Additional file 1 of Statin use as a moderator on the association between metformin and breast cancer risk in women with type 2 diabetes mellitus

Supplementary Material

Discrimination of Alismatis Rhizoma based on chromatographic fingerprint, multiple components quantification, and pattern recognition analysis

<p>A simple, sensible, and reliable HPLC–DAD method was first developed for fingerprint analysis of Alismatis Rhizoma, and then applied to analyze 85 samples from three main cultivated areas. In all, 40 common fingerprint peaks were designated, and six of which were definitely identified. Then, the combinatory analysis using similarity evaluation, principal component analysis, and orthogonal partial least square discriminant analysis revealed clear chemical consistency between samples from Fujian and Jiangxi provinces and substantial differences between those from Fujian/Jiangxi and Sichuan provinces. Furthermore, six components were dug out as potential chemical markers for distinguishing Alismatis Rhizoma from different areas, among which five were qualified for quantitative analysis. In conclusion, the combination of chemical fingerprint, multiple components quantification, and pattern recognition analysis was rather powerful and useful in discriminating Alismatis Rhizoma from different regions, which was a benefit for quality control.</p

Evidence network of B vitamin interventions included in the network meta-analysis for efficacy.

<p>The size of the node corresponds to the number of randomized participants (sample size), and the width of the line corresponds to the number of trials comparing each pair of treatments.</p

Flow diagram of the network meta-analysis.

<p>Flow diagram of the network meta-analysis.</p

Efficacy of the 8 treatments for stroke in network meta-analysis (RR with 95% CrI).

<p>FA, folic acid; 95% CrI, 95% credible intervals; VB, vitamin B.</p><p>Efficacy of the 8 treatments for stroke in network meta-analysis (RR with 95% CrI).</p

Structurally Diverse Cytotoxic Dimeric Chalcones from <i>Oxytropis chiliophylla</i>

Ten isomeric cyclobutane- and cyclohexene-containing chalcone dimers, oxyfadichalcones A–G, were isolated from the aerial parts of <i>Oxytropis chiliophylla</i>. These included six new compounds and three pairs of enantiomers that are being reported from natural sources for the first time. The relative configurations were elucidated by spectroscopic data analysis, while the absolute configurations were determined by comparing the experimental and calculated electronic circular dichroism spectra. Quantitative LC-MS analysis of the main dimers from different parts of the plant revealed their characteristic accumulation in the viscous secretion and provided supporting evidence for the hypothesized photochemical biosynthesis. In addition, the cytotoxic activities of all isolates against the PC-3 human prostate cancer cell line are reported

Short Placental Telomere was Associated with Cadmium Pollution in an Electronic Waste Recycling Town in China

<div><p>In Guiyu, an electronic waste recycling site near Shantou, Guangdong province, China, primitive ways of e-waste processing have caused severe cadmium and lead pollution to the local residents. However, the possible effects of cadmium or lead pollution to genomic integrity of the local residents have not been investigated. We examined the possible relationship between cadmium and lead concentrations in placenta and placental telomere length in Guiyu and compared the data with that of a non-polluted town. Graphite furnace atomic absorption spectrometry and real-time PCR were used to determine placental cadmium and lead concentrations, and placental telomere length. We found that placental cadmium concentration was negatively correlated with placental telomere length (r = −0.138, p = 0.013). We also found that placental cadmium concentration of 0.0294 µg/g might be a critical point at which attrition of placental telomere commenced. No significant correlation between placental lead concentration and placental telomere length was detected (r = 0.027, p = 0.639). Our data suggest that exposure to cadmium pollution during pregnancy may be a risk factor for shortened placental telomere length that is known to be related to cancer development and aging. Furthermore, grave consequence on the offspring from pregnancies in e-waste polluted area is indicated.</p> </div

Developing a dengue forecast model using machine learning: A case study in China

<div><p>Background</p><p>In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue.</p><p>Methodology/Principal findings</p><p>Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011–2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China.</p><p>Conclusion and significance</p><p>The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics.</p></div

Data_Sheet_1_Prevalence of potentially inappropriate medications and association with comorbidities in older adults with diabetes in an outpatient visitation setting.docx

AimsPotentially inappropriate medications had been found associated with adverse drug events such as falls, emergency department admissions and hospital readmissions. There is lack of information about the prevalence of potentially inappropriate medications and associated chronic conditions in older patients with diabetes in China. This study aimed to assess the prevalence of potentially inappropriate medications in older adults with diabetes in an outpatient visitation setting and the association with polypharmacy due to comorbidities.Materials and methodsThis was a 3-year repeated cross-sectional study which conducted in outpatient setting of 52 hospitals in Shenzhen, China, using 2019 Beers criteria. The prevalence of potentially inappropriate medications, polypharmacy and comorbidities in older adults with diabetes in an outpatient setting was expressed as percentages. Logistic models were used to investigate the association between potentially inappropriate medication exposure and age, sex, polypharmacy and comorbidities.ResultsAmong the 28,484 older adults with diabetes in 2015, 31,757 in 2016 and 24,675 in 2017, the prevalence of potentially inappropriate medications was 43.2%, 44.88% and 42.40%, respectively. The top five potentially inappropriate medications were diuretics (20.56%), benzodiazepines (13.85%), androgens (13.18%), non-steroidal anti-inflammatory drugs (12.94%) and sulfonylureas (6.23%). After adjustment for age and polypharmacy, the probability of potentially inappropriate medication exposure was associated with chronic gastrointestinal diseases, followed by osteoarthritis and rheumatoid arthritis, chronic pulmonary disease, chronic kidney disease, tumor, dementia, chronic liver disease, hypertension, cardiovascular disease, cerebrovascular disease and hyperlipemia.ConclusionPotentially inappropriate medications were common in older patients with diabetes in an outpatient visitation setting. Higher probability of potentially inappropriate medication exposure was associated with the comorbidity chronic gastrointestinal diseases as well as osteoarthritis and rheumatoid arthritis. To ensure that iatrogenic risks remain minimal for older adults with diabetes, the clinical comorbidities should be considered.</p

Observations and model predictions (1-week-ahead predictions) for the dengue outbreak in Guangdong, 2014.

<p>(A) Observations and model predictions of dengue case counts were only shown for five cities with a high risk of dengue infection in Guangdong province. In each panel, the blue points represent observed case counts, the red dashed lines denote model-based predicted values. Dynamic forecasts of dengue epidemics are presented in Video Files 1–5, respectively. (B) The actual dengue incidence map and that from the SVR model-based 1-week-ahead predictions in Guangdong, 2014. Incidence is expressed as the number of case counts per 100,000 people.</p