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We seek to transform how new and emergent variants of pandemiccausing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pretraining on over 110 million prokaryotic gene sequences and finetuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.

Urban digitalization is a critical focus of economic development and low carbon transition. Recognizing how urban digitalization influences carbon emissions efficiency (CEE) is of great practical significance to high-quality urban development. Based on data from 2011-2019 at the municipal level in China, this paper adopts efficiency analysis and entropy value method to measure urban digitalization development and CEE and analyzes their spatial-temporal evolution characteristics. Moreover, this paper empirically tests the overall effect, time effect and spatial effect of urban digitalization on CEE as well as the effect pathway. According to research findings, urban digitalization has a significant stimulative influence over CEE. The promotion effect shows a trend of increasing over time. Urban digitalization has a positive spatial spillover effect on CEE of surrounding cities, which is conducive to accelerating the integration process of low-carbon development among cities. Urban digitalization improves CEE by raising the level of human and ICT capital and optimizing the industrial structure. The above conclusions still hold after robustness and endogenous tests. In addition, compared with cities in the eastern part of China and cities with low levels of digitalization, the promoting effect of urban digitalization on CEE is more significantly than that in the center and western part of China and cities with high digitalization levels. These discoveries have policy design reference value for the region to enhance the development strategy of urban digitalization and achieve a green development transition.

Chronic coronary heart disease (CHD) is correlated with an increased risk of cognitive impairment (CI), but the mechanisms underlying these changes remain unclear. The aim of the present study was to explore the potential changes in regional spontaneous brain activities and their association with CI, to explore the pathophysiological mechanisms underlying CI in patients with CHD.A total of 71 CHD patients and 73 matched healthy controls (HCs) were included in this study. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess the participants' cognitive functions. Regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation(fALFF) values were calculated to determine regional spontaneous brain activity. Coronary artery calcium (CAC) score provides a measure of the total coronary plaque burden. Mediation analyses were performed to test whether CHD's effects on cognitive decline are mediated by decreased regional spontaneous brain activity.Patients with CHD had significantly lower MMSE and MoCA scores than the HCs. Compared with the HCs, the patients with CHD demonstrated significantly decreased ReHo and fALFF values in the bilateral medial superior frontal gyrus (SFGmed), left superior temporal gyrus (TPOsup) and left middle temporal gyrus (TPOmid). Impaired cognitive performance was positively correlated with decreased activities in the SFGmed. Mediation analyses revealed that the decreased regional spontaneous brain activity in the SFGmed played a critical role in the relationship between the increase in CAC score and the MoCA and MMSE scores.The abnormalities of spontaneous brain activity in SFGmed may provide insights into the neurological pathophysiology underlying CHD associated with cognitive dysfunction.

Vinyl acetate is an organic chemical raw material of great industrial value. It is widely used in synthetic film, adhesive, coating and textile slurry. The production route of vinyl acetate is introduced, and the advantages and disadvantages of synthesis methods of vinyl acetate method, acetylene method, EDA cracking method, base synthesis method and Halcon method are compared. The method of carbide acetylene has high economic efficiency, low energy consumption and good environmental protection, proposing the development direction of ethylene acetate production technology.

Walking stability is an important factor that is related to working accidents at height. The understanding of the relationship between walking stability and walking conditions remains an unmet need. Therefore, this study aimed to investigate the effect of path height, width, and asymmetric conditions on the pressure and time information of the foot-ground interaction during walking. 12 subjects were required to walk at two height, three width, and asymmetric conditions. Plantar pressures during walking were measured with the F-scan insole sensors. The total pressures were normalized with body weight, and the temporal parameters were normalized with stance time. When the walking height increased, the plantar pressure at the “heel strike” phase did not change significantly, while that at “heel rise” and “toe off” phases significantly increased, and the “heel rise” occurred earlier, indicating a greater foot-ground interaction at the forefoot part of the sole. As the path width increased from 0.6 m to 1.2 m, the foot-ground interaction as well as the asymmetric effect approached to that of overground walking. The findings could help improve the risk assessment and footwear design.

The scientific and reasonable measurement of agricultural green total factor productivity is helpful to grasp the direction of rural-factor-market reform. This study constructs a Malmquist productivity index based on a non-radial and non-angular SBM directional distance function. This study calculates the agricultural green total factor productivity of 28 provinces (cities and autonomous regions) in China from 1997 to 2020 by considering unexpected outputs such as carbon emissions and agricultural non-point-source pollution. Finally, this study uses the spatial Dobbin model to explore the spatial impact of agricultural green total factor productivity under the distortion of the factor market. The results show that the agricultural green total factor productivity, considering the unexpected outputs, is more in line with the level of high-quality green development in China’s agriculture. Regardless of whether the unexpected output is included, the increase in China’s agricultural total factor productivity is primarily due to progress in agricultural technology, and the double boost is little in agricultural technology progress and technical efficiency. Agricultural green total factor productivity shows an increasing trend, but the growth rate is slow, and differences in different regions are significant. Factor market distortion negatively impacts agricultural green total factor productivity, and other factors improve the agricultural total green factor productivity. However, factor market distortion has a particular spatial spillover effect, which hinders the synchronous growth of agricultural green total factor productivity in different regions. Therefore, the government should promote the reform of the agricultural mode of production and agricultural green production, eliminate the blocking effect of factor market distortion on the improvement in agricultural green total factor productivity, narrow the regional gap of agricultural total factor productivity, and establish a policy system for high-quality green development of modern agriculture.

In this study, the effect of polyethylene barriers with different blockage ratios on the explosion behavior of a propane-air premixed gas in a confined space is investigated. The maximum explosion pressure (

Major depressive disorder (MDD) is an overbroad and heterogeneous diagnosis with no reliable or quantifiable markers. We aim to combine machine-learning techniques with the individual minimum spanning tree of the morphological brain network (MST-MBN) to determine whether the network properties can provide neuroimaging biomarkers to identify patients with MDD.Eight morphometric features of each region of interest (ROI) were extracted from 3D T1 structural images of 106 patients with MDD and 97 healthy controls. Six feature distances of the eight morphometric features were calculated to generate a feature distance matrix, which was defined as low-order MBN. Further linear correlations of feature distances between ROIs were calculated on the basis of low-order MBN to generate individual high-order MBN. The Kruskal's algorithm was used to generate the MST to obtain the core framework of individual low-order and high-order MBN. The regional and global properties of the individual MSTs were defined as the feature. The support vector machine and back-propagation neural network was used to diagnose MDD and assess its severity, respectively.The low-order and high-order MST-MBN constructed by cityblock distance had the excellent classification performance. The high-order MST-MBN significantly improved almost 20 % diagnostic accuracy compared with the low-order MST-MBN, and had a maximum RWe proposed an innovative individual high-order MST-MBN to capture the cortical high-order morphological correlation and make an excellent performance for individualized diagnosis and assessment of MDD.

