Interleukin-6 level is an independent predictor of right ventricular systolic dysfunction in patients hospitalized with COVID-19

Long-term cardio-vascular risk assessment in chronic kidney disease and kidney transplanted patients following SARS-COV-2 disease: protocol for multi-center observational match controlled trial

BACKGROUND

The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) produced a pandemic since March 2020 by affecting more than 243 million people with more than 5 million deaths globally. SARS-CoV-2 infection is produced by binding to angiotensin-converting enzyme, which among other sites is highly expressed in the endothelial cells of the blood vessels, pericytes and the heart, as well as in renal podocytes and proximal tubular epithelial cells. SARS-CoV-2 and cardiovascular disease (CVD) are interconnected by risk factors association with an increased incidence of the disease and by determining de novo cardiac complications. At the same time, COVID-19 disease can lead to acute kidney injury directly, or due to sepsis, multi-organ failure and shock. Therefore, the pre-existence of both CVD and chronic kidney disease (CKD) is linked with a higher risk of severe disease and worse prognosis.

METHODS

The main aim of this study is to assess the CV risk in a CKD (stage 3 to 5), dialysis and kidney transplanted population, following SARS-CoV-2 infection, with focus on the endothelial dysfunction as compared to a control group of matched patients. By using clinical evaluation, flow-mediated dilatation, carotid-femoral pulse wave velocity, intima-media thickness, echocardiographic parameters, lung ultrasound, bioimpedance spectroscopy and a series of novel biomarkers, the investigators will determine the long-term impact of this disease on CV and renal outcomes.

DISCUSSION

This study will address the challenges and implications in long-term CV sequeale of COVID-19 and focus on a better understanding of the underlying mechanisms and possible therapeutic options.

TRIAL REGISTRATION

Patient enrolment in the trial started in January 2021 and is expected to finish at the end of 2022. The study can be found on ClinicalTrials.gov database with NCT05125913 identifier. Registered on 18 November 2021 - Retrospectively registered.

The Potential Bioactive Components of Nine TCM Prescriptions Against COVID-19 in Lung Cancer Were Explored Based on Network Pharmacology and Molecular Docking

Objective

The purpose of this study was to screen active components and molecular targets of nine prescriptions recommended by the National Health Commission (NHC) of China by network pharmacology, and to explore the potential mechanism of the core active components against COVID-19 with molecular docking.

Methods

Differentially expressed genes of lung adenocarcinoma (LUAD) screened by edgeR analysis were overlapped with immune-related genes in MMPORT and COVID-19-related genes in GeneCards. The overlapped genes were also COVID-19 immune-related genes in LUAD. TCMSP platform was used to identify active ingredients of the prescription, potential targets were identified by the UniProt database, and the cross genes with COVID-19 immune-related genes in LUAD were used to construct a Chinese Medicine-Logy-immune target network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the target genes of each prescription. Finally, the key active components were selected for molecular docking simulation with ACE2.

Results

We obtained 15 overlapping immunization target genes from FPQXZ, HSYFZ, HSZFZ, and QFPDT, 16 overlapping immunization target genes from QYLFZ, SDYFZ, SRYFZ, and YDBFZ, and 17 overlapping immunization target genes from QYLXZ. ADRB2, FOS, HMOX1, ICAM1, IL6, JUN, NFKBIA, and STAT1 also had the highest-ranked therapeutic targets for 9 prescriptions, and their expressions were positively correlated with TME-related stromal score, immune score, and ESTIMATE score. Among 9 compounds with the highest frequency of occurrence in the 9 prescriptions, baicalein had the highest ACE2 binding affinity and can be well-combined into the active pocket of ACE2 It is stabilized by forming hydrogen bonds with ASN290 and ILE291 in ACE2 and hydrophobic interaction with PHE438, ILE291, and PRO415.

Conclusion

The nine Chinese medicine prescriptions may play an anti-SARS-CoV-2 role via regulating viral transcription and immune function through multi-component, multi-target, and multi-pathway.