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1.
Cancer Epidemiol Biomarkers Prev ; 30(10): 1884-1894, 2021 10.
Article in English | MEDLINE | ID: covidwho-2194255

ABSTRACT

BACKGROUND: We described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza. METHODS: We conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes. RESULTS: We included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%-18% and 1%-14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events. CONCLUSIONS: Patients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent. IMPACT: This study provides epidemiologic characteristics that can inform clinical care and etiologic studies.


Subject(s)
COVID-19/mortality , Neoplasms/epidemiology , Outcome Assessment, Health Care/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Child , Cohort Studies , Comorbidity , Databases, Factual , Female , Hospitalization/statistics & numerical data , Humans , Influenza, Human/epidemiology , Male , Middle Aged , Pandemics , Prevalence , Risk Factors , SARS-CoV-2 , Spain/epidemiology , United States/epidemiology , Young Adult
2.
Medicine (Baltimore) ; 100(19): e25924, 2021 May 14.
Article in English | MEDLINE | ID: covidwho-2191010

ABSTRACT

ABSTRACT: At present, coronavirus disease 2019 (COVID-19) remains a significant challenge for health workers around the world. This survey aims to highlight the status of the implementation of occupational protection measures for nurses working on the front line against COVID-19, and to analyze the problems in the process of wearing protective equipment.This cross-sectional study was conducted among 165 nurses who worked in COVID-19-stricken areas in China in March 2020. The questionnaire covered 3 aspects, namely: general information, the current condition of protective equipment wearing, and the wearing experience of protective equipment.A total of 160 (96.97%) valid questionnaires were collected. The average time of wearing protective equipment for the nurses surveyed was 6.38 ±â€Š3.30 hours per working day. For first-line nurses with low risk of infection, repeated wear of protective equipment was as follows: medical protective mask 30.77%, double latex gloves 8.46%, goggles/protective mask 15.38%, protective suit 15.38%; less wear of protective equipment were as follows: work cap 7.69%, surgical mask 7.69%, single layer latex gloves 30.77%, goggles/protective mask 30.77%, and isolation gown 46.15%. For nurses who were at moderate risk of infection, repeated wear of protective equipment was as follows: surgical mask 62.22%, goggles/protective mask 68.89%, and isolation gown 65.56%; less wear: work cap 3.33%, medical protective mask 15.56%, latex gloves 15.56%, goggles/protective mask 5.56%, and protective suit 16.67%. For front-line nurses with high risk of infection, repeated wear of protective equipment was as follows: surgical mask 64.91%, more than double latex gloves 8.77%, goggles/protective mask 75.44%, isolation gown 75.44%; less wear: work cap 1.75%, medical protective mask 1.75%, latex gloves 26.32%, goggles/ protective mask 1.75%, protective suit 1.75%. The main discomforts of wearing protective equipment were poor vision due to fogging (81.88%), stuffiness (79.38%), poor mobility (74.38%), sweating (72.5%), and skin damage (61.25%).More detailed personal protection standards should be developed, and the work load of nurses should be reduced. Actions should be taken to ensure the scientific implementation of personal protective measures. To solve practical clinical problems, future protective equipment may focus on the research and development of protective equipment applicable for different risk levels, as well as the research on integrated design, fabric innovation, and reusability.


Subject(s)
COVID-19/prevention & control , Infection Control/statistics & numerical data , Nurses/statistics & numerical data , Personal Protective Equipment/statistics & numerical data , China , Cross-Sectional Studies , Humans , Risk Factors , SARS-CoV-2
3.
Computer Methods and Programs in Biomedicine ; : 107348, 2023.
Article in English | ScienceDirect | ID: covidwho-2177759

