Hepatic Fibroblast Growth Factor 21 Is Involved in Mediating Functions of Liraglutide in Mice With Dietary Challenge.

BACKGROUND AND AIMS: Several studies have shown that expression of hepatic fibroblast growth factor 21 (FGF21) can be stimulated by glucagon-like peptide 1 (GLP-1)-based diabetes drugs. As GLP-1 receptor (GLP-1R) is unlikely to be expressed in hepatocytes, we aimed to compare such stimulation in mice and in mouse hepatocytes, determine the involvement of GLP-1R, and clarify whether FGF21 mediates certain functions of the GLP-1R agonist liraglutide. APPROACH AND RESULTS: Liver FGF21 expression was assessed in mice receiving a daily liraglutide injection for 3 days or in mouse primary hepatocytes (MPHs) undergoing direct liraglutide treatment. The effects of liraglutide on metabolic improvement and FGF21 expression were then assessed in high-fat diet (HFD)-fed mice and compared with the effects of the dipeptidyl-peptidase 4 inhibitor sitagliptin. Animal studies were also performed in Glp1r-/- mice and liver-specific FGF21-knockout (lFgf21-KO) mice. In wild-type mouse liver that underwent RNA sequencing and quantitative reverse-transcription PCR, we observed liraglutide-stimulated hepatic Fgf21 expression and a lack of Glp1r expression. In MPHs, liraglutide did not stimulate Fgf21. In mice with HFD-induced obesity, liraglutide or sitagliptin treatment reduced plasma triglyceride levels, whereas their effect on reducing body-weight gain was different. Importantly, increased hepatic FGF21 expression was observed in liraglutide-treated mice but was not observed in sitagliptin-treated mice. In HFD-fed Glp1r-/- mice, liraglutide showed no beneficial effects and could not stimulate Fgf21 expression. In lFgf21-KO mice undergoing dietary challenge, the body-weight-gain attenuation and lipid homeostatic effects of liraglutide were lost or significantly reduced. CONCLUSIONS: We suggest that liraglutide-stimulated hepatic Fgf21 expression may require GLP-1R to be expressed in extrahepatic organs. Importantly, we revealed that hepatic FGF21 is required for liraglutide to lower body weight and improve hepatic lipid homeostasis. These observations advanced our mechanistic understanding of the function of GLP-1-based drugs in NAFLD.

Estrogen-Wnt signaling cascade regulates expression of hepatic fibroblast growth factor 21.

We have generated the transgenic mouse line LTCFDN in which dominant negative TCF7L2 (TCF7L2DN) is specifically expressed in the liver during adulthood. Male but not female LTCFDN mice showed elevated hepatic and plasma triglyceride (TG) levels, indicating the existence of estrogen-ß-cat/TCF signaling cascade that regulates hepatic lipid homeostasis. We show here that hepatic fibroblast growth factor 21 (FGF21) expression was reduced in male but not in female LTCFDN mice. The reduction was not associated with altered hepatic expression of peroxisome proliferator-activated receptor α (PPARα). In mouse primary hepatocytes (MPH), Wnt-3a treatment increased FGF21 expression in the presence of PPARα inhibitor. Results from our luciferase-reporter assay and chromatin immunoprecipitation suggest that evolutionarily conserved TCF binding motifs (TCFBs) on Fgf21 promoter mediate Wnt-3a-induced Fgf21 transactivation. Female mice showed reduced hepatic FGF21 production and circulating FGF21 level following ovariectomy (OVX), associated with reduced hepatic TCF expression and ß-catenin S675 phosphorylation. Finally, in MPH, estradiol (E2) treatment enhanced FGF21 expression, as well as binding of TCF7L2 and ribonucleic acid (RNA) polymerase II to the Fgf21 promoter; and the enhancement can be attenuated by the G-protein-coupled estrogen receptor 1 (GPER) antagonist G15. Our observations hence indicate that hepatic FGF21 is among the effectors of the newly recognized E2-ß-cat/TCF signaling cascade.NEW & NOTEWORTHY FGF21 is mainly produced in the liver. Therapeutic effect of FGF21 analogues has been demonstrated in clinical trials on reducing hyperlipidemia. We show here that Fgf21 transcription is positively regulated by Wnt pathway effector ß-cat/TCF. Importantly, hepatic ß-cat/TCF activity can be regulated by the female hormone estradiol, involving GPER. The investigation enriched our understanding on hepatic FGF21 hormone production, and expanded our view on metabolic functions of the Wnt pathway in the liver.

