Cyy-287, a novel pyrimidine-2,4-diamine derivative, efficiently mitigates inflammatory responses, fibrosis, and lipid synthesis in obesity-induced cardiac and hepatic dysfunction.

Background: Inflammation and metabolic disorders are important factors in the occurrence and development of obesity complications. In this study, we investigated the protective effect and underlying mechanism of a novel pyrimidine-2,4-diamine derivative, Cyy-287, on mice fed a high-fat diet (HFD). Methods: The mice were randomly separated into four groups (n ≥ 7): control (regular diet), HFD, HFD with Cyy-287 (5 mg/kg), and HFD with Cyy-287 (20 mg/kg) following HFD feeding for 10 weeks. After a 10-week administration, ALT and AST enzymes, echocardiography, immunohistochemical (IHC), Western blot (WB), Masson and Sirius Red staining were used to evaluate functional and morphological changes to the heart and liver. Microsomes from the mouse liver were extracted to quantify the total amount of CYP450 enzymes after drug treatment. Results: Cyy-287 decreased the levels of serum glucose, LDL, TC, ALT, and AST activities in HFD-treated mice. However, Cyy-287 administration increased ejection fraction (EF) and fractional shortening (FS) index of the heart. Cyy-287 inhibited histopathological changes in the heart and liver; decreased inflammatory activity; significantly diminished p38 mitogen-activated protein kinase (MAPK), the nuclear factor-kappa B (NF-κB) axis, and sterol regulatory element-binding protein-1c (SREBP-1c); and upregulated the AMP-activated protein kinase (AMPK) pathway in HFD-treated mice. Cyy-287 restored the content of hepatic CYP450 enzymes. Conclusion: These findings demonstrated that Cyy-287 protected heart and liver cells from obesity-induced damage by inhibiting inflammation, fibrosis, and lipid synthesis.

Gene Polymorphisms and Drug-Drug Interactions Determine the Metabolic Profile of Blonanserin.

This study aimed to evaluate the effects of cytochrome P450 3A4 (CYP3A4) gene polymorphism and drug interaction on the metabolism of blonanserin. Human recombinant CYP3A4 was prepared using the Bac-to-Bac baculovirus expression system. A microsomal enzyme reaction system was established, and drug-drug interactions were evaluated using Sprague-Dawley rats. Ultra-performance liquid chromatography-tandem mass spectrometry was used to detect the concentrations of blonanserin and its metabolite. Compared with wild type CYP34A, the relative clearance of blonanserin by CYP3A4.29 significantly increased to 251.3%, while it decreased notably with CYP3A4.4, 5, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 23, 24, 28, 31, 33, and 34, ranging from 6.09% to 63.34%. Among 153 tested drugs, nimodipine, felodipine, and amlodipine were found to potently inhibit the metabolism of blonanserin. Moreover, the inhibitory potency of nimodipine, felodipine, and amlodipine varied with different CYP3A4 variants. The half-maximal inhibitory concentration and enzymatic kinetics assay demonstrated that the metabolism of blonanserin was noncompetitively inhibited by nimodipine in rat liver microsomes and was inhibited in a mixed manner by felodipine and amlodipine in both rat liver microsomes and human liver microsomes. When nimodipine and felodipine were coadministered with blonanserin, the area under the blood concentration-time curve (AUC)(0-t), AUC(0-∞), and C max of blonanserin increased. When amlodipine and blonanserin were combined, the C max of blonanserin C increased remarkably. The vast majority of CYP3A4 variants have a low ability to catalyze blonanserin. With combined administration of nimodipine, felodipine, and amlodipine, the elimination of blonanserin was inhibited. This study provides the basis for individualized clinical use of blonanserin. SIGNIFICANCE STATEMENT: The enzyme kinetics of novel CYP3A4 enzymes for metabolizing blonanserin were investigated. Clearance of blonanserin by CYP3A4.4, 5, 7-10, 12-14, 16-18, 23-24, 28, 31, 33, and 34 decreased notably, but increased with CYP3A4.29. Additionally, we established a drug interaction spectrum for blonanserin, in which nimodipine, felodipine, and amlodipine kinetics exhibited mixed inhibition. Moreover, their inhibitory potencies decreased with CYP3A4.4 and 5 compared to CYP3A4.1. This study provides essential data for personalized clinical use of blonanserin.

Spatial transcriptomics deconvolution at single-cell resolution using Redeconve.

Computational deconvolution with single-cell RNA sequencing data as reference is pivotal to interpreting spatial transcriptomics data, but the current methods are limited to cell-type resolution. Here we present Redeconve, an algorithm to deconvolute spatial transcriptomics data at single-cell resolution, enabling interpretation of spatial transcriptomics data with thousands of nuanced cell states. We benchmark Redeconve with the state-of-the-art algorithms on diverse spatial transcriptomics platforms and datasets and demonstrate the superiority of Redeconve in terms of accuracy, resolution, robustness, and speed. Application to a human pancreatic cancer dataset reveals cancer-clone-specific T cell infiltration, and application to lymph node samples identifies differential cytotoxic T cells between IgA+ and IgG+ spots, providing novel insights into tumor immunology and the regulatory mechanisms underlying antibody class switch.