ABSTRACT

Background and objective: COVID-19 is a serious threat to human health. Traditional convolutional neural networks (CNNs) can realize medical image segmentation, whilst transformers can be used to perform machine vision tasks, because they have a better ability to capture long-range relationships than CNNs. The combination of CNN and transformers to complete the task of semantic segmentation has attracted intense research. Currently, it is challenging to segment medical images on limited data sets like that on COVID-19. Methods: This study proposes a lightweight transformer+CNN model, in which the encoder sub-network is a two-path design that enables both the global dependence of image features and the low layer spatial details to be effectively captured. Using CNN and MobileViT to jointly extract image features reduces the amount of computation and complexity of the model as well as improves the segmentation performance. So this model is titled Mini-MobileViT-Seg (MMViT-Seg). In addition, a multi query attention (MQA) module is proposed to fuse the multi-scale features from different levels of decoder sub-network, further improving the performance of the model. MQA can simultaneously fuse multi-input, multi-scale low-level feature maps and high-level feature maps as well as conduct end-to-end supervised learning guided by ground truth. Results: The two-class infection labeling experiments were conducted based on three datasets. The final results show that the proposed model has the best performance and the minimum number of parameters among five popular semantic segmentation algorithms. In multi-class infection labeling results, the proposed model also achieved competitive performance. Conclusions: The proposed MMViT-Seg is tested on three COVID-19 segmentation datasets, with results showing that this model has better performance than other models. In addition, the proposed MQA module, which can effectively fuse multi-scale features of different levels further improves the segmentation accuracy.

4.
Frontiers in medicine ; 9, 2022.
Article in English | EuropePMC | ID: covidwho-2124726

ABSTRACT

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Serologic testing is complementary to nucleic acid screening to identify SARS-CoV-2. This study aimed to evaluate unspecific reactivity in SARS-CoV-2 serologic tests. Materials and methods Total anti-SARS-CoV-2 antibodies from 46,777 subjects who were screened for SARS-CoV-2 were retrospectively studied to evaluate the incidence and characteristics of the unspecific reactivity. A total of 1,114 pre-pandemic samples were also analysed to compare unspecific reactivity. Results The incidence of unspecific reactivity in anti-SARS-CoV-2 total antibody testing was 0.361% in 46,777 post-pandemic samples, similar to the incidence of 0.359% (4/1,114) in 1,114 pre-pandemic samples (p = 0.990). Subjects ≥ 19 years old had a 2.753-fold [95% confidence interval (CI), 1.130–6.706] higher probability of unspecific reactivity than subjects < 19 years old (p = 0.026). There was no significant difference between the sexes. The unspecific reactivity was associated with 14 categories within the disease spectrum, with three tops being the skin and subcutaneous tissue diseases (0.93%), respiratory system diseases (0.78%) and neoplasms diseases (0.76%). The percentage of patients with a titer ≥ 13.87 cut-off index (COI) in the unspecific reactivity was 7.69%. Conclusion Our results suggest a unspecific reactivity incidence rate of 0.361% involving 14 categories on the disease spectrum. Unspecific reactivity needs to be excluded when performing serologic antibody testing in COVID-19 epidemiological analyses or virus tracing.

5.
J Epidemiol Glob Health ; 2022 Nov 24.
Article in English | MEDLINE | ID: covidwho-2129635

ABSTRACT

Is Long COVID-19 under-diagnosed? The definition of this new condition has received many contributions, and it is still under development as a great variety of symptoms have been associated to it. This study explores the possibility that there are non-diagnosed cases among individuals who have been infected by SARS-CoV-2 and have not been vaccinated. The long-term symptoms identified among a sample 255 individuals have been associated to Long COVID-19 by recent literature. The study relates these symptoms to risk factors and health-related quality of life (HRQoL) negative impacts. The individuals were screened 1 year after discharge to explore its potential relation to Long COVID-19. Patients diagnosed with COVID-19 and discharged from designated hospitals in a Chinese province between January and April 2020 were included in this study. They received computed tomography (CT) scans one month after discharge. One year after discharge, patients were invited to physical examination and interviewed with questionnaire on health-related quality of life (HRQoL) and post-COVID-19 symptoms. Tobit regression and Logistic regression were applied to evaluate the risk factors for health utility value and pain/discomfort and anxiety/depression. One year after discharge, 39.61% patients complained of several of the symptoms associated to Long COVID-19. More than half had abnormal chest CT. Previous studies focused on the post-COVID-19 symptoms and chest CT findings of patients, but few studies have assessed the COVID-19-associated risk factors for health-related quality of life.

