Hepatoprotective mechanism of Silybum marianum on nonalcoholic fatty liver disease based on network pharmacology and experimental verification

The study aimed to identify the key active components in Silybum marianum (S. marianum) and determine how they protect against nonalcoholic fatty liver disease (NAFLD). TCMSP, DisGeNET, UniProt databases, and Venny 2.1 software were used to identify 11 primary active components, 92 candidate gene targets, and 30 core hepatoprotective gene targets in this investigation, respectively. The PPI network was built using a string database and Cytoscape 3.7.2. The KEGG pathway and GO biological process enrichment, biological annotation, as well as the identified hepatoprotective core gene targets were analyzed using the Metascape database. The effect of silymarin on NAFLD was determined using H&E on pathological alterations in liver tissues. The levels of liver function were assessed using biochemical tests. Western blot experiments were used to observe the proteins that were expressed in the associated signaling pathways on the hepatoprotective effect, which the previous network pharmacology predicted. According to the KEGG enrichment study, there are 35 hepatoprotective signaling pathways. GO enrichment analysis revealed that 61 biological processes related to the hepatoprotective effect of S. marianum were identified, which mainly involved in response to regulation of biological process and immune system process. Silymarin was the major ingredient derived from S. marianum, which exhibited the hepatoprotective effect by reducing the levels of ALT, AST, TC, TG, HDL-C, LDL-C, decreasing protein expressions of IL-6, MAPK1, Caspase 3, p53, VEGFA, increasing protein expression of AKT1. The present study provided new sights and a possible explanation for the molecular mechanisms of S. marianum against NAFLD

R32 Compressor for Air conditioning and Refrigeration applications in China

This paper evaluates the compressor performance and reliability impact by using R32 refrigerant for air conditioning (residential and commercial system); Performance and reliability impacts are compared with different popular refrigerants used in China, for example, R410A & R22 for AC. The design improvement on the scroll compressor will be discussed in order to reach required efficiency and reliability; these improvements include lubrication, internal heat management, motor design, and vapor injection technologies, etc

Oxybaphus himalaicus Mitigates Lipopolysaccharide-Induced Acute Kidney Injury by Inhibiting TLR4/MD2 Complex Formation

Acute kidney injury (AKI) is described as the abrupt decrease in kidney function always accompanied by inflammation. The roots of Oxybaphus himalaicus Edgew. have long been used in Tibetan folk medicine for the treatment of nephritis. Nevertheless, modern pharmacological studies, especially about the underlying mechanism of O. himalaicus medications, are still lacking. Here, in lipopolysaccharide (LPS)-induced RAW264.7 macrophages, the O. himalaicus extract (OE) showed significant anti-inflammatory activity with the dose dependently reducing the LPS-stimulated release of nitric oxide and the mRNA level and protein expression of inflammatory cytokines and reversed the activation of nuclear factor kappa B (NF-κB). Co-immunoprecipitation assay indicated that OE inhibited Toll-like receptor 4/myeloid differentiation factor 2 (TLR4/MD2) complex formation and further suppressed both myeloid differentiation factor 88 (MyD88)-dependent and TIR-domain-containing adapter-inducing interferon-β (TRIF)-dependent cascades activation. In addition, OE could restrain NADPH oxidase 2 (NOX2) endocytosis by blocking TLR4/MD2 complex formation to prevent reactive oxygen species production. In LPS-induced AKI mice, OE treatment mitigated renal injury and inflammatory infiltration by inhibiting TLR4/MD2 complex formation. UPLC-MS/MS analysis tentatively identified 41 components in OE. Our results indicated that OE presented significant anti-inflammatory activity by inhibiting TLR4/MD2 complex formation, which alleviated LPS-induced AKI in mice

Additional file 1 of Pregabalin mitigates microglial activation and neuronal injury by inhibiting HMGB1 signaling pathway in radiation-induced brain injury