Ginsenoside Rb1 attenuates age-associated vascular impairment by modulating the Gas6 pathway.

CONTEXT: Ginsenoside Rb1 (Rb1) exerts many beneficial effects and protects against cardiovascular disease. OBJECTIVE: To investigate whether Rb1 could attenuate age-related vascular impairment and identify the mechanism. MATERIALS AND METHODS: Female C57BL/6J mice aged 2 and 18 months, randomly assigned to Young, Young + 20 mg/kg Rb1, Old + vehicle, Old + 10 mg/kg Rb1 and Old + 20 mg/kg Rb1 groups, were daily intraperitoneal injected with vehicle or Rb1 for 3 months. The thoracic aorta segments were used to inspect the endothelium-dependent vasorelaxation. Left thoracic aorta tissues were collected for histological or molecular expression analyses, including ageing-related proteins, markers relevant to calcification and fibrosis, and expression of Gas6/Axl. RESULTS: We found that in Old + vehicle group, the expression of senescence proteins and cellular adhesion molecules were significantly increased, with worse endothelium-dependent thoracic aorta relaxation (58.35% ± 2.50%) than in Young group (88.84% ± 1.20%). However, Rb1 treatment significantly decreased the expression levels of these proteins and preserved endothelium-dependent relaxation in aged mice. Moreover, Rb1 treatment also reduced calcium deposition, collagen deposition, and the protein expression levels of collagen I and collagen III in aged mice. Furthermore, we found that the downregulation of Gas6 protein expression by 41.72% and mRNA expression by 52.73% in aged mice compared with young mice was abrogated by Rb1 treatment. But there was no significant difference on Axl expression among the groups. CONCLUSIONS: Our study confirms that Rb1 could ameliorate vascular injury, suggesting that Rb1 might be a potential anti-ageing related vascular impairment agent.

Glucagon-like peptide-1 receptor mediates the beneficial effect of liraglutide in an acute lung injury mouse model involving the thioredoxin-interacting protein.

Repurposing clinically used drugs is among the important strategies in drug discovery. Glucagon-like peptide-1 (GLP-1) and its diabetes-based drugs, such as liraglutide, possess a spectrum of extra-pancreatic functions, while GLP-1 receptor (GLP-1R) is most abundantly expressed in the lung. Recent studies have suggested that GLP-1-based drugs exert beneficial effects in chronic, as well as acute, lung injury rodent models. Here, we show that liraglutide pretreatment reduced LPS induced acute lung injury in mice. It significantly reduced lung injury score, wet/dry lung weight ratio, bronchoalveolar lavage fluid immune cell count and protein concentration, and cell apoptosis in the lung, and it was associated with reduced lung inflammatory cytokine and chemokine gene expression. Importantly, these effects were virtually absent in GLP-1R-/- mice. A well-known function of GLP-1 and GLP-based drugs in pancreatic ß-cells is the attenuation of high-glucose stimulated expression of thioredoxin-interacting protein (TxNIP), a key component of inflammasome. LPS-challenged lungs showed elevated TxNIP mRNA and protein expression, which was attenuated by liraglutide treatment in a GLP-1R-dependent manner. Hence, our observations suggest that GLP-1R is essential in mediating beneficial effects of liraglutide in acute lung injury, with the inflammasome component TxNIP as a potential target.