Tuberculosis, caused by mycobacteria, continues to pose a substantial public health threat. Mycobacteria typically use cholesterol from the membranes of host macrophages as a carbon and energy source. Most genes that control cholesterol degradation are regulated by KstR, which is highly conserved in Mycobacterium tuberculosis and Mycobacterium smegmatis. Through bioinformatic analysis, we found a typical global nitrogen regulator (GlnR)-binding motif (CCGAC-AACAGT-GACAC) in the promoter region of kstR of M. smegmatis, and we determined its binding activity in vitro using electrophoretic mobility shift assays. Using RT-qPCR, we found that nine genes involved in side-chain or sterol-ring oxidation were upregulated in a ΔglnR M. smegmatis strain compared to the WT strain and glnR-complemented strains under nitrogen limitation. ATP assays in macrophages revealed that coordinated GlnR-KstR regulation significantly reduced the viability of M. smegmatis in macrophages. Thus, we found that various genes involved in cholesterol catabolism are regualted by GlnR via KstR in response to environmental nitrogen, and that they further affect the invasive ability of M. smegmatis. These findings revealed a novel regulatory mechanism of cholesterol catabolism, which may be useful in the development of new strategies for controlling tuberculosis. This article is protected by copyright. All rights reserved.

Deep aquifers are a common geological disaster source in coal mines and they can lead to water and mud inrush disasters. Grouting is the most effective method to reinforce aquifers and block water. However, grouting only at the water inrush area cannot obtain a stable effect. A combination of groundwater runoff analysis and grouting keyholes optimization was adopted to solve the problem of water inrush in deep mines. First, the structural pattern of the grouting area was identified and the position of the water inrush channel was deduced, yielding the mine’s groundwater runoff pattern. Then, the quality of grouting holes was evaluated by AHP analysis and the keyholes in the runoff network were determined according to the maximum membership degree principle. Finally, the keyholes were blocked by grouting. After the grouting treatment, the grouting effect was evaluated by using working face water inflow and water detection radar. The results indicate that combining groundwater runoff analysis with keyhole selection can effectively control water inrush in deep mining.

The oxygen concentration in near-surface air, which has been previously documented to be nearly constant (~20.946%), varies due to photosynthesis, respiration, and combustion processes, including combustion of fossil fuels. As the biggest and highest plateau in the world, the Qinghai-Tibet Plateau (QTP) hosts the largest high altitude population and tourists. The hypoxic environment of the QTP challenges its inhabitants and visitors both physically and psychologically. Health problems associated with the exposure to high altitude have long been observed by the scientific community. However, few studies have investigated the key drivers and their contribution to spatio-temporal oxygen concentration variations over the QTP. To fill this gap, a field investigation conducted along the Qinghai-Tibet National Highway in the summer of 2017 found that, in addition to altitude, vegetation and weather conditions may also impact on oxygen concentrations. Subsequent investigations during 2018−2020 along other national highways and within the Qinghai Lake region, the Qilian Mountains and their vicinities recorded a total of 487 samples. These observations showed clear spatial and seasonal variations in oxygen concentrations. Statistical analysis showed that oxygen concentration is positively affected by air temperature and fractional vegetation cover (FVC) but decreases with altitudes. The Lindeman, Merenda and Gold (LMG) method showed that the relative contributions of altitude, air temperature, and FVC to oxygen concentration were 46.69%, 31.64% and 3.44%, respectively, jointly explaining ~82% of the total variance in oxygen concentration. The remaining unexplained variance could be possibly due to factors such as vegetation net primary productivity (NPP) and soil heterotrophic respiration. Spatio-temporal variations in oxygen concentration are likely caused by the oxygen production from photosynthesis and soil heterotrophic respiration and by changes in atmospheric density resulting from topography and near-surface air temperature. Under a warming climate, improved vegetation cover and higher air temperature over the QTP could increase oxygen concentration and, to some extent, reduce the risks of hypoxia in the populations of the QTP. These findings improve our understanding of the spatio-temporal variations in oxygen concentration over the QTP in the context of climate change. The results can also be used to support the health and safety of residents and tourists and promote the sustainable development of high altitude regions worldwide.

This work aimed to explore whether radiomic features on magnetic resonance diffusion weighted image (MR DWI) can be used to identify triple-negative breast cancer (TNBC) and other subtypes (non-TNBC).This retrospective study included 221 unilateral patients who underwent breast MR imaging prior to neoadjuvant chemotherapy. The subtypes of breast cancer include luminal A (n = 63), luminal B (n = 103), human epidermal growth factor receptor-2 (HER2) overexpressing (n = 30), and triple negative (n = 25). Radiomic features were extracted using Omini-Kinetic software on DWI. Student's t-test and Mann-Whitney U test were used to compare the features between TNBC and non-TNBC patients. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to evaluate the diagnostic efficiency of radiomic features. The Fisher discriminant model was employed to distinguish TNBC and non-TNBC patients automatically. An additional validation dataset with 169 patients was utilized to validate the model.A total of 76 imaging features were extracted from each lesion on DWI images, and 12 radiomic features were statistically significant between TNBC and non-TNBC patients (P 0.05). The area of receiver operating characteristic curve (AUC) was 0.817 to apply logistic regression analysis. The accuracy of Fisher discriminant model in distinguishing TNBC and non-TNBC patients was 95.4%, and leave-one-out cross validation was achieved with an accuracy of 83.7%. The same classification analysis of the validation dataset showed an accuracy of 83.4% and an AUC of 0.804.Breast lesions exhibit differences in radiomic features from DWI, enabling good discrimination between TNBC and non-TNBC tumors.

