Xingnaojing injection alleviates cerebral ischemia/reperfusion injury through regulating endoplasmic reticulum stress in Vivo and in Vitro.

Background: Xingnaojing (XNJ) injection, an extract derived from traditional Chinese medicine, is commonly used to treat ischemic stroke (IS). Previous studies have shown that XNJ has the ability to alleviate apoptosis in cerebral ischemia-reperfusion injury. However, the potential mechanisms have not been clarified. Objective: To identify the neuroprotective effect of XNJ and explore whether XNJ inhibits cell apoptosis associated with endoplasmic reticulum stress (ERS) after IS. Methods: In this study, cultured hippocampal neurons from mouse embryos and Sprague-Dawley rats were assigned randomly to four groups: sham, model, XNJ, and edaravone. The treatment groups were administered 2 h after modelling. Neurological deficit scores and motor performance tests were performed after 24 h of modelling. Additionally, pathomorphology, cell apoptosis and calcium content were evaluated. To ascertain the expression of ERS proteins, western blotting and polymerase chain reaction were employed. Results: The results indicated that XNJ treatment resulted in a notable decrease in infarct volume, apoptosis and missteps compared with the model group. XNJ also exhibited improvements in neurological function, grip strength and motor time. The calcium content significantly reduced in XNJ group. The XNJ administration resulted in a reduction in the levels of proteins associated with ERS including CHOP, GRP78, Bax, caspase-12, caspase-9, and cleaved-caspase-3, but an increase of the Bcl-2/Bax ratio. Furthermore, the downregulation of mRNA expression of CHOP, GRP78, caspase-12, caspase-9, and caspase-3 was confirmed in both cultured neurons and rat model. Conclusion: These findings suggest that XNJ may alleviate apoptosis by modulating the ERS-induced apoptosis pathway, making it a potential novel therapeutic approach for ischemic stroke.

Transcriptome Analysis of Deoxynivalenol (DON)-Induced Hepatic and Intestinal Toxicity in Zebrafish: Insights into Gene Expression and Potential Detoxification Pathways.

The effects of deoxynivalenol (DON, 50 µg/mL) on the zebrafish liver and intestine were studied. Differentially expressed genes (DEGs) from mRNA and lncRNA were analyzed by RNA seq. Gene Ontology (GO) and signaling pathways were studied where the top 30 DEGs of each type of RNA were involved. The results showed there were 2325 up-regulated and 934 down-regulated DEGs of lncRNA in the intestinal tract, and 95 up-regulated genes and 211 down-regulated genes in the liver, respectively. GO functional annotation analysis showed that lncRNA was enriched in the biological processes, involving the RNA splicing, CSF1-CSF1R complexes, and MAP kinase activity. DEGs of lncRNA located in the KEGG signal pathways include the C-type lectin receptor signaling and the NOD-like receptor signaling pathways. Metabolism involves the biosynthesis of indole alkaloids, cancer pathways for human disease, MAPK and Rap1signaling pathways for environmental information processing, necroptosis and focal adhesion for cell processes. The mRNA gene expression analysis showed there were 1939 up-regulated, 1172 down-regulated genes and 866 up-regulated, 1211 down-regulated genes in the intestine and liver of zebrafish, respectively. This study provides transcriptome analysis and toxicological investigation of DON in the zebrafish liver and intestine, offering insights into gene expression patterns and potential detoxification pathways.

China Stroke Registry for Patients With Traditional Chinese Medicine (CASES-TCM): Rationale and Design of a Prospective, Multicenter, Observational Study.

Background: Given the complexity of stroke treatment and the current widespread use of traditional Chinese medicine (TCM) in the absence of robust, large, long-term effectiveness and safety studies, and the lack of nationwide epidemiology and clinical characteristics of patients with stroke receiving TCM treatment, the acquisition of data from longitudinal cohorts is essential. We intend to generate the major clinical characteristics of patients with stroke who receive TCM treatment and to investigate the effectiveness and safety of TCM in the Chinese population. Methods: The China Stroke Registry for Patients with Traditional Chinese Medicine (CASES-TCM) study is a prospective, multicenter, observational disease registry aiming to register 20,000 hospitalized patients. Eligible adult patients with clearly diagnosed acute ischemic stroke or intracerebral hemorrhage within 7 days of symptom onset will be consecutively registered from 126 participating sites across China. Baseline data will be recorded, and all patients will be regularly followed up at 3, 6, 12, and 24 months after stroke onset. Collected data will be entered into a web-based system with high-level data security. The primary outcomes include the distribution of scores on the modified Rankin Scale at the 3-months follow-up, and recurrent stroke events within the 12-months follow-up. Conclusion: To our knowledge, the CASES-TCM study is the first and largest nationwide registry to document comprehensive data on TCM treatment in patients with acute stroke. The findings of this study will be valuable to improve our knowledge about TCM treatment for patients with stroke and its subsequent outcomes in the actual clinical setting, consequently facilitating and standardizing the optimization of individualized interventions with TCM for stroke prevention and treatment in China. Study registration: This study was registered with Clinicaltrials.gov (URL: https://clinicaltrials.gov/, Unique identifier: NCT04921397).

Attention based convolutional network for automatic sleep stage classification.

