Dynamic evolution mechanism of water-bearing coal permeability and water film under stress

To explore coal permeability evolution mechanism under the comprehensive action of multiple factors including stress - adsorption - water and slippage effect, considering the coal deformation induced by stress - adsorption, the expression of water film thickness was corrected to quantitatively characterize the effective pore size, and based on this, the intensity of gas slippage effect of water-bearing coal was further quantified and the permeability model was established under the comprehensive action of multiple factors. Combined with experimental research to verify the reliability of permeability model, and then the evolution mechanism of coal permeability, water film and slippage factors under the comprehensive action of multiple factors was further revealed. The results show that under different water saturation conditions, the permeability decreases sharply first and then tends to flat with the increase of effective stress; under the same effective stress condition, the permeability decreases with the increase of water saturation. The water film thickness changes dynamically under the action of stress - adsorption – water, the water film thickness has a negative correlation with stress and adsorption, but a positive correlation with water saturation; the slippage factor increases gradually with the increase of water saturation, but the increase trend is gentle under low stress condition, and more sharply under high stress condition. In addition, based on the disjoining pressure of gas-liquid-solid surface, the expressions of dynamic water film in square and equilateral triangle under the effect of stress-adsorption were deduced, and the evolution mechanisms of gas permeability, water film and slip coefficient of pores with different geometric shapes are compared and analyzed. Due to the presence of corner holes, the order of water film thickness in pores of different geometric forms is circle > square > equilateral triangle from large to small, the order of permeability is opposite; the slippage factor in circular is larger than that in angular pore, while the slippage factor in square and equilateral triangle pore has little difference

A-Optimal designs for mixture polynomial models with heteroscedastic errors

This paper searches $A$-optimal designs for mixture polynomial models when the errors are heteroscedastic. Sufficient conditions are given so that $A$-optimal designs for the complex mixture polynomial models can be constructed from the direct sum of $A$-optimal designs for their sub-mixture models with different structures of heteroscedasticity. Several examples are presented to further illustrate and check optimal designs based on $A$-optimality criterion

Role of glucose in the repair of cell membrane damage during squeeze distortion of erythrocytes in microfluidic capillaries

The rapid development of portable precision detection methods and the crisis of insufficient blood supply worldwide has led scientists to study mechanical visualization features beyond the biochemical properties of erythrocytes. Combined evaluation of currently known biochemical biomarkers and mechanical morphological biomarkers will become the mainstream of single-cell detection in the future. To explore the mechanical morphology of erythrocytes, a microfluidic capillary system was constructedin vitro, with flow velocity and glucose concentration as the main variables, and the morphology and ability of erythrocytes to recover from deformation as the main objects of analysis. We showed the mechanical distortion of erythrocytes under various experimental conditions. Our results showed that glucose plays important roles in improving the ability of erythrocytes to recover from deformation and in repairing the damage caused to the cell membrane during the repeated squeeze process. These protective effects were also confirmed inin vivoexperiments. Our results provide visual detection markers for single-cell chips and may be useful for future studies in cell aging

Identification and verification of a prognostic signature based on a miRNA–mRNA interaction pattern in colon adenocarcinoma

The expression characteristics of non-coding RNA (ncRNA) in colon adenocarcinoma (COAD) are involved in regulating various biological processes. To achieve these functions, ncRNA and a member of the Argonaute protein family form an RNA-induced silencing complex (RISC). The RISC is directed by ncRNA, especially microRNA (miRNA), to bind the target complementary mRNAs and regulate their expression by interfering with mRNA cleavage, degradation, or translation. However, how to identify potential miRNA biomarkers and therapeutic targets remains unclear. Here, we performed differential gene screening based on The Cancer Genome Atlas dataset and annotated meaningful differential genes to enrich related biological processes and regulatory cancer pathways. According to the overlap between the screened differential mRNAs and differential miRNAs, a prognosis model based on a least absolute shrinkage and selection operator-based Cox proportional hazards regression analysis can be established to obtain better prognosis characteristics. To further explore the therapeutic potential of miRNA as a target of mRNA intervention, we conducted an immunohistochemical analysis and evaluated the expression level in the tissue microarray of 100 colorectal cancer patients. The results demonstrated that the expression level of POU4F1, DNASE1L2, and WDR72 in the signature was significantly upregulated in COAD and correlated with poor prognosis. Establishing a prognostic signature based on miRNA target genes will help elucidate the molecular pathogenesis of COAD and provide novel potential targets for RNA therapy

