Pathogenesis, Animal Models, and Drug Discovery of Alzheimer's Disease.

Alzheimer's disease (AD), the most common cause of dementia, is a chronic neurodegenerative disease induced by multiple factors. The high incidence and the aging of the global population make it a growing global health concern with huge implications for individuals and society. The clinical manifestations are progressive cognitive dysfunction and lack of behavioral ability, which not only seriously affect the health and quality of life of the elderly, but also bring a heavy burden to the family and society. Unfortunately, almost all the drugs targeting the classical pathogenesis have not achieved satisfactory clinical effects in the past two decades. Therefore, the present review provides more novel ideas on the complex pathophysiological mechanisms of AD, including classical pathogenesis and a variety of possible pathogenesis that have been proposed in recent years. It will be helpful to find out the key target and the effect pathway of potential drugs and mechanisms for the prevention and treatment of AD. In addition, the common animal models in AD research are outlined and we examine their prospect for the future. Finally, Phase I, II, III, and IV randomized clinical trials or on the market of drugs for AD treatment were searched in online databases (Drug Bank Online 5.0, the U.S. National Library of Medicine, and Alzforum). Therefore, this review may also provide useful information in the research and development of new AD-based drugs.

Machine-learning analysis to predict the fluorescence quantum yield of carbon quantum dots in biochar.

Biochar nanoparticles have recently attracted attention, owing to their environmental behavior and ecological effects. However, biochar has not been shown to contain carbon quantum dots (< 10 nm) with unique photovoltaic properties. Therefore, this study utilized several characterization techniques to demonstrate the generation of carbon quantum dots in biochar produced from 10 types of farm waste. The generated carbon quantum dots had a quasi-spherical morphology and high-resolution lattice stripes with lattice spacings of 0.20-0.23 nm. Moreover, they contained functional groups with good hydrophilic properties, such as amino and hydroxyl groups, and elemental O, C, and N on the surface. A crucial determinant of the photoluminescence properties of carbon quantum dots is their fluorescence quantum yield. Therefore, the relationship between the biochar preparation parameters and the fluorescence quantum yield was investigated using six machine learning analytical models based on 480 samples. Among the models, the gradient-boosting decision-tree regression model exhibited the best predictive performance (R2 > 0.9, RMSE <0.02, and MAPE <3), and was used for the analysis of feature importance; compared to the properties of the raw material, the production parameters had a greater effect on the fluorescence quantum yield. Additionally, four key features were identified: pyrolysis temperature, residence time, N content, and C/N ratio, which were independent of farm waste type. These features can be used to accurately predict the fluorescence quantum yield of carbon quantum dots in biochar. The relative error range between the predicted and the experimental value of fluorescence quantum yield is 0.00-4.60 %. Thus, the prediction model has the potential to predict the fluorescence quantum yield of carbon quantum dots in other types of farm waste biochar, and provides fundamental information for the study of biochar nanoparticles.

Research progress on metabolomics in the quality evaluation and clinical study of Panax ginseng.

Panax ginseng, an essential component of traditional medicine and often referred to as the king of herbs, has played a pivotal role in medicine globally for several millennia. Previously, traditional phytochemical methods were mainly used for quality evaluation and pharmacological mechanism studies of ginseng, resulting in the lack of systematicness and innovation and hindering the development and utilization of ginseng resources. Since the beginning of the new century, systems biology technology represented by metabolomics has shown unique advantages in the modernization and internationalization of herbal medicine, establishing a bridge for communication between traditional medicine and modern medicine. P. ginseng, a special herb used in medicine and food, is one of the main research objects for qualitative and quantitative analysis of metabolomics and has gradually become the focus of researchers globally. Here, we conducted a comprehensive summary and analysis of numerous studies published in ginseng metabolomics. This review aims to provide more novel ideas for the quality evaluation, development, and clinical application of ginseng in the future and offer more useful technical references for the modernization and internationalization of herbal medicine based on metabolomics.