Beneficial effect of ER stress preconditioning in protection against FFA-induced adipocyte inflammation via XBP1 in 3T3-L1 adipocytes.

Adipose tissue inflammation is closely associated with the development of obesity and insulin resistance. Free fatty acids (FFAs) are a major inducer of obesity-related insulin resistance. Previously, we reported that endoplasmic reticulum (ER) stress potentially mediated retinal inflammation in diabetic retinopathy. The unfolded protein response (UPR) protects cells against damage induced by oxidative stress. X-box binding protein 1 (XBP1) plays a major role in protecting cells by modulating the UPR. However, the link between ER stress and adipocyte inflammation has been poorly investigated. In the present study, we found that pretreatment of 3T3-L1 adipocytes with a low dose of ER stress inducer tunicamycin inhibited FFA-induced upregulated expression of inflammatory cytokines. In addition, FFAs induced phosphorylation of the p65 subunit of NF-κB was largely inhibited by pretreatment with tunicamycin in 3T3-L1 adipocytes. Knockdown of XBP1 by siRNA markedly mitigated the protective effects of preconditioning against inflammation. Conversely, overexpression of XBP1 alleviated FFA-induced phosphorylation of IκB-α, IKKα/ß, and NF-κB, which was accompanied by decreased inflammatory cytokine expression. Collectively, these results imply a beneficial role of ER stress preconditioning in protecting against FFA-induced 3T3-L1 adipocyte inflammation, which is likely mediated through inhibition of the IKK/NF-κB pathway via XBP1.

Ginsenoside Rb1 Alleviates Oxidative Low-Density Lipoprotein-Induced Vascular Endothelium Senescence via the SIRT1/Beclin-1/Autophagy Axis.

Oxidative low-density lipoprotein (ox-LDL) induces endothelium senescence and promotes atherosclerosis. Ginsenoside Rb1 (gRb1) has been proved to protect human umbilical vein cells (HUVECs), but its effect on ox-LDL-induced endothelium senescence and the underlying mechanism remains unknown. This study is to explore the involvement of the SIRT1/Beclin-1/autophagy axis in the effect of gRb1 on protecting endothelium against ox-LDL-induced senescence. Hyperlipidemia of Sprague Dawley rats was induced by high-fat diet, and gRb1 was intraperitoneal injected. A senescence model of HUVECs induced by ox-LDL was also established. The results showed that gRb1 alleviated hyperlipidemia-induced endothelium senescence and ox-LDL-induced HUVECs senescence. GRb1 also restored the reductions in SIRT1 and autophagy, which were involved in the anti-senescence effects. Beclin-1 acetylation was reduced, and the correlation between SIRT1 and Beclin-1 was increased by gRb1. Results of our study demonstrated the anti-senescence function of gRb1 against hyperlipidemia in the endothelium, and the underlying mechanism involves the SIRT1/Beclin-1/autophagy axis.

Meta-analysis of the adverse effects of long-term azithromycin use in patients with chronic lung diseases.

The adverse effects of azithromycin on the treatment of patients with chronic lung diseases (CLD) were evaluated in the present study. MEDLINE and other databases were searched for relevant articles published until August 2013. Randomized controlled trials that enrolled patients with chronic lung diseases who received long-term azithromycin treatment were selected, and data on microbiological studies and azithromycin-related adverse events were abstracted from articles and analyzed. Six studies were included in the meta-analysis. The risk of bacterial resistance in patients receiving long-term azithromycin treatment was increased 2.7-fold (risk ratio [RR], 2.69 [95% confidence interval {95% CI}, 1.249, 5.211]) compared with the risk in patients receiving placebo treatment. On the other hand, the risk of bacterial colonization decreased in patients receiving azithromycin treatment (RR, 0.551 [95% CI, 0.460, 0.658]). Patients receiving long-term azithromycin therapy were at risk of increased impairment of hearing (RR, 1.168 [95% CI, 1.030, 1.325]). This analysis provides evidence supporting the idea that bacterial resistance can develop with long-term azithromycin treatment. Besides the increasingly recognized anti-inflammatory role of azithromycin used in treating chronic lung diseases, we should be aware of the potential for adverse events with its long-term use.

