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We investigated proximal and distal renal tubular sodium handling, as assessed by fractional excretion of lithium (FELi) and fractional distal reabsorption rate of sodium (FDRNa), in relation to environmental and genetic factors in untreated patients.

Our study participants were suspected hypertensive patients being off antihypertensive medication for ≥2 weeks and referred for 24-hour ambulatory blood pressure monitoring. We collected serum and 24-hour urine for measurement of sodium, creatinine and lithium concentration, and calculated FELi and FDRNa. We genotyped 19 SNPs associated with renal sodium handling or blood pressure using the ABI SNapShot method.

The 1409 participants (664 men, 47.1%) had a mean (±SD) age of 51.0±10.5 years. After adjustment for host factors, both FELi and FDRNa were significantly (P≤0.01) associated with season and humidity, explaining ~1.3% and ~3.5% of the variance, respectively. FELi was highest in autumn and lowest in summer and intermediate in spring and winter (P=0.007). FDRNa was also highest in autumn but lowest in winter and intermediate in spring and summer (P<0.001). Neither FELi nor FDRNa was associated with outdoor temperature or atmospheric pressure (P≥0.13). After adjustment for host and environmental factors and Bonferroni multiple testing, among the 19 studied genetic variants, only rs12513375 was significantly associated with FELi and FDRNa (P≤0.004) and explained about 1.7% of the variance.

Renal sodium handling as measured by endogenous lithium clearance was sensitive to major environmental and genetic factors. Our finding is towards the use of these indexes for the definition of renal tubular dysfunction.

Renal sodium handling as measured by endogenous lithium clearance was sensitive to major environmental and genetic factors. Our finding is towards the use of these indexes for the definition of renal tubular dysfunction.

Health professions educators seek understanding of the process of learner performance and achievement. Grit, defined as passion and perseverance for long-term goals, has been implicated in this process. Research suggests that effort counts twice in achievement skill times effort equals skill and, subsequently, skill times effort equals achievement. Research also suggests that an individual's interest influences job performance and satisfaction. Grit, composed of Perseverance of Effort and Consistency of Interest, has been shown to positively correlate with performance and achievement in various disciplines. Limited research reveals Grit negatively correlates with resident attrition and physician burnout. This study evaluates relationships between Grit and medical student performance measures. We gather validity evidence for Grit scale use among medical students and, subsequently, use this data to evaluate for differences in Grit score by gender and assess whether there is a relationship between Grit and stascores. Though the correlations in this study were not significant, the results showed that Grit may tend to positively correlate with Step 1 and Step 2 Clinical Knowledge examinations. Given that these three exams are taken at different levels of training, the stepwise progression towards positive correlation may suggest that the theory "effort counts twice" applies to medical training.DNA/RNA motif mining is the foundation of gene function research. The DNA/RNA motif mining plays an extremely important role in identifying the DNA- or RNA-protein binding site, which helps to understand the mechanism of gene regulation and management. For the past few decades, researchers have been working on designing new efficient and accurate algorithms for mining motif. selleck screening library can be roughly divided into two categories the enumeration approach and the probabilistic method. #link# In recent years, machine learning methods had made great progress, especially the algorithm represented by deep learning had achieved good performance. Existing deep learning methods in motif mining can be roughly divided into three types of models convolutional neural network (CNN) based models, recurrent neural network (RNN) based models, and hybrid CNN-RNN based models. We introduce the application of deep learning in the field of motif mining in terms of data preprocessing, features of existing deep learning architectures and comparing the differences between the basic deep learning models. Through the analysis and comparison of existing deep learning methods, we found that the more complex models tend to perform better than simple ones when data are sufficient, and the current methods are relatively simple compared with other fields such as computer vision, language processing (NLP), computer games, etc. Therefore, it is necessary to conduct a summary in motif mining by deep learning, which can help researchers understand this field.Interrupted time series designs are a valuable quasi-experimental approach for evaluating public health interventions. Interrupted time series extends a single group pre-post comparison by using multiple time points to control for underlying trends. But history bias-confounding by unexpected events occurring at the same time of the intervention-threatens the validity of this design and limits causal inference. Synthetic control methodology, a popular data-driven technique for deriving a control series from a pool of unexposed populations, is increasingly recommended. In this paper, we evaluate if and when synthetic controls can strengthen an interrupted time series design. First, we summarize the main observational study designs used in evaluative research, highlighting their respective uses, strengths, biases and design extensions for addressing these biases. link2 Second, we outline when the use of synthetic controls can strengthen interrupted time series studies and when their combined use may be problematic. Third, we provide recommendations for using synthetic controls in interrupted time series and, using a real-world example, we illustrate the potential pitfalls of using a data-driven approach to identify a suitable control series. Finally, we emphasize the importance of theoretical approaches for informing study design and argue that synthetic control methods are not always well suited for generating a counterfactual that minimizes critical threats to interrupted time series studies. Advances in synthetic control methods bring new opportunities to conduct rigorous research in evaluating public health interventions. However, incorporating synthetic controls in interrupted time series studies may not always nullify important threats to validity nor improve causal inference.In the bioinformatics field, there has been a growing interest in modeling dihedral angles of amino acids by viewing them as data on the torus. This has motivated, over the past years, new proposals of distributions on the torus. The main drawback of most of these models is that the related densities are (pointwise) symmetric, despite the fact that the data usually present asymmetric patterns. This motivates the need to find a new way of constructing asymmetric toroidal distributions starting from a symmetric distribution. We tackle this problem in this article by introducing the sine-skewed toroidal distributions. The general properties of the new models are derived. Based on the initial symmetric model, explicit expressions for the shape and dependence measures are obtained, a simple algorithm for generating random numbers is provided, and asymptotic results for the maximum likelihood estimators are established. An important feature of our construction is that no extra normalizing constant needs to be calculated, leading to more flexible distributions without increasing the complexity of the models. The benefit of employing these new sine-skewed toroidal distributions is shown on the basis of protein data, where, in general, the new models outperform their symmetric antecedents.The domestication and breeding of crops has been a major achievement for mankind enabling the development of stable societies and civilisation. Crops have become more productive per unit area of cultivated land over the course of domestication supporting a current global population of 7.8 billion. Food security crops such as wheat and maize have seen large changes compared with early progenitors. Amongst processes that have been altered in these crops, is the allocation of carbon resources to support larger grain yield (grain number and size). In wheat, reduction in stem height has enabled diversion of resources from stems to ears. This has freed up carbon to support greater grain yield. Green revolution genes responsible for reductions in stem height are known, but a unifying mechanism for the active regulation of carbon resource allocation towards and within sinks has however been lacking. The trehalose 6-phosphate (T6P) signalling system has emerged as a mechanism of resource allocation and has been implicated in several crop traits including assimilate partitioning and improvement of yield in different environments. Understanding the mode of action of T6P through the SnRK1 protein kinase regulatory system is providing a basis for a unifying mechanism controlling whole-plant resource allocation and source-sink interactions in crops. link3 Latest results show it is likely that the T6P/SnRK1 pathway can be harnessed for further improvements such as grain number and grain filling traits and abiotic stress resilience through targeted gene editing, breeding and chemical approaches.

