Mechanism of acupuncture and moxibustion in ameliorating liver injury induced by cisplatin by regulating IRE-1 signaling pathway. / "扶正益肝"é’ˆç¸ç©´æ–¹åŸºäºŽè‚Œé†‡éœ€æ±‚é ¶1ä¿¡å·é€šè·¯æ”¹å–„é¡ºé“‚è‡´å°é¼ è‚æŸä¼¤çš„æœºåˆ¶.

OBJECTIVES: To investigate the mechanism of the effect of acupuncture and moxibustion on improving liver injury in cisplatin (DDP) induced liver injury model mice by observing the changes of inositol-requiring enzyme (IRE) -1 signaling pathway. METHODS: Forty KM mice were randomly divided into control, model, acupuncture and moxibustion groups, with 10 mice in each group. The liver injury model was replicated by intraperitoneal injection of DDP (10 mg/kg). In the acupuncture group and the moxibustion group, acupuncture and moxibustion were performed at "Dazhui"(GV14), and bilateral "Ganshu"(BL18), "Shenshu" (BL23), and "Zusanli"(ST36), respectively for 6 min, once per day for 7 d. The apoptosis of hepatocytes was detected by TUNEL staining. The expression of phosphorylation(p)-IRE-1α, glucose-regulated protein (Grp) 78 and cysteine aspartic protease (Caspase) -12 in liver tissue were detected by immunohistochemistry and Western blot, respectively. The expression levels of Grp78 and Caspase-12 mRNA in liver tissue were detected by quantitative real-time PCR. RESULTS: Compared with the control group, the apoptosis rate of hepatocytes was increased (P<0.05), the positive expression and protein expression of p-IRE-1α, Grp78, and Caspase-12 were increased (P<0.05), the expression levels of Grp78 and Caspase-12 mRNA were increased (P<0.05) in the model group. Compared with the model group, all these indicators showed opposite trends (P<0.05) in the acupuncture and moxibustion groups. CONCLUSIONS: Acupuncture and moxibustion can reduce liver injury due to DDP chemotherapy by modulating IRE-1 signaling pathway, inhibiting the excessive activation of endoplasmic reticulum stress, and reducing liver cell apoptosis.

[Exploration of cancer biological characteristics in people with different five movements and six climates constitution based on pan-cancer Bulk RNA-Seq].

According to the theory of five movements and six climates, the innate constitution plays a crucial role in determining the underlyingpa thological mechanisms of diseases later in life. Previous studies have demonstrated a close association between the constitution, as defined by the theory of five movements and six climates, and the development of various types of tumors. Furt hermore,the tumorsubtype determined by the constitution has prognostic implications. This highlights the potential of utilizing the fivemovements and six climates theory to guide the implementation of precision medicine strategies in thefield of oncology. However, no resear ch has yet been conducted to investigate the use of this theory in guiding the development of tumor molecular classification and precisi onmedicine strategies. The objective of this research is to uncover the biological characteristics of each constitution within a pancanc ercohort and identify potential anti-tumor drugs that are applicable to patients with different constitutional types. By doing so, we aimto c ontribute to the establishment of a precision medicine strategy for tumors derived from the original concepts of traditional Chi nesemedicine(TCM). In this study, we obtainedpan-cancer Bulk RNA-Seq data from UCSC Xena, GWAS cohort data from the UKBiobank, and cis-eQTLs data from eQ TLGen and GTEx V8. We employed machine learning methods to screen for hub genes associated with each constitution. Subsequently, we utilized informatics tools to explore the biological characteristics of each constitut iondefined by the theory of five movements and six bioclimates. Further, potential anti-tumor drugs suitable for patients with differen tconstitutional types were identified through mendelian randomization, molecular docking, and drug-like prediction techniques. Withinthe pan-cancer cohort, significant differences were observed among different constitutions in terms of progression-free interval, biological f unctions, immune cell abundance, tumor drug sensitivity, and immunotherapy response. These findings suggest that the five movements and six climates theory can guide tumor molecular classification and the development of precision medicine strategies. Moreover,the biological characteristics inherent to each constitution partially shed light on the scientific implications of Chinese medicinetheories, offering a fresh perspective towards clinical cancer treatment. Through molecular docking and drug-like prediction, several po tential anti-tumor drugs such as 17-beta-estradiol, serotonin, trans-resveratrol, and linoleic acid were identified. Overall, the util izationof multi-omics approaches pro vides a powerful tool to unravel the scientific foundations of TCM theories. The elucidation of themu lti-omics features associated witheach constitution in tumors serves as the basis for applying the five movements and six climates theoryto tumor molecular classification and the development of precision medicine strategies.

Cerebral endothelial cells mediated enhancement of brain pericyte number and migration in oxygen-glucose deprivation involves the HIF-1α/PDGF-ß signaling.

The present study focused on whether hypoxia-inducible factor-1alpha (HIF-1α) and platelet-derived factor-beta (PDGF-ß) are involved in the crosstalk between brain microvascular endothelial cells (BMECs) and brain vascular pericytes (BVPs) under ischaemic-hypoxic conditions. Mono-cultures or co-cultures of BVPs and BMECs were made for the construction of the blood-brain barrier (BBB) model in vitro and then exposed to control and oxygen-glucose deprivation (OGD) conditions. BBB injury was determined by assessing the ability, apoptosis, and migration of BVPs and the transendothelial electrical resistance and horseradish peroxidase permeation of BMECs. Relative mRNA and protein levels of HIF-1α and PDGF-ß, as well as tight junction proteins ZO-1 and claudin-5 were analyzed by western blotting, reverse transcription quantitative PCR, and/or immunofluorescence staining. Dual-luciferase reporter assays assessed the relationship between PDGF-ß and HIF-1α. Co-culturing with BMECs alleviated OGD-induced reduction in BVP viability, elevation in BVP apoptosis, and repression in BVP migration. Co-culturing with BVPs protected against OGD-induced impairment on BMEC permeability. OGD-induced HIF-1α upregulation enhanced PDGF-ß expression in mono-cultured BMECs and co-cultured BMECs with BVPs. Knockdown of HIF-1α impaired the effect of BMECs on BVPs under OGD conditions, and PDGFR-ß silencing in BVPs blocked the crosstalk between BMECs and BVPs under OGD conditions. The crosstalk between BMECs and BVPs was implicated in OGD-induced BBB injury through the HIF-1α/PDGF-ß signaling.

Mining channel-regulated peptides from animal venom by integrating sequence semantics and structural information.

Channel-regulated peptides (CRPs) derived from animal venom hold great promise as potential drug candidates for numerous diseases associated with channel proteins. However, discovering and identifying CRPs using traditional bio-experimental methods is a time-consuming and laborious process. While there were a few computational studies on CRPs, they were limited to specific channel proteins, relied heavily on complex feature engineering, and lacked the incorporation of multi-source information. To address these problems, we proposed a novel deep learning model, called DeepCRPs, based on graph neural networks for systematically mining CRPs from animal venom. By combining the sequence semantic and structural information, the classification performance of four CRPs was significantly enhanced, reaching an accuracy of 0.92. This performance surpassed baseline models with accuracies ranging from 0.77 to 0.89. Furthermore, we employed advanced interpretable techniques to explore sequence and structural determinants relevant to the classification of CRPs, yielding potentially valuable bio-function interpretations. Comprehensive experimental results demonstrated the precision and interpretive capability of DeepCRPs, making it an accurate and bio-explainable suit for the identification and categorization of CRPs. Our research will contribute to the discovery and development of toxin peptides targeting channel proteins. The source data and code are freely available at https://github.com/liyigerry/DeepCRPs.