Chenyang Zhang

Ginsenoside Rg3 extracted from Panax notoginseng has therapeutic effects on diabetes and heart diseases. However, the underlying mechanism of ginsenoside Rg3 on diabetic cardiomyopathy (DCM) remains unclear. 24-week-old diabetic db/db mice were treated with ginsenoside Rg3 for 12 weeks, then body weight, serum lipids, adiponectin levels, as well as cardiac function and pathological morphology, were measured. The targets of ginsenoside Rg3 and its regulation of the adiponectin pathway were also evaluated on 3T3-L1 or H9c2 cells. Ginsenoside Rg3 directly bound to PPAR-γ, improving adiponectin secretion and promoting adiponectin signaling. Significantly attenuated overweight, hyperglycemia, and hyperlipidemia, as well as alleviated lipid accumulation and dysfunction in adipose, liver, and heart tissues, were observed in the ginsenoside Rg3-treated group. Ginsenoside Rg3 could be a promising drug targeting PPAR-γ to treat diabetic cardiomyopathy.

Currently, hundreds of herbal products with potential hepatotoxicity were available in the literature. A comprehensive summary and analysis focused on these potential hepatotoxic herbal products may assist in understanding herb-induced liver injury (HILI). In this work, we collected 335 hepatotoxic medicinal plants, 296 hepatotoxic ingredients, and 584 hepatoprotective ingredients through a systematic literature retrieval. Then we analyzed these data from the perspectives of phylogenetic relationship and structure-toxicity relationship. Phylogenetic analysis indicated that hepatotoxic medicinal plants tended to have a closer taxonomic relationship. By investigating the structures of the hepatotoxic ingredients, we found that alkaloids and terpenoids were the two major groups of hepatotoxicity. We also identified eight major skeletons of hepatotoxicity and reviewed their hepatotoxic mechanisms. Additionally, 15 structural alerts (SAs) for hepatotoxicity were identified based on SARpy software. These SAs will help to estimate the hepatotoxic risk of ingredients from herbs. Finally, a herb-ingredient network was constructed by integrating multiple datasets, which will assist to identify the hepatotoxic ingredients of herb/herb-formula quickly. In summary, a systemic analysis focused on HILI was conducted which will not only assist to identify the toxic molecular basis of hepatotoxic herbs but also contribute to decipher the mechanisms of HILI.

As one of the leading causes of drug failure in clinical trials, drug-induced liver injury (DILI) seriously impeded the development of new drugs. Assessing the DILI risk of drug candidates in advance has been considered as an effective strategy to decrease the rate of attrition in drug discovery. Recently, there have been continuous attempts in the prediction of DILI. However, it indeed remains a huge challenge to predict DILI successfully. There is an urgent need to develop a quantitative structure–activity relationship (QSAR) model for predicting DILI with satisfactory performance. In this work, we reported a high-quality QSAR model for predicting the DILI risk of xenobiotics by incorporating the use of eight effective classifiers and molecular descriptors provided by Marvin. In model development, a large-scale and diverse dataset consisting of 1254 compounds for DILI was built through a comprehensive literature retrieval. The optimal model was attained by an ensemble method, averaging the probabilities from eight classifiers, with accuracy (ACC) of 0.783, sensitivity (SE) of 0.818, specificity (SP) of 0.748, and area under the receiver operating characteristic curve (AUC) of 0.859. For further validation, three external test sets and a large negative dataset were utilized. Consequently, both the internal and external validation indicated that our model outperformed prior studies significantly. Data provided by the current study will also be a valuable source for modeling/data mining in the future.

Patients with diabetes mellitus (DM) suffer more risks from diabetic encephalopathy such as cognitive dysfunction and depressive-like behaviors. Numerous studies show that ER (endoplasmic reticulum) stress and inflammation play important roles in the development of diabetic encephalopathy. Gastrodin (Gas), one major component of Gastrodia elata, is traditionally used in central nervous system disorders and is believed to possess anti-inflammatory, anti-apoptotic, and other neuroprotective effects. This present study aims to explore the protective effects of Gas on diabetic encephalopathy. Gas was administrated daily (70 and 140 mg/Kg) for 12 weeks. Meanwhile, the fasting blood glucose and body weight of db/db mice were measured every two weeks. After Gas treatment, the Morris water maze (MWM) test and novel object recognition (NOR) test were performed to assess the learning and memory functions of db/db mice, and the forced swim test was performed to evaluate depressive-like behaviors of db/db mice. Additionally, the expression of ER stress and Nucleotide binding and oligomerization domain-like (Nod) receptor family pyrin domain-containing 3 (NLRP3) inflammasome related proteins were evaluated by using Western blot. Our study suggested that Gas attenuated blood glucose levels and dyslipidemia of db/db mice. It has been shown that Gas could improve learning and memory function and depressive-like behaviors of db/db mice. Moreover, Gas inhibited ER stress and NLRP3 inflammasome activation in the hippocampus. Taken together, this study demonstrates that Gas attenuates the diabetic encephalopathy by inhibiting ER stress and NLRP3 inflammasome activation.