Previously, Cu2O cubes have been shown to remain photocatalytically inert toward methyl orange degradation even after surface decoration with ZnO, ZnS, CdS, and Ag3PO4 nanostructures. Surprisingly, when Ag2S nanoparticles are lightly deposited on Cu2O cubes as seen through scanning electron microscopy (SEM) images, the heterostructures become highly photocatalytically active. X-ray diffraction (XRD) patterns show mainly Cu2O diffraction peaks due to lightly deposited Ag2S, but Ag2S peaks can emerge with increased Ag2S deposition. X-ray photoelectron spectroscopy (XPS) analysis also supports Ag2S formation on Cu2O crystals. The Ag2S-deposited Cu2O octahedra and rhombic dodecahedra show the expected activity enhancement. Electron paramagnetic resonance (EPR) measurements, as well as electron, hole, and radical scavenger tests, all confirmed the emergence of photocatalytic activity from the Ag2S-Cu2O cubes. Photoluminescence lifetimes are shortened after Ag2S deposition. Electrochemical impedance measurements revealed a large decrease in charge transfer resistance for Cu2O cubes after the Ag2S deposition. Unexpectedly, the separately synthesized Ag2S particles are also photocatalytically inactive. No specific lattice planes of Ag2S are formed directly over the {100} face of Cu2O. Diffuse reflectance and ultraviolet photoelectron spectral data were used to construct band diagrams of different Cu2O crystals and Ag2S nanoparticles. A Z-scheme charge transfer mechanism may be involved at the heterojunction interface to promote charge carrier separation. However, to explain the sudden appearance of photocatalytic activity from the Ag2S-deposited Cu2O cubes, a large change in the {100} surface band bending after Ag2S deposition should be used. This work illustrates that an unusual photocatalytic outcome is possible to semiconductor heterojunctions, where two photocatalytically inert components can become highly active when joined together.

We outline recent developments in artificial intelligence (AI) and machine learning (ML) techniques for integrative structural biology of intrinsically disordered proteins (IDP) ensembles. IDPs challenge the traditional protein structure-function paradigm by adapting their conformations in response to specific binding partners leading them to mediate diverse, and often complex cellular functions such as biological signaling, self-organization and compartmentalization. Obtaining mechanistic insights into their function can therefore be challenging for traditional structural determination techniques. Often, scientists have to rely on piecemeal evidence drawn from diverse experimental techniques to characterize their functional mechanisms. Multiscale simulations can help bridge critical knowledge gaps about IDP structure-function relationships-however, these techniques also face challenges in resolving emergent phenomena within IDP conformational ensembles. We posit that scalable statistical inference techniques can effectively integrate information gleaned from multiple experimental techniques as well as from simulations, thus providing access to atomistic details of these emergent phenomena.

Although much is known about how adipose tissue affects the development of clear cell renal carcinoma (ccRCC), little information is available for the utility of sex-specific abdominal visceral fat composition as a predictor of clear cell renal carcinoma (ccRCC) T stage. We conducted CT-based sex-specific abdominal fat measurements in ccRCC patients to assess whether VFA distribution could predict the ccRCC T stage. In total, 253 patients (182 males and 71 females) from our hospital with pathologically confirmed ccRCC (178 low T-stage and 75 high T-stage) were retrospectively reviewed for the present study. Computed tomography (CT) scans were assessed using ImageJ to differentiate between the visceral and subcutaneous fat areas (VFA and SFA), after which the relative VFA (rVFA) and total fat area (TFA) were computed. The relationships between these fat area-related variables, patient age, sex, and BMI, and ccRCC T stage were then evaluated through univariate and multivariate logistic regression analysis to clarify the association between general or sex-specific abdominal visceral fat and T stage. Following adjustment for age, males with high T stage ccRCC exhibited an increased rVFA as compared to males with low T stage ccRCC, with the same relationship being observed among females. This association between rVFA and high T stage was confirmed through both univariate and multivariate models. As thus, sex-specific visceral fat composition is a reliable independent predictor that can identify both male and female patients with high T stage ccRCC.

The groundwater level has been continuously decreasing due to climate change and long-time overexploitation in the Xiong’an New Area, North China, which caused the enhanced mixing of groundwater in different aquifers and significant changes in regional groundwater chemistry characteristics. In this study, groundwater and sediment pore-water in drilling cores obtained from a 600 m borehole were investigated to evaluate hydrogeochemical processes in shallow and deep aquifers and paleo-environmental evolution in the past ca. 3.10 Ma. Results showed that there was no obvious change overall in chemical composition along the direction of groundwater runoff, but different hydrochemical processes occurred in shallow and deep groundwater in the vertical direction. Shallow groundwater ( 1000 mg/L) and high concentrations of Mn and Fe, while deep groundwater had better water quality with lower salinity. The high TDS values mostly occurred in aquifers with depth 500 m below land surface. Water isotopes showed that aquifer pore-water mostly originated from meteoric water under the influence of evaporation, and aquitard pore-water belonged to Paleo meteoric water. In addition, the evolution of the paleoclimate since 3.10 Ma BP was reconstructed, and four climate periods were determined by the δ18O profiles of pore-water and sporopollen records from sediments at different depths. It can be inferred that the Quaternary Pleistocene (0.78–2.58 Ma BP) was dominated by the cold and dry climate of the glacial period, with three interglacial intervals of warm and humid climate. What’s more, this study demonstrates the possibilities of the applications of pore-water on the hydrogeochemical study and further supports the finding that pore-water could retain the feature of paleo-sedimentary water. © 2021 China Geology Editorial Office.

Hypertensive nephropathy is embodied by kidney tissue fibrosis and glomerular sclerosis, as well as renal inflammation. The Hippo/YAP (yes-associated protein, YAP) axis has been reported to promote inflammation and fibrosis and may participate in the pathogenesis of heart, vascular and renal injuries. However, the role of the Hippo/YAP pathway in hypertensive renal injury has not been reported so far. We explored the role of the Hippo/YAP signalling pathway in hypertensive renal injury and the effect of peptide 17 on its effects.Histopathological analyses were performed based on the Masson and Haematoxylin/eosin (HE) staining approaches. Biochemical indexes were determined and immunofluorescence and western blotting were used to detect protein expression levels. The mRNA expression levels were determined by qRT-PCR.Our results showed that peptide 17 reduced the systolic blood pressure (SBP) and urine protein/creatinine ratio in hypertensive rats. In addition, peptide 17 reduced the histopathological damage of kidneys in spontaneously hypertensive rats (SHRs). Moreover, peptide 17 downregulated genes in the Hippo/Yap pathway in kidney tissue of SHRs and Ang II-treated kidney cells. The expression levels of inflammatory factors TNF-α, IL-1β and MCP-1 and the pro-fibrotic factors TGF-β1, fibronectin, and CTGF were increased in the kidney of hypertensive rats, but reversed by peptide 17 treatment. Silencing of YAP had effect similar to that of peptide 17 in vivo and in vitro.Peptide 17 alleviates early renal injury in hypertension by regulating the Hippo/YAP signalling pathway. These findings may be useful in the treatment of hypertensive renal injury.

