SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity (preprint)

Pregnancy is a risk factor for increased severity of SARS-CoV-2 and other respiratory infections. The mechanisms underlying this risk have not been well-established, partly due to a limited understanding of how pregnancy shapes immune responses. To gain insight into the role of pregnancy in modulating immune responses at steady state and upon perturbation, we collected peripheral blood mononuclear cells (PBMC), plasma, and stool from 226 women, including 152 pregnant individuals (n = 96 with SARS-CoV-2 infection and n = 56 healthy controls) and 74 non-pregnant women (n = 55 with SARS-CoV-2 and n = 19 healthy controls). We found that SARS-CoV-2 infection was associated with altered T cell responses in pregnant compared to non-pregnant women. Differences included a lower percentage of memory T cells, a distinct clonal expansion of CD4-expressing CD8+ T cells, and the enhanced expression of T cell exhaustion markers, such as programmed cell death-1 (PD-1) and T cell immunoglobulin and mucin domain-3 (Tim-3), in pregnant women. We identified additional evidence of immune dysfunction in severely and critically ill pregnant women, including a lack of expected elevation in regulatory T cell (Treg) levels, diminished interferon responses, and profound suppression of monocyte function. Consistent with earlier data, we found maternal obesity was also associated with altered immune responses to SARS-CoV-2 infection, including enhanced production of inflammatory cytokines by T cells. Certain gut bacterial species were altered in pregnancy and upon SARS-CoV-2 infection in pregnant individuals compared to non-pregnant women. Shifts in cytokine and chemokine levels were also identified in the sera of pregnant individuals, most notably a robust increase of interleukin-27 (IL-27), a cytokine known to drive T cell exhaustion, in the pregnant uninfected control group compared to all non-pregnant groups. IL-27 levels were also significantly higher in uninfected pregnant controls compared to pregnant SARS-CoV-2-infected individuals. Using two different preclinical mouse models of inflammation-induced fetal demise and respiratory influenza viral infection, we found that enhanced IL-27 protects developing fetuses from maternal inflammation but renders adult female mice vulnerable to viral infection. These combined findings from human and murine studies reveal nuanced pregnancy-associated immune responses, suggesting mechanisms underlying the increased susceptibility of pregnant individuals to viral respiratory infections.

Chinese Normal Students' Satisfaction of Emergency Remote Learning in Higher Education during COVID-19 Pandemic

Despite the widespread use of emergency remote learning (ERL) during the COVID-19 pandemic in higher education, little is known about the determinants of Chinese normal student satisfaction with ERL. This study uses a questionnaire survey method to examine how Chinese normal students' satisfaction with ERL during the COVID-19 pandemic. The results show that Chinese normal students prefer face-to-face teaching to online teaching to some extent. According to the findings, it is important to emphasize students' pre-class preparation, adjust course assessment methods, change teachers' teaching strategies, create a positive teaching environment, boost students' learning confidence, and help them deal with their anxiety during ERL to improve the online course experience for Chinese students at normal universities. © 2023 ACM.

