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SWI/SNF and NuRD are protein complexes that antagonistically regulate DNA accessibility. However, repression of theiractivities often leads to unanticipated changes in target gene expression (paradoxical), highlighting our incomplete understandingof their activities. Here we show that SWI/SNF and NuRD are in a tug-of-war to regulate PRC2 occupancy at lowlyexpressed and bivalent genes in mouse embryonic stem cells (mESCs). In contrast, at promoters of average or highly expressedgenes, SWI/SNF and NuRD antagonistically modulate RNA polymerase II (Pol II) release kinetics, arguably owingto accompanying alterations in H3.3 and H2A.Z levels at promoter-flanking nucleosomes, leading to paradoxical changes ingene expression. Owing to this mechanism, the relative activities of the two remodelers potentiate gene promoters towardPol II–dependent open or PRC2-dependent closed chromatin states. Our results highlight RNA Pol II occupancy as the keyparameter in determining the direction of gene expression changes in response to SWI/SNF and NuRD inactivation at genepromoters in mESCs. SWI/SNF and NuRD are protein complexes that antagonistically regulate DNA accessibility. However, repression of their activities often leads to unanticipated changes in target gene expression (paradoxical), highlighting our incomplete understanding of their activities. Here we show that SWI/SNF and NuRD are in a tug-of-war to regulate PRC2 occupancy at lowly expressed and bivalent genes in mouse embryonic stem cells (mESCs). In contrast, at promoters of average or highly expressed genes, SWI/SNF and NuRD antagonistically modulate RNA polymerase II (Pol II) release kinetics, arguably owing to accompanying alterations in H3.3 and H2A.Z levels at promoter-flanking nucleosomes, leading to paradoxical changes in gene expression. Owing to this mechanism, the relative activities of the two remodelers potentiate gene promoters toward Pol II–dependent open or PRC2-dependent closed chromatin states. Our results highlight RNA Pol II occupancy as the key parameter in determining the direction of gene expression changes in response to SWI/SNF and NuRD inactivation at gene promoters in mESCs.

Supplemental Material for Relationship Between Serum Uric Acid and Carotid Plaque in Patients With Coronary Artery Disease by Sex and Blood Pressure Status by Guangwei Pan, Yijia Liu, Lu Yu, Rongrong Yang, Tong Yang, Yang Wang, Jinyu Su, Zhu Li, Qi Cheng, Sheng Gao, Lin Li, and Chunquan Yu in Angiology.

Additional file 1: Table S1. Association between the TyG index and the number of vessels with stenosis ≥ 50%. Table S2. Association between the TyG index and degree of coronary stenoses.

Aiming at the classification difficulty of complex and diverse ECG signals, this paper proposes a feature extraction method based on standard deviation. This method solves the problems of multi-dimensional, diverse, high similarity and the difficulty in extracting main features effectively of ECG(electrocardiogram, ECG) signal features. In addition, this method overcomes the difficulty of low classification accuracy because of large differences in ECG signals of the same type among different patients. This paper adopts optimized probabilistic neural network methods to achieve automatic classification of arrhythmia. First, the standard deviation of the dimensions of each sampling point of the ECG signal would be calculated and sorted by size. Second, the first m dimensions as the feature dimensions of arrhythmia would be extracted. After that, the probabilistic neural network would be used to train and classify feature dimension data. Finally Bayesian Optimization(BO) method would be used to optimize the parameters globally. In the experiment of the MIT-BIH arrhythmia database, the arrhythmia data was divided into 5 categories and verified, experimental results show that the correct rate of classification of the arrhythmia data of patients reached 99.67%, which proved the effectiveness of the method in this paper.