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1.
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases ; 2022.
Article in English | EuropePMC | ID: covidwho-1615443

ABSTRACT

Objective: The mortality rate for critically ill coronavirus disease 2019 (COVID-19) cases was more than 80%. Nonetheless, research about the effect of common respiratory diseases on critically ill COVID-19 expression and outcomes is scarce. Design: We performed proteomic analyses on airway mucus obtained by bronchoscopy from severe COVID-19 patients, or induced sputum from patients with chronic obstructive pulmonary disease (COPD), asthma, and healthy controls. Results: Out of the total identified and quantified proteins, 445 differentially expressed proteins (DEPs) were found in different comparison groups. In comparison to COPD, asthma, and controls, 11 proteins were uniquely present in COVID-19 patients. Apart from DEPs associated with COPD vs controls and asthma vs controls, there were a total of 59 DEPs specific to COVID-19 patients. Finally, the findings revealed that there were 8 overlapping proteins in COVID-19 patients, including C9, FGB, FGG, PRTN3, HBB, HBA1, IGLV3-19, and COTL1. Functional analyses revealed that the majority of them were associated with complement and coagulation cascades, platelet activation, or iron metabolism, and anemia-related pathways. Conclusions: This study provides fundamental data for identifying COVID-19-specific proteomic changes in comparison to COPD and asthma, which may suggest molecular targets for specialized therapy. Graphical Image, graphical

2.
Brain Sciences ; 12(1):79, 2022.
Article in English | MDPI | ID: covidwho-1613617

ABSTRACT

During the pandemic era, quarantines might potentially have negative effects and disproportionately exacerbate health condition problems. We conducted this cross-sectional, national study to ascertain the prevalence of constant pain symptoms and how quarantines impacted the pain symptoms and identify the factors associated with constant pain to further guide reducing the prevalence of chronic pain for vulnerable people under the pandemic. The sociodemographic data, quarantine conditions, mental health situations and pain symptoms of the general population were collected. After adjusting for potential confounders, long-term quarantine (≥15 days) exposures were associated with an increased risk of constant pain complaints compared to those not under a quarantine (Odds Ratio (OR): 1.26;95% Confidence Interval (CI): 1.03, 1.54;p = 0.026). Risk factors including unemployment (OR: 1.55), chronic disease history (OR: 2.38) and infection with COVID-19 (OR: 2.15), and any of mental health symptoms including depression, anxiety, insomnia and PTSD (OR: 5.44) were identified by a multivariable logistic regression. Additionally, mediation analysis revealed that the effects of the quarantine duration on pain symptoms were mediated by mental health symptoms (indirect effects: 0.075, p < 0.001). These results advocated that long-term quarantine measures were associated with an increased risk of experiencing pain, especially for vulnerable groups with COVID-19 infection and with mental health symptoms. The findings also suggest that reducing mental distress during the pandemic might contribute to reducing the burden of pain symptoms and prioritizing interventions for those experiencing a long-term quarantine.

5.
Cell Reports ; : 110271, 2021.
Article in English | ScienceDirect | ID: covidwho-1588135

ABSTRACT

Summary The utility of the urinary proteome in infectious diseases remains unclear. Here we analyzed the proteome and metabolome of urine and serum samples from patients with COVID-19 and healthy controls. Our data show that urinary proteins effectively classify COVID-19 by severity. We detect 197 cytokines and their receptors in urine but only 124 in serum using TMT-based proteomics. Decrease of urinary ESCRT complex proteins correlates with active SARS-CoV-2 replication. Downregulation of urinary CXCL14 in severe COVID-19 cases positively correlates with blood lymphocyte counts. Integrative multiomic analysis suggests that innate immune activation and inflammation triggered renal injuries in patients with COVID-19. COVID-19-associated modulation of the urinary proteome offers unique insights into the pathogenesis of this disease. This study demonstrates the added value of including the urinary proteome in a suite of multiomic analytes in evaluating the immune pathobiology and clinical course of COVID-19 and, potentially, other infectious diseases.