Lottery Jackpots Exist in Pre-Trained Models.

Network pruning is an effective approach to reduce network complexity with acceptable performance compromise. Existing studies achieve the sparsity of neural networks via time-consuming weight training or complex searching on networks with expanded width, which greatly limits the applications of network pruning. In this paper, we show that high-performing and sparse sub-networks without the involvement of weight training, termed "lottery jackpots", exist in pre-trained models with unexpanded width. Our presented lottery jackpots are traceable through empirical and theoretical outcomes. For example, we obtain a lottery jackpot that has only 10% parameters and still reaches the performance of the original dense VGGNet-19 without any modifications on the pre-trained weights on CIFAR-10. Furthermore, we improve the efficiency for searching lottery jackpots from two perspectives. First, we observe that the sparse masks derived from many existing pruning criteria have a high overlap with the searched mask of our lottery jackpot, among which, the magnitude-based pruning results in the most similar mask with ours. In compliance with this insight, we initialize our sparse mask using the magnitude-based pruning, resulting in at least 3× cost reduction on the lottery jackpot searching while achieving comparable or even better performance. Second, we conduct an in-depth analysis of the searching process for lottery jackpots. Our theoretical result suggests that the decrease in training loss during weight searching can be disturbed by the dependency between weights in modern networks. To mitigate this, we propose a novel short restriction method to restrict change of masks that may have potential negative impacts on the training loss, which leads to a faster convergence and reduced oscillation for searching lottery jackpots. Consequently, our searched lottery jackpot removes 90% weights in ResNet-50, while it easily obtains more than 70% top-1 accuracy using only 5 searching epochs on ImageNet.

Enzymatic activity of 38 CYP2C9 genotypes on ibuprofen.

BACKGROUND AND OBJECTIVE: Ibuprofen, a common non-steroidal anti-inflammatory drug, is used clinically for pain relief and antipyretic treatment worldwide. However, regular or long-term use of ibuprofen may lead to a series of adverse reactions, including gastrointestinal bleeding, hypertension and kidney injury. Previous studies have shown that CYP2C9 gene polymorphism plays an important role in the elimination of various drugs, which leads to the variation in drug efficacy. This study aimed to evaluate the effect of 38 CYP2C9 genotypes on ibuprofen metabolism. METHODS: Thirty-eight recombinant human CYP2C9 microsomal enzymes were obtained using a frugiperda 21 insect expression system according to a previously described method. Assessment of the catalytic function of these variants was completed via a mature incubation system: 5 pmol CYP2C9*1 and 38 CYP2C9 variants recombinant human microsomes, 5 µL cytochrome B5, ibuprofen (5-1000 µM), and Tris-HCl buffer (pH 7.4). The ibuprofen metabolite contents were determined using HPLC analysis. HPLC analysis included a UV detector, Plus-C18 column, and mobile phase [50% acetonitrile and 50% water (containing 0.05% trifluoroacetic acid)]. The kinetic parameters of the CYP2C9 genotypes were obtained by Michaelis-Menten curve fitting. RESULTS: The intrinsic clearance (CLint) of eight variants was not significantly different from CYP2C9*1; four CYP2C9 variants (CYP2C9*38, *44, *53 and *59) showed significantly higher CLint (increase by 35%-230%) than that of the wild-type; the remaining twenty-six variants exhibited significantly reduced CLint (reduced by 30%-99%) compared to that of the wild-type. CONCLUSION: This is the first systematic evaluation of the catalytic characteristics of 38 CYP2C9 genotypes involved ibuprofen metabolism. Our results provide a corresponding supplement to studies on CYP2C9 gene polymorphisms and kinetic characteristics of different variants. We need to focus on poor metabolizers (PMs) with severely abnormal metabolic functions, because they are more susceptible to drug exposure.

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an automated software package for accurate and direct generation of clinical diagnostic reports for prenatal and products of conception (POC) samples. METHODS: We applied natural language process (NLP) methods for analyzing 30,235 in-house historical clinical reports through active learning, and then, developed clinical knowledge bases, evidence-based interpretation methods and reporting criteria to support the whole postdetection pipeline. RESULTS: Of the 30,235 reports, we obtained 37,175 CNV-paragraph pairs. For these pairs, the active learning approaches achieved a 0.9466 average F1-score in sentence classification. The overall accuracy for variant classification was 95.7%, 95.2%, and 100.0% in retrospective, prospective, and clinical utility experiments, respectively. CONCLUSION: By integrating NLP methods in CNVs postdetection pipeline, REDBot is a robust and rapid tool with clinical utility for prenatal and POC diagnosis.