Trace Analysis of Emerging Virus: an Ultrasensitive ECL-Scan Imaging System for Viral Infectious Disease (preprint)

Background: Emerging infectious disease have brought a huge impact on human society in recent years. The outbreak of Zika virus (ZIKV) in the Americas resulted in a large number of babies born with microcephaly. More seriously, the Coronavirus Disease 2019 (COVID-19) caused the global spreads and immeasurable damages. Thus, the monitoring of highly pathogenic virus is of significance to the prevention and control of emerging infectious disease.ResultsHerein, a dendritic polymer probe-amplified ECL-scan imaging system was constructed to realize trace analysis of viral emerging infectious disease. Dendritic polymer probe was employed as the efficient signal giving-out component that could generate amplified electrochemiluminescence (ECL) signal on the integrated chip. And the signal was detected by a single-photon level charge coupled device-based ECL-scan imaging system. With this strategy,the ZIKV in the complex system of blood, urine and saliva were detected. The results indicated that high sensitivity of 50 copies and superior specificity were achieved. Furthermore, this strategy realized highly sensitive detection (10 copies) of S and N protein gene sequence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov2) and spiked pseudovirus samples.ConclusionsThus, the dendritic polymer probe-amplified ECL-scan imaging system suitably met the strict clinical-requirements for trace analysis of emerging virus, and thus has the potential to serve as a paradigm for monitoring of emerging infectious disease.

Risk assessment of progression to severe conditions for patients with COVID-19 pneumonia: a single-center retrospective study (preprint)

Background: Management of high mortality risk due to significant progression requires prior assessment of time-to-progression. However, few related methods are available for COVID-19 pneumonia. Methods: We retrospectively enrolled 338 adult patients admitted to one hospital between Jan 11, 2020 to Feb 29, 2020. The final follow-up date was March 8, 2020. We compared characteristics between patients with severe and non-severe outcome, and used multivariate survival analyses to assess the risk of progression to severe conditions. Results: A total of 76 (31.9%) patients progressed to severe conditions and 3 (0.9%) died. The mean time from hospital admission to severity onset is 3.7 days. Age, body mass index (BMI), fever symptom on admission, co-existing hypertension or diabetes are associated with severe progression. Compared to non-severe group, the severe group already demonstrated, at an early stage, abnormalities in biomarkers indicating organ function, inflammatory responses, blood oxygen and coagulation function. The cohort is characterized with increasing cumulative incidences of severe progression up to 10 days after admission. Competing risks survival model incorporating CT imaging and baseline information showed an improved performance for predicting severity onset (mean time-dependent AUC = 0.880). Conclusions: Multiple predisposition factors can be utilized to assess the risk of progression to severe conditions at an early stage. Multivariate survival models can reasonably analyze the progression risk based on early-stage CT images that would otherwise be misjudged by artificial analysis.