6.
Phytomedicine ; : 153922, 2022.
Article in English | ScienceDirect | ID: covidwho-1586870

ABSTRACT

Background Although Qing-Fei-Pai-Du decoction (QFPDD) is extensively used clinically to treat COVID-19 patients, the mechanism by which it modulates the immunological and metabolic functions of liver tissue remains unknown. Purpose The purpose of this study is to investigate the mechanism of action of QFPDD in the treatment of mice with coronavirus-induced pneumonia by combining integrated hepatic single-cell RNA sequencing and untargeted metabolomics. Methods We developed a human coronavirus pneumonia model in BALB/c mice by infecting them with human coronavirus HCoV-229E with stimulating them with cold-damp environment. We initially assessed the status of inflammation and immunity in model mice treated with or without QFPDD by detecting peripheral blood lymphocytes and inflammatory cytokines. Then, single-cell RNA sequencing and untargeted metabolomics were performed on mouse liver tissue. Results HCoV-229E infection in combination with exposure to a cold-damp environment significantly decreased the percentage of peripheral blood lymphocytes (CD4+ and CD8+ T cells, B cells) in mice, which was enhanced by QFPDD therapy. Meanwhile, the levels of inflammatory cytokines such as IL-6, TNF-α, and IFN-γ were significantly increased in mouse models but significantly decreased by QFPDD treatment. Single-cell RNA sequencing analysis showed that QFPDD could attenuate disease-associated alterations in gene expression, core transcriptional regulatory networks, and cell-type composition. Computational predictions indicated that QFPDD rectified the observed aberrant patterns of cell-cell communication. Additionally, the metabolic profiles of liver tissue in the Model group were distinct from mice in the Control group, and QFPDD significantly regulated hepatic purine metabolism. Conclusion To the best of our knowledge, this study is the first to integrate hepatic single-cell RNA sequencing and untargeted metabolomics into a TCM formula and these valuable findings indicate that QFPDD can improve immune function and reduce liver injury and inflammation.

7.
BMC Infect Dis ; 21(1): 1282, 2021 Dec 27.
Article in English | MEDLINE | ID: covidwho-1582099

ABSTRACT

BACKGROUND: The temporal relationship between SARS-CoV-2 and antibody production and clinical progression remained obscure. The aim of this study was to describe the viral kinetics of symptomatic patients with SARS-CoV-2 infection and identify factors that might contribute to prolonged viral shedding. METHODS: Symptomatic COVID-19 patients were enrolled in two hospitals in Wuhan, China, from whom the respiratory samples were collected and measured for viral loads consecutively by reverse transcriptase quantitative PCR (RT-qPCR) assay. The viral shedding pattern was delineated in relate to the epidemiologic and clinical information. RESULTS: Totally 2726 respiratory samples collected from 703 patients were quantified. The SARS-CoV-2 viral loads were at the highest level during the initial stage after symptom onset, which subsequently declined with time. The median time to SARS-CoV-2 negativity of nasopharyngeal test was 28 days, significantly longer in patients with older age (> 60 years old), female gender and those having longer interval from symptom onset to hospital admission (> 10 days). The multivariate Cox regression model revealed significant effect from older age (HR 0.73, 95% CI 0.55-0.96), female gender (HR 0.72, 95% CI 0.55-0.96) and longer interval from symptom onset to admission (HR 0.44, 95% CI 0.33-0.59) on longer time to SARS-CoV-2 negativity. The IgM antibody titer was significantly higher in the low viral loads group at 41-60 days after symptom onset. At the population level, the average viral loads were higher in early than in late outbreak periods. CONCLUSIONS: The prolonged viral shedding of SARS-CoV-2 was observed in COVID-19 patients, particularly in older, female and those with longer interval from symptom onset to admission.


Subject(s)
COVID-19 , Aged , Female , Humans , Middle Aged , Prospective Studies , RNA, Viral , SARS-CoV-2 , Viral Load , Virus Shedding
8.
Infect Dis Poverty ; 10(1): 140, 2021 Dec 28.
Article in English | MEDLINE | ID: covidwho-1582000

ABSTRACT

BACKGROUND: Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China. METHODS: We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (Reff) was used to estimate the transmission interaction in different age groups. RESULTS: A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (Reff = 4.28), followed by group 2 to 3 (Reff = 2.61), and group 2 to 4 (Reff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45-64 years old. CONCLUSIONS: Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15-64 years should first be vaccinated to prevent transmission in China.