Scaling law of COVID-19 cases and city size and its evolution over time

Urban scaling law quantifies the disproportional growth of urban indicators with urban population size, which is one of the simple rules behind the complex urban system. Infectious diseases are closely related to social interactions that intensify in large cities, resulting in a faster speed of transmission in large cities. However, how this scaling relationship varies in an evolving pandemic is rarely investigated and remains unclear. Here, taking the COVID- 19 epidemic in the United States as an example, we collected daily added cases and deaths from January 2020 to June 2022 in more than three thousand counties to explore the scaling law of COVID- 19 cases and city size and its evolution over time. Results show that COVID- 19 cases super- linearly scaled with population size, which means cases increased faster than population size from a small city to a large city, resulting in a higher morbidity rate of COVID- 19 in large cities. Temporally, the scaling exponent that reflects the scaling relationship stabilized at around 1.25 after a fast increase from less than one. The scaling exponent gradually decreased until it was close to one. In comparison, deaths caused by the epidemic did not show a super-linear scaling relationship with population size, which revealed that the fatality rate of COVID-19 in large cities was not higher than that in small or medium-sized cities. The scaling exponent of COVID- 19 deaths shared a similar trend with that of COVID- 19 cases but with a lag in time. We further estimated scaling exponents in each wave of the epidemic, respectively, which experienced the common evolution process of first rising, then stabilizing, and then decreasing. We also analyzed the evolution of scaling exponents over time from regional and provincial perspectives. The northeast, where New York State is located, had the highest scaling exponent, and the scaling exponent of COVID- 19 deaths was higher than that of COVID-19 cases, which indicates that large cities in this region were more prominently affected by the epidemic. This study reveals the size effect of infectious diseases based on the urban scaling law, and the evolution process of scaling exponents over time also promotes the understanding of the urban scaling law. The mechanism behind temporal variations of scaling exponents is worthy of further exploration. © 2023 Science Press. All rights reserved.

Extrafollicular IgD-CD27-CXCR5-CD11c- DN3 B cells infiltrate inflamed tissues in autoimmune fibrosis and in severe COVID-19.

Although therapeutic B cell depletion dramatically resolves inflammation in many diseases in which antibodies appear not to play a central role, distinct extrafollicular pathogenic B cell subsets that accumulate in disease lesions have hitherto not been identified. The circulating immunoglobulin D (IgD)-CD27-CXCR5-CD11c+ DN2 B cell subset has been previously studied in some autoimmune diseases. A distinct IgD-CD27-CXCR5-CD11c- DN3 B cell subset accumulates in the blood both in IgG4-related disease, an autoimmune disease in which inflammation and fibrosis can be reversed by B cell depletion, and in severe COVID-19. These DN3 B cells prominently accumulate in the end organs of IgG4-related disease and in lung lesions in COVID-19, and double-negative B cells prominently cluster with CD4+ T cells in these lesions. Extrafollicular DN3 B cells may participate in tissue inflammation and fibrosis in autoimmune fibrotic diseases, as well as in COVID-19.

A Gesture Controlled System to Train and Guide the Healthcare Workers While Donning and Doffing Personal Protective Equipment

During the COVID-19 outbreak, many healthcare workers (HCWs) have been infected because they failed to comply with the correct process of donning and doffing personal protective equipment (PPE). Based on this, we develop a gesture-controlled system that not only can train HCWs but also can give HCWs real-time guidance during the process of donning and doffing PPE. It can effectively prevent the infection of HCWs. We first use the hand detection algorithm to locate the position of the HCWs, helping them to enter the proper area. Then they can use our gesture recognition algorithm to control the playback of the videos which guides them in donning and doffing PPE. We verify the effectiveness of the system through a series of experiments. The results show the great value of our system in the protection of HCWs. © 2022 IEEE.

Diagnostic TR-FRET assays for detection of antibodies in patient samples.

Serological assays are important diagnostic tools for surveying exposure to the pathogen, monitoring immune response post vaccination, and managing spread of the infectious agent among the population. Current serological laboratory assays are often limited because they require the use of specialized laboratory technology and/or work with a limited number of sample types. Here, we evaluate an alternative by developing time-resolved Förster resonance energy transfer (TR-FRET) homogeneous assays that exhibited exceptional versatility, scalability, and sensitivity and outperformed or matched currently used strategies in terms of sensitivity, specificity, and precision. We validated the performance of the assays measuring total immunoglobulin G (IgG) levels; antibodies against severe acute respiratory syndrome coronavirus (SARS-CoV) or Middle Eastern respiratory syndrome (MERS)-CoV spike (S) protein; and SARS-CoV-2 S and nucleocapsid (N) proteins and applied it to several large sample sets and real-world applications. We further established a TR-FRET-based ACE2-S competition assay to assess the neutralization propensity of the antibodies. Overall, these TR-FRET-based serological assays can be rapidly extended to other antigens and are compatible with commonly used plate readers.