This study aims to develop an attention-based deep learning model for distinguishing benign from malignant breast lesions on CESM.Preoperative CESM images of 1239 patients, which were definitely diagnosed on pathology in a multicentre cohort, were divided into training and validation sets, internal and external test sets. The regions of interest of the breast lesions were outlined manually by a senior radiologist. We adopted three conventional convolutional neural networks (CNNs), namely, DenseNet 121, Xception, and ResNet 50, as the backbone architectures and incorporated the convolutional block attention module (CBAM) into them for classification. The performance of the models was analysed in terms of the receiver operating characteristic (ROC) curve, accuracy, the positive predictive value (PPV), the negative predictive value (NPV), the F1 score, the precision recall curve (PRC), and heat maps. The final models were compared with the diagnostic performance of conventional CNNs, radiomics models, and two radiologists with specialised breast imaging experience.The best-performing deep learning model, that is, the CBAM-based Xception, achieved an area under the ROC curve (AUC) of 0.970, a sensitivity of 0.848, a specificity of 1.000, and an accuracy of 0.891 on the external test set, which was higher than those of other CNNs, radiomics models, and radiologists. The PRC and the heat maps also indicated the favourable predictive performance of the attention-based CNN model. The diagnostic performance of two radiologists improved with deep learning assistance.Using an attention-based deep learning model based on CESM images can help to distinguishing benign from malignant breast lesions, and the diagnostic performance of radiologists improved with deep learning assistance.

Background and Purpose Whereas whether metformin reduce all-cause, cardiovascular mortality, and incidence of cardiovascular events in patients with cardiac diseases remains inconclusive. Experimental Approach PubMed and Embase were searched up to May 2020 with a registration in PROSPERO (CRD42020189905) were collected. This article includes randomized controlled trials (RCT) and cohort studies. Hazard ratio (HR) with 95% CI was pooled across various trials by a random-effects model. Risk of bias was accounted as per Cochrane and Newcastle-Ottawa Scale (NOS) guidelines. Key Results This article enrolled 48 articles (1999-2020) for qualitative synthesis and identified 26 articles (33 studies in total, 61,704 patients) for final quantitative synthesis. Compared with non-metformin control, metformin is associated with reduced all-cause mortality (HR: 0.90; 95% CI: 0.83, 0.98; P = 0.01), cardiovascular mortality (HR: 0.89; 95% CI: 0.85, 0.94; P < 0.0001), incidence of coronary revascularization (HR: 0.79; 95% CI: 0.64, 0.98; P = 0.03), and heart failure (HR: 0.90; 95% CI: 0.87, 0.94; P < 0.0001) in patients with cardiac diseases, whereas metformin is not associated with reduced incidence of myocardial infarction (HR: 0.97; 95% CI: 0.80, 1.17; P = 0.73), angina (HR: 0.29; 95% CI: 0.04, 2.35; P = 0.25), and stroke (HR: 0.95; 95% CI: 0.78, 1.16; P = 0.59). Conclusion and Implications Metformin reduces all-cause mortality, cardiovascular mortality, incidence of coronary revascularization, and heart failure of patients with cardiac diseases, whereas metformin is not associated with reduced incidence of myocardial infarction, angina, and stroke.

Background Cardiac MRI is an emerging modality for evaluating left ventricular (LV) diastolic dysfunction (LVDD), a pathological condition that is prevalent in aging populations. However, there is a lack of reports of MRI-derived LV diastolic properties in late diastole. Purpose To test the hypothesis that cine MRI-derived motion/deformation indices can be used to characterize age-related changes on LV relaxation patterns in late diastole. Study type Retrospective. Population In all, 412 participants (72.5 ± 4.6 years old, range 65-84) without a documented history of cardiovascular diseases. Field strength/sequence Balanced steady-state free precession(bSSFP) acquired at 1.5T. Assessment Participants were divided into younger (65-74 years old, n = 275) and older (75-84 years old, n = 137) groups. Status of diabetes mellitus (DM), hypertension (HTN), and lipid disorders were recorded for each participant. Cine MRI datasets were analyzed by using heart deformation analysis (HDA). LV motion/deformation indices (displacement, velocity, strain, and strain rate) were measured through 22 phases within a cardiac cycle. Statistical tests The prevalence of traditional cardiovascular risk conditions, LV ejection fraction (LVEF), peak LV regional displacement, velocity, and strain rates at early and late diastole were compared between two participant groups using chi-square tests or t-tests. Results Older participants had a significantly lower peak early radial displacement (0.797 ± 0.249 cm vs. 0.876 ± 0.286 cm), radial velocity (19.3 ± 6.3 mm/s vs. 17.5 ± 5.2 mm/s), and circumferential strain rate (64.6 ± 15.7%/s vs. 70.1 ± 17%/s) but a higher peak late circumferential strain rate (69.8 ± 16.3 %/s vs. 66 ± 15.8 %/s) than their younger counterparts. Data conclusion Cine MRI can be used to characterize age-related LV relaxation patterns in late diastole. Level of evidence 3. Technical efficacy stage 1.

The MG53 (also known as TRIM72) is a conserved, muscle-specific tripartite motif family protein that is abundantly expressed in cardiac or skeletal muscle and present in circulation. Recently, the MG53 had been hypothesized to serve a dual role in the heart: involving in repairing cell membranes that protect myocardial function while acting as an E3 ligase to trigger insulin resistance and cardiovascular complications. This review discusses the roles of MG53 in cardiac physiological function with emphasis on MG53 protective function in the heart and its negative impact on the myocardium due to the continuous elevation of MG53. Besides, this work reviewed the significance of MG53 as a potential therapeutic in human cardiovascular diseases. Despite the expression of MG53 being rare in the human, thus exogenous MG53 can potentially be a new treatment for human cardiovascular diseases. Notably, the specific mechanism of MG53 in cardiovascular diseases remains elusive.

Clinical cases have reported pulmonary arterial structural and functional abnormalities in patients with Kawasaki disease (KD); however, the underlying mechanisms are unclear. In this study, a KD rat model was established via the intraperitoneal injection of Lactobacillus casei cell wall extract (LCWE). The results showed that pulmonary arterial functional and structural abnormalities were observed in KD rats. Furthermore, proliferative endoplasmic reticulum stress (ER stress) was observed in the pulmonary arteries of KD rats. Notably, the level of lipocalin-2 (Lcn 2), a trigger factor of inflammation, was remarkably elevated in the plasma and lung tissues of KD rats; increased Lcn 2 levels following LCWE stimulation may result from polymorphonuclear neutrophils (PMNs). Correspondingly, in cultured pulmonary artery smooth muscle cells (PASMCs), Lcn 2 markedly augmented the cleavage and nuclear localization of activating transcription factor-6 (ATF6), upregulated the transcription of glucose regulated protein 78 (GRP78) and neurite outgrowth inhibitor (NOGO), and promoted PASMCs proliferation. However, proapoptotic C/EBP homologous protein (CHOP) and caspase 12 levels were not elevated. Treatment with 4-phenyl butyric acid (4-PBA, a specific inhibitor of ER stress) inhibited PASMCs proliferation induced by Lcn 2 and attenuated pulmonary arterial abnormalities and right ventricular hypertrophy and reduced right ventricular systolic pressure in KD rats. In conclusion, Lcn 2 remarkably facilitates proliferative ER stress in PASMCs, which probably accounts for KD-related pulmonary arterial abnormalities.

