BACH1 deficiency prevents neointima formation and maintains the differentiated phenotype of vascular smooth muscle cells by regulating chromatin accessibility.

The transcription factor BTB and CNC homology 1(BACH1) has been linked to coronary artery disease risk by human genome-wide association studies, but little is known about the role of BACH1 in vascular smooth muscle cell (VSMC) phenotype switching and neointima formation following vascular injury. Therefore, this study aims to explore the role of BACH1 in vascular remodeling and its underlying mechanisms. BACH1 was highly expressed in human atherosclerotic plaques and has high transcriptional factor activity in VSMCs of human atherosclerotic arteries. VSMC-specific loss of Bach1 in mice inhibited the transformation of VSMC from contractile to synthetic phenotype and VSMC proliferation and attenuated the neointimal hyperplasia induced by wire injury. Mechanistically, BACH1 suppressed chromatin accessibility at the promoters of VSMC marker genes via recruiting histone methyltransferase G9a and cofactor YAP and maintaining the H3K9me2 state, thereby repressing VSMC marker genes expression in human aortic smooth muscle cells (HASMCs). BACH1-induced repression of VSMC marker genes was abolished by the silencing of G9a or YAP. Thus, these findings demonstrate a crucial regulatory role of BACH1 in VSMC phenotypic transition and vascular homeostasis and shed light on potential future protective vascular disease intervention via manipulation of BACH1.

Deletion of BACH1 Attenuates Atherosclerosis by Reducing Endothelial Inflammation.

BACKGROUND: The transcription factor BACH1 (BTB and CNC homology 1) suppressed endothelial cells (ECs) proliferation and migration and impaired angiogenesis in the ischemic hindlimbs of adult mice. However, the role and underlying mechanisms of BACH1 in atherosclerosis remain unclear. METHODS: Mouse models of atherosclerosis in endothelial cell (EC)-specific-Bach1 knockout mice were used to study the role of BACH1 in the regulation of atherogenesis and the underlying mechanisms. RESULTS: Genetic analyses revealed that coronary artery disease-associated risk variant rs2832227 was associated with BACH1 gene expression in carotid plaques from patients. BACH1 was upregulated in ECs of human and mouse atherosclerotic plaques. Endothelial Bach1 deficiency decreased turbulent blood flow- or western diet-induced atherosclerotic lesions, macrophage content in plaques, expression of endothelial adhesion molecules (ICAM1 [intercellular cell adhesion molecule-1] and VCAM1 [vascular cell adhesion molecule-1]), and reduced plasma TNF-α (tumor necrosis factor-α) and IL-1ß levels in atherosclerotic mice. BACH1 deletion or knockdown inhibited monocyte-endothelial adhesion and reduced oscillatory shear stress or TNF-α-mediated induction of endothelial adhesion molecules and/or proinflammatory cytokines in mouse ECs, human umbilical vein ECs, and human aortic ECs. Mechanistic studies showed that upon oscillatory shear stress or TNF-α stimulation, BACH1 and YAP (yes-associated protein) were induced and translocated into the nucleus in ECs. BACH1 upregulated YAP expression by binding to the YAP promoter. BACH1 formed a complex with YAP inducing the transcription of adhesion molecules. YAP overexpression in ECs counteracted the antiatherosclerotic effect mediated by Bach1-deletion in mice. Rosuvastatin inhibited BACH1 expression by upregulating microRNA let-7a in ECs, and decreased Bach1 expression in the vascular endothelium of hyperlipidemic mice. BACH1 was colocalized with YAP, and the expression of BACH1 was positively correlated with YAP and proinflammatory genes, as well as adhesion molecules in human atherosclerotic plaques. CONCLUSIONS: These data identify BACH1 as a mechanosensor of hemodynamic stress and reveal that the BACH1-YAP transcriptional network is essential to vascular inflammation and atherogenesis. BACH1 shows potential as a novel therapeutic target in atherosclerosis.

Structural and functional insights into the epigenetic regulator MRG15.