Persistent circulating SARS-CoV-2 spike is associated with post-acute COVID-19 sequelae.

The diagnosis of post-acute sequelae of COVID-19 (PASC) poses an ongoing medical challenge. To identify biomarkers associated with PASC we analyzed plasma samples collected from PASC and COVID-19 patients to quantify viral antigens and inflammatory markers. We detect SARS-CoV-2 spike predominantly in PASC patients up to 12 months post-diagnosis.

Temporal evolution and spatial pattern of the COVID-19 epidemic in the United States

It is the cornerstone of precise and scientific prevention and control to understand the temporal evolution and spatial pattern of the COVID-19 epidemic. Based on the county-level COVID-19 case of the United States from January 22, 2020 to October 8, 2021, we explored and analyzed the epidemic by using time series analysis, spatial autocorrelation analysis and gravity center trajectory analysis. The results show that: (1) the epidemic in the United States experienced four stages of low incidence, growth, peak and rebound with June 15, September 30 and October 1, 2020 as the cut-off points. (2) The global Moran index experienced a process of 'increase-decrease-increase-stability', with the maximum value exceeding 0.6, indicating that the epidemic has obvious spatial aggregation;the epidemic is dominated by high-high clusters (over 150 counties) and low-low clusters (over 500 counties), presenting a pattern of 'three cores and multiple islands' and 'north-south belt'. (3) In 60% of states, the trajectory of the epidemic center of gravity is near-linear type. The epidemic hotspots in these states were relatively stable over time. In more than half of the states, the curve of the moving distance of the epidemic center of gravity is exponential. These states experienced a very rapid epidemic. This study is expected to provide a reference for evaluating the effectiveness of epidemic prevention measures and determining targeted epidemic prevention measures, as well as accumulate experience for future research on the spread of different infectious diseases in different regions. © 2022 IEEE.

Spatio-Temporal Variations of the COVID-19 Epidemic in Mexico

Mexico is one of the countries worst affected by the Coronavirus Disease 2019 (COVID-19). Analyzing the spatiotemporal spread processes of the COVID-19 epidemic in Mexico is of great significance in terms of preventing its further transmission. This study obtained COVID-19 cases and deaths at the municipality level in Mexico from February 28, 2020, to February 27, 2022, and adopted Hoover index, spatial autocorrelation analysis, and epidemic center calculation to reveal the spatio-temporal pattern of the pandemic nationwide. The results showed that the COVID-19 outbreak in Mexico experienced an initial low-level transmission and four concentrated outbreaks. In terms of spatial transmission pattern, COVID-19 cases showed clear spatial clustering characteristics (Moran's I: 0.48), and large cities with more social interactions (such as Mexico City, Guadalajara, etc.) were most affected. In terms of the directional characteristics of the COVID-19 impact, the epidemiological center constantly shifted in the northeast-southwest direction due to the changing severity of the epidemic in the northwestern coast and the central part of Mexico during the initial outbreak phase. Accordingly, the centers of the three subsequent outbreaks moved to the southeast, northwest, and southeast. The COVID-19 epidemic spread very rapidly in Mexico, especially in the second phase. In the four concentrated outbreaks, the time for the distribution of cases to form a relatively stable spatial pattern was 99 days, 15 days, 95 days, and 42 days, respectively. But the difference of transmission rate at the state level is significant. The state with earlier outbreaks, such as Mexico City, spreads faster. This study revealed the characteristics and laws of the spread of infectious diseases at the national scale, and provided a reference for the prevention and control of the COVID-19 epidemic and future emerging infectious diseases. © 2022 IEEE.

