Drinking water aromaticity and treatability is predicted by dissolved organic matter fluorescence

Samples from fifty-five surface water resources and twenty-five drinking water treatment plants in Europe, Africa, Asia, and USA were used to analyse the fluorescence composition of global surface waters and predict aromaticity and treatability from fluorescence excitation emission matrices. Nine underlying fluorescence components were identified in the dataset using parallel factor analysis (PARAFAC) and differences in aromaticity and treatability could be predicted from ratios between components Hii (λex/λem= 395/521), Hiii (λex/λem= 330/404), Pi, (λex/λem=290/365) and Pii (λex/λem= 275/302). Component Hii tracked humic acids of primarily plant origin, Hiii tracked weathered/oxidised humics and the “building block” fraction measured by LC-OCD, while Pi and Pii tracked amino acids in the “low molecular weight neutrals” LC-OCD fraction. Ratios between PARAFAC components predicted DOC removal at lab scale for French rivers in standardized tests involving coagulation, powdered activated carbon (PAC), chlorination, ion exchange (IEX), and ozonation, alone and in combination. The ratio Hii/Hiii, for convenience named “PARIX” standing for “PARAFAC index”, predicted SUVA according to a simple relationship: SUVA = 4.0 x PARIX (RMSEp=0.55) Lmg−1m−1. These results expand the utility of fluorescence spectroscopy in water treatment applications, by demonstrating the existence of previously unknown relationships between fluorescence composition, aromaticity and treatability that appear to hold across diverse surface waters at various stages of drinking water treatment

Association between blood heavy metal exposure levels and risk of metabolic dysfunction associated fatty liver disease in adults: 2015–2020 NHANES large cross-sectional study

BackgroundThe relationships between heavy metals and fatty liver, especially the threshold values, have not been fully elucidated. The objective of this research was to further investigate the correlation between blood heavy metal exposures and the risk of Metabolic dysfunction Associated Fatty Liver Disease (MAFLD) in adults.MethodsLaboratory data on blood metal exposure levels were obtained from National Health and Nutrition Examination Survey (NHANES) data for the period 2015 to 2020 for a cross-sectional study in adults. Associations between blood levels of common heavy metals and the risk of MAFLD in adults were analyzed using multifactorial logistic regression and ranked for heavy metal importance using a random forest model. Finally, thresholds for important heavy metals were calculated using piecewise linear regression model.ResultsIn a multifactorial logistic regression model, we found that elevated levels of selenium (Se) and manganese (Mn) blood exposure were strongly associated with the risk of MAFLD in adults. The random forest model importance ranking also found that Se and Mn blood exposure levels were in the top two positions of importance for the risk of disease in adults. The restricted cubic spline suggested a non-linear relationship between Se and Mn blood exposure and adult risk of disease. The OR (95% CI) for MAFLD prevalence was 3.936 (2.631–5.887) for every 1 unit increase in Log Mn until serum Mn levels rose to the turning point (Log Mn = 1.10, Mn = 12.61 μg/L). This correlation was not significant (p > 0.05) after serum Mn levels rose to the turning point. A similar phenomenon was observed for serum Se levels, with a turning point of (Log Se = 2.30, Se = 199.55 μg/L).ConclusionBlood heavy metals, especially Se and Mn, are significantly associated with MAFLD in adults. They have a non-linear relationship with a clear threshold

Pre-pregnancy body mass index and glycated-hemoglobin with the risk of metabolic diseases in gestational diabetes: a prospective cohort study

