Yinchen lipid-lowering tea attenuates lipid deposition in a fatty liver model by regulating mitochondrial dysfunction through activation of AdipoR1/AMPK/SIRT1 signaling.

This study investigated the ameliorative effects of Yinchen lipid-lowering tea (YCLLT) on Non-alcoholic fatty liver disease (NAFLD), the specific mechanism involved was also studied. We modeled hepatocellular steatosis with HepG2 cells and intervened with different concentrations of YCLLT-containing serum. Lipid deposition was assessed by oil red O staining and AdipoR1 expression was analyzed by Western blot.

Metal Atoms (Li, Na, and K) Tuning the Configuration of Pyrrole for the Selective Recognition of C.

Host-guest structure assembly is significant in the recognition of molecules, and the fullerene-based host-guest structure is a convenient method to determine the structures of fullerenes of which recognition is with many difficulties in experiments. Here, with density functional theory calculations, we designed several crown-shaped pyrrole-based hosts tuned by doping metal atoms (Li, Na, and K) for the effective recognition of C with modest interaction between the host and guest. Binding energy calculations showed an enhanced interaction of the concave-convex host-guest system with the doped metal atoms, enabling the selective recognition of C.

Screening of Biomarkers and Toxicity Mechanisms of Rifampicin-Induced Liver Injury Based on Targeted Bile Acid Metabolomics.

Rifampicin (RIF) is a critical first-line drug for tuberculosis. However, long-term or high-dose treatment with RIF can induce severe liver injury; the underlying mechanism of this effect has not yet been clarified. This study was performed to screen reliable and sensitive biomarkers in serum bile acids (BAs) using targeted BA metabolomics and evaluate the toxicity mechanisms underlying RIF-induced liver injury through the farnesoid x receptor (Fxr)-multidrug resistance-associated proteins (Mrps) signaling pathway.

A novel multivariable grey prediction model and its application in forecasting coal consumption.

Coal is an important energy source worldwide. Objectively and accurately predicting coal consumption is conducive to healthy coal industry development, because such predictions can provide references and warnings that are useful in formulating energy strategies and implementing environmental policies. Population size and area economic development are the main factors that affect coal consumption.

A novel grey model based on traditional Richards model and its application in COVID-19.

In 2020, a new type of coronavirus is in the global pandemic. Now, the number of infected patients is increasing. The trend of the epidemic has attracted global attention.

Grey optimization Verhulst model and its application in forecasting coal-related CO emissions.

Energy saving and emission reduction are the most concerned issues in the world. Objective and accurate prediction of carbon emissions can provide reference and early warning for the implementation of the government's environmental strategy. Based on the traditional grey Verhulst model, this paper analyzes the main causes of its errors, introduces the extrapolation method to optimize the background value, and uses particle swarm optimization algorithm to optimize its parameters.

A Novel Riccati Equation Grey Model And Its Application In Forecasting Clean Energy.

and accurate prediction of clean energy can supply an important reference for governments to formulate social and economic development policies. This paper begins with the logistic equation which is the whitening equation of the Verhulst model, introduces the Riccati equation with constant coefficients to optimize the whitening equation, and establishes a grey prediction model (CCRGM(1,1)) based on the Riccati equation. This model organically combines the characteristics of the grey model, and flexibly improves the modelling precision.