Spatio-temporal variations of night-time lights at early stages of the COVID-19 epidemic in the United States

The COVID-19 epidemic swept the world and continued to spread. Without effective medical treatments and vaccine during the early stage of the pandemic, local governments in various countries had to lock down cities and adopt non-pharmaceutical interventions (NPIs), such as the stay-at-home order, social distancing, and so on. NPIs against the COVID-19 epidemic have significantly changed socioeconomic activities in cities. However, characteristics and patterns of urban socio-economic activities under this influence are still unclear. Benefiting from the development of earth observation technologies, such large-scale changes in socioeconomic activities are enough to be captured by satellites through remotely sensed night-time lights (NTL). In this study, we selected 20 major cities in the United States including New York, Chicago and Los Angeles to analyze spatio-temporal variations of NTL caused by the lockdown of cities. The first round of COVID-19 epidemic occurred in the United States in mid-March 2020. Since March 2020, American cities have successively issued stay-at-home orders, but there are differences in the time and strictness of policy implementation. Large cities have a higher population density and a higher intensity of social activities, so they are more susceptible to infectious diseases. The diversity of lockdown dates and strictness of lockdowns in cities in the United States are conducive to investigating the spatio-temporal variations of NTL. We acquired monthly averaged NPP VIIRS products of February, March and April, 2020, which are from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (NPP). We further analyzed the spatial pattern, distance decay and disparities in land use types of changes in NTL. Results show that NTL generally dimmed by 5-8% in U.S. cities caused by the lockdown of cities. There are 6 cities where the luminous brightness has dropped by more than 10%: Chicago, Dallas, Denver, Detroit, Minneapolis, and St. Louis. Among them, Minneapolis has the largest decrease in luminous brightness, with a decrease of about 40% in March. The spatial change of NTL shows obvious "core-periphery" pattern that the reduction of NTL declines with the distance from the city center. This is mainly because the central area of the city is a concentrated commercial area. After the closure of the city, commercial activities have dropped significantly, resulting in an obvious reduction in NTL around city centers. The reduction of NTL varies among diverse urban land use types. In New York, NTL decreased the most on land for residence and aviation facilities by 12% and 11%, respectively. In Chicago, NTL generally decreased by 20% in all types of urban land, and NTL recovered after one month of the lockdown of cities in other urban land except sports facilities land. This study only analyzes the spatio-temporal changes of NTL. In the future, it can be combined with multi-source data to explain the driving force of NTL changes. Nighttime light remote sensing effectively reflects urban socio-economic dynamics with an important application in monitoring and assessing socio-economic impacts of emergencies. © 2022 National Remote Sensing Bulletin. All rights reserved.

Hemodialysis Program in a Subacute Care Facility for ESRD Patients With Tracheostomy

Background: ESRD patients with tracheostomy require long-term mechanical ventilation in addition to need for maintenance dialysis. Due to regulations in California, majority of such patients have prolonged acute hospital stays due to lack of availability of a lower level of care facility, capable of providing ventilation care and hemodialysis. Need for these services increased during the COVID 19 pandemic. Kaiser Permanente Northern California (KPNC) is an integrated health care system providing health care for 4.6 million members. Partnering with a large dialysis organization (LDO) and a local Subacute Care facility (SAC), a program has been developed to provide home hemodialysis for patients requiring long-term mechanical ventilation using Low Dialysate Volume Approach (LDVA) machines. Method(s): The program was initiated in Q4 2017. A set of clinical criteria for admission was developed between the LDO, SAC and KPNC. Weekly meetings with physicians, dialysis nurses, and SAC staffs were conducted to review the potential candidates currently hospitalized in one of twenty-one KPNC hospitals. Dialysis has been performed by a HD nurse four times a week (M-T-Th-F) for 3-3.5 hours for each dialysis treatment. Each treatment was conducted using a LDVA machine with standard LDVA prescriptions using a Watson calculator to achieve a weekly Kt/V above 2.1. Result(s): Since the inception of the program, 45 patients have been admitted to the program, 24 female and 21 male patients. The mean age is 65 (+/-13) on the date of admission. The average length of stay per patient at an acute hospital prior to admission was 125 days, and after the admission, the total days in the SAC is 7,498 days, an average of 167 days per person. Total acute hospital re-admission days after admission to the program is 1,071 days, an average of 25 days per patient (range: 0 to 115 days). Nine patients are currently residing in the SAC. Conclusion(s): It is feasible to provide hemodialysis care for patients requiring long term mechanical ventilation at the appropriate level of care. This approach reduces the patient length of stay (LOS) in acute hospitals and burden to critically stretched healthcare system. Further discussion with local regulatory agencies is needed to develop additional models of care to effectively deliver dialysis to patients requiring facility-based long-term care.