Sleep staging is an important basis for diagnosing sleep-related problems. In this paper, an attention based convolutional network for automatic sleep staging is proposed. The network takes time-frequency image as input and predict sleep stage for each 30-s epoch as output. For each CNN feature maps, our model generate attention maps along two separate dimensions, time and filter, and then multiplied to form the final attention map. Residual-like fusion structure is used to append the attention map to the input feature map for adaptive feature refinement. In addition, to get the global feature representation with less information loss, the generalized mean pooling is introduced. To prove the efficacy of the proposed method, we have compared with two baseline method on sleep-EDF data set with different setting of the framework and input channel type, the experimental results show that the paper model has achieved significant improvements in terms of overall accuracy, Cohen's kappa, MF1, sensitivity and specificity. The performance of the proposed network is compared with that of the state-of-the-art algorithms with an overall accuracy of 83.4%, a macro F1-score of 77.3%, κ = 0.77, sensitivity = 77.1% and specificity = 95.4%, respectively. The experimental results demonstrate the superiority of the proposed network.

Hydroxysafflor Yellow A Exerts Anti-Inflammatory Effects Mediated by SIRT1 in Lipopolysaccharide-Induced Microglia Activation.

Abnormal microglia activation causes sever neuroinflammation, contributing to the development of many diseases, yet the mechanism remains incompletely unknown. In current study, we identified that Hydroxysafflor yellow A (HYA), a chalcone glycoside derived from Carthamus tinctorius L effectively attenuates LPS-induced inflammation response in primary microglia via regulating the expression of inflammatory genes and remodeling the polarization of microglia. We also reported the effects of HYA on improving lipopolysaccharide (LPS)-stimulated mitochondrial dysfunction and oxidative stress for the first time. Interestingly, we found that HYA could serves as an effective SIRT1 activator. Deficiency of SIRT1 abrogates the protective effects of HYA against LPS-induced response. Overall, our data suggest HYA, a novel SIRT1 activator, could serve as an effective approach to treat LPS-induced neurodegenerative diseases.

Author Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Analysis of the Human Protein Atlas Image Classification competition.

Pinpointing subcellular protein localizations from microscopy images is easy to the trained eye, but challenging to automate. Based on the Human Protein Atlas image collection, we held a competition to identify deep learning solutions to solve this task. Challenges included training on highly imbalanced classes and predicting multiple labels per image. Over 3 months, 2,172 teams participated. Despite convergence on popular networks and training techniques, there was considerable variety among the solutions. Participants applied strategies for modifying neural networks and loss functions, augmenting data and using pretrained networks. The winning models far outperformed our previous effort at multi-label classification of protein localization patterns by ~20%. These models can be used as classifiers to annotate new images, feature extractors to measure pattern similarity or pretrained networks for a wide range of biological applications.

Effect of Pre-Oxidation Treatment of Nano-SiC Particulates on Microstructure and Mechanical Properties of SiC/Mg-8Al-1Sn Composites Fabricated by Powder Metallurgy Combined with Hot Extrusion.

Nano-SiC particulates (n-SiCp) reinforced Mg-8Al-1Sn (AT81) composites with different pre-oxidation parameters were fabricated by powder metallurgy (P/M) process combined with hot extrusion. The effects of pre-oxidization treatment of n-SiCp on the microstructure and tensile properties of 0.5 vol % n-SiCp/AT81 composites were investigated accordingly. The distribution of n-SiCp with different pre-oxidation parameters was homogeneous in the composites. Moreover, it was found that a thin MgAl2O4 layer formed at the interface when the n-SiCp were pre-oxidized at 1073 K for 2 h, while the MgAl2O4 layer became much thicker with pre-oxidization temperature increasing to 1273 K for 2 h. After an appropriate pre-oxidization treatment of n-SiCp at 1073 K for 2 h, the as-extruded 0.5 vol % n-SiCp/AT81 composites exhibited an enhanced strength. It was found that the yield strength (YS) and ultimate tensile strength (UTS) increased from 168 MPa and 311 MPa to 255 MPa and 393 MPa compared with the as-extruded AT81 alloy, reflecting 51.8% and 26.4% increments, respectively. The improvement of mechanical properties should be mainly attributed to the grain refinement and homogeneous distribution of n-SiCp in the composites. Moreover, a well-bonded interface and the formation of an appropriate amount of interfacial product (MgAl2O4) benefited the material's mechanical properties.

[Optimization of hydroxylating DHEA to 7alpha,15alpha-diOH-DHEA by compound mutation and fermentation optimization].

Combined with method of ketoconazole resistance screening, a 7alpha,15alpha-diOH-DHEA high-producing mutant Colletotrichum lini ST-1 was obtained by compound mutation of NTG and low energy N+ ion beam implantation. With the substrate concentration of 10 g/L DHEA, the molar yield of 7alpha,15alpha-diOH-DHEA reached 34.2%, increased by 46.2% than that of the original strain. Then we optimized the medium. First, Plackett-Burman design was used to evaluate the effects of medium components on molar yield of the product. Results show that glucose, yeast extract and MgSO4 x 7H2O were the important parameters for the biotransformation process. Subsequently, the path of steepest ascent was used to approach the optimal levels. To obtain the optimal levels, central composite design and response surface analysis were carried out. The optimal medium was as follows (g/L): glucose 26.34, yeast extract 12.15, corn flour 3.00, FeSO4 x 7H2O 0.015, MgSO4 x 7H2O 0.14, KH2PO4 0.90. Under the optimal conditions, the molar yield of 7alpha,15alpha-diOH-DHEA reached 49.3%, which was 44.2% higher than that of using the medium before optimization.