Myocardial ischaemia is usually accompanied by inflammatory response which plays a critical role in the myocardial healing and scar formation, while persistent inflammatory response contributes greatly to the myocardial remodeling and consequent heart failure. Metformin (Met), a widely used hypoglycemic drug, has increasingly been shown to exert remarkable cardioprotective effect on ischaemic myocardial injury such as acute myocardial infarction (AMI). However, the underlying mechanisms are still far from being fully understood. In this study, a mouse model of AMI was established through ligating the left anterior descending coronary artery (LAD), 100 mg/kg Met was given immediately after operation once daily for 3 days. It was demonstrated that Met effectively improved the cardiac haemodynamics (LVSP, LVEDP, +dp/dt, −dp/dt), diminished the infarct size, alleviated the disarrangement of myocardial cells and reduced the infiltration of inflammatory cells (macrophages, neutrophils and lymphocytes) in the heart of AMI mice. Mechanistically, Met decreased the expression of NLRP3 and enhanced the accumulation of LC3 puncta in F4/80-positive macrophages in the heart of AMI mice. Single cell suspension of cardiac macrophages was prepared from AMI mice and exhibited increased NLRP3 mRNA and protein expression. In contrast, Met decreased the expression of NLRP3 and p62, whereas increased the ratio of LC3II/LC3I. Additionally, both conditioned medium from H9c2 cardiomyocytes exposed to hydrogen peroxide (H9c2-H2O2-CM) and combination of mtDNA and ATP (mtDNA-ATP) increased the expression of NLRP3 and cleaved caspase-1 (p10) as well as intracellular ROS production in RAW264.7 macrophages, which were abrogated by Met treatment. Strikingly, chloroquine (CQ), 3-methyladenine (3-MA) and knockdown of autophagy-related gene (Atg5) abrogated the inhibitory effects of Met on H9c2-H2O2-CM and mtDNA-ATP-induced NLRP3 expression, release of IL-1β and IL-18 as well as ROS production in RAW264.7 macrophages. Collectively, these findings suggest that Met protects against ischaemic myocardial injury through alleviating autophagy-ROS-NLRP3 axis-mediated inflammatory response in macrophages.

Aging is a pivotal risk factor for developing cardiovascular diseases (CVD) due to the lifelong exposure to various risk factors that may affect the heart and vasculature during aging. AMP-activated protein kinase (AMPK), a serine/threonine protein kinase, is a pivotal endogenous energy regulator that protects against various pathological alterations. In this report, we first introduced the protective mechanisms of AMPK signaling in myocardium, such as oxidative stress, apoptosis, inflammation, autophagy and inflammatory response. Next, we introduced the potential correlation between AMPK and cardiac aging. Then, we highlighted the roles of AMPK signaling in cardiovascular diseases, including myocardial ischemia, cardiomyopathy, and heart failure. Lastly, some potential directions and further perspectives were expanded. The information extends our understanding on the protective roles of AMPK in myocardial aging, which may contribute to the design of drug targets and sheds light on potential treatments of AMPK for aging-related CVD.

This study aims to establish and validate a radiomics nomogram based on contrast-enhanced spectral mammography (CESM) for prediction of axillary lymph node (ALN) metastasis in breast cancer. This retrospective study included 394 patients with breast cancer who underwent CESM examination in two hospitals. The least absolute shrinkage and selection operator (LASSO) logistic regression was established for feature selection and utilized to construct radiomics signature. The nomogram model included the radiomics signature and independent clinical factors. The receiver operating characteristic (ROC) curves were used to confirm the performance of the nomogram in training and validation sets. The nomogram model, which includes the radiomics signature and the CESM-reported lymph node status, has areas under the ROC curves of 0.774 (95% confidence interval (CI) 0.689–0.858), 0.767 (95% CI 0.583–0.857), and 0.79 (95% CI 0.63–0.94) in the training, internal validation, and external validation sets, respectively. We identified the cutoff score in the radiomics nomogram as − 1.49, which corresponded to a total point of 49 that could diagnose ALN metastasis with a sensitivity of > 95%. The CESM-based radiomics nomogram is a noninvasive predictive tool that shows good application prospects in the preoperative prediction of ALN metastasis in breast cancer. • The CESM-based radiomics nomogram shows good performance in predicting ALN metastasis in breast cancer. • The application of radiomics nomogram in this study provides a new approach for establishing a prediction model with multiple characteristics. • The nomogram has good application prospects in assisting clinical decision makers.

Membership determination with classification is an essential function for a variety of applications, such as network routing and packet inspection. We aim to constitute a mechanism capable of performing such a service with the considerations of efficiency and error ratio issues. The proposed method employs an array structure, in which each unit composes of multiple bits. The array houses a circular bound representation and a Bloom filter, where the former encodes the members and makes judgments of queries, while the latter acts as a secondary means for programming cases indeterministic by the former. Experimental results show that the error ratios were competitive and consistent with different levels of classification, as well as the memory space utilized. The lookup time decreased as the memory space increased. We depict specific characteristics for tackling the problem, including simplicity of data structure for encoding the members, avoidance of checking all classification IDs in the lookup process, and adoption of an auxiliary means for improving the error ratios. The ID-bound method is novel, and with the Bloom filter as the assistant, the proposed approach is robust in performances of both efficiency and error ratio.

In recent years, all-inorganic perovskite materials have set off a research boom owing to features, such as good thermal stability, suitable bandgap, and fascinating optical properties. However, the power conversion efficiency (PCE) and the ambient stability of all-inorganic perovskite solar cells still remain a challenge. Herein, we investigate the effect of the addition of InI3 into CsPbI3 film on the corresponding device. InI3 incorporation could retard the crystallization process and control the growth rate of CsPbI3 polycrystalline films, yielding a high quality film with large grains and few voids. The increment in electrostatic potential and the reduction of carrier recombination enabled the open-circuit voltage of fabricated perovskite solar cell to be increased from 0.89 to 0.99 V. The champion device delivered a power conversion efficiency of 17.09%, which is higher than 14.36% for the reference device. And the InI3-included solar cell without any encapsulation retained 77% of its original efficiency after 860 h aging at room temperature in N2 condition.