Immune-profiling of SARS-CoV-2 viremic patients reveals dysregulated innate immune responses.

SARS-CoV-2 plasma viremia has been associated with severe disease and death in COVID-19. However, the effects of viremia on immune responses in blood cells remain unclear. The current study comprehensively examined transcriptional signatures of PBMCs involving T cells, B cells, NK cells, monocytes, myeloid dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs) respectively, from three different groups including individuals with moderate (nM), or severe disease with (vS) or without (nS) detectable plasma viral load. Whole transcriptome analysis demonstrated that all seven immune cell subsets were associated with disease severity regardless of cell type. Supervised clustering analysis demonstrated that mDCs and pDCs gene signatures could distinguish disease severity. Notably, transcriptional signatures of the vS group were enriched in pathways related to DNA repair, E2F targets, and G2M checkpoints; in contrast, transcriptional signatures of the nM group were enriched in interferon responses. Moreover, we observed an impaired induction of interferon responses accompanied by imbalanced cell-intrinsic immune sensing and an excessive inflammatory response in patients with severe disease (nS and vS). In sum, our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in seven major immune cells in COVID-19 patients.

[Epidemiological characteristics of a local cluster epidemic caused by 2019-nCoV Delta variant in Ningbo, 2021].

Objective: To understand the epidemiological characteristics of a local clustered epidemic caused by 2019-nCoV Delta variant in Ningbo and provide reference for the improvement of COVID-19 epidemic prevention and control. Methods: Case finding was conducted based on case definitions, and field epidemiological investigation of COVID-19 cases was carried out. In which Nasal and oropharyngeal swabs of the cases were collected for pathogen testing, and the results were analyzed with descriptive epidemiological methods. Results: A total of 74 COVID-19 cases were reported in this epidemic, and the cases were mainly mild ones, accounting for 87.84% (65/74), and there were no severe or critical cases. The epidemic curve showed a human-to-human transmission mode, indicating that a transmission for at least six generations had occurred. The age of the COVID-19 patients ranged from 2 years to 80 years, and 27.03% (20/74) of the cases were older than 60 years. The cases were mainly workers (55.41%, 41/74) and housework/the unemployed (27.03%, 20/74). The COVID-19 epidemic was limited, and no further spread to other areas occurred. The transmission chain among the cases was clear, and the gene sequencing results confirmed that the current epidemic was caused by 2019-nCoV Delta variant, which was highly homologous to the strains from other province. Conclusion: The local COVID-19 epidemic in Ningbo was caused by imported cases of COVID-19 from other province, and local community spread occurred through daily contacts between cases and contacts.

Aberrant DNA 5mC and 6mA methylations increase ACE2 expression in intestinal cancer cells susceptible to SARS-CoV-2 infection