Additional file 1: Fig. S1. Body weight changes in mice receiving radiation or pregabalin. Body weight changes in mice after 14 days of continuous injection of pregabalin (PGB) or saline solution (Con) in RIBI mice. For days 1–4 post-treatment, n = 14–23 mice per group. For days 5–8 post-treatment, n = 10–15 mice per group. For days 9–14 post-treatment, n = 4–9 mice per group. Fig. S2. Microglial body size and CD68 expression changes after radiation in vivo. A Representative confocal images of IBA1 and CD68 co-labeling in the cortex of mice 3, 7, or 14 days after radiation. Red: IBA1, green: CD68. B-C Quantification of the body size of IBA1+ cells and the proportion of CD68+ area / IBA1+ area in the cortex. Data were analyzed by one-way ANOVA followed by the Student’s t-test analysis. All other groups were compared with the control group. n = 4 mice per group and 2–3 slices per mouse for immunofluorescence staining. Data were presented as mean ± SEM, *p < 0.05, **p < 0.01, and ***p < 0.001. Fig. S3. Pregabalin inhibited microglia activation in the cortex of RIBI mice. A Representative images of IBA1 and CD68 co-labeling in the cortex of mice 3 days after radiation. Red: IBA1, green: CD68. B Quantification of the proportion of CD68+ area / IBA1+ area in the cortex of mice 3 days after radiation. C Representative images of IBA1 and CD68 co-labeling in the cortex of mice 7 days after radiation. D Quantification of the proportion of CD68+ area / IBA1+ area in the cortex of mice 7 days after radiation. Data were analyzed by one-way ANOVA followed by the Student’s t-test analysis. All other groups were compared with the indicated group. n = 4 mice per group and 2–3 slices per mouse for immunofluorescence staining. Data were presented as mean ± SEM, *p < 0.05, **p < 0.01, and ***p < 0.001. Fig. S4. Pregabalin inhibited microglia activation in the hippocampus of RIBI mice. A-B Representative confocal images of IBA1 and CD68 co-labeling in the hippocampal CA1 (A) and DG (B) regions of RIBI mice 14 days after pregabalin treatment. Red: IBA1, green: CD68, and blue: DAPI. n = 4 mice per group and 2–3 slices per mouse for immunofluorescence staining. See Fig. 1I-J for statistical data in the main text. Fig. S5. Effect of pregabalin on microglial inflammatory response induced by radiation in vitro. A-D Q-PCR analysis the effects of pregabalin, with different concentration (1 µM, 6.25 µM, 12.5 µM, 25 µM, and 50 µM), on the mRNA levels of inflammatory factors Il-1β, Tnf-α, Cox-2, and iNos in BV2 cells after a single dose of 10 Gy radiation. Data were analyzed by one-way ANOVA followed by the Student’s t-test analysis. All other groups were compared with the indicated group. n = 3 per group for Q-PCR analysis in vitro. Data were presented as mean ± SEM, ns = not significant, **p < 0.01, and ***p < 0.001. Fig. S6. Effect of pregabalin on IL-6 and TNF-α expressions in microglia after radiation. A Representative immunofluorescent images of IL-6 and β-tubulin in BV2 cells among the different groups. Staining with β-tubulin to visualize cytoskeleton and staining with DAPI to visualize nucleus. B The fluorescence intensity data of IL-6 were recorded by confocal microscopy. C Representative immunofluorescent images of TNF-α and β-tubulin in BV2 cells among the different groups. D The fluorescence intensity data of TNF-α were recorded by confocal microscopy. Data were analyzed by one-way ANOVA followed by the Student’s t-test analysis. All other groups were compared with the indicated group. n = 3 per group for immunofluorescence staining in vitro. Data were presented as mean ± SEM, ns = not significant and **p < 0.01. Fig. S7. Pregabalin inhibited microglial inflammatory response not by acting on astrocyte in vitro. A Schematic diagram of BV2 cells incubated with the culture supernatant from astrocyte after different treatment. B-E Q-PCR analysis of Il-1β, Tnf-α, iNos, and Icam-1 mRNA levels in BV2 cells after incubated with the supernatant from pregabalin-treated astrocyte. Data were analyzed by one-way ANOVA followed by the Student’s t-test analysis. All other groups were compared with the indicated group. n = 4 per group for Q-PCR analysis in vitro. Data were presented as mean ± SEM, ns = not significant and *p < 0.05. Fig. S8. Effect of pregabalin on potential chemokines in injured neurons. A-G Q-PCR analysis of Mmp9, Cgrp, Tac1, Cx3cl1, Ccl21, Mmp2, and Ccl2 mRNA levels in neurons after treatment with the different supernatant from BV2 cells. Data were analyzed by one-way ANOVA followed by the Student’s t-test analysis. All other groups were compared with the indicated group. n = 3 per group for Q-PCR analysis in vitro. Data were presented as mean ± SEM, ns = not significant, *p < 0.05, and ***p < 0.001. Fig. S9. Knocking out TLR2/TLR4/RAGE mitigated microglia activation. A-C Schematic diagram of CRISPR/Cas9-mediated TLR2/TLR4/RAGE knockout in BV2 cells and Q-PCR analysis was used to detect the knockout efficiency. D-F Q-PCR analysis of Il-6, Tnf-α, and Cox-2 mRNA levels in activated BV2 cells which were treated with culture supernatant from radiation-injured (activated) or normal (control) neurons for 24 h. Data were analyzed by one-way ANOVA followed by the Student’s t-test analysis. All other groups were compared with the indicated group. n = 3–4 per group for Q-PCR analysis in vitro. Data were presented as mean ± SEM, *p < 0.05, **p < 0.01, and ***p < 0.001. Table S1. List of primers used for RNA analyses. Table S2. List of antibodies used in this study. Table S3. List of gRNA sequences used for CRISPR/Cas9-mediated gene knockout. Table S4. List of oligonucleotide sequences used for plasmid construction. Table S5. List of primers used for the verification of CRISPR/Cas9-mediated gene knockout

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field