Many information technology courses frequently use the learning by doing strategy in vocational high schools. Particularly, learning computer application operating skills is essential for students because excellent computer application operating skills can help them attain good jobs. However, when fostering students’ computer application operating skills by teaching in vocational high school using the learning by doing strategy, a teacher learns that helping all students, evaluating their learning problems, and providing feedback to correct their mistakes are challenging. After investigating the challenge, a machine-learning-based peer tutor recommender system (MPTRS) with automated assessment was proposed to enhance students’ learning performance in computer application operating skills. The advanced automated assessment system (AAS) used computer vision technology to evaluate student assignments and instantly return feedback. The recommendation mechanism of the MPTRS enhanced mutual help among students based on their social relationships, learning performance, and recommendation feedback. Furthermore, machine-learning techniques were used to improve recommendations. In the experiment, the experimental group used the proposed system, and the control group used a conventional commercial automated grading system. From the experimental results, the learning performance of the experimental group significantly improved between the pretest and post-test. Students can correct and complete more assignments using the advanced AAS and students who behind in learning also can use the peer tutor recommender function for asking help. Participants were also satisfied with the proposed advanced AAS and MPTRS. It is worth to promote the proposed system to teachers of adopting the learning-by-doing strategy in computer application classes.

Ovarian cancer (OC) is the most lethal gynaecological malignancy, characterized by high recurrence and mortality. However, the mechanisms of its pathogenesis remain largely unknown, hindering the investigation of the functional roles. This study sought to identify key hub genes that may serve as biomarkers correlated with prognosis. Here, we conduct an integrated analysis using the weighted gene co‐expression network analysis (WGCNA) to explore the clinically significant gene sets and identify candidate hub genes associated with OC clinical phenotypes. The gene expression profiles were obtained from the MERAV database. Validations of candidate hub genes were performed with RNASeqV2 data and the corresponding clinical information available from The Cancer Genome Atlas (TCGA) database. In addition, we examined the candidate genes in ovarian cancer cells. Totally, 19 modules were identified and 26 hub genes were extracted from the most significant module (R 2 = .53) in clinical stages. Through the validation of TCGA data, we found that five hub genes (COL1A1, DCN, LUM, POSTN and THBS2) predicted poor prognosis. Receiver operating characteristic (ROC) curves demonstrated that these five genes exhibited diagnostic efficiency for early‐stage and advanced‐stage cancer. The protein expression of these five genes in tumour tissues was significantly higher than that in normal tissues. Besides, the expression of COL1A1 was associated with the TAX resistance of tumours and could be affected by the autophagy level in OC cell line. In conclusion, our findings identified five genes could serve as biomarkers related to the prognosis of OC and may be helpful for revealing pathogenic mechanism and developing further research.

Transverse bending damage morphologies of carbon fiber composite tubes with different ply structures were investigated by the micro-XCT characterization. Structural effects of the plain, twill and winding on the damage mechanism were analyzed. The experimental results present fiber-resin cracking, interlayer delamination and fiber tows breakage with structural deformation from the peak load to final catastrophic failure. Woven fabric plies in the plain and twill composite tubes cannot be effectively slipped because of their tight interlaced structures, which makes the load propagate along the warp and weft fiber tows, resulting in more fiber tows breakage under bending-induced stretching. There is no interlaced effect on the failure mechanism for the winding tubes, resulting in a fact that the bending load can only be transferred from the fiber-resin or the layer-to-layer interface, with more interlaminar slippage and obvious springback behaviors under in-plane shear. For investigating the interlaced effect on failure mechanism, plain and winding models under transverse bending were established using continuous shell elements, and different constitutive description were used to simulate interlayer failure and intra-layer failure behaviors. By comparing the numerical results with the experimental ones, the influence of the fabric structure on the failure behavior of the tube were analyzed.

OBJECTIVES To investigate the coronary venous system (CVS) and its spatial relationship with coronary arteries by using 256-slice computed tomography (CT). METHODS One hundred one patients underwent coronary CT angiography by using a 256-slice CT. In each patient, the CVS and its spatial relationship with coronary arteries were analyzed. We measured the diameters and angulations of the coronary sinus (CS), great cardiac vein, anterior interventricular vein (AIV), left marginal vein, posterior vein of the left ventricle (PVLV), and posterior interventricular vein (PIV), and the distances, respectively, from the CS ostium and from the crossing point to the ostium of corresponding tributaries. RESULTS The following 5 pairs of veins and arteries had a higher frequency of intersecting compared with others: the CS/great cardiac vein and the left circumflex coronary artery (97.1%), the AIV and the diagonal or ramus branch (92.1%), the PIV and the posterior branch of left ventricle artery (88.1%), the left marginal vein and the circumflex or circumflex marginal (73.9%), and the PVLV and the circumflex or circumflex marginal (31.6%). The other 2 pairs had a higher frequency of running parallel to each other: the AIV and the left anterior descending artery (76.2%) and the PIV and the posterior descending artery (54.4%). Most tributaries were lateral to their corresponding arteries at the crossing point except for the AIV. For the PVLV and PIV, the distances from the crossing point to the ostium of corresponding veins when the veins were lateral to the arteries were smaller than those when the veins were medial to the arteries (P < 0.05). CONCLUSIONS The CVS and its anatomical relationship with the coronary arterial system can be examined with details by using a 256-slice CT, which has important clinical implications.

We providethe spatial distribution of cattle, sheep, and livestock grazing on grasslands at a spatial resolution of 15 arc-second (approximately 500 m at the equator) on the Qinghai-Tibet Plateau (QTP) by using the dasymetric mapping approach. Spatial disaggregation weights were derived by using the prediction from a random forest model that linked county-level census livestock numbers to topography, climate, vegetation, and socioeconomic predictors. Both internal and external cross-validation showed model results could well capture the spatial variation of livestock numbers on the QTP.This study is supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, grant no. 2019QZKK0906).

Incorporating seasonality into livestock spatial distribution is of great significance for studying the complex system interaction between climate, vegetation, water, and herder activities, associated with livestock. The Qinghai-Tibet Plateau (QTP) has the world’s most elevated pastoral area and is a hot spot for global environmental change. This study provides the spatial distribution of cattle, sheep, and livestock grazing on the warm-season and cold-season pastures at a 15 arc-second spatial resolution on the QTP. Warm/cold-season pastures were delineated by identifying the key elements that affect the seasonal distribution of grazing and combining the random forest classification model, and the average area under the receiver operating characteristic curve of the model is 0.98. Spatial disaggregation weights were derived using the prediction from a random forest model that linked county-level census livestock numbers to topography, climate, vegetation, and socioeconomic predictors. The coefficients of determination of external cross-scale validations between dasymetric mapping results and township census data range from 0.52 to 0.70. The data could provide important information for further modeling of human-environment interaction under climate change for this region.