Angiotensin converting enzyme II (ACE2) is the cellular receptor of SARS-CoV-2. At present, ACE2 receptor is considered to be the key component in the SARS-CoV-2 infection and transmitting in the host. Among the cancer patients with COVID-19, the gastrointestinal cancer is the second most prevalent. The MethyLight and QASM assays were used to evaluated the genomic DNA 5mC methylation, while the CviAII enzyme-based 6mA-RE-qPCR was applied to determine motif-specific DNA 6mA methylation. The 6mA and 5mC methylation analyses of the long interspersed nuclear elements 1 (LINE1) were used to evaluate the global level of genomic 6mA and 5mC methylations, respectively. To investigate the role of ACE2 DNA methylation in regulating ACE2 expression, we performed a genome-wide methylation analysis in colorectal cancer samples collected at the Sixth Affiliated Hospital of Sun Yat-sen University. The DNA 5mC methylation of ACE2 promoter in tumor tissues were significantly lower than that in normal tissues, while the DNA 6mA methylation of ACE2 promoter in tumor tissues was significantly higher than that in normal tissues. In addition, the mRNA and protein expression of ACE2 in tumor tissues were lower than that in normal tissues. To explore the epigenetic regulation on ACE2 expression, we treated colon cancer cell lines with 5-Azacytidine and found ACE2 expression was upregulated after lowering the DNA 5mC methylation. The correlation analysis in patient cohort samples showed that ACE2 mRNA expression was positively correlated with DNA 5mC and negatively associated with DNA 6mA methylation. Next, a novel CRISPR-based tool was developed for sequence-specific 6mA editing on ACE2 promoter region, and it was applied in HCT116 cell to further confirm the regulatory role of DNA 6mA methylation in ACE2 mRNA expression. This tool was proved to be reliable with our findings that the CRISPR/dCas9-METTL3 tool could dramatically upregulate DNA 6mA methylation in ACE2 promoter, while the global level of genomic 6mA methylation remained unchanged. Both the mRNA and protein expression of ACE2 were significantly increased following a sequence-specific DNA 6mA editing in ACE2 promoter. In conclusion, we revealed the aberrant DNA 5mC and 6mA methylations in colorectal cancer, which upregulate ACE2 expression in colorectal cancer cells that may confer the susceptibility to SARS-CoV-2 infection. We developed a novel CRISPR-based tool that could realize site-directed 6mA methylation editing. Notably, the epigenetic regulation of DNA 6mA methylation on ACE2 expression provides an insight into the intersection of the biology of cancer, SARS-CoV-2 infection and organ-specific complication in COVID-19. Aberrant ACE2 methylation may serve as a biomarker and treatment target in these patients.

A lab-on-a-chip for the concurrent electrochemical detection of SARS-CoV-2 RNA and anti-SARS-CoV-2 antibodies in saliva and plasma.

Rapid, accurate and frequent detection of the RNA of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and of serological host antibodies to the virus would facilitate the determination of the immune status of individuals who have Coronavirus disease 2019 (COVID-19), were previously infected by the virus, or were vaccinated against the disease. Here we describe the development and application of a 3D-printed lab-on-a-chip that concurrently detects, via multiplexed electrochemical outputs and within 2 h, SARS-CoV-2 RNA in saliva as well as anti-SARS-CoV-2 immunoglobulins in saliva spiked with blood plasma. The device automatedly extracts, concentrates and amplifies SARS-CoV-2 RNA from unprocessed saliva, and integrates the Cas12a-based enzymatic detection of SARS-CoV-2 RNA via isothermal nucleic acid amplification with a sandwich-based enzyme-linked immunosorbent assay on electrodes functionalized with the Spike S1, nucleocapsid and receptor-binding-domain antigens of SARS-CoV-2. Inexpensive microfluidic electrochemical sensors for performing multiplexed diagnostics at the point of care may facilitate the widespread monitoring of COVID-19 infection and immunity.

The dark side of remote working during pandemics: Examining its effects on work-family conflict and workplace wellbeing

While remote working has been applied as an emerging flexible modern work arrangement and as an effective way to maintain social distancing during pandemics, it may result in negative workplace outcomes. Despite the eulogy on remote working, more research is needed to examine its possible negative effects on employees in the workplace. This study aims to fill these gaps by examining the effects of remote working on work-family conflict and workplace wellbeing during pandemics, and how such effects are moderated by employees’ general self-efficacy and job autonomy. Survey data was collected from 399 Chinese employees during COVID-19. The results show that remote working has a positive effect on work-family conflict, which in turn decreases workplace wellbeing. Further analyses show that while the work-family conflict dimension of family interfering with work (FIW) has a negative effect on wellbeing, the effect of the work-family conflict dimension of work interfering with family (WIF) on wellbeing is not significant. Besides, the effect of remote working on FIW is positively moderated by general self-efficacy and job autonomy. Lastly, the effect of remote working differs depending on the extent to which remote working is implemented. Our study contributes to the literature by explaining the negative effect of remote working on workplace wellbeing during pandemics and clarifying its boundary conditions. Our results provide managers useful guidelines regarding how to implement remote working. © 2022 Elsevier Ltd

[Transmission chains of local epidemic of COVID-19 caused by 2019-nCoV Delta variant in Zhenhai district, Ningbo].