Subject(s)
COVID-19 , Adolescent , Adult , Aged , China , Cities , Humans , Middle Aged , SARS-CoV-2 , Vaccination , Young Adult
9.
BMC Public Health ; 21(1): 2239, 2021 Dec 09.
Article in English | MEDLINE | ID: covidwho-1566517

ABSTRACT

BACKGROUND: COVID-19 patients with long incubation period were reported in clinical practice and tracing of close contacts, but their epidemiological or clinical features remained vague. METHODS: We analyzed 11,425 COVID-19 cases reported between January-August, 2020 in China. The accelerated failure time model, Logistic and modified Poisson regression models were used to investigate the determinants of prolonged incubation period, as well as their association with clinical severity and transmissibility, respectively. RESULT: Among local cases, 268 (10.2%) had a prolonged incubation period of > 14 days, which was more frequently seen among elderly patients, those residing in South China, with disease onset after Level I response measures administration, or being exposed in public places. Patients with prolonged incubation period had lower risk of severe illness (ORadjusted = 0.386, 95% CI: 0.203-0.677). A reduced transmissibility was observed for the primary patients with prolonged incubation period (50.4, 95% CI: 32.3-78.6%) than those with an incubation period of ≤14 days. CONCLUSIONS: The study provides evidence supporting a prolonged incubation period that exceeded 2 weeks in over 10% for COVID-19. Longer monitoring periods than 14 days for quarantine or persons potentially exposed to SARS-CoV-2 should be justified in extreme cases, especially for those elderly.

10.
Frontiers in public health ; 9, 2021.
Article in English | EuropePMC | ID: covidwho-1564436

ABSTRACT

Coronavirus Disease 2019 (COVID-19) restrictions, including national lockdown, social distancing, compulsory quarantine, and organizational measures of remote working, are imposed in many countries and organizations to combat the coronavirus. The various restrictions have caused different impacts on the employees' mental health worldwide. The purpose of this mini-review is to investigate the impact of COVID-19 restrictions on employees' mental health across the world. We searched articles in Web of Science and Google Scholar, selecting literature focusing on employees' mental health conditions under COVID-19 restrictions. The findings reveal that the psychological impacts of teleworking are associated with employees' various perceptions of its pros and cons. The national lockdown, quarantine, and resuming to work can cause mild to severe mental health issues, whereas the capability to practice social distancing is positively related to employees' mental health. Generally, employees in developed countries have experienced the same negative and positive impacts on mental health, whereas, in developing countries, employees have reported a more negative effect of the restrictions. One explanation is that the unevenly distributed mental health resources and assistances in developed and developing countries.

11.
Clin Infect Dis ; 73(11): e4154-e4165, 2021 12 06.
Article in English | MEDLINE | ID: covidwho-1559099

ABSTRACT

BACKGROUND: Children and older adults with coronavirus disease 2019 (COVID-19) display a distinct spectrum of disease severity yet the risk factors aren't well understood. We sought to examine the expression pattern of angiotensin-converting enzyme 2 (ACE2), the cell-entry receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the role of lung progenitor cells in children and older patients. METHODS: We retrospectively analyzed clinical features in a cohort of 299 patients with COVID-19. The expression and distribution of ACE2 and lung progenitor cells were systematically examined using a combination of public single-cell RNA-seq data sets, lung biopsies, and ex vivo infection of lung tissues with SARS-CoV-2 pseudovirus in children and older adults. We also followed up patients who had recovered from COVID-19. RESULTS: Compared with children, older patients (>50 years.) were more likely to develop into serious pneumonia with reduced lymphocytes and aberrant inflammatory response (P = .001). The expression level of ACE2 and lung progenitor cell markers were generally decreased in older patients. Notably, ACE2 positive cells were mainly distributed in the alveolar region, including SFTPC positive cells, but rarely in airway regions in the older adults (P < .01). The follow-up of discharged patients revealed a prolonged recovery from pneumonia in the older (P < .025). CONCLUSIONS: Compared to children, ACE2 positive cells are generally decreased in older adults and mainly presented in the lower pulmonary tract. The lung progenitor cells are also decreased. These risk factors may impact disease severity and recovery from pneumonia caused by SARS-Cov-2 infection in older patients.

