Quantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 RNA from 77 patients, and compared with RT-PCR in terms of the diagnostic accuracy based on the results of follow-up survey. 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by ddPCR. The sensitivity, specificity, PPV, NPV, negative likelihood ratio (NLR) and accuracy were improved from 40% (95% CI: 27-55%), 100% (95% CI: 54-100%), 100%, 16% (95% CI: 13-19%), 0.6 (95% CI: 0.48-0.75) and 47% (95% CI: 33-60%) for RT-PCR to 94% (95% CI: 83-99%), 100% (95% CI: 48-100%), 100%, 63% (95% CI: 36-83%), 0.06 (95% CI: 0.02-0.18), and 95% (95% CI: 84-99%) for ddPCR, respectively. Moreover, 6/14 (42.9%) convalescents were detected as positive by ddPCR at 5-12 days post discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the RT-PCR.
The upcoming flu season in the Northern Hemisphere merging with the current COVID-19 pandemic raises a potentially severe threat to public health. Through experimental coinfection with influenza A virus (IAV) and either pseudotyped or live SARS-CoV-2 virus, we found that IAV preinfection significantly promoted the infectivity of SARS-CoV-2 in a broad range of cell types. Remarkably, in vivo, increased SARS-CoV-2 viral load and more severe lung damage were observed in mice coinfected with IAV. Moreover, such enhancement of SARS-CoV-2 infectivity was not observed with several other respiratory viruses, likely due to a unique feature of IAV to elevate ACE2 expression. This study illustrates that IAV has a unique ability to aggravate SARS-CoV-2 infection, and thus, prevention of IAV infection is of great significance during the COVID-19 pandemic.
Different primers/probes sets have been developed all over the world for the nucleic acid detection of SARS-CoV-2 by quantitative real time polymerase chain reaction (qRT-PCR) as a standard method. In our recent study, we explored the feasibility of droplet digital PCR (ddPCR) for clinical SARS-CoV-2 nucleic acid detection compared with qRT-PCR using the same primer/probe sets issued by Chinese Center for Disease Control and Prevention (CDC) targeting viral ORF1ab or N gene, which showed that ddPCR could largely minimize the false negatives reports resulted by qRT-PCR [Suo T, Liu X, Feng J, et al. ddPCR: a more sensitive and accurate tool for SARS-CoV-2 detection in low viral load specimens. medRxiv [Internet]
Nonalcoholic steatohepatitis (NASH) is a common clinical condition that can lead to advanced liver diseases. Lack of effective pharmacotherapies for NASH is largely attributable to an incomplete understanding of its pathogenesis. The deubiquitinase cylindromatosis (CYLD) plays key roles in inflammation and cancer. Here we identified CYLD as a suppressor of NASH in mice and in monkeys. CYLD is progressively degraded upon interaction with the E3 ligase TRIM47 in proportion to NASH severity. We observed that overexpression of Cyld in hepatocytes concomitantly inhibits lipid accumulation, insulin resistance, inflammation and fibrosis in mice with NASH induced in an experimental setting. Mechanistically, CYLD interacts directly with the kinase TAK1 and removes its K63-linked polyubiquitin chain, which blocks downstream activation of the JNK-p38 cascades. Notably, reconstitution of hepatic CYLD expression effectively reverses disease progression in mice with dietary or genetically induced NASH and in high-fat diet-fed monkeys predisposed to metabolic syndrome. Collectively, our findings demonstrate that CYLD mitigates NASH severity and identify the CYLD-TAK1 axis as a promising therapeutic target for management of the disease.
The rapid development of smart wearable and integrated electronic products has urgently increased the requirement for high‐performance microbatteries. Although few lithium ion microbatteries based on organic electrolytes have been reported so far, the problems, such as undesirable energy density, poor flexibility, inflammability, volatility toxicity, and high cost restrict their practical applications in the above‐mentioned electronic products. In order to overcome these problems, a low cost quasi‐solid‐state aqueous zinc ion microbattery (ZIMB) assembled by a vanadium dioxide (B)‐multiwalled carbon nanotubes (VO2 (B)‐MWCNTs) cathode, a zinc nanoflakes anode, and a zinc trifluoromethanesulfonate‐polyvinyl alcohol (Zn(CF3SO3)2‐PVA) hydrogel electrolyte is exploited. As expected, the ZIMB exhibits excellent electrochemical performance, e.g., a high capacity of 314.7 µAh cm−2, an ultrahigh energy density of 188.8 µWh cm−2, and a high power density of 0.61 mW cm−2. Furthermore, the ZIMB also shows high flexibility and excellent high temperature stability: the capacity has no obvious decay when the bending angle is up to 150° and the temperature reaches 100 °C. The ZIMB provides a way to develop next‐generation miniature energy storage devices with high performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.