Comparative prototypes and metabolites of Du-zhi pill in normal and cerebral ischemia rats by UHPLC-Q-TOF-MS/MS method.

Du-Zhi pill (DZP) is widely used as a Chinese medicine in treating cerebral ischemia. UHPLC-Q-TOF-MS/MS techniques were used to detect and identify the metabolites in rat brain samples of normal and middle cerebral artery occlusion (MCAO) model rats administered with DZP. It was tentatively found that 43 prototypes and 93 metabolites could be identified in rat brain samples. Normal and MCAO model rat brain samples contained 19 prototype components. Eight prototype components were only detected in normal rat brain samples, while 16 were found only in MCAO model rat brain samples. It was determined that 47 metabolites had been identified in the normal rats, while 86 had been placed in MCAO model rats. There were 40 common metabolites in both normal and MCAO model rat brain samples. Seven metabolites were only detected in normal rat brain samples, while 46 were found only in MCAO rat brain samples. The comparison of metabolites in brain samples of normal and MCAO rats showed apparent differences. It was discovered that glucuronidation, methylation, acetylation, and sulfation are phase II metabolic routes of DZP, while hydrogenation, hydroxylation, and dehydroxylation are phase I metabolic routes. Moreover, hydrogenation, glucuronidation, hydroxylation, and methylation were the main metabolic pathways because of the number of metabolites identified in these metabolic pathways. The results provide a valuable reference for further research into effective substances of DZP for treating cerebral ischemia.

Novel antidepressant mechanism of hypericin: Role of connexin 43-based gap junctions.

Hypericin is widely utilized for its precise antidepressant properties, but its exact antidepressant mechanism remains unclear. Gap junctions, which were predominantly expressed in astrocytes in the central nervous system, are concerned with the pathogenesis of depression. However, the role of hypericin in gap junctional dysfunction in depression has rarely been investigated. Here, we found that gap junctions were ultra-structurally broadened in the chronic unpredictable stress (CUS) rat model of depression, while hypericin repaired the dysfunction of gap junctions. Suppression of gap junctions by bilateral injection of carbenoxolone (CBX) in the prefrontal cortex of rats significantly inhibited the restoration of gap junctional dysfunction in depression by hypericin. Meanwhile, hypericin failed to show antidepressant benefits. Furthermore, in corticosterone (CORT)-stimulated primary astrocytes derived from neonatal rats, hypericin dramatically reversed the phosphorylation of connexin 43 (Cx43), normalizing the expression of Cx43 and thereby ameliorating gap junctional dysfunction. Comparatively, CBX inhibited the remission of hypericin on gap junctional intercellular communication function. Gap junctional function might be a novel therapeutic target for hypericin in the treatment of depression and provide potential novel insights into the antidepressant mechanism of other herbal ingredients.

SY-Net: A Rice Seed Instance Segmentation Method Based on a Six-Layer Feature Fusion Network and a Parallel Prediction Head Structure.

During the rice quality testing process, the precise segmentation and extraction of grain pixels is a key technique for accurately determining the quality of each seed. Due to the similar physical characteristics, small particles and dense distributions of rice seeds, properly analysing rice is a difficult problem in the field of target segmentation. In this paper, a network called SY-net, which consists of a feature extractor module, a feature pyramid fusion module, a prediction head module and a prototype mask generation module, is proposed for rice seed instance segmentation. In the feature extraction module, a transformer backbone is used to improve the ability of the network to learn rice seed features; in the pyramid fusion module and the prediction head module, a six-layer feature fusion network and a parallel prediction head structure are employed to enhance the utilization of feature information; and in the prototype mask generation module, a large feature map is used to generate high-quality masks. Training and testing were performed on two public datasets and one private rice seed dataset. The results showed that SY-net achieved a mean average precision (mAP) of 90.71% for the private rice seed dataset and an average precision (AP) of 16.5% with small targets in COCO2017. The network improved the efficiency of rice seed segmentation and showed excellent application prospects in performing rice seed quality testing.

STC-YOLO: Small Object Detection Network for Traffic Signs in Complex Environments.

The detection of traffic signs is easily affected by changes in the weather, partial occlusion, and light intensity, which increases the number of potential safety hazards in practical applications of autonomous driving. To address this issue, a new traffic sign dataset, namely the enhanced Tsinghua-Tencent 100K (TT100K) dataset, was constructed, which includes the number of difficult samples generated using various data augmentation strategies such as fog, snow, noise, occlusion, and blur. Meanwhile, a small traffic sign detection network for complex environments based on the framework of YOLOv5 (STC-YOLO) was constructed to be suitable for complex scenes. In this network, the down-sampling multiple was adjusted, and a small object detection layer was adopted to obtain and transmit richer and more discriminative small object features. Then, a feature extraction module combining a convolutional neural network (CNN) and multi-head attention was designed to break the limitations of ordinary convolution extraction to obtain a larger receptive field. Finally, the normalized Gaussian Wasserstein distance (NWD) metric was introduced to make up for the sensitivity of the intersection over union (IoU) loss to the location deviation of tiny objects in the regression loss function. A more accurate size of the anchor boxes for small objects was achieved using the K-means++ clustering algorithm. Experiments on 45 types of sign detection results on the enhanced TT100K dataset showed that the STC-YOLO algorithm outperformed YOLOv5 by 9.3% in the mean average precision (mAP), and the performance of STC-YOLO was comparable with that of the state-of-the-art methods on the public TT100K dataset and CSUST Chinese Traffic Sign Detection Benchmark (CCTSDB2021) dataset.

