Background: Coronavirus disease 2019 , caused by a novel coronavirus (designated as SARS-CoV-2) has become a pandemic worldwide. Based on the current reports, hypertension may be associated with increased risk of sever condition in hospitalized COVID-19 patients. Angiotensin-converting enzyme 2 (ACE2) was recently identified to functional receptor of SARS-CoV-2. Previous experimental data revealed ACE2 level was increased following treatment with ACE inhibitors (ACEIs) and angiotensin receptor blockers (ARBs). Currently doctors concern whether these commonly used renin-angiotensin system (RAS) blockers-ACEIs/ARBs may increase the severity of COVID-19.Methods: We extracted data regarding 50 hospitalized hypertension patients with laboratory confirmed COVID-19 in the Renmin Hospital of Wuhan University from Feb 7 to Mar 03, 2020. These patients were grouped into RAS blockers group (Group A, n=20) and non-RAS blockers group (Group B, n=30) according to the basic blood pressure medications. All patients continued to use pre-admission antihypertensive drugs.Clinical severity (symptoms, laboratory and chest CT findings, etc.), clinical course, and short time outcome were analyzed after hospital admission.Results: Ten (50%) and seventeen (56.7%) of the Group A and Group B participants were males (P=0.643), and the average age was 52.65±13.12 and 67.77±12.84 years (P=0.000), respectively. The blood pressure of both groups was under effective control. There was no significant difference in clinical severity, clinical course and in-hospital mortality between Group A and Group B. Serum cardiac troponin I (cTnI) (P=0.03), and N-terminal (NT)-pro hormone BNP (NT-proBNP) (P=0.04) showed significant lower level in Group A than in Group B. But the patients with more than 0.04ng/mL or elevated NT-proBNP level had no statistical significance between the two groups. In patients over 65 years or under 65 years, cTnI or NT-proBNP level showed no difference between the two groups. Conclusions:We observed there was no obvious difference in clinical characteristics between RAS blockers and non-RAS blockers groups. These data suggest ACEIs/ARBs may have few effects on increasing the clinical severe conditions of COVID-19.
BackgroundRNA-Seq is the recently developed high-throughput sequencing technology for profiling the entire transcriptome in any organism. It has several major advantages over current hybridization-based approach such as microarrays. However, the cost per sample by RNA-Seq is still prohibitive for most laboratories. With continued improvement in sequence output, it would be cost-effective if multiple samples are multiplexed and sequenced in a single lane with sufficient transcriptome coverage. The objective of this analysis is to evaluate what sequencing depth might be sufficient to interrogate gene expression profiling in the chicken by RNA-Seq.ResultsTwo cDNA libraries from chicken lungs were sequenced initially, and 4.9 million (M) and 1.6 M (60 bp) reads were generated, respectively. With significant improvements in sequencing technology, two technical replicate cDNA libraries were re-sequenced. Totals of 29.6 M and 28.7 M (75 bp) reads were obtained with the two samples. More than 90% of annotated genes were detected in the data sets with 28.7-29.6 M reads, while only 68% of genes were detected in the data set with 1.6 M reads. The correlation coefficients of gene expression between technical replicates within the same sample were 0.9458 and 0.8442. To evaluate the appropriate depth needed for mRNA profiling, a random sampling method was used to generate different number of reads from each sample. There was a significant increase in correlation coefficients from a sequencing depth of 1.6 M to 10 M for all genes except highly abundant genes. No significant improvement was observed from the depth of 10 M to 20 M (75 bp) reads.ConclusionThe analysis from the current study demonstrated that 30 M (75 bp) reads is sufficient to detect all annotated genes in chicken lungs. Ten million (75 bp) reads could detect about 80% of annotated chicken genes, and RNA-Seq at this depth can serve as a replacement of microarray technology. Furthermore, the depth of sequencing had a significant impact on measuring gene expression of low abundant genes. Finally, the combination of experimental and simulation approaches is a powerful approach to address the relationship between the depth of sequencing and transcriptome coverage.
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