Objective: To investigate the local epidemic of COVID-19 caused by 2019-nCoV Delta variant in Zhenhai district of Ningbo, identify the transmission chain and provide reference for the prevention and control of COVID-19 epidemic. Methods: The incidence data of COVID-19 in Zhenhai from 6 to 18 December, 2021 were collected in field investigation. Field epidemiological investigation was conducted to understand the epidemiological characteristics of COVID-19 cases and analyze the transmission chains. Results: The first case might be infected with 2019-nCoV through direct or indirect exposure when passing through a medium-risk area, then a family cluster was caused, and the epidemic spread through close contacts of family members with others such as work, daily life, and moxibustion. The epidemic lasted for 14 days, and 74 confirmed COVID-19 cases were reported. The median incubation period was 4.0(3.0,5.8)d. All the cases were in a chain of transmission for more than 6 generations, and the intergenerational interval was 3.5(2.0,5.3)d. The gene sequencing result indicated that the pathogen was Delta AY.4 variant of 2019-nCoV. Both the epidemiological investigation and the gene sequencing results supported that the local COVID-19 epidemic in Zhenhai was associated with the COVID-19 epidemic in Shanghai. Conclusions: The transmission chain of this epidemic was clear. Delta AY.4 variant has obvious characteristic to cause case clusters in families, places with poor ventilation, and residential communities. It is suggested to strengthen the health management in key areas and key populations, and increase the frequency of nucleic acid testing.

SARS-CoV-2 epitope-specific CD4+ memory T cell responses across COVID-19 disease severity and antibody durability.

CD4+ T cells are central to long-term immunity against viruses through the functions of T helper 1 (TH1) and T follicular helper (TFH) cell subsets. To better understand the role of these subsets in coronavirus disease 2019 (COVID-19) immunity, we conducted a longitudinal study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific CD4+ T cell and antibody responses in convalescent individuals who seroconverted during the first wave of the pandemic in Boston, MA, USA, across a range of COVID-19 disease severities. Analyses of spike (S) and nucleocapsid (N) epitope-specific CD4+ T cells using peptide and major histocompatibility complex class II (pMHCII) tetramers demonstrated expanded populations of T cells recognizing the different SARS-CoV-2 epitopes in most individuals compared with prepandemic controls. Individuals who experienced a milder disease course not requiring hospitalization had a greater percentage of circulating TFH (cTFH) and TH1 cells among SARS-CoV-2-specific cells. Analysis of SARS-CoV-2-specific CD4+ T cells responses in a subset of individuals with sustained anti-S antibody responses after viral clearance also revealed an increased proportion of memory cTFH cells. Our findings indicate that efficient early disease control also predicts favorable long-term adaptive immunity.

Improvement of the Detection Method for the Serum Titer of the Inactivated SARS-CoV-2 Vaccine

A mixed antigen coating method was designed to optimize the method for detecting the titer of the immune serum to inactivated SARS-CoV-2 vaccine, which based on the traditional single antigen coating.The authors determined the optimal coating concentration of the single antigen first by the checkerboard method, then combined two kinds of antigen and obtained coating concentration of the mixed antigen.The best combination of mixed coating antigen contains the whole-coronavirus antigen with total protein concentration of 25 ng/well and the recombinant new coro-navirus S1 protein antigen with protein concentration of 50 ng/well.This method can be used to detect all antibody-specific titers in serum effectively, especially serum containing high-level S protein-specific antibodies.