scholarly journals Influence of SARS-CoV-2 on airway mucus production: A review and proposed model

2021 ◽  
pp. 030098582110588
Author(s):  
David K. Meyerholz ◽  
Leah R. Reznikov
Keyword(s):  
Inflammatory Cells ◽  
Model Systems ◽  
Limited Attention ◽  
Mucus Production ◽  
Airway Diseases ◽  
Proposed Model ◽  
Airway Symptoms ◽  
Airway Mucus ◽  
The Impact ◽  
Airway Mucin

Coronavirus disease 2019 (COVID-19) is a worldwide pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has affected millions of lives. Individuals who survive severe COVID-19 can experience sustained respiratory symptoms that persist for months after initial infection. In other airway diseases, abnormal airway mucus contributes to sustained airway symptoms. However, the impact of SARS-CoV-2 on airway mucus has received limited attention. In the current review, we assess literature describing the impact of SARS-CoV-2 on airway pathophysiology with specific emphasis on mucus production. Accumulating evidence suggests that the 2 major secreted airway mucin glycoproteins, MUC5AC and MUC5B, are abnormal in some patients with COVID-19. Aberrations in MUC5AC or MUC5B in response to SARS-CoV-2 infection are likely due to inflammation, though the responsible mechanisms have yet to be determined. Thus, we also provide a proposed model highlighting mechanisms that can contribute to acute and sustained mucus abnormalities in SARS-CoV-2, with an emphasis on inflammatory cells and mediators, including mast cells and histamine. Last, we bring to light the challenges of studying abnormal mucus production in SARS-CoV-2 infections and discuss the strengths and limitations of model systems commonly used to study COVID-19. The evidence to date suggests that ferrets, nonhuman primates, and cats may have advantages over other models to investigate mucus in COVID-19.

scholarly journals A Modeling Framework: To Analyze the Relationship between Accessibility, Land Use and Densities in Urban Areas

2021 ◽  
Vol 13 (2) ◽  
pp. 467
Author(s):  
Amila Jayasinghe ◽  
N. B. S. Madusanka ◽  
Chethika Abenayake ◽  
P. K. S. Mahanama
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Urban Areas ◽  
Three Dimensional ◽  
Limited Attention ◽  
Modeling Framework ◽  
Transport Planning ◽  
Proposed Model ◽  
The Impact ◽  
The Relationship

The study proposes a framework to model the three-dimensional relationship among density, land use, and accessibility in urban areas constructively contributing to overcome the limitations noted in the domains of urban planning and transport planning. First, most of the existing studies have focused on the topological characteristics in capturing the accessibility, but a limited attention has been given on measuring the accessibility by considering both topological and roadway characteristics. Second, the existing research studies have acknowledged the relationship among density, land use, and accessibility while a limited attention has been given to develop a modeling framework to capture the three-dimensional relationship. The modelling framework was tested in three urban areas in Sri Lanka. The research first analyzed the three-dimensional link among density, land use, and accessibility in the case studies. Then, the study developed a set of regression models to capture the density from the land use and accesability. The proposed model recorded a satisfactory level of accuracy (i.e., R2 > 0.70) on a par with internationally accepted standards. The relationship was further elaborated through a decision tree analysis and 4D plot diagrams. Findings of the study can be utilized to model the density of a given land use and the correspondent accessibility scenarios. The proposed model is capable of quantifying the impact of the changes in the density correspondent to the accessibility and land use. Therefore, the study concludes that this will be an effective tool for decision-makers in the fields of land-use planning and transport planning for scenario building, impact analysis, and the formulation of land use zoning and urban development plans aiming at the overarching sustainability of future cities.

Test of Mediation and Moderation between Employee Empathy and Customers’ Advocacy

2020 ◽  
Author(s):  
Sajjad Ahmad Afridi ◽  
Asad Shahjehan ◽  
Maqsood Haider ◽  
Dr Uzma Munawar
Keyword(s):  
Factor Analysis ◽  
Customer Loyalty ◽  
Service Sector ◽  
Mediating Effect ◽  
First Line ◽  
Private Hospitals ◽  
Proposed Model ◽  
Confirmatory Factor ◽  
The Impact ◽  
Significant Moderator

This study examined the impact of employee empathy on customers’ advocacy directly and indirectly through customers’ loyalty. Moreover, the interacting effect of customers’ trust was verified between the association of customers’ loyalty and advocacy. The attributes of the proposed model were examined in the context of first line employee and patients’ interactions. A total of 220 responses were collected for analysis from the private hospitals of Peshawar. The model fitness was confirmed through confirmatory factor analysis and hypotheses were examined. Findings confirmed the positive and significant impact of employee empathy on customers’ advocacy. Further, the mediating effect was examined and found that loyalty partially mediates employee empathy and customers’ advocacy. Additionally, trust was found a significant moderator between the association of customer loyalty and advocacy. Furthermore, findings revealed that trust based loyalty significantly and positively mediates employee empathy and customers’ advocacy. Findings of the present study provide understanding for the service sector, particularly in healthcare, to enhance customers’ loyalty, advocacy, and trust through service employee’s empathic aptitude. Keywords: Employee empathy, Service Eco-system, Customers’ Loyalty, Customers’ Advocacy, Trust-Based Loyalty, Healthcare, S-D Logic

