Whole-genome resequencing reveals diversity and selective signals in the Wuxue goat.

Animal genetic resources are crucial for ensuring global food security. However, in recent years, a noticeable decline in the genetic diversity of livestock has occurred worldwide. This decline is pronounced in developing countries, where the management of these resources is insufficient. In the current study, we performed whole genome sequencing for 20 Wuxue (WX) and five Guizhou White (GW) goats. Additionally, we utilized the published genomes of 131 samples representing five different goat breeds from various regions in China. We investigated and compared the genetic diversity and selection signatures of WX goats. Whole genome sequencing analysis of the WX and GW populations yielded 120 425 063 SNPs, which resided primarily in intergenic and intron regions. Population genetic structure revealed that WX exhibited genetic resemblance to GW, Chengdu Brown, and Jintang Black and significant differentiation from the other goat breeds. In addition, three methods (nucleotide diversity, linkage disequilibrium decay, and runs of homozygosity) showed moderate genetic diversity in WX goats. We used nucleotide diversity and composite likelihood ratio methods to identify within-breed signatures of positive selection in WX goats. A total of 369 genes were identified using both detection methods, including genes related to reproduction (GRID2, ZNF276, TCF25, and SPIRE2), growth (HMGA2 and GJA3), and immunity (IRF3 and SRSF3). Overall, this study explored the adaptability of WX goats, shedding light on their genetic richness and potential to thrive in challenges posed by climatic changes and diseases. Further investigations are warranted to harness these insights to enhance more efficient and sustainable goat breeding initiatives.

Machine learning predictors of risk of death within 7 days in patients with non-traumatic subarachnoid hemorrhage in the intensive care unit: A multicenter retrospective study.

Non-traumatic subarachnoid hemorrhage (SAH) is a critical neurosurgical emergency with a high mortality rate, imposing a significant burden on both society and families. Accurate prediction of the risk of death within 7 days in SAH patients can provide valuable information for clinicians, enabling them to make better-informed medical decisions. In this study, we developed six machine learning models using the MIMIC III database and data collected at our institution. These models include Logistic Regression (LR), AdaBoosting (AB), Multilayer Perceptron (MLP), Bagging (BAG), Gradient Boosting Machines (GBM), and Extreme Gradient Boosting (XGB). The primary objective was to identify predictors of death within 7 days in SAH patients admitted to intensive care units. We employed univariate and multivariate logistic regression as well as Pearson correlation analysis to screen the clinical variables of the patients. The initially screened variables were then incorporated into the machine learning models, and the performance of these models was evaluated. Furthermore, we compared the performance differences among the six models and found that the MLP model exhibited the highest performance with an AUC of 0.913. In this study, we conducted risk factor analysis using Shapley values to identify the factors associated with death within 7 days in patients with SAH. The risk factors we identified include Gcsmotor, bicarbonate, wbc, spo2, heartrate, age, nely, glucose, aniongap, GCS, rbc, sysbp, sodium, and gcseys. To provide clinicians with a useful tool for assessing the risk of death within 7 days in SAH patients, we developed a web calculator based on the MLP machine learning model.

Enhanced photovoltaic response of lead-free ferroelectric solar cells based on (K,Bi)(Nb,Yb)O3 films.

Herein, we firstly present the (K,Bi)(Nb,Yb)O3 inorganic ferroelectric photovoltaic (FPV) film, in which a nearly ideal bandgap of ∼1.45 eV in the center of the solar spectrum and the co-existence of oxygen vacancies as well as ferroelectric polarization were confirmed. Furthermore, a novel cell structure is successfully fabricated by combining charge-transporting TiO2 nanoparticles, the perovskite sensitizer and a light-absorbing oxide hole p-type NiO conductor to realize a 1 V open circuit voltage, which can be increased to 1.56 V by adjusting the test bias near the coercive voltage. Additionally, under simulated standard AM 1.5G illumination, a fill factor of 86% and a power conversion efficiency of 0.85% are achieved via oxygen vacancy electromigration and polarization switching modulation. It is shown that the obtained power conversion efficiency is one to three orders of magnitude higher than those of pure BiFeO3 and Pb(Zr,Ti)O3. The enhanced PV effects are well elucidated using the transformation from a Schottky-like barrier to Ohmic contacts caused by polarization switching and oxygen vacancies. Building upon the above studies, deep insights into the bandgap tunability and PV effects in ferroelectric films with high oxygen vacancy concentration are provided and will facilitate a new versatile route for exploring high PV performance based on inorganic ferroelectric films.

Characterization on the phase separation behavior of styrene-butadiene rubber/polyisoprene/organoclay ternary blends under oscillatory shear.

The present work investigated the influence of organoclay (organo-montmorillonite, OMMT) on the phase separation behavior and morphology evolution of solution polymerized styrene-butadiene rubber (SSBR)/low vinyl content polyisoprene (LPI) blends with rheological methodology. It was found that the incorporation of OMMT not only reduced the droplet size of the dispersion phase, slowed down the phase separation kinetics, also enlarged the processing miscibility window of the blends. The determination on the wetting parameters indicated that due to the oscillatory shear effect, the OMMT sheets might localize at the interface between the two phases and act as compatibilizer or rigid barrier to prevent domain coarsening, resulting in slow phase separation kinetics, small droplet size, and stable morphology. The analysis of rheological data by the Palierne model provided further confirmation that the addition of OMMT can decrease the interfacial tension and restrict the relaxation of melt droplets. Therefore, a vivid "sea-fish-net" model was proposed to describe the effect of OMMT on the phase separation behavior of SSBR/LPI blends, in which the OMMT sheets acted as the barrier (net) to slow down the domain coarsening/coalescence in phase separation process of SSBR/LPI blends.