Shengmai san-derived compound prescriptions: A review on chemical constituents, pharmacokinetic studies, quality control, and pharmacological properties.

BACKGROUND: Shengmai San Formula (SMS), composed of Ginseng Radix et Rhizoma, Ophiopogon Radix and Schisandra chinensis Fructus, was a famous formula in Tradition Chinese Medicine (TCM). With the expansion of clinical applications, SMS was developed to different dosage forms, including Shengmai Yin Oral liquid (SMY), Shengmai Capsule (SMC), Shengmai Granule (SMG), Shengmai Injection (SMI) and Dengzhan Shengmai Capsule (DZSMC). These above SMS-derived compound prescriptions (SSCPs) play an important role in the clinical treatment. This review is aimed to providing a comprehensive perspective of SSCP. METHODS: The relevant literatures were collected from classical TCM books and a variety of databases, including PubMed, Google Scholar, Science Direct, Springer Link, Web of Science, China National Knowledge Infrastructure, and Wanfang Data. RESULTS: The chemical constituents of SSCPs, arrived from the individual medicinal materials including Ginseng Radix et Rhizoma, Ophiopogon Radix, Schisandra chinensis Fructus, Erigerontis Herba, were firstly summarized respectively. Then the pharmacokinetics studies, quality control, and pharmacological properties of SSCPs were all reviewed. The active compounds, pharmacokinetics characterizes, quality control markers, the effects and mechanisms of pharmacology of the different dosage forms of SSCPs were summarized. Furthermore, the research deficiencies of SSCPs and an innovative research paradigm for Chinese materia medica (CMM) formula were proposed. CONCLUSIONS: SMS, as a famous CMM formula, has great values in drug research and in clinical treatment especially for cardiocerebrovascular diseases. This article firstly make a comprehensive and systematic review on SMS.

Rapid characterization and identification of the chemical constituents and the metabolites of Du-zhi pill using UHPLC coupled with quadrupole time-of-flight mass spectrometry.

A reliable method using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was established to conduct a comprehensive analysis of the chemical constituents of Du-zhi pill (DZP) as well as their metabolites in rat plasma, urine and feces after gastric perfusion. The efficient on-line mass data acquisition modes combined the various off-line mass data mining strategy was applied. A full mass scan was performed, and then accurate MS/MS datasets were obtained through the use of a multiple mass defect filter (MMDF) and dynamic background subtraction (DBS)-dependent data acquisition method. Furthermore, post-acquisition data processing was conducted using various data-mining tools, including extracted ion chromatography (XIC), mass defect filtering (MDF), product ion filtering (PIF), and neutral loss filtering (NLF) (MetabolitePilot™). Finaly, a total of 176 compounds were identified or tentatively characterized in DZP. Moreover, a total of 233 components in vivo, which includes 92 prototype components and 141 metabolites, were unambiguously or tentatively identified in rat plasma, urine and feces. The metabolic pathways, including phase I reactions (hydroxylation, dehydroxylation and hydrogenation) and phase II reactions (acetylation, sulfation, glucuronidation and methylation), for the absorbed constituents, were explored and summarized. This is the first systematic study on the components of DZP and their metabolites in vivo. This study provide a valid analytical strategy for the characterization of chemical compounds and metabolites of TCM formulas. Moreover, an integrative strategy was proposed for the characterization and identification of chemical constituents and metabolites for additional TCM prescriptions.

An Energy Metabolism Study on the Efficacy of Naoxintong Capsules against Myocardial Infarction in a Rat Model.

Background: In myocardial ischemia, optimizing the myocardial metabolic phenotype to improve cardiac function is critical. Naoxintong capsules (NXT) are widely prescribed in Chinese medicine for the treatment of cerebrovascular and cardiovascular diseases. Methods: In this study, a rat model of myocardial infarction was established by ligation of the left anterior descending coronary artery. The structure and function of the heart were evaluated using echocardiography. The pathological changes of the rat myocardium and the myocardial volume collagen fraction (CVF) were examined using hematoxylin-eosin (HE) and Masson's trichrome staining (Masson). The expression of TNF-α and IL-6 were detected by immunohistochemistry. The level of cTnT was also measured to evaluate myocardial injury. In order to study the changes in energy metabolism in myocardial infarction and the effects of NXT, a targeted analysis method for detecting the 29 energy metabolites in cardiac muscle tissue was developed based on UPLC-QQQ-MS. Western blotting was used to detect the expression of proteins related to energy metabolism in myocardia. Results: In the rat model of myocardial infarction, NXT showed obvious effects, such as improving heart function and increasing LVEF and LVFS. HE staining, Masson staining, and immunohistochemical results revealed that NXT decreased inflammatory infiltration, improved myocardial fibrosis, and reduced infarct size. In addition, NXT significantly reduced the level of serum cTnT. The levels of the 29 energy metabolites in cardiac muscle tissue were analyzed using a newly developed targeted analysis method. Compared to the sham group, the levels of 17 metabolites from different energy metabolic pathways, including four compounds in glycolysis metabolism, four compounds in TCA cycle, three compounds in oxidative phosphorylation, four compounds in purine metabolism, and two compounds in glutathione metabolism, displayed obvious changes induced by myocardial ischemia. Expressions of SIRT1, PGC-1α, and ATP5D proteins related to energy metabolism were decreased after myocardial infarction. These perturbations could all be reversed by NXT intervention, suggesting that the therapeutic effects of NXT were partially due to interferences with energy metabolisms. Conclusion: This study provides a useful approach for investigating the mechanism of myocardial infarction and evaluating the efficacy of NXT from energy metabolism.