Shaofeng Zhan

Background: Acute lung injury (ALI) is primarily defined by hyper-inflammation and the breakdown of the alveolar-capillary barrier, frequently culminating in refractory respiratory failure. Current clinical interventions—predominantly glucocorticoids and supportive therapies—often yield suboptimal outcomes and are associated with significant side effects. Qingfei Litan Prescription (QFLTP), a traditional Chinese medical prescription indicated for inflammatory respiratory disorders, exhibits significant therapeutic potential; however, the precise molecular mechanisms driving its protective effects are currently under-investigated. Methods: Qualitative detection of the QFLTP ingredients was accomplished via UHPLC-MS/MS analysis. Active ingredients and their potential targets were screened using online prediction tools and traditional Chinese medicine databases, Concurrently, genes associated with ALI were retrieved via GeneCards, DisGeNET, and OMIM repositories. The intersection of these target sets underwent rigorous investigation, encompassing protein-protein interaction (PPI) mapping, alongside Gene Ontology (GO) and KEGG pathway enrichment evaluations, and multiple data-driven algorithms to identify hub genes. Computational modeling and simulation methods were performed to evaluate ligand-target binding. An LPS-induced ALI mouse model was established for in vivo validation. Histopathological examination, bronchoalveolar lavage fluid (BALF) protein quantification, inflammatory cytokine assays, arterial blood gas analysis, immunohistochemistry, immunofluorescence, Western blot, and qRT-PCR served to evaluate the therapeutic potential of QFLTP. Results: A total of 47 chemical constituents and 298 overlapping therapeutic targets were identified. Integrated computational and data-driven analyses highlighted POLB, FGF1, and ARG1 as potential hub genes involved in QFLTP-mediated protection against ALI. GO and KEGG enrichment analyses revealed that pharmacological restorative capacity of QFLTP activity demonstrated a robust functional linkage to inflammatory responses, PI3K-Akt signaling, VEGF signaling, and immune-related pathways. In vivo trials revealed that QFLTP administration markedly mitigated pulmonary histopathological impairment while simultaneously suppressing the secretion of pro-inflammatory mediators and pulmonary edema, improving lung function and arterial blood gas parameters, and promoted the recovery of junctional protein expression of ZO-1, ZO-2, and VE-cadherin in lung tissues. In addition, qRT-PCR profiling revealed that QFLTP treatment effectively normalized the aberrant mRNA levels of POLB, FGF1, and ARG1 in the lung tissues of the ALI cohort. Conclusion: QFLTP exerts protective effects against ALI via its multi-component, multi-target, and multi-pathway mechanisms, potentially by suppressing inflammatory responses, restoring pulmonary barrier integrity, and regulating the expression of hub genes including POLB, FGF1, and ARG1.

Influenza (Flu) is a severe health, medical, and economic problem, but no medication that has excellent outcomes and lowers the occurrence of these problems is now available. GanghuoQingwenGranules (GHQWG) is a common Chinese herbal formula for the treatment of influenza (flu). However, its methods of action remain unknown. We used network pharmacology, molecular docking, and molecular dynamics simulation techniques to investigate the pharmacological mechanism of GHQWG in flu. TCMSP and various types of literature were used to obtain active molecules and targets of GHQWG. Flu-related targets were found in the Online Mendelian Inheritance in Man (OMIM) database, the DisFeNET database, the Therapeutic Target Database (TTD), and the DrugBank database. To screen the key targets, a protein–protein interaction (PPI) network was constructed. DAVID was used to analyze GO and KEGG pathway enrichment. Target tissue and organ distribution was assessed. Molecular docking was used to evaluate interactions between possible targets and active molecules. For the ideal core protein–compound complexes obtained using molecular docking, a molecular dynamics simulation was performed. In total, 90 active molecules and 312 GHQWG targets were discovered. The PPI network's topology highlighted six key targets. GHQWG's effects are mediated via genes involved in inflammation, apoptosis, and oxidative stress, as well as the TNF and IL-17 signaling pathways, according to GO and KEGG pathway enrichment analysis. Molecular docking and molecular dynamics simulations demonstrated that the active compounds and tested targets had strong binding capabilities. This analysis accurately predicts the effective components, possible targets, and pathways involved in GHQWG flu treatment. We proposed a novel study strategy for future studies on the molecular processes of GHQWG in flu treatment. Furthermore, the possible active components provide a dependable source for flu drug screening.