The impact of duration observations on precision of results GNSS measurements

2017 ◽  
Vol 921 (3) ◽  
pp. 7-13 ◽  
Author(s):  
S.V. Grishko
Keyword(s):  
Measurement Accuracy ◽  
Functional Dependence ◽  
Observation Time ◽  
Satellite Networks ◽  
Satellite Measurements ◽  
Proposed Model ◽  
Actual Error ◽  
Gnss Measurements ◽  
The Impact ◽  
Qualitative Characteristics

This paper shows that the accuracy of relative satellite measurements depend not only on the length of the baseline, as it is regulated by the rating formula of accuracy of GNSS equipment, but also on the duration of observations. As a result of the strict adjustment much redundant satellite networks with different duration of observations obtained covariance matrix of baselines, the most realistic reflecting the actual error of satellite observations. Research of forms of communication of these errors from length of the baseline and duration of its measurement is executed. A significant influence of solar activity on accuracy of satellite measurements, in general, leads to unequal similar series of measurements made at different periods, for example, in the production of monitoring activities. The model of approximation of the functional dependence of accuracy of the baseline from its length and duration of observations having good qualitative characteristics is offered. Based on the proposed model, we analyzed the dynamics of changes in measurement accuracy with an increase in observation time.

scholarly journals The impact of quarantine on Covid-19 infections

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Pablo Marshall
Keyword(s):  
Health System ◽  
Infection Rate ◽  
District Level ◽  
Infection Model ◽  
Social Distancing ◽  
Proposed Model ◽  
Lower Infection ◽  
The Impact ◽  
Lower Infection Rate ◽  
Over Time

Abstract Objectives: Coronavirushas had profound effects on people’s lives and the economy of many countries, generating controversy between the need to establish quarantines and other social distancing measures to protect people’s health and the need to reactivate the economy. This study proposes and applies a modification of the SIR infection model to describe the evolution of coronavirus infections and to measure the effect of quarantine on the number of people infected. Methods: Two hypotheses, not necessarily mutually exclusive, are proposed for the impact of quarantines. According to the first hypothesis, quarantine reduces the infection rate, delaying new infections over time without modifying the total number of people infected at the end of the wave. The second hypothesis establishes that quarantine reduces the population infected in the wave. The two hypotheses are tested with data for a sample of 10 districts in Santiago, Chile. Results: The results of applying the methodology show that the proposed model describes well the evolution of infections at the district level. The data shows evidence in favor of the first hypothesis, quarantine reduces the infection rate; and not in favor of the second hypothesis, that quarantine reduces the population infected. Districts of higher socio-economic levels have a lower infection rate, and quarantine is more effective. Conclusions: Quarantine, in most districts, does not reduce the total number of people infected in the wave; it only reduces the rate at which they are infected. The reduction in the infection rate avoids peaks that may collapse the health system.

scholarly journals An adaptive social distancing SIR model for COVID-19 disease spreading and forecasting

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Said Gounane ◽  
Yassir Barkouch ◽  
Abdelghafour Atlas ◽  
Mostafa Bendahmane ◽  
Fahd Karami ◽  
...  
Keyword(s):  
Mathematical Theory ◽  
Real Data ◽  
Sir Model ◽  
Epidemic Threshold ◽  
Social Distancing ◽  
Sir Epidemic ◽  
Proposed Model ◽  
Disease Spreading ◽  
The Government ◽  
The Impact

Abstract Recently, various mathematical models have been proposed to model COVID-19 outbreak. These models are an effective tool to study the mechanisms of coronavirus spreading and to predict the future course of COVID-19 disease. They are also used to evaluate strategies to control this pandemic. Generally, SIR compartmental models are appropriate for understanding and predicting the dynamics of infectious diseases like COVID-19. The classical SIR model is initially introduced by Kermack and McKendrick (cf. (Anderson, R. M. 1991. “Discussion: the Kermack–McKendrick Epidemic Threshold Theorem.” Bulletin of Mathematical Biology 53 (1): 3–32; Kermack, W. O., and A. G. McKendrick. 1927. “A Contribution to the Mathematical Theory of Epidemics.” Proceedings of the Royal Society 115 (772): 700–21)) to describe the evolution of the susceptible, infected and recovered compartment. Focused on the impact of public policies designed to contain this pandemic, we develop a new nonlinear SIR epidemic problem modeling the spreading of coronavirus under the effect of a social distancing induced by the government measures to stop coronavirus spreading. To find the parameters adopted for each country (for e.g. Germany, Spain, Italy, France, Algeria and Morocco) we fit the proposed model with respect to the actual real data. We also evaluate the government measures in each country with respect to the evolution of the pandemic. Our numerical simulations can be used to provide an effective tool for predicting the spread of the disease.

