Early autoimmunity and outcome in virus encephalitis: a retrospective study based on tissue-based assay.

To explore the autoimmune response and outcome in the central nervous system (CNS) at the onset of viral infection and correlation between autoantibodies and viruses. METHODS: A retrospective observational study was conducted in 121 patients (2016-2021) with a CNS viral infection confirmed via cerebrospinal fluid (CSF) next-generation sequencing (cohort A). Their clinical information was analysed and CSF samples were screened for autoantibodies against monkey cerebellum by tissue-based assay. In situ hybridisation was used to detect Epstein-Barr virus (EBV) in brain tissue of 8 patients with glial fibrillar acidic protein (GFAP)-IgG and nasopharyngeal carcinoma tissue of 2 patients with GFAP-IgG as control (cohort B). RESULTS: Among cohort A (male:female=79:42; median age: 42 (14-78) years old), 61 (50.4%) participants had detectable autoantibodies in CSF. Compared with other viruses, EBV increased the odds of having GFAP-IgG (OR 18.22, 95% CI 6.54 to 50.77, p<0.001). In cohort B, EBV was found in the brain tissue from two of eight (25.0%) patients with GFAP-IgG. Autoantibody-positive patients had a higher CSF protein level (median: 1126.00 (281.00-5352.00) vs 700.00 (76.70-2899.00), p<0.001), lower CSF chloride level (mean: 119.80±6.24 vs 122.84±5.26, p=0.005), lower ratios of CSF-glucose/serum-glucose (median: 0.50[0.13-0.94] vs 0.60[0.26-1.23], p=0.003), more meningitis (26/61 (42.6%) vs 12/60 (20.0%), p=0.007) and higher follow-up modified Rankin Scale scores (1 (0-6) vs 0 (0-3), p=0.037) compared with antibody-negative patients. A Kaplan-Meier analysis revealed that autoantibody-positive patients experienced significantly worse outcomes (p=0.031). CONCLUSIONS: Autoimmune responses are found at the onset of viral encephalitis. EBV in the CNS increases the risk for autoimmunity to GFAP.

Eugenol Attenuates Transmissible Gastroenteritis Virus-Induced Oxidative Stress and Apoptosis Via ROS-NRF2-ARE Signaling.

Transmissible gastroenteritis virus (TGEV), a coronavirus that causes severe diarrhea due to oxidative stress in the piglet intestine, is a major cause of economic loss in the livestock industry. However, limited interventions have been shown to be effective in the treatment of TGEV. Here, we demonstrate the therapeutic activity of eugenol in TGEV-induced intestinal oxidative stress and apoptosis. Our data show that eugenol supplementation protects intestine and IPEC-J2 cells from TGEV-induced damage. Mechanistically, eugenol reduces TGEV-induced oxidative stress in intestinal epithelial cells by reducing reactive oxygen species levels. Interestingly, eugenol also inhibits TGEV-induced intestinal cell apoptosis in vitro and in vivo. In conclusion, our data suggest that eugenol prevents TGEV-induced intestinal oxidative stress by reducing ROS-mediated damage to antioxidant signaling pathways. Therefore, eugenol may be a promising therapeutic strategy for TGEV infection.

Correlation between anxiety-depression symptoms and immune characteristics in inpatients with 2019 novel coronavirus in Wuhan, China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is widely acknowledged as a severe traumatic event, and depression, anxiety, and psychological distress are common in diagnosed patients. However, the correlations of biological indicators with emotion are rarely reported. The primary objective of this study was to explore the dysfunction of immune-inflammatory characteristics in patients with depression-anxiety symptoms. METHODS: We investigated the mental status of inpatients with COVID-19 in Wuhan and compared the differences in cytokines and lymphocytes between patients with and without depression-anxiety symptoms at admission. After two weeks of treatment, we evaluated the mental conditions and measured the cytokines and lymphocytes of the patients with depression and anxiety symptoms and explored the changes and their associations. RESULTS: Approximately half of the patients with COVID-19 had depression and anxiety symptoms, and the symptoms were related to the ratio of CD4+/CD8+ and the level of CD4+T lymphocytes. When compared with patients without depression-anxiety symptoms, CD4+T lymphocytes level was significantly higher in COVID-19 patients with depression-anxiety symptoms. CONCLUSION: This study provided novel evidence regarding the association between depression and anxiety symptoms and immune characteristics, especially CD4+T lymphocyte levels, in COVID-19 patients. We emphasized the importance of paying attention to the dynamic immune process of patients diagnosed with COVID-19 with depression/anxiety.

Space-Time Cluster's Detection and Geographical Weighted Regression Analysis of COVID-19 Mortality on Texas Counties.

