Knockout of GGPPS1 restrains rab37-mediated autophagy in response to ventilator-induced lung injury.

Mechanical ventilation may cause ventilator-induced lung injury (VILI) in patients requiring ventilator support. Inhibition of autophagy is an important approach to ameliorate VILI as it always enhances lung injury after exposure to various stress agents. This study aimed to further reveal the potential mechanisms underlying the effects of geranylgeranyl diphosphate synthase large subunit 1 (GGPPS1) knockout and autophagy in VILI using C57BL/6 mice with lung-specific GGPPS1 knockout that were subjected to mechanical ventilation. The results demonstrate that GGPPS1 knockout mice exhibit significantly attenuated VILI based on the histologic score, the lung wet-to-dry ratio, total protein levels, neutrophils in bronchoalveolar lavage fluid, and reduced levels of inflammatory cytokines. Importantly, the expression levels of autophagy markers were obviously decreased in GGPPS1 knockout mice compared with wild-type mice. The inhibitory effects of GGPPS1 knockout on autophagy were further confirmed by measuring the ultrastructural change of lung tissues under transmission electron microscopy. In addition, knockdown of GGPPS1 in RAW264.7 cells reduced cyclic stretch-induced inflammation and autophagy. The benefits of GGPPS1 knockout for VILI can be partially eliminated through treatment with rapamycin. Further analysis revealed that Rab37 was significantly downregulated in GGPPS1 knockout mice after mechanical ventilation, while it was highly expressed in the control group. Simultaneously, Rab37 overexpression significantly enhances autophagy in cells that are treated with cyclin stretch, including GGPPS1 knockout cells. Collectively, our results indicate that GGPPS1 knockout results in reduced expression of Rab37 proteins, further restraining autophagy and VILI.

Coronary artery calcification and risk of mortality and adverse outcomes in patients with COVID-19: a Chinese multicenter retrospective cohort study.

Background: Coronary artery calcification (CAC) is an independent risk factor of major adverse cardiovascular events; however, the impact of CAC on in-hospital death and adverse clinical outcomes in patients with coronavirus disease 2019 (COVID-19) remains unclear. Objective: To explore the association between CAC and in-hospital mortality and adverse events in patients with COVID-19. Methods: This multicenter retrospective cohort study enrolled 2067 laboratory-confirmed COVID-19 patients with definitive clinical outcomes (death or discharge) admitted from 22 tertiary hospitals in China between January 3, 2020 and April 2, 2020. Demographic, clinical, laboratory results, chest CT findings, and CAC on admission were collected. The primary outcome was in-hospital death and the secondary outcome was composed of in-hospital death, admission to intensive care unit (ICU), and requiring mechanical ventilation. Multivariable Cox regression analysis and Kaplan-Meier plots were used to explore the association between CAC and in-hospital death and adverse clinical outcomes. Results: The mean age was 50 years (SD,16) and 1097 (53.1%) were male. A total of 177 patients showed high CAC level, and compared with patients with low CAC, these patients were older (mean age: 49 vs. 69 years, P < 0.001) and more likely to be male (52.0% vs. 65.0%, P = 0.001). Comorbidities, including cardiovascular disease (CVD) ([33.3%, 59/177] vs. [4.7%, 89/1890], P < 0.001), presented more often among patients with high CAC, compared with patients with low CAC. As for laboratory results, patients with high CAC had higher rates of increased D-dimer, LDH, as well as CK-MB (all P < 0.05). The mean CT severity score in high CAC group was also higher than low CAC group (12.6 vs. 11.1, P = 0.005). In multivariable Cox regression model, patients with high CAC were at a higher risk of in-hospital death (hazard ratio [HR], 1.731; 95% CI 1.010-2.971, P = 0.046) and adverse clinical outcomes (HR, 1.611; 95% CL 1.087-2.387, P = 0.018). Conclusion: High CAC is a risk factor associated with in-hospital death and adverse clinical outcomes in patients with confirmed COVID-19, which highlights the importance of calcium load testing for hospitalized COVID-19 patients and calls for attention to patients with high CAC. Supplementary Information: The online version contains supplementary material available at 10.1007/s42058-021-00072-4.