Simulation and prediction for the spatial heterogeneity of soil selenium bioavailability at different stratigraphic scales.

Stratigraphic lithology strongly influences the spatial heterogeneity of soil available selenium (ASe), however, it is often neglected in regional simulation. Therefore, taking the Jiangjin District, where the soil is richer in selenium (Se), as the research area, the changes of soil ASe at different spatial scales have been simulated by combining Geodetector and three popular models (Multiple linear regression (MLR), Random forest (RF) and BP neural network (BPN)). The results showed that modelling with 'Formation' as the spatial scale could reduce the influence of stratum lithology difference on the spatial heterogeneity of soil ASe and improve the model's prediction accuracy. Compared with the MLR (R2 = 0.52, root mean squares error (RMSE) = 13.217 µg kg-1) and BPN (R2 = 0.55, RMSE = 13.79 µg kg-1), the RF (R2 = 0.67, RMSE = 10.85 µg kg-1) exhibited higher R2 and smaller RMSE, and the simulation effect of soil ASe is the best in the Middle Jurassic Shaximiao Formation (J2s). The outcomes of variable importance analysis revealed that soil total selenium (TSe) and soil organic matter (SOM) were the imperative factors for predicting ASe. The scenario simulation prediction showed that in the next 40 years, due to the combined influence of SOM and pH, the content of ASe in soil developed in the J2s would decrease from 40.8 µg kg-1 to 37.8 µg kg-1, a 7.8 percent drop. The main areas of soil ASe loss were in the western farming areas. The ASe content in dry land and paddy fields decreased by 12.0% and 4.9%, respectively. Therefore, long-term agricultural production activities would lead to soil ASe loss. The present results could provide a new scheme for the simulation and prediction of regional soil ASe, which is helpful for scientific planning, utilization of selenium-rich soil resources, and development of regional agricultural economy.

Positive Effects of Organic Amendments on Soil Microbes and Their Functionality in Agro-Ecosystems.

Soil microbial characteristics are considered to be an index for soil quality evaluation. It is generally believed that organic amendments replacing chemical fertilizers have positive effects on changing microbial activity and community structure. However, their effects on different agro-ecosystems on a global scale and their differences in different environmental conditions and experimental durations are unclear. This study performed a meta-analysis based on 94 studies with 204 observations to evaluate the overall effects and their differences in different experimental conditions and duration. The results indicated that compared to chemical fertilizer, organic amendments significantly increased total microbial biomass, bacterial biomass, fungal biomass, Gram-positive bacterial biomass and Gram-negative bacterial biomass, and had no effect on the ratio of fungi to bacteria and ratio of Gram-positive bacteria to Gram-negative bacteria. Meanwhile, land use type, mean annual precipitation and soil initial pH are essential factors affecting microbial activity response. Organic-amendment-induced shifts in microbial biomass can be predominantly explained by soil C and nutrient availability changes. Additionally, we observed positive relationships between microbial functionality and microbial biomass, suggesting that organic-amendment-induced changes in microbial activities improved soil microbial functionality.

Meta-Analysis of Organic Fertilization Effects on Soil Bacterial Diversity and Community Composition in Agroecosystems.

