Aucubin provides protection against cerebral ischaemia-reperfusion injury by suppressing neuronal apoptosis, oxidative stress, and inflammation through the modulation of the AKT-GSK-3ß-Nrf2 signal cascade.

Aucubin (AU) is a naturally occurring iridoid glycoside known to possess a wide range of pharmacological properties and exhibit a notable protective effect against various pathological conditions. Studies have shown that AU has neuroprotective properties in different neurological diseases. However, its potential protective effects against cerebral ischemia-reperfusion (CIR) injury have not been thoroughly investigated. This study aimed to investigate the impact of AU on CIR injury and explore the underlying mechanism. Cultured neurons treated with AU showed a significant reduction in apoptosis, oxidative stress, and inflammation caused by oxygen-glucose deprivation and reoxygenation (OGD/R). In a rat model of CIR, treatment with AU resulted in a significant decrease in cerebral infarct size and neurological deficits. AU treatment also reversed the increased apoptosis, oxidative stress, and inflammation in the brains of CIR rats. Furthermore, AU was found to enhance the activation of nuclear factor-erythroid 2-related factor 2 (Nrf2), accompanied by increased phosphorylation of serine/threonine-protein kinase AKT and glycogen synthase kinase-3 beta (GSK-3ß). The activation of Nrf2 induced by AU was reversed when the AKT-GSK-3ß cascade was blocked. Additionally, the neuroprotective effect of AU was significantly reduced when Nrf2 was pharmacologically suppressed. In conclusion, these findings suggest that AU exerts a neuroprotective effect on CIR injury, and this effect is mediated by the activation of Nrf2 through the AKT-GSK-3ß axis. This work highlights the potential of AU as a drug candidate for the treatment of CIR injury.

[SIC algorithm based model updating for near infrared analysis of Salvia miltiorrhiza alcohol extraction process].

The near-infrared (NIR) spectroscopy for offline monitoring of alcohol extraction process of Salvia miltiorrhiza was investigated, with high performance liquid chromatography (HPLC) determination of value for reference. The partial least squares method was adopted to establish the tanshinone ⅡA quantitative calibration model, so as to detect extraction process of Salvia miltiorrhiza. Because the differences between batches of raw materials may endanger the robustness of the original model, the simple interval calculation (SIC) was applied in updating the near-infrared quantitative model for traditional Chinese medicine extraction process for the first time, and compared with Random Selection (RS) method. SIC's final updating results showed that root mean square with cross validation (RMSECV), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) of tanshinone ⅡA were 0.006 8 g•L⁻¹, 0.005 4 g•L⁻¹ and 3.14, respectively; but RS' final updating results showed that RMSECV, RMSEP and RPD were 0.006 4 g•L⁻¹, 0.006 8 g•L⁻¹ and 2.50, respectively. This study suggested that SIC is superior to RS, and provided a research foundation for quality control and monitoring of S. miltiorrhiza extraction process in the future.

[Rapid multi-elemental analysis on four precious Tibetan medicines based on LIBS technique].

The laser-induced breakdown spectroscopy (LIBS) was applied to perform a qualitative elementary analysis on four precious Tibetan medicines, i. e. Renqing Mangjue, Renqing Changjue, 25-herb coral pills and 25-herb pearl pills. The specific spectra of the four Tibetan medicines were established. In the experiment, Nd: YAG and 1 064 nm-baseband pulse laser were adopted to collect the spectra. A laser beam focused on the surface of the samples to generate plasma. Its spectral signal was detected by using spectrograph. Based on the National Institute of Standard and Technology (NIST) database, LIBS spectral lines were indentified. The four Tibetan medicines mainly included Ca, Na, K, Mg and other elements and C-N molecular band. Specifically, Fe was detected in Renqing Changjue and 25-herb pearl pills; heavy mental elements Hg and Cu were shown in Renqing Mangjue and Renqing Changjue; Ag was found in Renqing Changjue. The results demonstrated that LIBS is a reliable and rapid multi-element analysis on the four Tibetan medicines. With Real-time, rapid and nondestructive advantages, LIBS has a wide application prospect in the element analysis on ethnic medicines.

Dealing with heterogeneous classification problem in the framework of multi-instance learning.

To deal with heterogeneous classification problem efficiently, each heterogeneous object was represented by a set of measurements obtained on different part of it, and the heterogeneous classification problem was reformulated in the framework of multi-instance learning (MIL). Based on a variant of count-based MIL assumption, a maximum count least squares support vector machine (maxc-LS-SVM) learning algorithm was developed. The algorithm was tested on a set of toy datasets. It was found that maxc-LS-SVM inherits all the sound characters of both LS-SVM and MIL framework. A comparison study between the proposed approach and the other two MIL approaches (i.e., mi-SVM and MI-SVM) was performed on a real wolfberry fruit spectral dataset. The results demonstrate that by formulating the heterogeneous classification problem as a MIL one, the heterogeneous classification problem can be solved by the proposed maxc-LS-SVM algorithm effectively.