Change in estimated glomerular filtration rate and fracture risk in the Action to Control Cardiovascular Risk in Diabetes Trial

ObjectivePatients with type 2 diabetes (T2DM) are at increased risk of fracture. High prevalence of chronic kidney disease (CKD) in T2DM may contribute to bone fragility, but whether dynamic change in kidney function is associated with fracture risk is unclear.Research design and methodsTo evaluate the association of pre-randomization baseline estimated glomerular filtration (eGFR) and its change over time with subsequent fracture risk in the Bone substudy of Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial, we conducted an observational study of 2262 women and 4737 men with T2DM and with at least 2 eGFR values.ResultsDuring a mean follow-up of 4.40 ± 1.54 years, 235 women and 223 men sustained a new non-vertebral fracture. In multivariable adjusted sex-specific models, pre-randomization baseline eGFR was not a significant predictor of fracture risk in either men or women. However, a steeper decline in eGFR was associated with greater risk of fracture in women (hazard ratio [HR] per standard deviation [SD] decrement in eGFR slope, 1.30; 95%CI 1.17–1.44) but not men (HR per SD decrement in eGFR slope, 0.97; 95%CI 0.82–1.13). Accounting for competing risk of death modestly attenuated the association in women (HR per SD decrement in eGFR slope, 1.19; 95%CI 1.04–1.37), with the relationship in men remaining non-significant (HR per SD decrement in eGFR slope, 0.96; 95%CI 0.77–1.18).ConclusionsDeclining kidney function predicts fracture risk in women but not in men with T2DM. Future studies should investigate the mechanisms for these associations.     

Impulsive synchronization schemes of stochastic complex networks with switching topology: Average time approach

In this paper, a novel impulsive control law is proposed for synchronization of stochastic discrete complex networks with time delays and switching topologies, where average dwell time and average impulsive interval are taken into account. The side effect of time delays is estimated by Lyapunov–Razumikhin technique, which quantitatively gives the upper bound to increase the rate of Lyapunov function. By considering the compensation of decreasing interval, a better impulsive control law is recast in terms of average dwell time and average impulsive interval. Detailed results from a numerical illustrative example are presented and discussed. Finally, some relevant conclusions are drawn.     

Development of the decision tree model for distinguishing individuals of Chinese four surnames from Zhanjiang Han population based on Y-STR haplotypes

Co-separation studies between surnames and Y chromosome genetic markers are beneficial to revealing population migrations, surname origins, population formation histories and forensic familial searching. Genetic distributions of 27 Y-STRs in Chinese four surnames (Li, Lin, Chen and Huang) from Zhanjiang Han population were investigated. Meanwhile, we tried to develop a decision tree model for surname predictions based on Y-STR haplotypes. Allelic frequencies of 27 Y-STRs showed that unique alleles were only observed in a certain surname; besides, some alleles displayed higher frequencies in a certain surname than those in other surnames, implying these alleles might be employed as the useful indicators for surname predictions. Haplotype match probability values of 27 Y-STRs in these surnames revealed that the system could be used as a valuable tool for forensic male identification. The developed decision tree model performed well for the training set with the accuracy of 0.9860 and obtained the relatively high accuracy (>0.70) for surname predictions of the testing set. To sum up, we explored the power of the machine learning to the surname predictions based on obtained Y-STR haplotypes, which showed promising application values in forensic familial searching.     

An Impact study of highway design on casualty and non-casualty traffic accidents

Background Road Safety has become a worldwide concern due to the alarming repercussions road accidents may bear. This study examined the relationship between different geometric design elements and the accident rates on Rashid Bin Saeed Street, Arabian Gulf Street, and Sultan Bin Zayed Street in Abu Dhabi, United Arab Emirates.Methods The geometric design was collected from the satellite images of google earth in compliance with the standard geometric design manual of Abu Dhabi roads. The recorded geometric data consisted of the number of lanes, lane widths, median length, and width. The traffic volume data was provided by the Integrated Transport Center of Abu Dhabi, which was then converted into Annual Average Daily Traffic (AADT) for analytical purposes. For the studied roads, AADT ranges ranged between 26,509 and 121,890 vehicles per day. The crash data related to the period of 2012–2019 was collected from the online open-access data provided by the United Arab Emirates Ministry of Interior. The data provided had considered variables related to driver gender, age and speed, travel direction, and time of the day amongst other factors. A comprehensive statistical analysis was conducted to study the impact of geometric design elements on road safety through a stable distribution. Stable distributions are generally characterized by four parameters and expressed as X～S(α,β,σ,μ). The statistical model included several graphical representations such as accident frequency at two levels of severity, casualty and non-casualty accidents for different road segments, traffic volumes, day of the week, age of the injured person, and the geometric design parameters on the three roads. Variance-based methods of sensitivity analysis are also used that are a class of probabilistic approaches that quantify the input and output uncertainties as probability distributions and decompose the output variance into parts attributable to input variables and combinations of variables. The sensitivity of the output to an input variable is therefore measured by the amount of variance in the output caused by that input.Findings The results showed that the accident profiles differ with varying segments on each road, revealing some segments to be of higher accident rates than others. Also, a higher accident frequency was shown with young adult drivers, and a high majority of accidents had occurred on weekends. Regarding the road's geometric design, which is the focus of this study, a sensitivity analysis was made to determine the most influential geometric design element on accident frequency.Interpretation The number of lanes had the highest sensitivity index followed by the median width, and then came the lane width. Thus, modifying the number of lanes on a highway is anticipated to have the highest impact on accident frequency and road safety than any other geometric parameter.