OBJECTIVE Subtypes of gestational diabetes mellitus (GDM) based on insulin sensitivity and secretion have been described. We addressed the hypothesis that GDM subtypes are differentially associated with newborn and child anthropometric and glycemic outcomes. RESEARCH DESIGN AND METHODS Newborn and child (age 11–14 years) outcomes were examined in 7,970 and 4,160 mother-offspring dyads, respectively, who participated in the Hyperglycemia and Adverse Pregnancy Outcome Study (HAPO) and Follow-Up Study. GDM was classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity), insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion), or mixed-defect GDM (both <25th percentile). Regression models for newborn and child outcomes included adjustment for field center, maternal BMI, and other pregnancy covariates. Child models also included adjustment for child age, sex, and family history of diabetes. RESULTS Compared with mothers with normal glucose tolerance, all three GDM subtypes were associated with birth weight and sum of skinfolds >90th percentile. Insulin-resistant and mixed-defect GDM were associated with higher risk of cord C-peptide levels >90th percentile. Insulin-resistant GDM was associated with higher risk of neonatal hypoglycemia. Insulin-resistant GDM was associated with higher risk of neonatal hypoglycemia and childhood obesity (odds ratio [OR] 1.53, 95% CI 1.127–2.08). The risk of child-impaired glucose tolerance was higher with insulin-resistant (OR 2.21, 95% CI 1.50–3.25) and mixed-defect GDM (OR 3.01, 95% CI 1.47–6.19). CONCLUSIONS GDM subtypes are differentially associated with newborn and childhood outcomes. Better characterizing individuals with GDM could help identify at-risk offspring to offer targeted, preventative interventions early in life.
The optimal conditions of flavonoids extraction from chestnut were studied. The effects of five factors including alcohol content,extraction period,extraction time,temperature,and the ratio of raw materials and solution on extraction amount were investigated. The best technical conditions for flavonoids extraction were obtained through orthogonal experiments based on single factor as following: extracting with 60 % alcohol,temperature at 70 ℃ extracting 30 min,ration of raw materials and solution was 1:9. Under the optimized condition,the extraction amount of flavonoids from chestnut was 137.7 mg/g.
The effects of Folin volume, the ration of Folin and 10% Na2CO3, operation time on determining the polyphenols content and the alcohol concentration, extraction time, the ratio of raw materials and solution, temperature and extraction period on extracting the polyphenols from the chestnut were investigated. The best conditions for polyphenol determination were 0.5 mL Folin, 1.5 mL 10% Na2CO3 and operation at 20~25 ℃. The best technical conditions for chestnut polyphenol extraction were obtained through orthogonal experiments as follows: ratio of raw material and solution of 1∶10, temperature at 35 ℃, 50% alcohol and extraction time of 25 min. Under the optimized condition, the extraction amount of polyphenols from chestnut was 2.45%.
<p dir="ltr">OBJECTIVE Subtypes of gestational diabetes (GDM) based on insulin sensitivity and secretion have been described. We addressed the hypothesis that GDM subtypes are differentially associated with newborn and child anthropometric and glycemic outcomes. RESEARCH DESIGN AND METHODS Newborn and child (age 11-14 yrs) outcomes were examined in 7970 and 4160 mother-offspring dyads, respectively, who participated in the Hyperglycemia and Adverse Pregnancy Outcome Study (HAPO) and Follow-Up Study. GDM was classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity), insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion) or mixed-defect GDM (both <25th percentile). Regression models for newborn and child outcomes included adjustment for field center, maternal BMI and other pregnancy covariates. Child models also included adjustment for child age, sex, and family history of diabetes. RESULTS Compared to mothers with normal glucose tolerance, all three GDM subtypes were associated with birthweight and sum of skinfolds >90th percentile. Insulin-resistant and mixed-defect GDM were associated with higher risk of cord C-peptide levels >90th percentile; insulin-resistant GDM was associated with higher risk of neonatal hypoglycemia. Insulin-resistant GDM was associated with higher risk of childhood obesity (OR=1.53, CI=1.127-2.08). Insulin-resistant and mixed-defect GDM were associated with higher risk of child impaired glucose tolerance (OR=2.21, CI=1.50-3.25 and OR=3.01, 1.47-6.19, respectively). CONCLUSIONS GDM subtypes are differentially associated with newborn and childhood outcomes. Better characterizing individuals with GDM could help identify at-risk offspring to offer targeted, preventative interventions early in life.</p>
Water-insoluble β-(1−3)-d-glucan isolated from the sclerotium of Poria cocos hardly exhibits biological activity. Therefore, it is advantageous to produce a value-added product from P. cocos. We extracted the β-(1−3)-d-glucan from the sclerotium of P. cocos and synthesized a carboxymethylated derivative. The structural and physiological properties of the derivative were investigated. The carboxymethylation of the polysaccharides was confirmed by Fourier transform infrared spectroscopy, and the degree of substitution (DS) and molecular weight were obtained by the potentiometric titration and gel permeation chromatography (GPC) analysis, respectively. The carboxymethylation caused the enhancement of in vitro bile acid binding capacity of the polysaccharides, which would be explained by the improved water solubility and structural changes caused by carboxymethylation. In addition, in vitro antiradical capacity of the derivative was observed by the method of 2,2-diphenyl-1-picrylhydrazyl (DPPH).
