewal and multi-lineage differentiation ability, which will provide a good model for toxicological research.

Support vector machine: classifying and predicting mutagenicity of complex mixtures based on pollution profiles.

Powerful, robust in silico approaches offer great promise for classifying and predicting biological effects of complex mixtures and for identifying the constituents of greatest concern. Support vector machine (SVM) methods can deal with high dimensional data and small sample size and examine multiple interrelationships among samples. In this work, we applied SVM methods to examine pollution profiles and mutagenicity of 60 water samples obtained from 6 cities in China during 2006-2011. Pollutant profiles were characterized in water extracts by gas chromatography-mass spectrometry (GC/MS) and mutagenicity examined by Ames assays. We encoded feature vectors of GS-MS peaks in the mixtures and used 48 samples as the training set, reserving 12 samples as the test set. The SVM model and regression were constructed from whole pollution profiles that ranked compounds in relation to their correlation to the mutagenicity. Both classification and prediction performance were evaluated. The SVM model based on whole pollution profiles showed lower performance (sensitivity, specificity, accuracy and correlation coefficient were 69.5-70.7%, 70.6-73.2%, 69.9-72.1%, and 0.55-0.59%, respectively) than one based on compounds with highest association with mutagenicity. A SVM model with the top 10 compounds had the highest performance (sensitivity, specificity, accuracy, and correlation coefficient were 89.8-90.3%, 90.1-92.1%, 90.1-91.3%, and 0.80-0.82%, respectively), with negligible decreases in performance between the test and training set. SVM can be a powerful, robust classifier of the relationship of pollutants and mutagenicity in complex real-world mixtures. The top 14 compounds have the greatest contribution to mutagenicity and deserve further studies to identify these constituents.

Water pollutant fingerprinting tracks recent industrial transfer from coastal to inland China: a case study.

In recent years, China's developed regions have transferred industries to undeveloped regions. Large numbers of unlicensed or unregistered enterprises are widespread in these undeveloped regions and they are subject to minimal regulation. Current methods for tracing industrial transfers in these areas, based on enterprise registration information or economic surveys, do not work. We have developed an analytical framework combining water fingerprinting and evolutionary analysis to trace the pollution transfer features between water sources. We collected samples in Eastern China (industrial export) and Central China (industrial acceptance) separately from two water systems. Based on the water pollutant fingerprints and evolutionary trees, we traced the pollution transfer associated with industrial transfer between the two areas. The results are consistent with four episodes of industrial transfers over the past decade. Our results also show likely types of the transferred industries - electronics, plastics, and biomedicines - that contribute to the water pollution transfer.