12.
J Allergy Clin Immunol ; 148(6): 1481-1492.e2, 2021 12.
Article in English | MEDLINE | ID: covidwho-1555521

ABSTRACT

BACKGROUND: Understanding the complexities of immune memory to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is key to gain insights into the durability of protective immunity against reinfection. OBJECTIVE: We sought to evaluate the immune memory to SARS-CoV-2 in convalescent patients with longer follow-up time. METHODS: SARS-CoV-2-specific humoral and cellular responses were assessed in convalescent patients with coronavirus disease 2019 (COVID-19) at 1 year postinfection. RESULTS: A total of 78 convalescent patients with COVID-19 (26 moderate, 43 severe, and 9 critical) were recruited after 1 year of recovery. The positive rates of both anti-receptor-binding domain and antinucleocapsid antibodies were 100%, whereas we did not observe a statistical difference in antibody levels among different severity groups. Accordingly, the prevalence of neutralizing antibodies (nAbs) reached 93.59% in convalescent patients. Although nAb titers displayed an increasing trend in convalescent patients with increased severity, the difference failed to achieve statistical significance. Notably, there was a significant correlation between nAb titers and anti-receptor-binding domain levels. Interestingly, SARS-CoV-2-specific T cells could be robustly maintained in convalescent patients, and their number was positively correlated with both nAb titers and anti-receptor-binding domain levels. Amplified SARS-CoV-2-specific CD4+ T cells mainly produced a single cytokine, accompanying with increased expression of exhaustion markers including PD-1, Tim-3, TIGIT, CTLA-4, and CD39, while the proportion of multifunctional cells was low. CONCLUSIONS: Robust SARS-CoV-2-specific humoral and cellular responses are maintained in convalescent patients with COVID-19 at 1 year postinfection. However, the dysfunction of SARS-CoV-2-specific CD4+ T cells supports the notion that vaccination is needed in convalescent patients for preventing reinfection.

13.
Preprint in English | Other preprints | ID: ppcovidwho-296380

ABSTRACT

Spatial transcriptomics has been emerging as a powerful technique for resolving gene expression profiles while retaining tissue spatial information. These spatially resolved transcriptomics make it feasible to examine the complex multicellular systems of different microenvironments. To answer scientific questions with spatial transcriptomics and expand our understanding of how cell types and states are regulated by microenvironment, the first step is to identify cell clusters by integrating the available spatial information. Here, we introduce SC-MEB, an empirical Bayes approach for spatial clustering analysis using a hidden Markov random field. We have also derived an efficient expectation-maximization algorithm based on an iterative conditional mode for SC-MEB. In contrast to BayesSpace, a recently developed method, SC-MEB is not only computationally efficient and scalable to large sample sizes but is also capable of choosing the smoothness parameter and the number of clusters. We performed comprehensive simulation studies to demonstrate the superiority of SC-MEB over some existing methods. We applied SC-MEB to analyze the spatial transcriptome of human dorsolateral prefrontal cortex tissues and mouse hypothalamic preoptic region. Our analysis results showed that SC-MEB can achieve a similar or better clustering performance to BayesSpace, which uses the true number of clusters and a fixed smoothness parameter. Moreover, SC-MEB is scalable to large ‘sample sizes’. We then employed SC-MEB to analyze a colon dataset from a patient with colorectal cancer (CRC) and COVID-19, and further performed differential expression analysis to identify signature genes related to the clustering results. The heatmap of identified signature genes showed that the clusters identified using SC-MEB were more separable than those obtained with BayesSpace. Using pathway analysis, we identified three immune-related clusters, and in a further comparison, found the mean expression of COVID-19 signature genes was greater in immune than non-immune regions of colon tissue. SC-MEB provides a valuable computational tool for investigating the structural organizations of tissues from spatial transcriptomic data.

