The Role of Forensic Medicine in Responding to Emergencies and New Major Epidemics.

In recent years, human beings are constantly facing the threat of emerging infectious diseases. Forensic technology plays a unique role in responding to the emergencies and new epidemics. In epidemic prevention and control, forensic partitioners can provide important clues for the identification of vector animal species and the traceability of pathogen regions based on non-human DNA testing technology. In epidemic-related judicial practice, forensic partitioners bear more and more evidence responsibilities in dealing with biosafety laws-related issues, such as improper handling of epidemics and vaccine safety issues, which require forensic evidence. In terms of pathogen tracing, forensic physical evidence examinations identify species and individuals through biological materials extracted from the scene of death and autopsy of infectious diseases, are expected to provide informative clues for epidemiological investigations and point out the direction for pathogen tracing. In addition, forensic pathological examination can provide an important pathophysiological basis for determining the cause of death and the mechanism of death through autopsy, also offer necessary scientific evidence for clarifying the epidemiological characteristics of the epidemic and predicting the development trend of the epidemic.

A population antibody response against SARS-CoV-2 with differential neutralization activities towards the Delta and Omicron variants (preprint)

Population antibody response is believed to be important in selection of new variant viruses. We identified that SARS-CoV-2 infections elicit a population immune response mediated by a lineage of VH1-69 germline antibodies. The representative antibody R1-32 targets a novel semi-cryptic epitope defining a new class of RBD targeting antibodies. Binding to this non-ACE2 competing epitope leading to spike destruction impairing virus entry. Based on epitope location, neutralization mechanism and analysis of antibody binding to spike variants we propose that recurrent substitutions at 452 and 490 are associated with immune evasion of this population antibody response. These substitutions, including L452R found in the Delta variant, disrupt interaction mediated by the VH1-69 specific hydrophobic HCDR2 to impair antibody-antigen association allowing variants to escape. Lacking 452/490 substitutions, the Omicron variant is sensitive to this class of antibodies. Our results provide new insights into SARS-CoV-2 variant genesis and immune evasion.

Novel pectin from crude polysaccharide of Syzygium aromaticum against SARS-CoV-2 activities by targeting 3CLpro (preprint)

To date, COVID-19 is still a severe threat to public health, hence specific effective therapeutic drugs development against SARS-CoV-2 is urgent needed. 3CLpro and PLpro and RdRp are the enzymes required for the SARS-CoV-2 RNA synthesis. Therefore, binding to the enzyme may interfere the enzyme function. Before, we found that sulfated polysaccharide binding to 3CLpro might block the virus replication. Hence, we hypothesize that negative charged pectin glycan may also impede the virus replication. Here we show that 922 crude polysaccharide from Syzygium aromaticum may near completely block SARS-CoV-2 replication. The inhibition rate was 99.9% (EC50 : 0.90 muM). Interestingly, 922 can associates with 3CLpro, PLpro and RdRp. We further show that the homogeneous glycan 922211 from 922 may specifically attenuate 3CL protease activity. The IC50s of 922 and 922211 against 3CLpro are 4.73 plusmn 1.05 muM and 0.18 plusmn 0.01 muM, respectively. Monosaccharide composition analysis reveals that 922211 with molecular weight of 78.7 kDa is composed of rhamnose, galacturonic acid, galactose and arabinose in the molar ratio of 8.21 : 37.81 : 3.58 : 4.49. The structure characterization demonstrated that 922211 is a homogalacturonan linked to RG-I pectin polysaccharide. The linear homogalacturonan part in the backbone may be partly methyl esterified while RG-I type part bearing 1, 4-linked alpha-GalpA, 1, 4-linked alpha-GalpAOMe and 1, 2, 4-linked alpha-Rhap. There are four branches attached to C-1 or C4 position of Rhamnose glycosyl residues on the backbone. The branches are composed of 1, 3-linked beta-Galp, terminal (T)-linked beta-Galp, 1, 5-linked alpha-Araf, T-linked alpha-Araf, 4-linked alpha-GalpA and/or 4-linked beta-GalpA. The above results suggest that 922 and 922211 might be a potential novel leading compound for anti-SARS-CoV-2 new drug development.

Longitudinal peripheral blood transcriptional analysis of COVID-19 patients captures disease progression and reveals potential biomarkers (preprint)

COVID-19, caused by SARS-CoV-2, is an acute self-resolving disease in most of the patients, but some patients can develop a severe illness or even death. To characterize the host responses and identify potential biomarkers during disease progression, we performed a longitudinal transcriptome analysis for peripheral blood mononuclear cells (PBMCs) collected from 4 COVID-19 patients at 4 different time points from symptom onset to recovery. We found that PBMCs at different COVID-19 disease stages exhibited unique transcriptome characteristics. SARS-CoV-2 infection dysregulated innate immunity especially type I interferon response as well as the disturbed release of inflammatory cytokines and lipid mediators, and an aberrant increase of low-density neutrophils may cause tissue damage. Activation of cell death, exhaustion and migratory pathways may lead to the reduction of lymphocytes and dysfunction of adaptive immunity. COVID-19 induced hypoxia may exacerbate disorders in blood coagulation. Based on our analysis, we proposed a set of potential biomarkers for monitoring disease progression and predicting the risk of severity.

Using Reports of Own and Others' Symptoms and Diagnosis on Social Media to Predict COVID-19 Case Counts: Observational Infoveillance Study in Mainland China (preprint)

Can public social media data be harnessed to predict COVID-19 case counts? We analyzed approximately 15 million COVID-19 related posts on Weibo, a popular Twitter-like social media platform in China, from November 1, 2019 to March 31, 2020. We developed a machine learning classifier to identify "sick posts," which are reports of one's own and other people's symptoms and diagnosis related to COVID-19. We then modeled the predictive power of sick posts and other COVID-19 posts on daily case counts. We found that reports of symptoms and diagnosis of COVID-19 significantly predicted daily case counts, up to 14 days ahead of official statistics. But other COVID-19 posts did not have similar predictive power. For a subset of geotagged posts (3.10% of all retrieved posts), we found that the predictive pattern held true for both Hubei province and the rest of mainland China, regardless of unequal distribution of healthcare resources and outbreak timeline. Researchers and disease control agencies should pay close attention to the social media infosphere regarding COVID-19. On top of monitoring overall search and posting activities, it is crucial to sift through the contents and efficiently identify true signals from noise.