A review in Chinese Journal of Natural Medicines evaluates Ziziphora clinopodioides, a Lamiaceae medicinal plant rich in flavonoids, phenolic acids, and essential oils, and summarizes mechanistic evidence supporting anti-inflammatory, antioxidant, anti-apoptotic, mitochondrial, and vasodilatory actions relevant to cardiovascular diseases.

In mouse and cell-based models, tracheloside mitigated fibrotic remodeling by activating AMPK and suppressing NOX4-driven oxidative stress, implicating an AMPK/NOX4 axis in anti-fibrotic activity.

An accurate assessment of the state of health (SOH) is the cornerstone for guaranteeing the long-term stable operation of electrical equipment. However, the noise the data carries during cyclic aging poses a severe challenge to the accuracy of SOH estimation and the generalization ability of the model. To this end, this paper proposed a novel SOH estimation model for lithium-ion batteries that incorporates advanced signal-processing techniques and optimized machine-learning strategies. The model employs a whale optimization algorithm (WOA) to seek the optimal parameter combination (K, α) for the variational modal decomposition (VMD) method to ensure that the signals are accurately decomposed into different modes representing the SOH of batteries. Then, the excellent local feature extraction capability of the convolutional neural network (CNN) was utilized to obtain the critical features of each modal of SOH. Finally, the support vector machine (SVM) was selected as the final SOH estimation regressor based on its generalization ability and efficient performance on small sample datasets. The method proposed was validated on a two-class publicly available aging dataset of lithium-ion batteries containing different temperatures, discharge rates, and discharge depths. The results show that the WOA-VMD-based data processing technique effectively solves the interference problem of cyclic aging data noise on SOH estimation. The CNN-SVM optimized machine learning method significantly improves the accuracy of SOH estimation. Compared with traditional techniques, the fused algorithm achieves significant results in solving the interference of data noise, improving the accuracy of SOH estimation, and enhancing the generalization ability.

A review article entitled "Scaffold-Mediated Microenvironmental Modulation Targeting Osteoclasts for ONFH Niche Reprogramming" has been published in Research. This article systematically summarizes the latest progress in functionalized bioactive scaffolds for regulating the intraosseous microenvironment in the treatment of early osteonecrosis of the femoral head (ONFH). Innovatively, from the perspective of osteoclast heterogeneity, it proposes a novel concept of "osteoclast-centric reprogramming of the osteonecrotic microenvironment," providing a new theoretical framework and design direction for the material-based treatment of ONFH.