Epidemiological Characteristics and Clinical Manifestations of Hepatitis E in a Tertiary Hospital in China: A Retrospective Study

Background

Hepatitis E virus (HEV) infection is the most common cause of acute viral hepatitis worldwide and one of the main causes of death in the last decade, causing chronic hepatitis and liver failure in some populations. The aging population and obesity are two major factors threatening human health. Therefore, we want to understand the relationship between these two groups and HEV infection.

Objectives

The study aimed to analyze the epidemiological, clinical, and laboratory features of HEV infection and evaluate probable high-risk factors for disease progression and the current diagnostic strategies of hepatitis E infection.

Study Design

Patients diagnosed with acute hepatitis E with symptoms and liver dysfunction were enrolled. For statistical analysis, clinical features and laboratory findings were collected between the elderly and non-elderly and HEV+ fatty liver disease (FLD) groups. Statistical analysis was performed using Excel and the platform VassarStats, and statistical significance was taken as P < 0.05.

Results

Jaundice and the bilirubin peak were significantly deeper, the duration of hospitalization was significantly longer, and the proportion of ascites and liver failure was significantly higher in the elderly group. The aging population is one of the risk factors of severe hepatitis E. Hepatitis E becomes more serious in the HEV + FLD group, although the results did not reach statistical significance.

Conclusion

The aging and FLD were suggested to aggravate HEV infection. However, the diagnosis of HEV infection remains a challenge. A prospective study with sufficient sample size is needed to confirm this conclusion.

SERS-based lateral flow immunoassay for sensitive and simultaneous detection of anti-SARS-CoV-2 IgM and IgG antibodies by using gap-enhanced Raman nanotags

The lateral flow immunoassay (LFIA) has played a crucial role in early diagnosis during the current COVID-19 pandemic owing to its simplicity, speed and affordability for coronavirus antibody detection. However, the sensitivity of the commercially available LFIAs needs to be improved to better prevent the spread of the infection. Here, we developed an ultra-sensitive surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-based LFIA) strip for simultaneous detection of anti-SARS-CoV-2 IgM and IgG by using gap-enhanced Raman nanotags (GERTs). The GERTs with a 1 nm gap between the core and shell were used to produce the "hot spots", which provided about 30-fold enhancement as compared to conventional nanotags. The COVID-19 recombinant antigens were conjugated on GERTs surfaces and replaced the traditional colloidal gold for the Raman sensitive detection of human IgM and IgG. The LODs of IgM and IgG were found to be 1 ng/mL and 0.1 ng/mL (about 100 times decrease was observed as compared to commercially available LFIA strips), respectively. Moreover, under the condition of common nano-surface antigen, precise SERS signals proved the unreliability of quantitation because of the interference effect of IgM on IgG.

Evaluation of Production Lots of a Rapid Point-of-Care Lateral Flow Serological Test Intended for Identification of IgM and IgG against the N-Terminal Part of the Spike Protein (S1) of SARS-CoV-2

The potential of rapid point-of-care (POC) tests has been subject of doubt due to an eventual risk of production errors. The aim was therefore to evaluate the two separate production lots of a commercial POC lateral flow test, intended for the detection of IgM and IgG against the SARS-CoV-2 spike protein (S1). Control samples consisted of serum from individuals with confirmed SARS-CoV-2 infection and pre-COVID-19 negative sera gathered from a biobank. The presence of anti-S1 IgM/IgG in the sera was verified by an in-house Luminex-based serological assay (COVID-19 SIA). One hundred samples were verified as positive for anti-S1 IgG and 74 for anti-S1 IgM. Two hundred samples were verified as negative for anti-S1 IgM/IgG. For the two lots of the POC-test, the sensitivities were 93.2% and 87.8% for IgM and 93.0% and 100% for IgG. The specificities were 100% for IgM and 99.5% for IgG. The positive predictive value was 100% for IgM and 98.9% and 99.0% for IgG. The negative predictive value was 97.6% and 95.7% for IgM, and 96.6% and 100% for IgG. The evaluated POC-test is suitable to assess anti-SARS-CoV-2 S1 IgM and IgG, as a measure of previous virus exposure on an individual level. The external validation of separate lots of rapid POC-tests is encouraged to ensure high sensitivity before market introduction.

Blood Plasma Microfluidic Device: Aiming for the Detection of COVID-19 Antibodies Using an On-Chip ELISA Platform

COVID-19 is a public health emergency of international concern. Detection of SARS-CoV-2 virus is an important step towards containing the virus spread. Although viral detection using molecular diagnostic methods is quite common and efficient, these methods are prone to errors, laborious and time consuming. There is an urgent need for blood-based tests which are simple to use, accurate, less time consuming, portable and cost-effective. Human blood plasma contains water, proteins, organic and in-organic substances including bacteria and viruses. Blood plasma can be effectively used to detect COVID-19 antibodies. The immune system generates antibodies (IgM/IgG proteins) in response to the virus and identification of these antibodies is related to the presence of the infection in the patient in the past. Therefore, detecting and testing the presence of these antibodies will be extremely useful for monitoring and surveillance of the population (Petherick, Lancet 395:1101-1102, 2020). Herein, we describe and propose a microfluidic ELISA (enzyme-linked immunosorbent assay) system to detect COVID-19 antibodies on a lab-on-chip platform. We propose to first separate plasma from whole human blood using a microfluidic device and subsequently perform the detection of antibodies in the separated plasma using a semi-automated on-chip ELISA.