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Methionine and choline both are essential nutrients which are needed for methyl group metabolism. A methionine-choline-deficient (MCD) diet leads to pathological changes in the kidney. The mechanism of the MCD diet is complex, and fundamental research is still required to provide a better understanding of the driving forces behind it. We evaluated the regional effects of the MCD diet on the metabolites of mouse kidney tissue using desorption electrospray ionization mass spectrometry imaging technology. A total of 20, 17, and 13 metabolites were significantly changed in the cortex, outer medulla, and inner medulla, respectively, of the mouse kidney tissue after the administration of the MCD diet. Among the discriminating metabolites, only three metabolites (guanidoacetic acid, serine, and nicotinamide riboside) were significantly increased, and all the other metabolites showed a significant decrease. The results showed that there were significant region-specific changes in the serine metabolism, carnitine metabolism, choline metabolism, and arginine metabolism. This study presents unique regional metabolic data, providing a more comprehensive understanding of the molecular characteristics of the MCD diet in the kidney. [ABSTRACT FROM AUTHOR]

Objectives: This study aims to decrease the scan time and enhance image quality in pediatric total-body PET imaging by utilizing multimodal artificial intelligence techniques. Methods: A total of 270 pediatric patients who underwent total-body PET/CT scans with a uEXPLORER at the Sun Yat-sen University Cancer Center were retrospectively enrolled. 18F-fluorodeoxyglucose (18F-FDG) was administered at a dose of 3.7 MBq/kg with an acquisition time of 600 s. Short-term scan PET images (acquired within 6, 15, 30, 60 and 150 s) were obtained by truncating the list-mode data. A three-dimensional (3D) neural network was developed with a residual network as the basic structure, fusing low-dose CT images as prior information, which were fed to the network at different scales. The short-term PET images and low-dose CT images were processed by the multimodal 3D network to generate full-length, high-dose PET images. The nonlocal means method and the same 3D network without the fused CT information were used as reference methods. The performance of the network model was evaluated by quantitative and qualitative analyses. Results: Multimodal artificial intelligence techniques can significantly improve PET image quality. When fused with prior CT information, the anatomical information of the images was enhanced, and 60 s of scan data produced images of quality comparable to that of the full-time data. Conclusion: Multimodal artificial intelligence techniques can effectively improve the quality of pediatric total-body PET/CT images acquired using ultrashort scan times. This has the potential to decrease the use of sedation, enhance guardian confidence, and reduce the probability of motion artifacts. [ABSTRACT FROM AUTHOR]

Spontaneous bacterial peritonitis (SBP) is a life-threatening complication in patients with cirrhosis. We aimed to develop an explainable machine learning model to achieve the early prediction and outcome interpretation of SBP. We used CatBoost algorithm to construct MODEL-1 with 46 variables. After dimensionality reduction, we constructed MODEL-2. We calculated and compared the sensitivity and negative predictive value (NPV) of MODEL-1 and MODEL-2. Finally, we used the SHAP (SHapley Additive exPlanations) method to provide insights into the model's outcome or prediction. MODEL-2 (AUROC: 0.822; 95% confidence interval [CI] 0.783–0.856), liked MODEL-1 (AUROC: 0.822; 95% CI 0.784–0.856), could well predict the risk of SBP in cirrhotic ascites patients. The 6 most influential predictive variables were total protein, C-reactive protein, prothrombin activity, cholinesterase, lymphocyte ratio and apolipoprotein A1. For binary classifier, the sensitivity and NPV of MODEL-1 were 0.894 and 0.885, respectively, while for MODEL-2 they were 0.927 and 0.904, respectively. We applied CatBoost algorithm to establish a practical and explainable prediction model for risk of SBP in cirrhotic patients with ascites. We also identified 6 important variables closely related to the occurrence of SBP. [ABSTRACT FROM AUTHOR]

Estimation of low or high conditional quantiles is called for in many applications, but commonly encountered data sparsity at the tails of distributions makes this a challenging task. We develop a Bayesian joint-quantile regression method to borrow information across tail quantiles through a linear approximation of quantile coefficients. Motivated by a working likelihood linked to the asymmetric Laplace distributions, we propose a new Bayesian estimator for high quantiles by using a delayed rejection and adaptive Metropolis and Gibbs algorithm. We demonstrate through numerical studies that the proposed estimator is generally more stable and efficient than conventional methods for estimating tail quantiles, especially at small and modest sample sizes. [ABSTRACT FROM AUTHOR]

In this paper, we study the log-behavior of a new sequence $\{S_{n}\} _{n=0}^{\infty}$ , which was defined by Z-W Sun. We find that the sequence is log-convex by using the interlacing method. Additionally, we consider ratio log-behavior of $\{S_{n}\}_{n=0}^{\infty}$ and find the sequences $\{S_{n+1}/S_{n}\}_{n=0}^{\infty}$ and $\{\sqrt[n]{S_{n}}\} _{n=1}^{\infty}$ are log-concave. Our results give an affirmative answer to a conjecture of Z-W Sun on the ratio monotonicity of this new sequence. [ABSTRACT FROM AUTHOR]