14.
Preprint in English | Other preprints | ID: ppcovidwho-296343

ABSTRACT

In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, it’s much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future. Highlights An automatic tool to quickly analyze candidate key mutations and epidemic trends for any virus was developed. Our integrated analysis method and tool could become a standard process for virus mutation and epidemic trend analysis based on genome sequences in the future. N501Y with the other 16 highly linked mutation sites of SARS-CoV-2 in the UK and Europe were further confirmed, and some valuable mutation sites of HBV and HPV-16 were detected.

15.
Preprint in English | EuropePMC | ID: ppcovidwho-293976

ABSTRACT

Severe COVID-19 patients account for most of the mortality of this disease. Early detection and effective treatment of severe patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model correctly classified severe patients with an accuracy of 93.5%, and was further validated using ten independent patients, seven of which were correctly classified. We identified molecular changes in the sera of COVID-19 patients implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study shows that it is possible to predict progression to severe COVID-19 disease using serum protein and metabolite biomarkers. Our data also uncovered molecular pathophysiology of COVID-19 with potential for developing anti-viral therapies.<br><br>Funding: This work is supported by grants from Westlake Special Program for COVID19 (2020), and Tencent foundation (2020), National Natural Science Foundation of China (81972492, 21904107, 81672086), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Hangzhou Agriculture and Society Advancement Program (20190101A04). <br><br>Conflict of Interest: The research group of T.G. is partly supported by Tencent, Thermo Fisher Scientific, SCIEX and Pressure Biosciences Inc. C.Z., Z.K., Z.K. and S.Q. are employees of DIAN Diagnostics.

16.
Front Psychiatry ; 12: 749379, 2021.
Article in English | MEDLINE | ID: covidwho-1551543

ABSTRACT

Background: COVID-19 has had a wide impact on the mental health of college students. This study aims to explore the relationship between time perception, risk perception, and the mental health of college students during COVID-19 through a questionnaire survey. Subjects: One thousand two hundred and eighteen college students, 449 male and 769 female, who studied online during the COVID-19 epidemic were selected. Methods: Time Perception Scale, Risk Perception Scale, and SCL-90 were used to investigate the relationship using correlation analysis. Results: During the COVID-19 period, mental health problems of college students were widespread, and 65.93% of college students reported moderate to severe mental health problems. The correlation analysis showed that risk perception, time perception, and the mental health of college students were significantly related. Risk perception played a partial mediating role between present enjoyment and mental health, and risk perception played a partial mediating role between future time perception and mental health. Conclusion: In the case of sudden public crises, we should pay close attention to the mental health of college students, adjust their attitude toward the present and the future, and pay attention to their perception of risk so as to improve their mental health level under crisis.

17.
Front Pharmacol ; 12: 735223, 2021.
Article in English | MEDLINE | ID: covidwho-1551527

ABSTRACT

Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne virus causing serious infectious disease with a high case-fatality of up to 50% in severe cases. Currently, no effective drug has been approved for the treatment of SFTSV infection. Here, we performed a high-throughput screening of a natural extracts library for compounds with activities against SFTSV infection. Three hit compounds, notoginsenoside Ft1, punicalin, and toosendanin were identified for displaying high anti-SFTSV efficacy, in which, toosendanin showed the highest inhibition potency. Mechanistic investigation indicated that toosendanin inhibited SFTSV infection at the step of virus internalization. The anti-viral effect of toosendanin against SFTSV was further verified in mouse infection models, and the treatment with toosendanin significantly reduced viral load and histopathological changes in vivo. The antiviral activity of toosendanin was further expanded to another bunyavirus and the emerging SARS-CoV-2. This study revealed a broad anti-viral effect of toosendanin and indicated its potential to be developed as an anti-viral drug for clinical use.