Application of organic fertilizers or their combination with chemical fertilizers is a feasible practice for improving soil fertility and reducing soil degradation in agroecosystems, and these regulations are mainly mediated though soil microbial communities. Despite bacteria ranking among the most abundant and diverse groups of soil microorganisms, the effects of long-term organic fertilization (OF) and chemical-organic fertilization (COF) on soil bacterial diversity and community composition remain unclear. In this study, we conducted a meta-analysis and demonstrated that OF had no significant effect on bacterial alpha diversity. Application of chemical fertilizer and crop residue significantly decreased bacterial Richness index. Both OF and COF significantly altered bacterial community structure, with these changes being predominately attributed to shifts in soil pH. For bacterial phyla, both OF and COF significantly increased the relative abundance of Proteobacteria and Bacteroidetes, suggesting that OF and COF may cause the enrichment of copiotrophic taxa. In addition, COF significantly increased the relative abundance of Gammaproteobacteria but decreased the relative abundance of Acidobacteria. Overall, our results suggest that organic and chemical-organic fertilization can effectively maintain bacterial diversity and enhance soil fertility in agroecosystems, and the alteration of soil bacterial community structure is closely intertwined with soil pH.

Differential diagnosis of secondary hypertension based on deep learning.

Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and cerebrovascular disease events. Early aetiology identification can eliminate aetiologies and control blood pressure. However, inexperienced doctors often fail to diagnose secondary hypertension, and comprehensively screening for all causes of high blood pressure increases health care costs. To date, deep learning has rarely been involved in the differential diagnosis of secondary hypertension. Relevant machine learning methods cannot combine textual information such as chief complaints with numerical information such as the laboratory examination results in electronic health records (EHRs), and the use of all features increases health care costs. To reduce redundant examinations and accurately identify secondary hypertension, we propose a two-stage framework that follows clinical procedures. The framework carries out an initial diagnosis process in the first stage, on which basis patients are recommended for disease-related examinations, followed by differential diagnoses of different diseases based on the different characteristics observed in the second stage. We convert the numerical examination results into descriptive sentences, thus blending textual and numerical characteristics. Medical guidelines are introduced through label embedding and attention mechanisms to obtain interactive features. Our model was trained and evaluated using a cross-sectional dataset containing 11,961 patients with hypertension from January 2013 to December 2019. The F1 scores of our model were 0.912, 0.921, 0.869 and 0.894 for primary aldosteronism, thyroid disease, nephritis and nephrotic syndrome and chronic kidney disease, respectively, which are four kinds of secondary hypertension with high incidence rates. The experimental results show that our model can powerfully use the textual and numerical data contained in EHRs to provide effective decision support for the differential diagnosis of secondary hypertension.

Resveratrol intervention attenuates chylomicron secretion via repressing intestinal FXR-induced expression of scavenger receptor SR-B1.

Two common features of dietary polyphenols have hampered our mechanistic understanding of their beneficial effects for decades: targeting multiple organs and extremely low bioavailability. We show here that resveratrol intervention (REV-I) in high-fat diet (HFD)-challenged male mice inhibits chylomicron secretion, associated with reduced expression of jejunal but not hepatic scavenger receptor class B type 1 (SR-B1). Intestinal mucosa-specific SR-B1-/- mice on HFD-challenge exhibit improved lipid homeostasis but show virtually no further response to REV-I. SR-B1 expression in Caco-2 cells cannot be repressed by pure resveratrol compound while fecal-microbiota transplantation from mice on REV-I suppresses jejunal SR-B1 in recipient mice. REV-I reduces fecal levels of bile acids and activity of fecal bile-salt hydrolase. In Caco-2 cells, chenodeoxycholic acid treatment stimulates both FXR and SR-B1. We conclude that gut microbiome is the primary target of REV-I, and REV-I improves lipid homeostasis at least partially via attenuating FXR-stimulated gut SR-B1 elevation.

Ginsenoside Rb1 reverses H2O2-induced senescence in human umbilical endothelial cells: involvement of eNOS pathway.