MORF4-related gene on chromosome 15 (MRG15), a chromatin remodeller, is evolutionally conserved and ubiquitously expressed in mammalian tissues and cells. MRG15 plays vital regulatory roles in DNA damage repair, cell proliferation and division, cellular senescence and apoptosis by regulating both gene activation and gene repression via associations with specific histone acetyltransferase and histone deacetylase complexes. Recently, MRG15 has also been shown to rhythmically regulate hepatic lipid metabolism and suppress carcinoma progression. The unique N-terminal chromodomain and C-terminal MRG domain in MRG15 synergistically regulate its interaction with different cofactors, affecting its functions in various cell types. Thus, how MRG15 elaborately regulates target gene expression and performs diverse functions in different cellular contexts is worth investigating. In this review, we provide an in-depth discussion of how MRG15 controls multiple physiological and pathological processes.

Incidence and risk factors of subsequent vertebral fracture following percutaneous vertebral augmentation in postmenopausal women.

PURPOSE: Subsequent vertebral fracture (SVF) is a severe advent event of percutaneous vertebral augmentation (PVA). However, the incidence and risk factors of SVF following PVA for OVCF in postmenopausal women remain unclear. This research aims to investigative the incidence and risk factors of SVF after PVA for OVCF in postmenopausal women. METHODS: Women who underwent initial PVA for OVCF between August 2019 and December 2021 were reviewed. Univariate logistic regression analysis was performed to identify possible risk factors of SVF, and independent risk factors were determined by multivariate logistic regression. RESULTS: A total of 682 women after menopause were enrolled in the study. Of these women, 100 cases had an SVF after PVA, with the incidence of 14.66%. Univariate logistic regression analysis demonstrated that age (p = 0.001), body mass index (BMI) (p < 0.001), steroid use (p = 0.008), history of previous vertebral fracture (p < 0.001), multiple vertebral fracture (p = 0.033), postoperative wedge angle (p = 0.003), and HU value (p < 0.001) were significantly correlated with SVF following PVA. Furthermore, BMI (OR [95%CI] = 0.892 [0.825 - 0.965]; p = 0.004), steroid use (OR [95%CI] = 3.029 [1.211 - 7.574]; p = 0.018), history of previous vertebral fracture (OR [95%CI] = 1.898 [1.148 - 3.139]; p = 0.013), postoperative wedge angle (OR [95%CI] = 1.036 [1.004 - 1.070]; p = 0.028), and HU value (OR [95%CI] = 0.980 [0.971 - 0.990]; p < 0.001) were identified as independent risk factors of SVF after PVA by multivariate logistic regression analysis. CONCLUSIONS: The incidence of SVF following PVA for OVCF in postmenopausal women was 14.66%. BMI, steroid use, history of previous vertebral fracture, postoperative wedge angle, and HU value were independent risk factors of SVF after PVA for OVCF in postmenopausal women.

A Rotating Machinery Fault Diagnosis Method Based on Dynamic Graph Convolution Network and Hard Threshold Denoising.

With the development of precision sensing instruments and data storage devices, the fusion of multi-sensor data in gearbox fault diagnosis has attracted much attention. However, existing methods have difficulty in capturing the local temporal dependencies of multi-sensor monitoring information, and the inescapable noise severely decreases the accuracy of multi-sensor information fusion diagnosis. To address these issues, this paper proposes a fault diagnosis method based on dynamic graph convolutional neural networks and hard threshold denoising. Firstly, considering that the relationships between monitoring data from different sensors change over time, a dynamic graph structure is adopted to model the temporal dependencies of multi-sensor data, and, further, a graph convolutional neural network is constructed to achieve the interaction and feature extraction of temporal information from multi-sensor data. Secondly, to avoid the influence of noise in practical engineering, a hard threshold denoising strategy is designed, and a learnable hard threshold denoising layer is embedded into the graph neural network. Experimental fault datasets from two typical gearbox fault test benches under environmental noise are used to verify the effectiveness of the proposed method in gearbox fault diagnosis. The experimental results show that the proposed DDGCN method achieves an average diagnostic accuracy of up to 99.7% under different levels of environmental noise, demonstrating good noise resistance.