Classically activated macrophages contribute to the development of renal ischemia-reperfusion injury (IRI). This study aimed to investigate the role of transient receptor potential ankyrin 1 (Trpa1), a regulator of macrophage activation, in IRI-induced acute kidney injury (AKI) by using the Trpa1 gene knockout (Trpa1-/-) mouse model.

Male 8-week-old Trpa1-/- mice and wild-type (WT) littermates were subjected to renal ischemia for 35 minutes by clamping bilateral renal pedicles under isoflurane anesthesia, and blood and tissue samples were collected 24 hours after reperfusion and analyzed with histological and molecular measurements.

Following IRI, Trpa1-/- mice developed more deteriorated biochemical and morphological signs of AKI when comparing with WT mice. More classically activated M1 macrophages were found in the kidneys of Trpa1-/- mice comparing with WT mice after IRI, while the counts of alternatively activated M2 macrophages in the kidney were similar between the 2 strains after IRI. Furthermore, significantly higher expression levels of proinflammatory markers including interleukin-1 beta and tumor necrosis factor alpha were detected in the kidney of Trpa1-/- mice compared with WT mice after IRI. The levels of TRPA1 protein in the kidney of WT mice were also decreased after IRI.

Our results show that ablation of Trpa1 exacerbates infiltration of classically activated macrophages, renal inflammation, and renal injury in mice after IRI. These findings suggest that activation of TRPA1 may protect against IRI-induced AKI via regulation of macrophage-mediated inflammatory pathway.

Our results show that ablation of Trpa1 exacerbates infiltration of classically activated macrophages, renal inflammation, and renal injury in mice after IRI. These findings suggest that activation of TRPA1 may protect against IRI-induced AKI via regulation of macrophage-mediated inflammatory pathway.