Notes

ALK7 Self-consciousness Guards Osteoblast Cellular material Towards Higher Glucose-induced ROS Production via Nrf2/HO-1 Signaling Walkway.
Exposure to ambient air pollution has been associated with white matter damage and neurocognitive decline. However, the mechanisms of this injury are not well understood and remain largely uncharacterized in experimental models. Prior studies have shown that exposure to particulate matter (PM), a sub-fraction of air pollution, results in neuroinflammation, specifically the upregulation of inflammatory microglia. This study examines white matter and axonal injury, and characterizes microglial reactivity in the corpus callosum of mice exposed to 10 weeks (150 hours) of PM. Nanoscale particulate matter (nPM, aerodynamic diameter ≤200 nm) consisting primarily of traffic-related emissions was collected from an urban area in Los Angeles. Male C57BL/6J mice were exposed to either re-aerosolized nPM or filtered air for 5 hours/day, 3 days/week, for 10 weeks (150 hours; n = 18/group). Microglia were characterized by immunohistochemical double staining of ionized calcium-binding protein-1 (Iba-1) with inducible nitric ia release cytokines and reactive oxygen/ nitrogen species which may further contribute to the white matter damage observed in this model.The water film depth is a key variable that affects traffic safety under rainfall conditions. According to the Federal Highway Administration, approximately 5700 people are killed and more than 544 700 people are injured in crashes on wet pavements annually. Androgen Receptor Antagonist cell line While several studies have attempted to address water film depth issues by establishing prediction models, a few focused on the relationship among road geometric features, capacity of drainage facilities and water film depth. To ascertain the influence of the geometric features of road and facility drainage capacities on the water film depth, the road geometry features were first classified into four types, and the facility drainage capacities were considered from three aspects in this study. Furthermore, the concept of short-time rainfall grade was proposed according to the results of the field test. Finally, the theoretical prediction model for the water film depth was conceived, based on the geometric features of road and facility drainage capacities with different rainfall intensities. Compared with the traditional regression prediction models, the theoretical prediction model clearly shows the effects of the geometric features of road and facility drainage capacities. When the road drainage facilities have no drainage capacity, the water film depth increases rapidly with the rainfall intensity. This model can be used to predict the water film depth of road surfaces on rainy days, evaluate the effect of rainfall on the driving environment, and provide guidance for determining safety control measures on rainy days.
Vascular endothelial dysfunction is an essential part of the pathophysiology of type 2 diabetes and its complications. In type 2 diabetes, endothelial dysfunction is characterized by reduced insulin signaling and increased transendothelial transport of fatty acids (FA). As the Abl kinase inhibitor imatinib was previously shown to reverse type 2 diabetes and to inhibit VEGF signaling via Abl kinases, we studied the effect of imatinib on vascular insulin sensitivity and fatty acid transport in vivo and in vitro.

C57/BL6J mice were fed a chow diet or Western diet (WD), and received daily imatinib injections for two weeks. Insulin-mediated vasoreactivity of resistance arteries was studied using intravital microscopy, and metabolic insulin sensitivity using the hyperinsulinemic-euglycemic clamp. The effect of imatinib on triglyceride content in skeletal muscle and heart in vivo was also determined. In vitro, the effect of imatinib on fatty acid transport was studied in human umbilical vein endothelial cells (Hs of imatinib.
Imatinib prevents weight gain and preserves insulin-mediated vasodilation in WD-fed mice, but does not affect endothelial FA transport despite inhibiting VEGF-B signaling. The beneficial effect of imatinib on insulin-mediated vasodilation may contribute to the anti-diabetic effects of imatinib.Porcine reproductive and respiratory syndrome (PRRS) is a disease caused by the PRRS virus (PRRSV) that has spread globally in the last 30 years and causes huge economic losses every year. This research aims to 1) investigate the relationship between the PRRSV detection in two age categories (wean-to-market and adult/sow farm), and 2) examine the extent to which the wean-to-market PRRSV positive rate forecasts the adult/sow farm PRRSV positive rate. The data we used are the PRRSV RNA detection results between 2007 and 2019 integrated by the US Swine Disease Reporting System project that represent 95% of all porcine submissions tested in the US National Animal Health Network. We first use statistical tools to investigate to what extent the increase in PRRSV positive submissions in the wean-to-market is related to the PRRSV increase in adult/sow farms. The statistical analysis confirms that an increase in the PRRSV positive rate of wean-to-market precedes the increase in the adult/sow farms to a large extent. Then we create the dynamic exponentially weighted moving average control charts to identify out-of-control points (i.e., signals) in the PRRSV rates for both wean-to-market and adult/sow farms. This control-chart-based analysis finds that 78% of PRRSV signals in the wean-to-market are followed by a PRRSV rate signal in the adult/sow farms within eight weeks. We expect that our findings will help the producers and veterinarians to justify and reinforce the implementation of bio-security and bio-contaminant practices to curb disease spread across farms.This study aimed to develop culturally sensitive pain neuroscience education (PNE) materials