Consistency of limb preference across unimanual feeding, bipedal locomotion, and social grooming in golden snub-nosed monkeys (Rhinopithecus roxellana).

The golden snub-nosed monkey (Rhinopithecus roxellana) is a typical arboreal group-living Old World primate. While limb preference has been extensively studied in this species, limb preference consistency has not yet been explored. Here, based on 26 R. roxellana adults, we investigated whether individuals exhibit consistent motor biases in manual- (e.g., unimanual feeding and social grooming) and foot-related (e.g., bipedal locomotion) tasks and whether limb preference consistency is influenced by increased social interactions during social grooming. Results showed no consistency in the direction or strength of limb preference among tasks, except for lateral strength in handedness for unimanual feeding and footedness in the initiation of locomotion. Population-level foot preference was only found among right-handers. Marked lateral bias was found in unimanual feeding, indicating that it may be a sensitive behavioural measure for assessing manual preference, especially for provisioned populations. This study not only improves our understanding of the relationship between hand and foot preference in R. roxellana but also reveals potential differential hemispheric regulation of limb preference and the influence of increased social interaction on handedness consistency.

A bibliometric analysis of global research on spinal cord injury: 1999-2019.

STUDY DESIGN: Bibliometric review. OBJECTIVE: The spatial structure of the global spinal cord injury (SCI) research field has not been summarized or analyzed. The objective of this study was to understand the current status and global trends of SCI research, and provide scholars knowledge to integrate into their plans for future research. SETTING: Not applicable. METHODS: The Web of Science database was searched for articles related to SCI published between 1999 and 2019. Metrics based on publication data, including publication counts, H indices, countries, institutions, authors, and journals were extracted. Co-citation analysis, collaboration analysis, and co-occurrence analysis of keywords were conducted using CiteSpace. RESULTS: The search identified a total of 41,012 articles related to SCI. Overall, the number of publications increased annually. The United States was the top ranked country by publication count, H index, and citation count. Harvard University and the University of Toronto made the most contributions. M.G. Fehlings was the top ranked author. Spinal Cord published the largest number of articles, and was the most frequently cited journal. The top 5 ranked keywords that appeared most frequently were spinal cord injury, functional recovery, adult rat rehabilitation, and paraplegia. Twelve major clusters of keywords and 15 clusters of co-cited references were generated. CONCLUSIONS: This study comprehensively analyzed and summarized the trends in SCI research during the past 20 years. Findings should provide scholars information on the countries, institutions, authors, and journals that are active in the field of SCI research, and a knowledge base for future projects.

Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems.

Fault diagnosis and health condition monitoring have always been critical issues in the engineering research community [...].

Advanced Sensing, Fault Diagnostics, and Structural Health Management.

Advanced sensing, fault diagnosis, and structural health management are important parts of the maintenance strategy of modern industries [...].

Partial Transfer Ensemble Learning Framework: A Method for Intelligent Diagnosis of Rotating Machinery Based on an Incomplete Source Domain.

Most cross-domain intelligent diagnosis approaches presume that the health states in training datasets are consistent with those in testing. However, it is usually difficult and expensive to collect samples under all failure states during the training stage in actual engineering; this causes the training dataset to be incomplete. These existing methods may not be favorably implemented with an incomplete training dataset. To address this problem, a novel deep-learning-based model called partial transfer ensemble learning framework (PT-ELF) is proposed in this paper. The major procedures of this study consist of three steps. First, the missing health states in the training dataset are supplemented by another dataset. Second, since the training dataset is drawn from two different distributions, a partial transfer mechanism is explored to train a weak global classifier and two partial domain adaptation classifiers. Third, a particular ensemble strategy combines these classifiers with different classification ranges and capabilities to obtain the final diagnosis result. Two case studies are used to validate our method. Results indicate that our method can provide robust diagnosis results based on an incomplete source domain under variable working conditions.