Association of triglyceride glucose-related parameters with all-cause mortality and cardiovascular disease in NAFLD patients: NHANES 1999-2018.

BACKGROUND: The relationship between the triglyceride-glucose (TyG) index and its derived index, the triglyceride glucose-waist height ratio (TyG-WHtR), with mortality and cardiovascular diseases (CVDs) in patients with non-alcoholic fatty liver disease (NAFLD) remains unclear. METHODS: This study enrolled 6627 adults aged 18 and above diagnosed NAFLD from the National Health and Nutrition Examination Survey (NHANES, 1999-2018). Binary weighted logistic regression analyses, cox proportional hazards model and restricted cubic spline (RCS) were used to analyze the relationship between TyG and TyG-WHtR with all-cause mortality, CVD mortality and CVDs. Mediation analysis explored the mediating role of glycohemoglobin, insulin and hypertension in the above relationships. Meanwhile, the incremental predictive value of the TyG index and TyG-WHtR was further assessed. RESULTS: Except for no significant association between the TyG index and both all-cause mortality and chronic heart failure (CHF), both TyG and TyG-WHtR exhibited significant positive correlations or trends of positive correlation with all-cause mortality, CVD mortality, total-CVD, CHF, coronary heart disease (CHD) and angina pectoris. For all-cause mortality, CVD mortality and CHF, TyG-WHtR was a better predictor than TyG (TyG-WHtR: HR 1.31, 95%CI 1.03-1.66; HR 2.22, 95%CI 1.42-3.47; OR 3.99, 95%CI 1.79-8.93). In contrast, TyG index demonstrated a stronger association with total-CVD, CHD and angina pectoris (TyG index: OR 2.00, 95%CI 1.26-3.18; OR 1.85, 95%CI 1.19-2.91; OR 2.93, 95%CI 1.23-7.00). RCS analysis showed that after adjusting for covariates, most of the aforementioned relationships were linear(P overall < 0.0001, P-nonlinear > 0.05), while the associations of the TyG index and TyG-WHtR with all-cause mortality and CHF were non-linear(P overall < 0.0001, P nonlinear < 0.05). The addition of the TyG index and TyG-WHtR to the basic model for outcomes improved the C-statistics, net reclassification improvement value, and integrated discrimination improvement value. CONCLUSIONS: The predictive value of TyG or TyG-WHtR for all-cause mortality and cardiovascular risk in NAFLD patients was significant. The TyG index and TyG-WHtR might be valid predictors of cardiovascular outcomes of patients with NAFLD.

Dysfunctional regulatory T cell: May be an obstacle to immunotherapy in cardiovascular diseases.

Inflammatory responses are linked to cardiovascular diseases (CVDs) in various forms. Tregs, members of CD4+ T cells, play important roles in regulating immune system and suppressing inflammatory response, thus contributing to maintaining immune homeostasis. However, Tregs exert their powerful suppressive function relying on the stable phenotype and function. The stability of Tregs primarily depends on the FOXP3 (Forkhead box P3) expression and epigenetic regulation. Although Tregs are quite stable under physiological conditions, prolonged exposure to inflammatory cues, Tregs may lose suppressive function and require proinflammatory phenotype, namely plastic Tregs or ex-Tregs. There are extensive researches have established the beneficial role of Tregs in CVDs. Nevertheless, the potential risks of dysfunctional Tregs lack deep research. Anti-inflammatory and immunological modulation have been hotspots in the treatment of CVDs. Tregs are appealing because of their crucial role in resolving inflammation and promoting tissue repair. If alleviating inflammatory response through modulating Tregs could be a new therapeutic strategy for CVDs, the next step to consider is how to prevent the formation of dysfunctional Tregs or reverse detrimental Tregs to normal phenotype.

A Dynamic Community Detection Method for Complex Networks Based on Deep Self-Coding Network.

Aiming at the problem of community detection in complex dynamic networks, a dynamic community detection method based on graph convolution neural network is proposed. An encoding-decoding mechanism is designed to reconstruct the feature information of each node in the graph. A stack of multiple graph convolutional layers is considered as an encoder that encodes the node feature information into the potential vector space, while the decoder employs a simple two-layer perceptron to reconstruct the initial node features from the encoded vector information. The encoding-decoding mechanism achieves a re-evaluation of the initial node features. Subsequently, an additional local feature reconstruction loss is added after the decoder to aid the goal of graph classification. Further, stochastic gradient descent is applied to solve the problem in the loss function. Finally, the proposed model is experimentally validated based on the Karate Club and Football datasets. The experimental results show that the proposed model improves the NMI metric by an average of 7.65% and effectively mitigates the node oversmoothing problem. The proposed model is proved to have good detection accuracy.

Inhibitory Smads suppress pancreatic stellate cell activation through negative feedback in chronic pancreatitis.

BACKGROUND: Activation of pancreatic stellate cells (PSCs) is a key cause of chronic pancreatitis (CP), while inhibition of transforming growth factor-ß (TGF-ß) signaling renders PSCs inactive. Inhibitory Smads (I-Smads) impede TGF-ß intracellular signaling and may provide a way to alleviate CP. Thus, we aimed to investigate the molecular mechanism of I-Smads in CP animals and freshly-isolated PSCs. METHODS: Sixteen male C57BL/6 mice were randomly divided into two groups; a control group (treated with saline) and a CP group (treated with caerulein) for 6 weeks. Masson's staining was performed to identify fibrosis, and immunohistochemistry (IHC) was performed to measure the levels of Smad6 between the two groups. An improved method derived from internal digestion was used to isolate PSCs from male Sprague Dawley rats. Quantitative real-time polymerase chain reaction (qRT-PCR) and immunofluorescence staining were used to measure the messenger ribonucleic acid (mRNA) and protein levels of alpha-smooth muscle actin (α-SMA). Plasmids of I-Smads or SB431542 were transfected into freshly-isolated PSCs, and relative mRNA levels of marker genes were quantified by qRT-PCR. The two-tailed Student's t-test was performed to assess significance. RESULTS: The Smad6 protein level was significantly higher in the pancreas tissue of CP mice compared to the control group. A large number of PSCs were isolated from rat pancreas using an improved isolating method and were confirmed by quiescent and active PSC markers including cluster differentiation antigen 133 (CD133), perilipin 2 (Plin2), α-SMA, Desmin, and collagen 1 (Col1). The mRNA levels of both Smad6 and Smad7 were down-regulated during freshly-isolated PSC activation. Over-expression of both Smad6 and Smad7 in freshly-isolated PSC reduced the mRNA level of α-SMA, glial fibrillary acidic protein (GFAP), Desmin, Col1, Col3, and fibronectin 1 (Fn1) significantly. SB431542 reduced the mRNA level of α-SMA, Col1, Col3, and Fn1 significantly in freshly-isolated PSCs. CONCLUSIONS: This study demonstrated that CP promoted the expression of I-Smads, which suppressed the activation of freshly-isolated PSCs via a negative feedback loop.