Dataset Information

Neuropilins: C-end rule peptides and their association with nociception and COVID-19.

ABSTRACT: Viral internalization is aided by host cell surface receptors. In the case of SARS-CoV-2 and SARS-CoV, the primary host receptor is the angiotensin-converting enzyme 2 (ACE2). Considering the disparities in the transmission rate and viral tropism of the two coronaviruses, additional host factors were suspected. Recently, a novel host factor for SARS-CoV-2 entry, neuropilin-1 (NRP-1) has been identified. These receptors potentiate viral infection in the presence of other host factors like ACE2. Through its C-end rule (CendR) motif exposed following furin processing, the SARS-CoV-2 spike protein binds to the CendR pocket of NRP-1 and achieves cell entry through endocytosis. The binding of SARS-CoV-2 spike protein to the NRP-1 receptor interferes with the docking of its endogenous ligand VEGF-A, signaling that would otherwise promote nociception. This review looks at the function of neuropilins and how it contributes to SARS-CoV-2 infection and nociception.

SUBMITTER: Jobe A

PROVIDER: S-EPMC7997051 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Neuropilins: C-end rule peptides and their association with nociception and COVID-19.

Jobe Amie A Vijayan Ranjit R

Computational and structural biotechnology journal 20210326

Viral internalization is aided by host cell surface receptors. In the case of SARS-CoV-2 and SARS-CoV, the primary host receptor is the angiotensin-converting enzyme 2 (ACE2). Considering the disparities in the transmission rate and viral tropism of the two coronaviruses, additional host factors were suspected. Recently, a novel host factor for SARS-CoV-2 entry, neuropilin-1 (NRP-1) has been identified. These receptors potentiate viral infection in the presence of other host factors like ACE2. T ...[more]

PMID: 33815686

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Project description:BackgroundThe COVID-19 pandemic is a significant public health crisis that is hitting hard on people's health, well-being, and freedom of movement, and affecting the global economy. Scientists worldwide are competing to develop therapeutics and vaccines; currently, three drugs and two vaccine candidates have been given emergency authorization use. However, there are still questions of efficacy with regard to specific subgroups of patients and the vaccine's scalability to the general public. Under such circumstances, understanding COVID-19 symptoms is vital in initial triage; it is crucial to distinguish the severity of cases for effective management and treatment. This study aimed to discover symptom patterns and overall symptom rules, including rules disaggregated by age, sex, chronic condition, and mortality status, among COVID-19 patients.MethodsThis study was a retrospective analysis of COVID-19 patient data made available online by the Wolfram Data Repository through May 27, 2020. We applied a widely used rule-based machine learning technique called association rule mining to identify frequent symptoms and define patterns in the rules discovered.ResultIn total, 1,560 patients with COVID-19 were included in the study, with a median age of 52 years. The most frequently occurring symptom was fever (67%), followed by cough (37%), malaise/body soreness (11%), pneumonia (11%), and sore throat (8%). Myocardial infarction, heart failure, and renal disease were present in less than 1% of patients. The top ten significant symptom rules (out of 71 generated) showed cough, septic shock, and respiratory distress syndrome as frequent consequents. If a patient had a breathing problem and sputum production, then, there was higher confidence of that patient having a cough; if cardiac disease, renal disease, or pneumonia was present, then there was a higher confidence of septic shock or respiratory distress syndrome. Symptom rules differed between younger and older patients and between male and female patients. Patients who had chronic conditions or died of COVID-19 had more severe symptom rules than those patients who did not have chronic conditions or survived of COVID-19. Concerning chronic condition rules among 147 patients, if a patient had diabetes, prerenal azotemia, and coronary bypass surgery, there was a certainty of hypertension.ConclusionThe most frequently reported symptoms in patients with COVID-19 were fever, cough, pneumonia, and sore throat; while 1% had severe symptoms, such as septic shock, respiratory distress syndrome, and respiratory failure. Symptom rules differed by age and sex. Patients with chronic disease and patients who died of COVID-19 had severe symptom rules more specifically, cardiovascular-related symptoms accompanied by pneumonia, fever, and cough as consequents.

Project description:BackgroundHuman behavior is crucial in health outcomes. Particularly, individual behavior is a determinant of the success of measures to overcome critical conditions, such as a pandemic. In addition to intrinsic public health challenges associated with COVID-19, in many countries, some individuals decided not to get vaccinated, streets were crowded, parties were happening, and businesses struggling to survive were partially open, despite lockdown or stay-at-home instructions. These behaviors contrast with the instructions for potential benefits associated with social distancing, use of masks, and vaccination to manage collective and individual risks.ObjectiveConsidering that human behavior is a result of individuals' social and economic conditions, we investigated the social and working characteristics associated with reports of appropriate protective behavior in Brazil.MethodsWe analyzed data from a large web survey of individuals reporting their behavior during the pandemic. We selected 3 common self-care measures: use of protective masks, distancing by at least 1 m when out of the house, and handwashing or use of alcohol, combined with assessment of the social context of respondents. We measured the frequency of the use of these self-protective measures. Using a frequent pattern-mining perspective, we generated association rules from a set of answers to questions that co-occur with at least a given frequency, identifying the pattern of characteristics of the groups divided according to protective behavior reports.ResultsThe rationale was to identify a pool of working and social characteristics that might have better adhesion to behaviors and self-care measures, showing these are more socially determined than previously thought. We identified common patterns of socioeconomic and working determinants of compliance with protective self-care measures. Data mining showed that social determinants might be important to shape behavior in different stages of the pandemic.ConclusionsIdentification of context determinants might be helpful to identify unexpected facilitators and constraints to fully follow public policies. The context of diseases contributes to psychological and physical health outcomes, and context understanding might change the approach to a disease. Hidden social determinants might change protective behavior, and social determinants of protective behavior related to COVID-19 are related to work and economic conditions.Trial registrationNot applicable.

Dataset Information

Neuropilins: C-end rule peptides and their association with nociception and COVID-19.

Publications

Neuropilins: C-end rule peptides and their association with nociception and COVID-19.

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