6.
J Affect Disord ; 2022 Nov 23.
Article in English | MEDLINE | ID: covidwho-2122556

ABSTRACT

BACKGROUND: The present study aimed to investigate the pandemic stage differences of mental health helpline help-seekers emotional responses, psychiatric symptoms, and related network structures during the COVID-19 pandemic in China. METHODS: The data was collected by a large-scale psychological helpline in response to the COVID-19 pandemic in mainland China. Counselor-reported information about the help-seekers pandemic-related emotional responses and psychiatric symptoms were recorded. A total of 26,870 callers' data from February 28, 2020, to April 23, 2021, were collected in the present study. A linear probability model and network analysis were conducted to determine the differences in help-seekers mental health concerns and network structures between the pandemic (stage I, from February 28, 2020, to April 28, 2020, N = 9821) and the regular prevention and control period (stage II, from April 29, 2020, to April 23, 2021, N = 17,049). RESULTS: Results revealed that anger, sadness, and obsession symptoms increased in stage II while symptoms of anxiety, somatization, and feelings of fear and stress were relieved. The network analysis results demonstrated both stage I and II networks centered on anxiety firmly. In stage II, the connection between anxiety and hypochondria and fear's strength centrality descended significantly. LIMITATIONS: The mental health outcomes of callers only included the counselor-reported data. CONCLUSIONS: The mental health concerns of helpline callers showed pandemic-related stage differences.

7.
Nat Commun ; 13(1): 6818, 2022 Nov 10.
Article in English | MEDLINE | ID: covidwho-2117855

ABSTRACT

Systemic characterisation of the human faecal microbiome provides the opportunity to develop non-invasive approaches in the diagnosis of a major human disease. However, shared microbial signatures across different diseases make accurate diagnosis challenging in single-disease models. Herein, we present a machine-learning multi-class model using faecal metagenomic dataset of 2,320 individuals with nine well-characterised phenotypes, including colorectal cancer, colorectal adenomas, Crohn's disease, ulcerative colitis, irritable bowel syndrome, obesity, cardiovascular disease, post-acute COVID-19 syndrome and healthy individuals. Our processed data covers 325 microbial species derived from 14.3 terabytes of sequence. The trained model achieves an area under the receiver operating characteristic curve (AUROC) of 0.90 to 0.99 (Interquartile range, IQR, 0.91-0.94) in predicting different diseases in the independent test set, with a sensitivity of 0.81 to 0.95 (IQR, 0.87-0.93) at a specificity of 0.76 to 0.98 (IQR 0.83-0.95). Metagenomic analysis from public datasets of 1,597 samples across different populations observes comparable predictions with AUROC of 0.69 to 0.91 (IQR 0.79-0.87). Correlation of the top 50 microbial species with disease phenotypes identifies 363 significant associations (FDR < 0.05). This microbiome-based multi-disease model has potential clinical application in disease diagnostics and treatment response monitoring and warrants further exploration.


Subject(s)
COVID-19 , Microbiota , Humans , COVID-19/diagnosis , Feces , Machine Learning
8.
Environ Microbiol ; 23(12): 7373-7381, 2021 12.
Article in English | MEDLINE | ID: covidwho-2078263

ABSTRACT

Coronavirus disease 2019 (COVID-19) pandemic has caused high number of infections and deaths of healthcare workers globally. Distribution and possible transmission route of SARS-CoV-2 in hospital environment should be clarified. We herein collected 431 environmental (391 surface and 40 air) samples in the intensive care unit (ICU) and general wards (GWs) of three hospitals in Wuhan, China from February 21 to March 4, 2020, and detected SARS-CoV-2 RNA by real-time quantitative PCR. The viral positive rate in the contaminated areas was 17.8% (28/157), whereas there was no virus detected in the clean areas. Higher positive rate (22/59, 37.3%) was found in ICU than that in GWs (3/63, 4.8%). The surfaces of computer keyboards and mouse in the ICU were the most contaminated (8/10, 80.0%), followed by the ground (6/9, 66.7%) and outer glove (2/5, 40.0%). From 17 air samples in the contaminated areas, only one sample collected at a distance of around 30 cm from the patient was positive. Enhanced surface disinfection and hand hygiene effectively decontaminated the virus from the environment. This finding might help understand the transmission route and contamination risk of SARS-CoV-2 and evaluate the effectiveness of infection prevention and control measures in healthcare facilities.