18.
Front Immunol ; 12: 750969, 2021.
Article in English | MEDLINE | ID: covidwho-1551506

ABSTRACT

The COVID-19 is an infectious disease caused by SARS-CoV-2 infection. A large number of clinical studies found high-level expression of pro-inflammatory cytokines in patients infected with SARS-CoV-2, which fuels the rapid development of the disease. However, the specific molecular mechanism is still unclear. In this study, we found that SARS-CoV-2 Nsp5 can induce the expression of cytokines IL-1ß, IL-6, TNF-α, and IL-2 in Calu-3 and THP1 cells. Further research found that Nsp5 enhances cytokine expression through activating the NF-κB signaling pathway. Subsequently, we investigated the upstream effectors of the NF-κB signal pathway on Nsp5 overexpression and discovered that Nsp5 increases the protein level of MAVS. Moreover, Nsp5 can promote the SUMOylation of MAVS to increase its stability and lead to increasing levels of MAVS protein, finally triggering activation of NF-κB signaling. The knockdown of MAVS and the inhibitor of SUMOylation treatment can attenuate Nsp5-mediated NF-κB activation and cytokine induction. We identified a novel role of SARS-CoV-2 Nsp5 to enhance cytokine production by activating the NF-κB signaling pathway.

19.
Brief Bioinform ; 2021 Nov 25.
Article in English | MEDLINE | ID: covidwho-1545905

ABSTRACT

Spatial transcriptomics has been emerging as a powerful technique for resolving gene expression profiles while retaining tissue spatial information. These spatially resolved transcriptomics make it feasible to examine the complex multicellular systems of different microenvironments. To answer scientific questions with spatial transcriptomics and expand our understanding of how cell types and states are regulated by microenvironment, the first step is to identify cell clusters by integrating the available spatial information. Here, we introduce SC-MEB, an empirical Bayes approach for spatial clustering analysis using a hidden Markov random field. We have also derived an efficient expectation-maximization algorithm based on an iterative conditional mode for SC-MEB. In contrast to BayesSpace, a recently developed method, SC-MEB is not only computationally efficient and scalable to large sample sizes but is also capable of choosing the smoothness parameter and the number of clusters. We performed comprehensive simulation studies to demonstrate the superiority of SC-MEB over some existing methods. We applied SC-MEB to analyze the spatial transcriptome of human dorsolateral prefrontal cortex tissues and mouse hypothalamic preoptic region. Our analysis results showed that SC-MEB can achieve a similar or better clustering performance to BayesSpace, which uses the true number of clusters and a fixed smoothness parameter. Moreover, SC-MEB is scalable to large 'sample sizes'. We then employed SC-MEB to analyze a colon dataset from a patient with colorectal cancer (CRC) and COVID-19, and further performed differential expression analysis to identify signature genes related to the clustering results. The heatmap of identified signature genes showed that the clusters identified using SC-MEB were more separable than those obtained with BayesSpace. Using pathway analysis, we identified three immune-related clusters, and in a further comparison, found the mean expression of COVID-19 signature genes was greater in immune than non-immune regions of colon tissue. SC-MEB provides a valuable computational tool for investigating the structural organizations of tissues from spatial transcriptomic data.

20.
Nat Commun ; 12(1): 6923, 2021 11 26.
Article in English | MEDLINE | ID: covidwho-1537314

ABSTRACT

Nationwide nonpharmaceutical interventions (NPIs) have been effective at mitigating the spread of the novel coronavirus disease (COVID-19), but their broad impact on other diseases remains under-investigated. Here we report an ecological analysis comparing the incidence of 31 major notifiable infectious diseases in China in 2020 to the average level during 2014-2019, controlling for temporal phases defined by NPI intensity levels. Respiratory diseases and gastrointestinal or enteroviral diseases declined more than sexually transmitted or bloodborne diseases and vector-borne or zoonotic diseases. Early pandemic phases with more stringent NPIs were associated with greater reductions in disease incidence. Non-respiratory diseases, such as hand, foot and mouth disease, rebounded substantially towards the end of the year 2020 as the NPIs were relaxed. Statistical modeling analyses confirm that strong NPIs were associated with a broad mitigation effect on communicable diseases, but resurgence of non-respiratory diseases should be expected when the NPIs, especially restrictions of human movement and gathering, become less stringent.

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