BackgroundMetabolic diseases during pregnancy result in negative consequences for mothers. Pre-pregnancy body mass index (BMI) and late-pregnancy glycated-hemoglobin (HbA1c) are most important factors independently affecting the risk of gestational diabetes mellitus (GDM). However how both affect the combined risk of other metabolic diseases in women with GDM is unclear. The study aims to investigate the influence of pre-pregnancy BMI and pregnancy glycemic levels on other gestational metabolic diseases in women with GDM.MethodsPregnancies with GDM from January 2015 to December 2018 in the Xi’an longitudinal mother-child cohort study (XAMC) were retrospectively enrolled. Those without other metabolic diseases by the time of oral glucose tolerance test (OGTT) detection were finally recruited and divided into four groups by pre-pregnancy BMI (Underweight <18.5kg/m2; Normal weight 18.5-23.9 kg/m2; Overweight 24.0-27.9 kg/m2; Obesity ≥28.0 kg/m2, respectively) or two groups by HbA1c in late pregnancy (normal HbA1c<5.7%; high HbA1c≥5.7%). Multivariate logistic regression analysis was used to identify risk factors. Interaction between pre-pregnancy BMI (reference group 18.5-23.9 kg/m2) and HbA1c (reference group <5.7%) was determined using strata-specific analysis.ResultsA total of 8928 subjects with GDM were included, 16.2% of which had a composite of metabolic diseases. The pre-pregnancy overweight and obesity, compared with normal BMI, were linked to the elevated risk of the composite of metabolic diseases, particularly pre-eclampsia (both P <0.001) and gestational hypertension (both P <0.001). Meanwhile, patients with high HbA1c had an obvious higher risk of pre-eclampsia (P< 0.001) and gestational hypertension (P= 0.005) compared to those with normal HbA1c. In addition, there were significant interactions between pre-pregnancy BMI and HbA1c (P< 0.001). The OR of pre-pregnancy BMI≥ 28 kg/m2 and HbA1c≥ 5.7% was 4.46 (95% CI: 2.85, 6.99; P< 0.001). The risk of other metabolic diseases, except for pre-eclampsia (P= 0.003), was comparable between the two groups of patients with different HbA1c levels at normal pre-pregnancy BMI group. However, that was remarkably elevated in obese patients (P= 0.004), particularly the risk of gestational hypertension (P= 0.004).ConclusionPre-pregnancy overweight/obesity and late-pregnancy high HbA1c increased the risk of other gestational metabolic diseases of women with GDM. Monitoring and controlling late-pregnancy HbA1c was effective in reducing metabolic diseases, particularly in those who were overweight/obese before conception

Metabolic Syndrome Increases the Risk for Knee Osteoarthritis: A Meta-Analysis

Background. Studies revealed that metabolic factors might contribute substantially to osteoarthritis (OA) pathogenesis. There has been an increasing interest to understand the relationship between knee OA and the metabolic syndrome (MetS). The purpose of this study was to explore the association between metabolic syndrome and knee osteoarthritis using meta-analysis. Methods. Databases, including PUBMED, EMBASE, and the Cochrane Library, were searched to get relevant studies. Data were extracted separately by two authors and pooled odds ratio (OR) with 95% confidence interval (CI) was calculated. Results. The meta-analysis was finished with 8 studies with a total of 3202 cases and 20968 controls finally retrieved from the database search. The crude pooled OR is 2.24 (95% CI = 1.38–3.64). Although there was significant heterogeneity among these studies, which was largely accounted for by a single study, the increase in risk was still significant after exclusion of that study. The pooled adjusted OR remained significant with pooled adjusted OR 1.05 (95% CI = 1.03–1.07, p<0.00001). No publication bias was found in the present meta-analysis. Conclusions. The synthesis of available evidence supports that metabolic syndrome increases the risk for knee osteoarthritis, even after adjustment for many risk factors

pRb Inactivation in Mammary Cells Reveals Common Mechanisms for Tumor Initiation and Progression in Divergent Epithelia

Retinoblastoma 1 (pRb) and the related pocket proteins, retinoblastoma-like 1 (p107) and retinoblastoma-like 2 (p130) (pRb(f), collectively), play a pivotal role in regulating eukaryotic cell cycle progression, apoptosis, and terminal differentiation. While aberrations in the pRb-signaling pathway are common in human cancers, the consequence of pRb(f) loss in the mammary gland has not been directly assayed in vivo. We reported previously that inactivating these critical cell cycle regulators in divergent cell types, either brain epithelium or astrocytes, abrogates the cell cycle restriction point, leading to increased cell proliferation and apoptosis, and predisposing to cancer. Here we report that mouse mammary epithelium is similar in its requirements for pRb(f) function; Rb(f) inactivation by T(121), a fragment of SV40 T antigen that binds to and inactivates pRb(f) proteins, increases proliferation and apoptosis. Mammary adenocarcinomas form within 16 mo. Most apoptosis is regulated by p53, which has no impact on proliferation, and heterozygosity for a p53 null allele significantly shortens tumor latency. Most tumors in p53 heterozygous mice undergo loss of the wild-type p53 allele. We show that the mechanism of p53 loss of heterozygosity is not simply the consequence of Chromosome 11 aneuploidy and further that chromosomal instability subsequent to p53 loss is minimal. The mechanisms for pRb and p53 tumor suppression in the epithelia of two distinct tissues, mammary gland and brain, are indistinguishable. Further, this study has produced a highly penetrant breast cancer model based on aberrations commonly observed in the human disease

Transglutaminase 2 in human diseases

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