The drug development process consumes 9–12 years and approximately one billion US dollars in costs. Due to the high finances and time costs required by the traditional drug discovery paradigm, repurposing old drugs to treat cancer and rare diseases is becoming popular. Computational approaches are mainly data-driven and involve a systematic analysis of different data types leading to the formulation of repurposing hypotheses. This study presents a novel scoring algorithm based on chemical and genomic data to repurpose drugs for 669 diseases from 22 groups, including various cancers, musculoskeletal, infections, cardiovascular, and skin diseases. The data types used to design the scoring algorithm are chemical structures, drug-target interactions (DTI), pathways, and disease-gene associations. The repurposed scoring algorithm is strengthened by integrating the most comprehensive manually curated datasets for each data type. At DrugRepo score ≥ 0.4, we repurposed 516 approved drugs across 545 diseases. Moreover, hundreds of novel predicted compounds can be matched with ongoing studies at clinical trials. Our analysis is supported by a web tool available at: http://drugrepo.org/. [ABSTRACT FROM AUTHOR]

Salvianolic acid B is an antioxidative ingredient derived from Radix Salviae miltiorrhizae that has been widely used to treat liver diseases. However, the therapeutic mechanism underlying Salvianolic acid B has remained largely unknown. Our studies verified that Salvianolic acid B efficiently blocked mitochondrial deformation and dysfunction induced by H2O2 in the human hepatocyte cell line HL7702. Mortalin, a mitochondrial molecular chaperone, maintains mitochondrial morphology stabilization and function integrity. Previous results showed that mortalin overexpression has been observed in hematoma carcinoma cells and that mortalin maintains mitochondrial homeostasis and antagonizes oxidative stress damage. We found that Salvianolic acid B significantly up-regulated mortalin protein expression levels. In addition, Salvianolic acid B lost the function of preventing mitochondrial deformation and dysfunction induced by oxidative stress under mortalin knockdown conditions. We further found that mortalin overexpression increases the mRNA expression of mitofusin-related factor Mfn1 and mitofission-related factor hFis1. In conclusion, Salvianolic acid B maintains the mitochondrial structure stabilization and functional integrity by up-regulating mortalin, which may be associated with increased mitofusin factor Mfn1 and reduced mitofission factor hFis1. [ABSTRACT FROM AUTHOR]

Aneuploid refers to the gene dosage imbalance due to copy number alterations. Aneuploidy is generally harmful to the growth, development and reproduction of organisms according to the numerous research. However, it has rarely been reported on whether aneuploid have a relevant pattern of genome expression between the parental and its offspring generations. In this study, mRNA sequencing analysis was performed on rice (Oryza sativa L.) primary trisomes 11 and 12, same primary trisomes and normal individuals in their filial generation. We systematically summarized the changes in gene expression patterns that occur on cis genes and on trans genes between parental and filial generations. In T11 and T12, the ratio of cis-gene expression showed intermediate type in parents and dosage compensation in filial generations, which maybe due to more genes being downregulated. The trans genes were also affected by aneuploidy and manifested as cis-related. The strains with normal chromosomes in filial generations, there are still aneuploid-sensitive genes differentially expressed in their genomes, indicating that the effect of aneuploidy is far-reaching and could not be easily eliminated. Meanwhile, among these differentially expressed genes, genes with low-expression level were more likely to be upregulated, while genes with medium- and high-expression level were easy to be downregulated. For the different types of rice aneuploid, upregulated genes were mainly associated with genomic imbalance while downregulated genes were mainly influenced by the specific added chromosome. In conclusion, our results provide new insights into the genetic characterization and evolution of biological aneuploidy genomes. [ABSTRACT FROM AUTHOR]

Atherosclerosis, a chronic inflammatory disease, is the major cause of life-threatening complications such as myocardial infarction and stroke. Endothelial apoptosis plays a vital role in the initiation and progression of atherosclerotic lesions. Although a subset of microRNAs (miRs) have been identified as critical regulators of atherosclerosis, studies on their participation in endothelial apoptosis in atherosclerosis have been limited. In our study, we found that miR-26a expression was substantially reduced in the aortic intima of ApoE−/− mice fed with a high-fat diet (HFD). Treatment of human aortic endothelial cells (HAECs) with oxidized low-density lipoprotein (ox-LDL) suppressed miR-26a expression. Forced expression of miR-26a inhibited endothelial apoptosis as evidenced by MTT assay and TUNEL staining results. Further analysis identified TRPC6 as a target of miR-26a, and TRPC6 overexpression abolished the anti-apoptotic effect of miR-26a. Moreover, the cytosolic calcium and the mitochondrial apoptotic pathway were found to mediate the beneficial effects of miR-26a on endothelial apoptosis. Taken together, our study reveals a novel role of miR-26a in endothelial apoptosis and indicates a therapeutic potential of miR-26a for atherosclerosis associated with apoptotic cell death. [ABSTRACT FROM AUTHOR]