Investigation on mechanism and active components of Shufeng Jiedu Capsule in treatment of COVID-19 based on network pharmacology and molecular docking

Objective: To explore the novel coronavirus disease 2019 (COVID-19) treatment mechanism and active ingredients of Shufeng Jiedu Capsule by network pharmacology and molecular docking. Methods: TCMSP databases were used to search the chemical composition and target of Shufeng Jiedu Capsule, which was composed of Isatidis Radix, Polygonum cuspidatum, Forsythia suspensa, Phragmitis Rhizoma, Patrinia, Verbena officinalis, Bupleurum chinense, and Glycyrrhiza uralensis. The Swiss target prediction database was used to remove the target with possibility of 0. The corresponding targets of the disease were searched in the GeneCards and OMIM databases with the key words of "coronavirus", "pneumonia", "cough", and "fever". Through the UniProt databases to correct the name of the target point, take the intersection of Shufeng Jiedu Capsule and the disease target point, then use the software of Cytoscape 3.7.2 to build the network of traditional Chinese medicine-compound-target for visualization, through DAVID databases to carry out the GO function enrichment analysis and KEGG pathway enrichment analysis, predict the interaction mechanism of the target, and draw the column and bubble chart for visualization. The novel coronavirus (SARS-CoV-2) 3CL hydrolase was then docking with all compounds and the first five compounds with the least binding energy were selected for docking with angiotensin-converting enzyme II (ACE2). Results: The traditional Chinese medicine-compound-target compound target network contains eight kinds of traditional Chinese medicine-compound-target, 157 compounds and 260 corresponding targets. The key targets were PTGS2, ESR1, AR, etc. There were 393 items in GO functional enrichment analysis (P < 0.05), and 139 signaling pathways in KEGG pathway enrichment analysis. Molecular docking results showed that SARS-CoV-2 3CL hydrolase and ACE2 binding energy of the five core compounds, including 6-(3-oxoindolin-2-ylidene) indolo [2,1-b] quinazolin-12-one, bicuculline, physciondiglucoside, dihydroverticillatine, and licoisoflavanone, was smaller than that of recommended chemical drugs, and the binding energy to ACE2 was similar to that of the recommended chemical drug. Conclusion: The compounds in Shufeng Jiedu Capsule can regulate the signaling pathway of human cytomegalovirus infection, Kaposi's sarcoma associated herpesvirus infection, IL-17 signaling pathway, small cell lung cancer, etc. to treat COVID-19 by binding with SARS-CoV-2 3CL hydrolase and ACE2.

Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study.

Background: The risk factors for adverse events of Coronavirus Disease-19 (COVID-19) have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods: This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results: Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR], 6.734; 95% CI; 3.239-14.003, p < 0.001), leukocytosis (HR, 9.639; 95% CI, 4.572-20.321, p < 0.001), lymphopenia (HR, 4.579; 95% CI, 1.334-15.715, p = 0.016) and CT severity score > 14 (HR, 2.915; 95% CI, 1.376-6.177, p = 0.005) on admission, while older age (HR, 2.231; 95% CI, 1.124-4.427, p = 0.022), ≥ 2 comorbidities (HR, 4.778; 95% CI; 2.451-9.315, p < 0.001), leukocytosis (HR, 6.349; 95% CI; 3.330-12.108, p < 0.001), lymphopenia (HR, 3.014; 95% CI; 1.356-6.697, p = 0.007) and CT severity score > 14 (HR, 1.946; 95% CI; 1.095-3.459, p = 0.023) were associated with increased odds of composite adverse outcomes. Conclusion: The risk factors of older age, multiple comorbidities, leukocytosis, lymphopenia and higher CT severity score could help clinicians identify patients with potential adverse events.