Abstract Background Around the world, there is a high incidence of gastric ulcers. YS, an extract from the Chinese herb Albizzia chinensis (Osbeck) Merr, has potential therapeutic applications for gastrointestinal diseases. Here we elucidated the protective effect and underlying mechanism of action of YS on gastric ulcer in rats injured by ethanol. Methods The ethanol‐induced gastric ulcer rat model was used to assess the protective effect of YS. A pathological examination of gastric tissue was performed by H&E staining. GES‐1 cells damaged by hydrogen peroxide were used to simulate oxidative damage in gastric mucosal epithelial cells. Endogenous NRF2 was knocked down using small interfering RNA. Immunoprecipitation was used to detect ubiquitination of NRF2. Co‐immunoprecipitation was used to detect the NRF2–Keap1 interaction. Results YS (10 and 30 mg/kg, i.g.) significantly reduced the ulcer index, decreased MDA level, and increased SOD and GSH levels in gastric tissues damaged by ethanol. YS promoted NRF2 translocation from cytoplasm to nucleus and enhanced the NQO1 and HO‐1 expression levels in injured rat gastric tissue. In addition, YS regulated NQO1 and HO‐1 via NRF2 in H 2 O 2 ‐induced oxidative injured GES‐1 cells. Further studies on the underlying mechanism indicated that YS reduced the interaction between NRF2 and Keap1 and decreased ubiquitylation of NRF2, thereby increasing its stability and expression of downstream factors. NRF2 knockdown abolished the effect of YS on MDA and SOD in GES‐1 cells treated with H 2 O 2 . Conclusion YS reduced the NRF2–Keap1 interaction, promoting NRF2 translocation into the nucleus, which increasing the transcription and translation of NQO1 and HO‐1 and improved the antioxidant capacity of rat stomach.
Background: Continuous glucose monitors (CGMs) in research and clinical settings characterize glycemic profiles through repeated measurement of interstitial glucose levels on the order of minutes. Missing values from devices are unavoidable. Data from the Glycemic Observation and Metabolic Outcomes in Mothers and Offspring (GO MOMs) study were used to investigate the impact of missing data on CGM summary metrics. Several imputation techniques were evaluated by comparing mean relative bias (MRB) between true and imputed CGM data for the summary metrics. Methods: We used 105 CGM profiles with nine days of complete glucose measurements and introduced missing data strings using a zero-inflated negative binomial hurdle model. Overall missingness was introduced at 2% consistent with GO MOMs data and increased to 5%, 10%, and 20%. Imputation approaches included single, multiple, machine learning techniques, and hot-deck imputation, where missing values are replaced with the participant’s observed values. Removing missing values prior to analysis (complete case analysis) was also evaluated. Results: The MRB is minimal across most metrics and imputation methods at overall 2% missing data and increases with higher missing data frequency, with trends depending on metric and imputation method. Hot-deck imputation and complete case analysis show consistently low MRB. Conclusions: Missing CGM data are to be expected. For periods of wear with up to 20% missing data, hot-deck imputation and complete case analysis may be acceptable if data are missing completely at random. Explored imputation techniques are robust, but each has their own limitations, which should be considered if these techniques are implemented.