Subject(s)
COVID-19 , Hospitals , Humans , Pandemics , RNA, Viral/genetics , SARS-CoV-2
9.
Curr Psychol ; 41(11): 8123-8131, 2022.
Article in English | MEDLINE | ID: covidwho-2075666

ABSTRACT

COVID-19 is a major public health event affecting the people worldwide. Nurses are still under immense psychological pressure. This study aimed to explore the relationship between mental fatigue and negative emotions among frontline medical staff during the COVID-19 pandemic. The study was conducted in August 2020, which included 419 medical staff between 17 to 28 years. The Fatigue Scale, Multidimensional Mental Flexibility Questionnaire, Cognitive Fusion Scale, and Depression-Anxiety-Stress Brief Version Scale were used. During the data collection period, the pandemic was under control in China and continued worldwide. The results indicated that 27.7% of the medical staff experienced depression, and 32.3% of them feel stressed. Specifically, first, correlation analyses showed significant positive pairwise correlations between mental fatigue, psychological inflexibility, cognitive fusion, and negative emotions among nurses. Second, mediation model tests showed statistically significant mediating effects of psychological inflexibility and cognitive fusion between mental fatigue on nurses' negative emotions, and statistically, significant chain mediating effects of psychological inflexibility and cognitive fusion. Mental fatigue indirectly affects nurses' negative effects through the mediating effects of psychological inflexibility, cognitive fusion, and the chain mediating effects of psychological inflexibility and cognitive fusion, respectively. the negative effects of mental fatigue come from impairment of cognitive functioning, and interventions using acceptance and commitment therapy for mental fatigue and negative emotions are more effective since both psychological inflexibility and cognitive fusion are important components of the therapy.

10.
PLoS Comput Biol ; 18(9): e1010472, 2022 09.
Article in English | MEDLINE | ID: covidwho-2054247

ABSTRACT

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.


Subject(s)
COVID-19 , Gastrointestinal Microbiome , Gastrointestinal Microbiome/genetics , Humans , Pandemics , Population Density , Sewage , Waste Water
11.
Gut Microbes ; 14(1): 2128603, 2022.
Article in English | MEDLINE | ID: covidwho-2051074

ABSTRACT

Dysbiosis of gut microbiota is well-described in patients with coronavirus 2019 (COVID-19), but the dynamics of antimicrobial resistance genes (ARGs) reservoir, known as resistome, is less known. Here, we performed longitudinal fecal metagenomic profiling of 142 patients with COVID-19, characterized the dynamics of resistome from diagnosis to 6 months after viral clearance, and reported the impact of antibiotics or probiotics on the ARGs reservoir. Antibiotic-naive patients with COVID-19 showed increased abundance and types, and higher prevalence of ARGs compared with non-COVID-19 controls at baseline. Expansion in resistome was mainly driven by tetracycline, vancomycin, and multidrug-resistant genes and persisted for at least 6 months after clearance of SARS-CoV-2. Patients with expanded resistome exhibited increased prevalence of Klebsiella sp. and post-acute COVID-19 syndrome. Antibiotic treatment resulted in further increased abundance of ARGs whilst oral probiotics (synbiotic formula, SIM01) significantly reduced the ARGs reservoir in the gut microbiota of COVID-19 patients during the acute infection and recovery phase. Collectively, these findings shed new insights on the dynamic of ARGs reservoir in COVID-19 patients and the potential role of microbiota-directed therapies in reducing the burden of accumulated ARGs.