Background:Influenza (Flu) is a severe health, medical, and economic problem, but no medication that has excellent outcomes and lowers the occurrence of these problems is now available. GanghuoQingwenGranules(GHQWG) is a common Chinese herbal formula for the treatment of influenza (flu). However, its methods of action remain unknown. We used network pharmacology, molecular docking, and molecular dynamics simulation techniques to investigate the pharmacological mechanism of GHQWGin flu. Methods: TCMSP and various types of literature were used to obtain active molecules and targets of GHQWG. Flu-related targets were found in the Online Mendelian Inheritance in Man (OMIM) database, the DisFeNET database, the Therapeutic Target Database (TTD), and the DrugBank database. To screen the key targets, a protein-protein interaction (PPI) network was constructed. DAVID was used to analyze GO and KEGG pathway enrichment. Target tissue and organ distribution was assessed. Molecular docking was used to evaluate interactions between possible targets and active molecules. For the ideal core protein-compound complexes obtained using molecular docking, a molecular dynamics simulation was performed. Results: In total, 90 active molecules and 312 GHQWG targets were discovered. The PPI network's topology highlighted six key targets. GHQWG's effects are mediated via genes involved in inflammation, apoptosis, and oxidative stress, as well as the TNF and IL-17 signaling pathways, according to GO and KEGG pathway enrichment analysis. Molecular docking and molecular dynamics simulations demonstrated that the active compounds and tested targets had strong binding capabilities. Conclusions: This analysis accurately predicts the effective components, possible targets, and pathways involved in GHQWG flu treatment. We proposed a novel study strategy for future studies on the molecular processes of GHQWGin flu treatment. Furthermore, the possible active components provide a dependable source for flu drug screening.

Background: There is increasing evidence pointing to a close relationship between sarcopenia and inflammatory bowel disease. However, it remains unclear whether or in which direction causal relationships exist, because these associations could be confounded.Methods: We conducted a two-sample bidirectional mendelian randomization analysis using data from European genome-wide association studies of the appendicular lean mass(n = 450,243), walking pace(n = 459,915), grip strength (left hand, n = 461,026; right hand, n = 461,089), inflammatory bowel disease (25,042 patients and 34,915 controls), ulcerative colitis (12,366 patients and 33,609 controls), and Crohn’s disease (12,194 patients and 28,072 controls) to investigate the causal relationship between sarcopenia-related traits and inflammatory bowel disease and its subtypes on each other. The inverse-variance weighted method was used as the primary analysis method to assess the causality, and a comprehensive sensitivity test was conducted.Results: Genetically predicted appendicular lean mass was significantly associated with inflammatory bowel disease (OR = 0.916, 95%CI: 0.853–0.984, P = 0.017), ulcerative colitis (OR =0.888, 95%CI: 0.813–0.971, P = 0.009), and Crohn’s disease (OR = 0.905, 95%CI: 0.820–0.999, P = 0.049). Similar results also revealed that the usual walking pace was causally associated with Crohn’s disease (OR = 0.467, 95%CI: 0.239–0.914, P = 0.026). Reverse mendelian randomization analysis results found that genetic susceptibility to inflammatory bowel disease, and Crohn’s disease were associated with lower appendicular lean mass. A series of sensitivity analyses ensured the reliability of the present research results.Conclusion: The mendelian randomization study supports a bidirectional causality between inflammatory bowel disease, Crohn’s disease and appendicular lean mass, but no such bidirectional causal relationship was found in ulcerative colitis. In addition, genetically predicted usual walking pace may reduce the risk of Crohn’s disease. These findings have clinical implications for sarcopenia and inflammatory bowel disease management.