BackgroundAlthough checkpoint blockade is a promising approach for the treatment of hepatocellular carcinoma (HCC), subsets of patients expected to show a response have not been established. As T cell-mediated tumor killing (TTK) is the fundamental principle of immune checkpoint inhibitor therapy, we established subtypes based on genes related to the sensitivity to TKK and evaluated their prognostic value for HCC immunotherapies.MethodsGenes regulating the sensitivity of tumor cells to T cell-mediated killing (referred to as GSTTKs) showing differential expression in HCC and correlations with prognosis were identified by high-throughput screening assays. Unsupervised clustering was applied to classify patients with HCC into subtypes based on the GSTTKs. The tumor microenvironment, metabolic properties, and genetic variation were compared among the subgroups. A scoring algorithm based on the prognostic GSTTKs, referred to as the TCscore, was developed, and its clinical and predictive value for the response to immunotherapy were evaluated.ResultsIn total, 18 out of 641 GSTTKs simultaneously showed differential expression in HCC and were correlated with prognosis. Based on the 18 GSTTKs, patients were clustered into two subgroups, which reflected distinct TTK patterns in HCC. Tumor-infiltrating immune cells, immune-related gene expression, glycolipid metabolism, somatic mutations, and signaling pathways differed between the two subgroups. The TCscore effectively distinguished between populations with different responses to chemotherapeutics or immunotherapy and overall survival.ConclusionsTTK patterns played a nonnegligible role in formation of TME diversity and metabolic complexity. Evaluating the TTK patterns of individual tumor will contribute to enhancing our cognition of TME characterization, reflects differences in the functionality of T cells in HCC and guiding more effective therapy strategies.

Background The interaction between tumor microenvironment (TME) and tumors offers various targets in mounting anti-tumor immunotherapies. However, the prognostic biomarkers in endometrial carcinoma (EC) are still limited. Here, we aimed to analyze the TME features and identify novel prognostic biomarkers for EC. Methods ESTIMATE, CIBERSORT, protein-protein interaction (PPI) network, univariate and multivariate Cox regression, and functional enrichment analysis were performed to identify immune- and survival-related hub genes as well as possible molecular mechanisms. The limma package and deconvolution algorithm were adopted to estimate the abundance of tumor-infiltrating immune cells (TICs) and their relationship with the target gene. In the validation section, tissue microarrays (TMAs) of EC and multiplex immunohistochemistry (m-IHC) were evaluated to validate the expression of TNFRSF4, and its correlation with immune markers, including CD4, CD8, and FOXP3. Besides, the receiver operating characteristic (ROC) curve was plotted to determine the diagnostic performance of TNFRSF4, CD4, CD8, and FOXP3 in EC. Results Two genes, TNFRSF4 and S1PR4, were screened out from 386 intersection differential expression genes (DEGs) shared by ImmuneScore and StromalScore in EC. Highlighted by TNFRSF4, we found that it was not only positively correlated with the TICs (mainly CD4+ T cells, CD8+ T cells, and Tregs) but significantly related to the prognosis in patients of EC, both verified by data from The Cancer Genome Altas (TCGA)-EC database and clinical samples. At the same time, the expression trend of TNFRSF4 was further confirmed by an integrated meta-analysis based on six microarrays from the Gene Expression Omnibus database (GEO). Conclusions Collectively, TNFRSF4, a previously unrecognized key player in EC, could serve as a potential biomarker for prognosis prediction and immunomodulation of EC.

The file attached to this record is the author's final peer reviewed version. This paper proposes a novel grey dynamic double incentive decision-making model to evaluate the high-quality development of manufacturing industry. First, we define the concepts of the improved grey incidence analysis and power weight Heronian aggregation (PWHA) operator. Then, we present the double incentive factors and determine incentive static evaluation values. In addition, we construct the weight vector of the time series. Guided by the incentive static evaluation values and weight vector of the time series, the dynamic evaluation values are produced. Finally, a practical example of the manufacturing industry in the Yangtze River Delta (YRD) demonstrates the effectiveness and application of the proposed model.

Cisplatin is widely used in the treatment of solid tumors, but its application is greatly limited due to its nephrotoxicity; thus, there is still no effective medicine for the treatment of cisplatin-induced acute kidney injury (Cis-AKI). We previously identified that polydatin (PD) exerts nephroprotective effects by antioxidative stress in AKI models. Recent evidence suggests that oxidative stress-induced molecular events overlap with the process of ferroptosis and that there are common molecular targets, such as glutathione (GSH) depletion and lipid peroxidation. Nevertheless, whether the nephroprotective effect of PD is related to anti-ferroptosis remains unclear. In this study, the inhibitory effect of PD on ferroptosis was observed in both cisplatin-treated HK-2 cells (20 μM) in vitro and a Cis-AKI mouse model (20 mg/kg, intraperitoneally) in vivo, characterized by the reversion of excessive intracellular free iron accumulation and reactive oxygen species (ROS) generation, a decrease in malondialdehyde (MDA) content and GSH depletion, and an increase in glutathione peroxidase-4 (GPx4) activity. Remarkably, PD dose-dependently alleviated cell death induced by the system Xc− inhibitor erastin (10 μM), and the effect of the 40 μM dose of PD was more obvious than that of ferrostatin-1 (1 μM) and deferoxamine (DFO, 100 μM), classical ferroptosis inhibitors. Our results provide insight into nephroprotection with PD in Cis-AKI by inhibiting ferroptosis via maintenance of the system Xc−-GSH-GPx4 axis and iron metabolism.

The aim of this study is to present three contributing factors to kinesthetic learning. This study employed advanced recognition technologies, pedagogical mechanisms, and interesting activity design. First, kinesthetic learning with a speaking accuracy measuring function to facilitate English as foreign language (EFL) learning is proposed. Namely, this function is about measuring the learners’ speaking accuracy and recognizing whether their body movements and facial expressions match their English speaking content via recognition technology. This function is expected to improve the learners’ pronunciation and motivation during the experiment. Second, we propose Collaborative Kinesthetic English Learning System based on the second-language acquisition method Total Physical Response. By integrating our system with Total Physical Response, it helps the learners improve EFL learning with physical movements and stimulates their memorization and motivation from collaborative perspectives. Finally, the last significant contribution of this study is to design and implement interesting interactive activities: Experience-based Sentence-Making and Interactive Dialogue. These two activities are to help learners produce their English output. In this study, our experimental results show Experience-based Sentence-Making and Interactive Dialogue can significantly improve EFL learning.