Subject(s)
COVID-19 , Gastrointestinal Microbiome , Probiotics , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , COVID-19/complications , COVID-19/drug therapy , Drug Resistance, Bacterial/genetics , Gastrointestinal Microbiome/genetics , Humans , Probiotics/therapeutic use , SARS-CoV-2/genetics , Tetracyclines , Vancomycin
12.
Frontiers in public health ; 10, 2022.
Article in English | EuropePMC | ID: covidwho-2047129

ABSTRACT

Objectives This study aims to clarify the profiles of the psychological antecedents of vaccine hesitancy among Shanghai nurses with a person-centered approach. Methods A population-based cross-sectional online survey was conducted on Shanghai nurses from July to August 2021 (N = 1,928). In the online survey, participants were asked to report their sociodemographic, the 5C vaccine hesitancy components, their knowledge level of COVID-19 vaccine and vaccination, and the COVID-19 vaccination uptake intention and attention to vaccine news. Latent profile analysis was used to reveal distinct profiles of vaccine hesitancy. Results The results revealed four profiles, including “believers” (68.9%;high confidence and collective responsibility), “free riders” (12.7%;similar characteristics to believers, except for a low collective responsibility), “middlemen” (14.6%;middle in all 5C constructs), and “contradictors” (3.7%;high in all 5C constructs). Compared to believers, middlemen were younger, more likely to be female, childless, less educated, held lower professional titles, had fewer years of nursing service, sometimes or never complied with recommended vaccinations, had satisfactory or poor self-assessed health status, had no work experience during the COVID-19 epidemic, and possessed greater levels of knowledge. Free riders were more likely to work in community health centers and have a lower degree than believers. Contradictors were more likely to work in community health centers, had junior college degrees or lower, and had no work experience during the COVID-19 epidemic than believers. From the highest to the lowest on vaccination intention and attention to vaccine news were believers, then free riders, contradictors, and finally middlemen. Conclusion This study could aid in the development of personalized vaccination strategies based on nurses' vaccine hesitancy profiles and predictors. In addition to vaccine believers, we identified other three profiles based on their 5C psychological antecedents, emphasizing the significance of establishing tailored vaccination campaigns. Further research into the prevalence of profile structure in other groups of healthcare workers is required.

13.
Vaccines (Basel) ; 10(9)2022 Sep 16.
Article in English | MEDLINE | ID: covidwho-2044014

ABSTRACT

Several vaccines have been developed for COVID-19 since the pandemic began. This study aimed to evaluate the factors associated with COVID-19 vaccination intention. A global survey was conducted across 26 countries from October, 2020 to December, 2021 using an online self-administered questionnaire. Demographic information, socio-economic status, and clinical information were collected. A logistic regression examined the associations between vaccine intention and factors such as perceptions and the presence of chronic physical and mental conditions. The sample included 2459 participants, with 384 participants (15.7%) expressing lower COVID-19 vaccination intent. Individuals who identified as female; belonged to an older age group; had a higher level of education; were students; had full health insurance coverage; or had a previous history of influenza vaccination were more willing to receive vaccination. Conversely, those who were working part-time, were self-employed, or were receiving social welfare were less likely to report an intention to get vaccinated. Participants with mental or physical health conditions were more unwilling to receive vaccination, especially those with sickle cell disease, cancer history within the past five years, or mental illness. Stronger vaccination intent was associated with recommendations from the government or family doctors. The presence of chronic conditions was associated with lower vaccine intention. Individuals with health conditions are especially vulnerable to health complications and may experience an increased severity of COVID-19 symptoms. Future research should evaluate the effectiveness of interventions targeting the vaccine perceptions and behaviours of at-risk groups. As such, public awareness campaigns conducted by the government and proactive endorsement from health physicians may help improve COVID-19 vaccination intention.

14.
Journal of inflammation research ; 15:5235-5246, 2022.
Article in English | EuropePMC | ID: covidwho-2033810

ABSTRACT

Acute respiratory distress syndrome (ARDS) presents as a form of acute respiratory failure resulting from non-cardiogenic pulmonary edema due to excessive alveolocapillary permeability, which may be pulmonary or systemic in origin. In the last 3 years, the coronavirus disease 2019 pandemic has resulted in an increase in ARDS cases and highlighted the challenges associated with this syndrome, as well as the unacceptably high mortality rates and lack of effective treatments. Currently, clinical treatment remains primarily supportive, including mechanical ventilation and drug-based therapy. Mesenchymal stem cell (MSC) therapies are emerging as a promising intervention in patients with ARDS and have promising therapeutic effects and safety. The therapeutic mechanisms include modifying the immune response and assisting with tissue repair. This review provides an overview of the general properties of MSCs and outlines their role in mitigating lung injury and promoting tissue repair in ARDS. Finally, we summarize the current challenges in the study of translational MSC research and identify avenues by which the discipline may progress in the coming years.