Background: Coronavirus disease 2019 (COVID‐19) is a highly contagious respiratory disease that has posed a serious threat to people’s daily lives and caused an unprecedented challenge to public health and people’s health worldwide. Lung squamous cell carcinoma (LUSC) is a common type of lung malignancy with a highly aggressive nature and poor prognosis. Patients with LUSC could be at risk for COVID-19, We conducted this study to examine the potential for naringenin to develop into an ideal medicine and investigate the underlying action mechanisms of naringenin in COVID-19 and LUSC due to the anti-viral, anti-tumor, and anti-inflammatory activities of naringenin.Methods: LUSC related genes were obtained from TCGA, PharmGKB, TTD,GeneCards and NCBI, and then the transcriptome data for COVID-19 was downloaded from GEO, DisGeNET, CTD, DrugBank, PubChem, TTD, NCBI Gene, OMIM. The drug targets of Naringenin were revealed through CTD, BATMAN, TCMIP, SymMap, Chemical Association Networks, SwissTargetPrediction, PharmMapper, ECTM, and DGIdb. The genes related to susceptibility to COVID-19 in LUSC patients were obtained through differential analysis. The interaction of COVID-19/LUSC related genes was evaluated and demonstrated using STRING to develop a a COX risk regression model to screen and evaluate the association of genes with clinical characteristics. To investigate the related functional and pathway analysis of the common targets of COVID-19/LUSC and Naringenin, KEGG and GO enrichment analysis were employed to perform the functional analysis of the target genes. Finally, The Hub Gene was screened and visualized using Cytoscape, and molecular docking between the drug and the target was performed using Autodock.Results: We discovered numerous COVID-19/LUSC target genes and examined their prognostic value in LUSC patients utilizing a variety of bioinformatics and network pharmacology methods. Furthermore, a risk score model with strong predictive performance was developed based on these target genes to assess the prognosis of LUSC patients with COVID-19. We intersected the therapeutic target genes of naringenin with the LUSC, COVID-19-related targets, and identified 354 common targets, which could be used as potential target genes for naringenin to treat COVID-19/LUSC. The treatment of COVID-19/LUSC with naringenin may involve oxidative stress, anti-inflammatory, antiviral, antiviral, apoptosis, immunological, and multiple pathways containing PI3K-Akt, HIF-1, and VEGF, according to the results of the GO and KEGG enrichment analysis of these 354 common targets. By constructing a PPI network, we ascertained AKT1, TP53, SRC, MAPK1, MAPK3, and HSP90AA1 as possible hub targets of naringenin for the treatment of COVID-19/LUSC. Last but not least, molecular docking investigations showed that naringenin has strong binding activity in COVID-19/LUSC.Conclusion: We revealed for the first time the pharmacological targets and potential molecular processes of naringenin for the treatment of COVID-19/LUSC. However, these results need to be confirmed by additional research and validation in real LUSC patients with COVID-19.

Background: Pneumonia caused by novel coronavirus (COVID-19) is spreading worldwide. Traditional Chinese medicines (TCM) have played an important role in COVID-19 treatment in China. This study explores the specific mechanisms of action of Reduning injection (RDN) as a novel clinical treatment for COVID-19. Material and Methods: We collected RDN chemical components and targets, COVID-19-related targets, and predictions of potential targets of RDN treatment for COVID-19 and performed network topology, Gene Ontology (GO) functional enrichment analysis and WikiPathways enrichment analysis of these potential targets. Results: This study identified 14 chemical components and 200 targets of RDN; 3,558 COVID-19-related targets; 54 potential targets of RDN treatment for COVID-19. GO functional enrichment analysis identified 83 entries in biological process, including regulation of vasoconstriction、arachidonic acid secretion, and 17 entries in molecular function, including oxidoreductase activity, acting on the aldehyde or oxo group of donors. WikiPathways enrichment analysis identified 16 entries including the interleukin-12 signaling pathway. Conclusion: In brief, RDN may be involved in the core anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) action and also in the reduction of the resulting inflammatory response, oxidative stress, and lung tissue damage, and the regulation of apoptosis, providing evidence for the characteristics of TCM in COVID-19 treatment involving multiple components, targets, and pathways.