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by unexplained physical fatigue, cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. People with ME/CFS often report a prodrome consistent with infections. Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of plasma from 106 ME/CFS cases and 91 frequency-matched healthy controls. Subjects in the ME/CFS group had significantly decreased levels of plasmalogens and phospholipid ethers (p < 0.001), phosphatidylcholines (p < 0.001) and sphingomyelins (p < 0.001), and elevated levels of dicarboxylic acids (p = 0.013). Using machine learning algorithms, we were able to differentiate ME/CFS or subgroups of ME/CFS from controls with area under the receiver operating characteristic curve (AUC) values up to 0.873. Our findings provide the first metabolomic evidence of peroxisomal dysfunction, and are consistent with dysregulation of lipid remodeling and the tricarboxylic acid cycle. These findings, if validated in other cohorts, could provide new insights into the pathogenesis of ME/CFS and highlight the potential use of the plasma metabolome as a source of biomarkers for the disease.
BackgroundThe US Environmental Protection Agency (EPA) currently sets maximum contaminant levels (MCLs) for ten metals or metalloids in public drinking water systems. Our objective was to estimate metal concentrations in community water systems (CWSs) across the USA, to establish if sociodemographic or regional inequalities in the metal concentrations exist, and to identify patterns of concentrations for these metals as a mixture.MethodsWe evaluated routine compliance monitoring records for antimony, arsenic, barium, beryllium, cadmium, chromium, mercury, selenium, thallium, and uranium, collected from 2006–11 (2000–11 for uranium; timeframe based on compliance monitoring requirements) by the US EPA in support of their second and third Six-Year Reviews for CWSs. Arsenic, barium, chromium, selenium, and uranium (detectable in >10% records) were included in the main analyses (subgroup and metal mixture analyses; arsenic data reported previously). We compared the mean, 75th percentile, and 95th percentile contaminant concentrations and the percentage of CWSs with concentrations exceeding the MCL across subgroups (region, sociodemographic county-cluster, size of population served, source water type, and CWSs exclusively serving correctional facilities). We evaluated patterns in CWS metal concentration estimate profiles via hierarchical cluster analysis. We created an online interactive map and dashboard of estimated CWS metal concentrations for use in future analyses.FindingsAverage metal concentrations were available for a total of 37 915 CWSs across the USA. The total number of monitoring records available was approximately 297 000 for arsenic, 165 000 for barium, 167 000 for chromium, 165 000 for selenium, and 128 000 for uranium. The percentage of analysed CWSs with average concentrations exceeding the MCL was 2·6% for arsenic (MCL=10 μg/L; nationwide mean 1·77 μg/L; n=36 798 CWSs), 2·1% for uranium (MCL=30 μg/L; nationwide mean 4·37 μg/L; n=14 503 CWSs), and less than 0·1% for the other metals. The number of records with detections was highest for uranium (63·1%). 75th and 95th percentile concentrations for uranium, chromium, barium, and selenium were highest for CWSs serving Semi-Urban, Hispanic communities, CWSs reliant on groundwater, and CWSs in the Central Midwest. Hierarchical cluster analysis revealed two distinct clusters: an arsenic–uranium–selenium cluster and a barium–chromium cluster.InterpretationsUranium is an under-recognised contaminant in CWSs. Metal concentrations (including uranium) are elevated in CWSs serving Semi-Urban, Hispanic communities independent of location or region, highlighting environmental justice concerns.FundingUS National Institutes of Health Office of the Director, US National Institutes for Environmental Health Sciences, and US National Institute of Dental and Craniofacial Research.TranslationFor the Spanish translation of the abstract see Supplementary Materials section.
Background. Nephrotic syndrome is an enormous public healthy threaten, which causes a variety of complications and secondary disease; however, the molecular mechanism of nephrotic syndrome remains unclear. Methods. In our study, RNA-seq were used to test the transcription level of patients with nephrotic syndrome, in order to investigate the interaction of circRNA-miRNA-mRNA in nephrotic syndrome patients. Results. Consistent with our hypothesis, miRNAs were confirmed to be associated with nephrotic syndrome, majority of their targeting circRNAs downregulated in nephrotic syndrome patients and at the same time, the KEGG pathway analysis found that target genes of the circRNAs bonding miRNAs was highly correlated with the occurrence of kidney diseases. Conclusion. Thus, we can draw a conclusion that downregulated circRNAs cause miRNA expressing aberrant and then affect the expression level of mRNA, finally leading to the generation of nephrotic syndrome.
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