15.
PLoS One ; 17(9): e0273323, 2022.
Article in English | MEDLINE | ID: covidwho-2021911

ABSTRACT

BACKGROUND: The humoral response to SARS-CoV-2 can provide immunity and prevent reinfection. However, less is known about how the diversity, magnitude, and length of the antibody response after a primary infection is associated with symptoms, post-infection immunity, and post-vaccinated immunity. METHODS: Cook County Health employees provided blood samples and completed an online survey 8-10 weeks after a PCR-confirmed positive SARS-CoV-2 test (pre-vaccinated, N = 41) and again, 1-4 weeks after completion of a 2-dose series mRNA BNT162b2 COVID-19 vaccine (post-vaccinated, N = 27). Associations were evaluated between SARS-CoV-2 antibody titers, participant demographics, and clinical characteristics. Antibody titers and angiotensin-converting enzyme 2 (ACE2) neutralization were compared before and after the mRNA BNT162b2 COVID-19 vaccine. RESULTS: Antibody titers to the spike protein (ST4), receptor binding domain (RBD), and RBD mutant D614G were significantly associated with anosmia and ageusia, cough, and fever. Spike protein antibody titers and ACE2 neutralization were significantly higher in participants that presented with these symptoms. Antibody titers to the spike protein N-terminal domain (NTD), RBD, and ST4, and ACE2 IC50 were significantly higher in all post-vaccinated participant samples compared to pre-vaccinated participant sample, and not dependent on previously reported symptoms. CONCLUSIONS: Spike protein antibody titers and ACE2 neutralization are associated with the presentation of anosmia and ageusia, cough, and fever after SARS-CoV-2 infection. Symptom response to previous SARS-CoV-2 infection did not influence the antibody response from subsequent vaccination. These results suggest a relationship between infection severity and the magnitude of the immune response and provide meaningful insights into COVID-19 immunity according to discrete symptom presentation.


Subject(s)
Ageusia , COVID-19 , Angiotensin-Converting Enzyme 2 , Anosmia , Antibodies, Viral , Antibody Formation , BNT162 Vaccine , COVID-19/diagnosis , COVID-19/prevention & control , COVID-19 Vaccines , Cough , Humans , RNA, Messenger/genetics , SARS-CoV-2 , Spike Glycoprotein, Coronavirus
17.
Health Res Policy Syst ; 20(1): 89, 2022 Aug 13.
Article in English | MEDLINE | ID: covidwho-2002196

ABSTRACT

BACKGROUND: Academic research is one of the main avenues through which humans can fight the threat of infectious diseases. However, there have been concerns regarding whether the academic system has provided sufficient efforts to fight infectious diseases we potentially face. Answering these questions could contribute to evidence-based recommendations for setting research priorities and third-mission policies. METHODS: With a focus on one of the most common categories of communicable diseases, infectious and parasitic diseases (IPDs), we searched Web of Science for articles and reviews relevant to IPDs published during the period 2000-2019 and retrieved WHO data on disease burden in corresponding years. The academic response patterns were explored by IPD subcategory and by human development level (an index established by the United Nations). We conduct the analysis in particular to gain insight into the dynamic relationship between disease burden and research effort on IPDs, scientific efforts contributed by countries with different development levels, and the variation trends in international joint efforts. RESULTS: The greatest burden of IPDs is clustered in the developing regions of Africa, but has received academic response from both developed and developing countries. Highly developed countries dominate the ranks of academic research in this area, yet there is also a clear increase in research efforts from the countries most affected, despite their low human development scale. In fact, the overall analysis reveals an improved capability for addressing local problems from African regions. In terms of international collaboration, highly developed countries such as the United States and United Kingdom have commonly collaborated with needy regions, whereas prolific but developing nations, like China, have not. CONCLUSIONS: From a global perspective, academia has positively responded to health needs caused by IPDs. Although the relevant research output contribution is primarily from the highly developed countries, concentrated and specialized efforts from the undeveloped regions to ease their local burden can be clearly observed. Our findings also indicate a tendency to focus more on local health needs for both developed and undeveloped regions. The insights revealed in this study should benefit a more informed and systemic plan of research priorities.