OBJECTIVE: Senescence of endothelial cells has been implicated in endothelial dysfunction and atherogenesis. This study investigated the effects of Rb1, a major ginsenoside in ginseng, on H2O2-induced senescence in primary human umbilical vein endothelial cells (HUVECs). METHODS AND RESULTS: Real-time PCR and Western blot were used to detect the mRNA and protein expression, respectively. H2O2 (40∼100 µmol/L) effectively increased SA-ß-gal activity and PAI-1 mRNA levels, two important senescence related biomarkers, in HUVECs, which were dramatically inhibited by Rb1 pre-incubation. Furthermore, Rb1 administration reversed the H2O2-decreased protein and mRNA levels of eNOS and its phosphorylation at Ser-1177, and the increased eNOS phosphorylation at Thr-495. As a result, Rb1 pretreatment restored the NO generation, as assayed by nitrate reductase method. However, pretreatment with L-NAME, a NOS inhibitor, abolished all the inhibitory effects of Rb1 on senescence. Importantly, Rb1 modulated the H2O2-altered caveolin-1 and pAkt, two most important regulators of eNOS expression and activity, in HUVECs. CONCLUSIONS: We showed that Rb1 effectively protects HUVECs from senescence through eNOS modulation.

Comparison of Beneficial Metabolic Effects of Liraglutide and Semaglutide in Male C57BL/6J Mice.

OBJECTIVES: Semaglutide and liraglutide are glucagon-like peptide-1 (GLP-1)-based diabetes drugs. Semaglutide possesses a longer half-life. Utilizing relatively lower doses, we compared the beneficial metabolic effects of these 2 drugs in mice fed a high-fat diet (HFD), aiming to deepen our mechanistic understanding on their energy homeostatic functions. METHODS: Male C57BL/6J mice were fed an HFD for 10 weeks, followed by daily phosphate-buffered saline (PBS, as control); liraglutide (150 µg/kg body weight); or semaglutide (12 µg/kg body weight, low dose [LD]; or 60 µg/kg body weight, high dose [HD]) injection for 4 weeks. Metabolic tolerance and other tests were conducted within the 4-week period. Expression of metabolism-related genes, including Fgf21 in the liver and adipose tissues, was assessed after mice were euthanized. RESULTS: HFD-induced body weight gain, increasing inguinal fat tissue mass, glucose defects and insulin intolerance were effectively and comparably attenuated in the 3 experimental groups. HD semaglutide showed an even better effect on attenuating hyperleptinemia. Liraglutide but not semaglutide treatment enhanced hepatic fibroblast growth factor 21 (FGF21) protein level. All 3 experimental groups showed elevated expression of genes that encode pyruvate dehydrogenase kinase 4 and enoyl-CoA hydratase and 3-hydroxyacyl-coenzyme A dehydrogenase, associated with reduced plasma triglyceride levels. Finally, the plasma "GLP-1" level in HD semaglutide-treated mice was 14-fold higher than in HFD-fed control mice. CONCLUSIONS: Liraglutide, but not semaglutide, increased hepatic FGF21 protein level, whereas semaglutide had a greater effect on attenuating hyperleptinemia. Thus, these 2 GLP-1-based diabetes drugs may target metabolic organs, including liver and adipose tissue, with differing levels of efficacy.

Liraglutide stimulates the ß-catenin signaling cascade in mouse epididymal fat tissue.

Although canonical Wnt signaling pathway activation was shown to negatively regulate adipogenesis, recent investigations suggest that Wnt pathway effectors TCF7L2 and ß-catenin (ß-cat) in adipose tissues are also involved in energy homeostasis during adulthood. In assessing the metabolic beneficial effect of GLP-1-based diabetes drugs in high-fat diet (HFD)-challenged mice, we observed that liraglutide treatment affected the expression of a battery of adipose tissue-specific genes, including those that encode adiponectin and leptin, mainly in epididymal white adipose tissue (eWAT). Fourteen-week HFD challenge repressed TCF7L2 and ß-cat S675 phosphorylation in eWAT, while such repression was reversed by liraglutide treatment (150 µg/kg body weight daily) during weeks 10-14. In Glp1r-/-mice, liraglutide failed in stimulating TCF7L2 or ß-cat in eWAT. We detected Glp1r expression in mouse eWAT and its level is enriched in its stromal vascular fraction (SVF). Mouse eWAT-SVF showed reduced expression of Tcf7l2 and its Tcf7l2 level could not be stimulated by liraglutide treatment; while following adipogenic differentiation, rat eWAT-SVF showed elevated Tcf7l2 expression. Direct in vitro liraglutide treatment in eWAT-SVF stimulated CREB S133, ß-cat S675 phosphorylation, and cellular cAMP level. Thus, cAMP/ß-cat signaling cascade can be stimulated by liraglutide in eWAT via GLP-1R expressed in eWAT-SVF.