A clinical prediction model based on interpretable machine learning algorithms for prolonged hospital stay in acute ischemic stroke patients: a real-world study

ObjectiveAcute ischemic stroke (AIS) brings an increasingly heavier economic burden nowadays. Prolonged length of stay (LOS) is a vital factor in healthcare expenditures. The aim of this study was to predict prolonged LOS in AIS patients based on an interpretable machine learning algorithm.MethodsWe enrolled AIS patients in our hospital from August 2017 to July 2019, and divided them into the “prolonged LOS” group and the “no prolonged LOS” group. Prolonged LOS was defined as hospitalization for more than 7 days. The least absolute shrinkage and selection operator (LASSO) regression was applied to reduce the dimensionality of the data. We compared the predictive capacity of extended LOS in eight different machine learning algorithms. SHapley Additive exPlanations (SHAP) values were used to interpret the outcome, and the most optimal model was assessed by discrimination, calibration, and clinical utility.ResultsProlonged LOS developed in 149 (22.0%) of the 677 eligible patients. In eight machine learning algorithms, prolonged LOS was best predicted by the Gaussian naive Bayes (GNB) model, which had a striking area under the curve (AUC) of 0.878 ± 0.007 in the training set and 0.857 ± 0.039 in the validation set. The variables sorted by the gap values showed that the strongest predictors were pneumonia, dysphagia, thrombectomy, and stroke severity. High net benefits were observed at 0%–76% threshold probabilities, while good agreement was found between the observed and predicted probabilities.ConclusionsThe model using the GNB algorithm proved excellent for predicting prolonged LOS in AIS patients. This simple model of prolonged hospitalization could help adjust policies and better utilize resources

Histone arginine methylation in cocaine action in the nucleus accumbens

Repeated cocaine exposure regulates transcriptional regulation within the nucleus accumbens (NAc), and epigenetic mechanisms - such as histone acetylation and methylation on Lys residues - have been linked to these lasting actions of cocaine. In contrast to Lys methylation, the role of histone Arg (R) methylation remains underexplored in addiction models. Here we show that protein-R-methyltransferase-6 (PRMT6) and its associated histone mark, asymmetric dimethylation of R2 on histone H3 (H3R2me2a), are decreased in the NAc of mice and rats after repeated cocaine exposure, including self-administration, and in the NAc of cocaine-addicted humans. Such PRMT6 down-regulation occurs selectively in NAc medium spiny neurons (MSNs) expressing dopamine D2 receptors (D2-MSNs), with opposite regulation occurring in D1-MSNs, and serves to protect against cocaine-induced addictive-like behavioral abnormalities. Using ChIP-seq, we identified Src kinase signaling inhibitor 1 (Srcin1; also referred to as p140Cap) as a key gene target for reduced H3R2me2a binding, and found that consequent Srcin1 induction in the NAc decreases Src signaling, cocaine reward, and the motiv ation to self-administer cocaine. Taken together, these findings suggest that suppression of Src signaling in NAc D2-MSNs, via PRMT6 and H3R2me2a down-regulation, functions as a homeostatic brake to restrain cocaine action, and provide novel candidates for the development of treatments for cocaine addiction. Keywords: histone arginine (R) methylation; drug addiction; medium spiny neurons; ChIP-seq; Sr