Frontometaphyseal dysplasia 2 (FMD2) is a rare disease caused by MAP3K7 gene mutation. We report a 7-year-old sporadic patient with FMD2 due to a de novo splicing variant in MAP3K7. He has the common characteristics of FMD2 but also has some characteristics that have never been reported, which increases the clinical phenotype of FMD2. Moreover, no systematic description of the imaging characteristics of FMD2 in computed tomography (CT) is available. In the present work, we found some different features of FMD2, reviewed previous literature, and summarized the general imaging manifestations of FMD2. This case emphasizes the important clinical value of CT and VR in the diagnosis of FMD2. We can clearly find the characteristics of FMD2 by CT examination, indicating its great significance for the prompt diagnosis and treatment of FMD2 patients.La displasia frontometafisaria 2 (DFM2) es una enfermedad rara causada por una mutación en el gen MAP3K7. En este artículo, se informa sobre un paciente de 7 años con DFM2 causada por una variante nueva de corte y empalme en MAP3K7. El paciente presenta las características frecuentes de la DFM2, pero algunas nunca antes informadas. No se dispone de una descripción sistemática de las características de las imágenes tomográficas de la DFM2. Describimos ciertas diferencias en las características de la DFM2, la bibliografía publicada y las manifestaciones imagenológicas generales de la DFM2. Este caso resalta la importancia del valor clínico de la tomografía computada (TC) y la renderización de volúmenes (VR) en el diagnóstico de la DFM2. Las características de la DFM2 pueden observarse claramente en los estudios tomográficos, lo que señala la gran importancia de la TC para el diagnóstico y el tratamiento precoces de los pacientes con DFM2.

Necroptosis contribute to the pathogenesis of myocardial ischemia/reperfusion (MI/R) injury. Ginsenoside Rg2 has been reported to have cardioprotective effects against MI/R injury; however, the underlying mechanism remains unclear. This work aimed to investigate the effect of ginsenoside Rg2 on necroptosis induced by MI/R and to explore the mechanism. In this study, hypoxia/reoxygenation (H/R) injury model was established in H9c2 cells.In vivo, male C57/BL6 mice were subjected to myocardial ischemia 30 min/reperfusion 4 h. Rg2 (50 mg/kg) or vehicle was intravenously infused 5 min before reperfusion. Cardiac function and the signaling pathway involved in necroptosis were investigated. Compared with H/R group, Rg2 significantly inhibited H/R-induced cardiomyocyte death. Rg2 treatment effectively inhibited the phosphorylation of RIP1, RIP3, and MLKL in H/R cardiomyocytes, and inhibited RIP1/RIP3 complex (necrosome) formation. In mice, Rg2 treatment manifested significantly lower ischemia/reperfusion (I/R)-induced myocardial necroptosis, as evidenced by decrease in phosphorylation of RIP1, RIP3, and MLKL, inhibited lactate dehydrogenase (LDH) release and Evans blue dye (EBD) penetration. Mechanically, an increased level of tumor necrosis factor α (TNFα), interleukin (IL)-1β, IL-6, and MCP-1 were found in MI/R hearts, and Rg2 treatment significantly inhibit the expression of these factors. We found that TNFα-induced phosphorylation of RIP1, RIP3, and MLKL was negatively correlated with transforming growth factor-activated kinase 1 (TAK1) phosphorylation, and inhibition of TAK1 phosphorylation led to necroptosis enhancement. More importantly, Rg2 treatment significantly increased TAK1 phosphorylation, enhanced TAK1 binding to RIP1 while inhibiting RIP1/RIP3 complex, ultimately reducing MI/R-induced necroptosis. These findings highlight a new mechanism of Rg2-induced cardioprotection: reducing the formation of RIP1/RIP3 necrosome by regulating TAK1 phosphorylation to block necroptosis induced by MI/R.

After long-term oxidation and energy storage, broken coal body borehole walls and drainage shaft walls may cause spontaneous combustion during gas extraction. The high-temperature thermal shock caused by the spontaneous combustion of coal incurs thermal damage on adjacent coal, which, in turn, causes changes in the mechanical properties of the coal. However, only a few studies have been conducted in this context, which has limited our understanding of the thermal damage characteristics of coal bodies in such situations. This study aimed to experimentally investigate the correlation between the crack evolution law and the mechanical properties of coal bodies at different temperatures (50–300°C) using heat-force loading considering Ping Mei No. 10 coal mine as the research object. The results suggest that the coal body experiences a large amount of visible damage, and becomes increasingly complex. At 50–300°C, some indexes (such as longitudinal wave velocity, Poisson’s ratio, compressive strength, elastic modulus, impact energy index, and pre-peak strain) are positively correlated with temperature. In addition, the dynamic failure time and temperature show a negative correlation, and the overall change slope is small. The relationship between each index and temperature at 200–300°C is opposite to that at 50–200°C, and the overall change slope is larger. Moreover, when the oxidation temperature exceeds 200°C, the destruction of the coal body changes from elastic brittleness to ductility-plasticity. High-temperature oxidation incurs irreversible thermal damage of coal. Hence, it is necessary to focus on the changes in mechanical properties of coal after a spontaneous combustion process is extinguished.

Background Postpartum depression (PPD) is a common mood disorder with increasing incidence year by year. However, the dynamic changes in local neural activity remain unclear. In this study, we utilized the dynamic amplitude of low-frequency (dALFF) to investigate the abnormal temporal variability of local neural activity. Methods Twenty-four patients with PPD and nineteen healthy postpartum women controls (HCs) matched for age, education level and body mass index were examined by resting-state functional magnetic resonance imaging (rs-fMRI). A sliding-window method was used to assess the dALFF, and a k-means clustering method was used to identify dALFF states. Two-sample t-test was used to compare the differences of dALFF variability and state metrics between PPD and HCs. Pearson correlation analysis was used to analyze the relationship between dALFF variability, states metrics and clinical severity. Results (1) Patients with PPD had lower variance of dALFF than HCs in the cognitive control network, cerebellar network, and sensorimotor network. (2) Four dALFF states were identified, and the number of transitions between the four dALFF states increased in the patients compared with that in HCs. (3) Multiple dALFF states were found to be correlated with the severity of depression. The variance of dALFF in the right middle frontal gyrus was negatively correlated with the Edinburgh postnatal depression scale score. Conclusion This study provides new insights into the brain dysfunction of PPD from the perspective of dynamic local brain activity, and highlights its important role in understanding the neurophysiological mechanisms of PPD.