Subject(s)
Communicable Diseases , Parasitic Diseases , China , Cost of Illness , Humans , Publications
18.
Brief Bioinform ; 23(5)2022 09 20.
Article in English | MEDLINE | ID: covidwho-2001208

ABSTRACT

Recently, N6-methylation (m6A) has recently become a hot topic due to its key role in disease pathogenesis. Identifying disease-related m6A sites aids in the understanding of the molecular mechanisms and biosynthetic pathways underlying m6A-mediated diseases. Existing methods treat it primarily as a binary classification issue, focusing solely on whether an m6A-disease association exists or not. Although they achieved good results, they all shared one common flaw: they ignored the post-transcriptional regulation events during disease pathogenesis, which makes biological interpretation unsatisfactory. Thus, accurate and explainable computational models are required to unveil the post-transcriptional regulation mechanisms of disease pathogenesis mediated by m6A modification, rather than simply inferring whether the m6A sites cause disease or not. Emerging laboratory experiments have revealed the interactions between m6A and other post-transcriptional regulation events, such as circular RNA (circRNA) targeting, microRNA (miRNA) targeting, RNA-binding protein binding and alternative splicing events, etc., present a diverse landscape during tumorigenesis. Based on these findings, we proposed a low-rank tensor completion-based method to infer disease-related m6A sites from a biological standpoint, which can further aid in specifying the post-transcriptional machinery of disease pathogenesis. It is so exciting that our biological analysis results show that Coronavirus disease 2019 may play a role in an m6A- and miRNA-dependent manner in inducing non-small cell lung cancer.


Subject(s)
COVID-19 , Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , MicroRNAs , Adenosine/metabolism , Alternative Splicing , COVID-19/genetics , Humans , Methylation , MicroRNAs/genetics , MicroRNAs/metabolism , RNA, Circular , RNA-Binding Proteins/metabolism
19.
Gastroenterology ; 162(7): 2135, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1984463
20.
Sci Transl Med ; 14(655): eabn3041, 2022 07 27.
Article in English | MEDLINE | ID: covidwho-1962063

ABSTRACT

As the coronavirus disease 2019 (COVID-19) pandemic evolves and vaccine rollout progresses, the availability and demand for monoclonal antibodies for the prevention and treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are also accelerating. This longitudinal serological study evaluated the magnitude and potency of the endogenous antibody response to COVID-19 vaccination in participants who first received a COVID-19 monoclonal antibody in a prevention study. Over the course of 6 months, serum samples were collected from a population of nursing home residents and staff enrolled in a clinical trial who were randomized to either bamlanivimab treatment or placebo. In an unplanned component of this trial, a subset of these participants was subsequently fully vaccinated with two doses of either SpikeVax (Moderna) or Comirnaty (BioNTech/Pfizer) COVID-19 mRNA vaccines. This post hoc analysis assessed the immune response to vaccination for 135 participants without prior SARS-CoV-2 infection. Antibody titers and potency were assessed using three assays against SARS-CoV-2 proteins that bamlanivimab does not efficiently bind to, thereby reflecting the endogenous antibody response. All bamlanivimab and placebo recipients mounted a robust immune response to full COVID-19 vaccination, irrespective of age, risk category, and vaccine type with any observed differences of uncertain clinical importance. These findings are pertinent for informing public health policy with results that suggest that the benefit of receiving COVID-19 vaccination at the earliest opportunity outweighs the minimal effect on the endogenous immune response due to prior prophylactic COVID-19 monoclonal antibody infusion.


Subject(s)
COVID-19 , Viral Vaccines , Antibodies, Monoclonal, Humanized/therapeutic use , Antibodies, Neutralizing , Antibodies, Viral , Antibody Formation , COVID-19 Vaccines , Humans , SARS-CoV-2 , Vaccination
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