Deep Learning Networks Accurately Detect ST-Segment Elevation Myocardial Infarction and Culprit Vessel.

Early diagnosis of acute ST-segment elevation myocardial infarction (STEMI) and early determination of the culprit vessel are associated with a better clinical outcome. We developed three deep learning (DL) models for detecting STEMIs and culprit vessels based on 12-lead electrocardiography (ECG) and compared them with conclusions of experienced doctors, including cardiologists, emergency physicians, and internists. After screening the coronary angiography (CAG) results, 883 cases (506 control and 377 STEMI) from internal and external datasets were enrolled for testing DL models. Convolutional neural network-long short-term memory (CNN-LSTM) (AUC: 0.99) performed better than CNN, LSTM, and doctors in detecting STEMI. Deep learning models (AUC: 0.96) performed similarly to experienced cardiologists and emergency physicians in discriminating the left anterior descending (LAD) artery. Regarding distinguishing RCA from LCX, DL models were comparable to doctors (AUC: 0.81). In summary, we developed ECG-based DL diagnosis systems to detect STEMI and predict culprit vessel occlusion, thus enhancing the accuracy and effectiveness of STEMI diagnosis.

LASSO Regression-Based Diagnosis of Acute ST-Segment Elevation Myocardial Infarction (STEMI) on Electrocardiogram (ECG).

Electrocardiogram (ECG) is an important tool for the detection of acute ST-segment elevation myocardial infarction (STEMI). However, machine learning (ML) for the diagnosis of STEMI complicated with arrhythmia and infarct-related arteries is still underdeveloped based on real-world data. Therefore, we aimed to develop an ML model using the Least Absolute Shrinkage and Selection Operator (LASSO) to automatically diagnose acute STEMI based on ECG features. A total of 318 patients with STEMI and 502 control subjects were enrolled from Jan 2017 to Jun 2019. Coronary angiography was performed. A total of 180 automatic ECG features of 12-lead ECG were input into the model. The LASSO regression model was trained and validated by the internal training dataset and tested by the internal and external testing datasets. A comparative test was performed between the LASSO regression model and different levels of doctors. To identify the STEMI and non-STEMI, the LASSO model retained 14 variables with AUCs of 0.94 and 0.93 in the internal and external testing datasets, respectively. The performance of LASSO regression was similar to that of experienced cardiologists (AUC: 0.92) but superior (p < 0.05) to internal medicine residents, medical interns, and emergency physicians. Furthermore, in terms of identifying left anterior descending (LAD) or non-LAD, LASSO regression achieved AUCs of 0.92 and 0.98 in the internal and external testing datasets, respectively. This LASSO regression model can achieve high accuracy in diagnosing STEMI and LAD vessel disease, thus providing an assisting diagnostic tool based on ECG, which may improve the early diagnosis of STEMI.

Deep learning assessment of left ventricular hypertrophy based on electrocardiogram.