for Hausa speaking patients with chronic spinal pain (CSP). PNE is a program of teaching patients about pain that has gained considerable attention in research and is increasingly used during physical therapy for patients with chronic pain. It helps in decreasing pain, disability, fear-avoidance, pain catastrophization, movement restriction, and health care utilization among patients with chronic pain. However, existing PNE materials and their application are limited to few languages and cultural inclinations. Due to the variations in pain perceptions, beliefs, and related outcomes among different population groups, culture-sensitive PNE materials addressing these outcomes are warranted. A focus-group discussion comprising 4 experts was used to adapt and develop preliminary PNE materials. Thereafter, an internet-based 3-round modified Delphi-study involving 22 experts ensued. Experts' consensus/recommendations concerning the content were used in modifying the PNE materials. Consensus was predefined as ≥75% level of (dis)agreement. Eighteen experts completed the Delphi rounds. Nineteen, 18 and 18 experts participated in rounds 1, 2 and 3 respectively, representing 86%, 94% and 100% participation rate respectively. Consensus agreement was reached in every round and content of the materials, including drawings, examples, figures and metaphors were adapted following the experts' suggestions. We therefore concluded that, culture-sensitive PNE materials for Hausa speaking patients with CSP were successfully produced. The present study also provides a direction for further research whereby the effects of culturally-sensitive PNE materials can be piloted among Hausa speaking patients with CSP.While advancements in genome sequencing have identified millions of somatic mutations in cancer, their functional impact is poorly understood. We previously developed the expression-based variant impact phenotyping (eVIP) method to use gene expression data to characterize the function of gene variants. The eVIP method uses a decision tree-based algorithm to predict the functional impact of somatic variants by comparing gene expression signatures induced by introduction of wild-type (WT) versus mutant cDNAs in cell lines. The method distinguishes between variants that are gain-of-function, loss-of-function, change-of-function, or neutral. We present eVIP2, software that allows for pathway analysis (eVIP Pathways) and usage with RNA-seq data. To demonstrate the eVIP2 software and approach, we characterized two recurrent frameshift variants in RNF43, a negative regulator of Wnt signaling, frequently mutated in colorectal, gastric, and endometrial cancer. RNF43 WT, RNF43 R117fs, RNF43 G659fs, or GFP control cDNA alysis. Lastly, we show primary colon adenocarcinoma patient samples with R117fs and G659fs variants have transcriptional profiles similar to BRAF missense mutations with activated RAS/MAPK signaling, consistent with KRAS signaling pathways being GOF in both variants. The eVIP2 method is an important step towards overcoming the current challenge of variant interpretation in the implementation of precision medicine. eVIP2 is available at https//github.com/BrooksLabUCSC/eVIP2.There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) and computational methods are vital. As part of one such HTS effort, embryonic zebrafish were used to examine a suite of morphological and mortality endpoints at six concentrations from over 1,000 unique chemicals found in the ToxCast library (phase 1 and 2). We hypothesized that by using a conditional generative adversarial network (cGAN) or deep neural networks (DNN), and leveraging this large set of toxicity data we could efficiently predict toxic outcomes of untested chemicals. Utilizing a novel method in this space, we converted the 3D structural information into a weighted set of points while retaining all information about the structure. In vivo toxicity and chemical data were used to train two neural network generators. The first was a DNN (Go-ZT) while the second utilized cGAN architecture (GAN-ZT) to train generators to produce toxicity data. Our results showed that Go-ZT significantly outperformed the cGAN, support vector machine, random forest and multilayer perceptron models in cross-validation, and when tested against an external test dataset. By combining both Go-ZT and GAN-ZT, our consensus model improved the SE, SP, PPV, and Kappa, to 71.4%, 95.9%, 71.4% and 0.673, respectively, resulting in an area under the receiver operating characteristic (AUROC) of 0.837. Considering their potential use as prescreening tools, these models could provide in vivo toxicity predictions and insight into the hundreds of thousands of untested chemicals to prioritize compounds for HT testing.Broad scale remote sensing promises to build forest inventories at unprecedented scales. A crucial step in this process is to associate sensor data into individual crowns. While dozens of crown detection algorithms have been proposed, their performance is typically not compared based on standard data or evaluation metrics. There is a need for a benchmark dataset to minimize differences in reported results as well as support evaluation of algorithms across a broad range of forest types. Combining RGB, LiDAR and hyperspectral sensor data from the USA National Ecological Observatory Network's Airborne Observation Platform with multiple types of evaluation data, we created a benchmark dataset to assess crown detection and delineation methods for canopy trees covering dominant forest types in the United States. This benchmark dataset includes an R package to standardize evaluation metrics and simplify comparisons between methods. The benchmark dataset contains over 6,000 image-annotated crowns, 400 field-annotated crowns, and 3,000 canopy stem points from a wide range of forest types.
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