As COVID-19 run rampant in high-density housing sites, it is important to use real-time data in tracking the virus mobility. Emerging cluster detection analysis is a precise way of blunting the spread of COVID-19 as quickly as possible and save lives. To track compliable mobility of COVID-19 on a spatial-temporal scale, this research appropriately analyzed the disparities between spatial-temporal clusters, expectation maximization clustering (EM), and hierarchical clustering (HC) analysis on Texas county-level. Then, based on the outcome of clustering analysis, the sensitive counties are Cottle, Stonewall, Bexar, Tarrant, Dallas, Harris, Jim hogg, and Real, corresponding to Southeast Texas analysis in Geographically Weighted Regression (GWR) modeling. The sensitive period took place in the last two quarters in 2020 and the first quarter in 2021. We explored PostSQL application to portray tracking Covid-19 trajectory. We captured 14 social, economic, and environmental impact's indices to perform principal component analysis (PCA) to reduce dimensionality and minimize multicollinearity. By using the PCA, we extracted five factors related to mortality of COVID-19, involved population and hospitalization, adult population, natural supply, economic condition, air quality or medical care. We established the GWR model to seek the sensitive factors. The result shows that adult population, economic condition, air quality, and medical care are the sensitive factors. Those factors also triggered high increase of COVID-19 mortality. This research provides geographical understanding and solution of controlling COVID-19, reference of implementing geographically targeted ways to track virus mobility, and satisfy for the need of emergency operations plan (EOP).

Exploration of spatial-temporal varying impacts on COVID-19 cumulative case in Texas using geographically weighted regression (GWR).

Since COVID-19 is extremely threatening to human health, it is significant to determine its impact factors to curb the virus spread. To tackle the complexity of COVID-19 expansion on a spatial-temporal scale, this research appropriately analyzed the spatial-temporal heterogeneity at the county-level in Texas. First, the impact factors of COVID-19 are captured on social, economic, and environmental multiple facets, and the communality is extracted through principal component analysis (PCA). Second, this research uses COVID-19 cumulative case as the dependent variable and the common factors as the independent variables. According to the virus prevalence hierarchy, the spatial-temporal disparity is categorized into four quarters in the GWR analysis model. The findings exhibited that GWR models provide higher fitness and more geodata-oriented information than OLS models. In El Paso, Odessa, Midland, Randall, and Potter County areas in Texas, population, hospitalization, and age structures are presented as static, positive influences on COVID-19 cumulative cases, indicating that they should adopt stringent strategies in curbing COVID-19. Winter is the most sensitive season for the virus spread, implying that the last quarter should be paid more attention to preventing the virus and taking precautions. This research is expected to provide references for the prevention and control of COVID-19 and related infectious diseases and evidence for disease surveillance and response systems to facilitate the appropriate uptake and reuse of geographical data.

Im/Mobility at the US–Mexico Border during the COVID-19 Pandemic

In March 2020, the United States government began a series of measures designed to dramatically restrict immigration as part of its response to the global health crisis caused by the coronavirus pandemic. This included Title 42, which deported asylum seekers immediately and prevented them from applying for asylum. These measures worsened an already precarious situation at the US–Mexico border for an estimated 60,000 asylum seekers who were prevented, by the Trump administration’s ‘Remain in Mexico’ (aka MPP) policy enacted in January 2019, from remaining in the United States while they awaited their asylum hearings. In-depth interviews, participant observation, and social media analysis with humanitarian and legal advocates for asylum seekers living in a camp at the border in Matamoros, Mexico reveal that COVID-19’s impacts are not limited to public health concerns. Rather, COVID-19’s impacts center on how the Trump administration weaponized the virus to indefinitely suspend the asylum system. We argue that the Matamoros refugee camp provides a strategic vantage point to understand the repercussions of state policies of exclusion on im/mobility and survival strategies for asylum seekers. Specifically, we use the analytical lenses of the politics of im/mobility, geographies of exclusion, and asylum seeker resilience to identify how COVID-19 has shaped the im/mobility and security of the camp and its residents in unexpected ways. At the same time, our research illustrates that camp residents exercise im/mobility as a form of political visibility to contest and ameliorate their precarity as they find themselves in conditions not of their choosing.

Early Use of Corticosteroid May Prolong SARS-CoV-2 Shedding in Non-Intensive Care Unit Patients with COVID-19 Pneumonia: A Multicenter, Single-Blind, Randomized Control Trial.

BACKGROUND: There is still no clinical evidence available to support or to oppose corticosteroid treatment for coronavirus disease 2019 (COVID-19) pneumonia. OBJECTIVE: To investigate the efficacy and safety of corticosteroid given to the hospitalized patients with COVID-19 pneumonia. METHODS: This was a prospective, multicenter, single-blind, randomized control trial. Adult patients with COVID-19 pneumonia who were admitted to the general ward were randomly assigned to either receive methylprednisolone or not for 7 days. The primary end point was the incidence of clinical deterioration 14 days after randomization. RESULTS: We terminated this trial early because the number of patients with COVID-19 pneumonia in all the centers decreased in late March. Finally, a total of 86 COVID-19 patients underwent randomization. There was no difference of the incidence of clinical deterioration between the methylprednisolone group and control group (4.8 vs. 4.8%, p = 1.000). The duration of throat viral RNA detectability in the methylprednisolone group was 11 days (interquartile range, 6-16 days), which was significantly longer than that in the control group (8 days [2-12 days], p = 0.030). There were no significant differences between the 2 groups in other secondary outcomes. Mass cytometry discovered CD3+ T cells, CD8+ T cells, and NK cells in the methylprednisolone group which were significantly lower than those in the control group after randomization (p < 0.05). CONCLUSIONS: From this prematurely closed trial, we found that the short-term early use of corticosteroid could suppress the immune cells, which may prolong severe acute respiratory syndrome coronavirus 2 shedding in patients with COVID-19 pneumonia. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04273321.