Background: Current electrocardiogram (ECG) criteria of left ventricular hypertrophy (LVH) have low sensitivity. Deep learning (DL) techniques have been widely used to detect cardiac diseases due to its ability of automatic feature extraction of ECG. However, DL was rarely applied in LVH diagnosis. Our study aimed to construct a DL model for rapid and effective detection of LVH using 12-lead ECG. Methods: We built a DL model based on convolutional neural network-long short-term memory (CNN-LSTM) to detect LVH using 12-lead ECG. The echocardiogram and ECG of 1,863 patients obtained within 1 week after hospital admission were analyzed. Patients were evenly allocated into 3 sets at 3:1:1 ratio: the training set (n = 1,120), the validation set (n = 371) and the test set 1 (n = 372). In addition, we recruited 453 hospitalized patients into the internal test set 2. Different DL model of each subgroup was developed according to gender and relative wall thickness (RWT). Results: The LVH was predicted by the CNN-LSTM model with an area under the curve (AUC) of 0.62 (sensitivity 68%, specificity 57%) in the test set 1, which outperformed Cornell voltage criteria (AUC: 0.57, sensitivity 48%, specificity 72%) and Sokolow-Lyon voltage (AUC: 0.51, sensitivity 14%, specificity 96%). In the internal test set 2, the CNN-LSTM model had a stable performance in predicting LVH with an AUC of 0.59 (sensitivity 65%, specificity 57%). In the subgroup analysis, the CNN-LSTM model predicted LVH by 12-lead ECG with an AUC of 0.66 (sensitivity 72%, specificity 60%) for male patients, which performed better than that for female patients (AUC: 0.59, sensitivity 50%, specificity 71%). Conclusion: Our study established a CNN-LSTM model to diagnose LVH by 12-lead ECG with higher sensitivity than current ECG diagnostic criteria. This CNN-LSTM model may be a simple and effective screening tool of LVH.

Rb1 protects endothelial cells from hydrogen peroxide-induced cell senescence by modulating redox status.

Senescence of endothelial cells has been proposed to play an important role in endothelial dysfunction and atherogenesis. In the present study we aimed to investigate whether ginsenoside Rb1, a major constituent of ginseng, protects endothelial cells from H(2)O(2)-induced endothelial senescence. While H(2)O(2) induced premature senescent-like phenotype of human umbilical vein endothelial cells (HUVECs), as judged by increased senescence-associated ß-galactosidase (SA-ß-gal) activity, enlarged, flattened cell morphology and sustained growth arrest, our results demonstrated that Rb1 protected endothelial cells from oxidative stress induced senescence. Mechanistically, we found that Rb1 could markedly increase intracellular superoxide dismutase (Cu/Zn SOD/SOD1) activity and decrease the malondialdehyde (MDA) level in H(2)O(2)-treated HUVECs, and suppress the generation of intracellular reactive oxygen species (ROS). Consistent with these findings, Rb1 could effectively restore the protein expression of Cu/Zn SOD, which was down-regulated in H(2)O(2) treated cells. Taken together, our data demonstrate that Rb1 exhibits antioxidant effects and antagonizes H(2)O(2)-induced cellular senescence.

Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data.

Cardiovascular and cerebrovascular diseases are leading causes of death worldwide, accounting for more than 40% of all deaths in China. Acute myocardial infarction (AMI) is a common cardiovascular disease and traditionally divided into ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI), which are known with different prognoses and treatment strategies. However, key regulatory genes and pathways involved in AMI that may be used as potential biomarker for prognosis are unknown. In this study, we employed both bulk and single-cell RNA-seq to construct gene regulatory networks and cell-cell communication networks. We first constructed weighted gene co-expression networks for differential expressed genes between STEMI and NSTEMI patients based on whole-blood RNA-seq transcriptomics. Network topological attributes (e.g., node degree, betweenness) were analyzed to identify key genes involved in different functional network modules. Furthermore, we used single-cell RNA-seq data to construct multilayer signaling network to infer regulatory mechanisms of the above key genes. PLAUR (receptor for urokinase plasminogen activator) was found to play a vital role in transducing inter-cellular signals from endothelial cells and fibroblast cells to intra-cellular pathways of myocardial cells, leading to gene expression involved in cellular response to hypoxia. Our study sheds lights on identifying molecular biomarkers for diagnosis and prognosis of AMI, and provides candidate key regulatory genes for further experimental validation.