scholarly journals Gut-Ex-Vivo system as a model to study gluten response in celiac disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mara Gagliardi ◽  
Nausicaa Clemente ◽  
Romina Monzani ◽  
Luca Fusaro ◽  
Eleonora Ferrari ◽  
...  
Keyword(s):  
Celiac Disease ◽  
Intestinal Epithelium ◽  
Complex Disease ◽  
Ex Vivo ◽  
Dynamic Condition ◽  
Model Systems ◽  
In Vivo Models ◽  
Effective Manner ◽  
Junction Protein ◽  
The Impact

AbstractCeliac disease (CD) is a complex immune-mediated chronic disease characterized by a consistent inflammation of the gastrointestinal tract induced by gluten intake in genetically predisposed individuals. Although initiated by the interaction between digestion-derived gliadin, a gluten component, peptides, and the intestinal epithelium, the disorder is highly complex and involving other components of the intestine, such as the immune system. Therefore, conventional model systems, mainly based on two- or three-dimension cell cultures and co-cultures, cannot fully recapitulate such a complex disease. The development of mouse models has facilitated the study of different interacting cell types involved in the disorder, together with the impact of environmental factors. However, such in vivo models are often expensive and time consuming. Here we propose an organ ex vivo culture (gut-ex-vivo system) based on small intestines from gluten-sensitive mice cultivated in a dynamic condition, able to fully recapitulate the biochemical and morphological features of the mouse model exposed to gliadin (4 weeks), in 16 h. Indeed, upon gliadin exposure, we observed: i) a down-regulation of cystic fibrosis transmembrane regulator (CFTR) and an up-regulation of transglutaminase 2 (TG2) at both mRNA and protein levels; ii) increased intestinal permeability associated with deregulated tight junction protein expression; iii) induction and production of pro-inflammatory cytokines such as interleukin (IL)-15, IL-17 and interferon gamma (IFNγ); and iv) consistent alteration of intestinal epithelium/villi morphology. Altogether, these data indicate that the proposed model can be efficiently used to study the pathogenesis of CD, test new or repurposed molecules to accelerate the search for new treatments, and to study the impact of the microbiome and derived metabolites, in a time- and cost- effective manner.

scholarly journals A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wilfredo Angulo ◽  
José M. Ramírez ◽  
Dany De Cecchis ◽  
Juan Primera ◽  
Henry Pacheco ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Risk Perceptions ◽  
Transmission Rate ◽  
Early Stage ◽  
Individual Risk ◽  
Seir Model ◽  
Proposed Model ◽  
Probable Site ◽  
Adjusted Model ◽  
The Impact

AbstractCOVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.

scholarly journals Optimizing a Reverse Supply Chain Network for Electronic Waste under Risk and Uncertain Factors

2021 ◽  
Vol 11 (4) ◽  
pp. 1946
Author(s):  
Linh Thi Truc Doan ◽  
Yousef Amer ◽  
Sang-Heon Lee ◽  
Phan Nguyen Ky Phuc ◽  
Tham Thi Tran
Keyword(s):  
Supply Chain ◽  
Electronic Waste ◽  
Decision Makers ◽  
Reverse Supply Chain ◽  
Satisfactory Solution ◽  
Level Of Satisfaction ◽  
Proposed Model ◽  
Objective Value ◽  
The Right ◽  
The Impact

Minimizing the impact of electronic waste (e-waste) on the environment through designing an effective reverse supply chain (RSC) is attracting the attention of both industry and academia. To obtain this goal, this study strives to develop an e-waste RSC model where the input parameters are fuzzy and risk factors are considered. The problem is then solved through crisp transformation and decision-makers are given the right to choose solutions based on their satisfaction. The result shows that the proposed model provides a practical and satisfactory solution to compromise between the level of satisfaction of constraints and the objective value. This solution includes strategic and operational decisions such as the optimal locations of facilities (i.e., disassembly, repairing, recycling facilities) and the flow quantities in the RSC.

scholarly journals A Two-Population Mortality Model to Assess Longevity Basis Risk

Risks ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 44
Author(s):  
Selin Özen ◽  
Şule Şahin
Keyword(s):  
Risk Reduction ◽  
Significant Risk ◽  
Reference Population ◽  
Mortality Data ◽  
Basis Risk ◽  
Mortality Model ◽  
Proposed Model ◽  
Population Mortality ◽  
Mortality Jumps ◽  
The Impact

Index-based hedging solutions are used to transfer the longevity risk to the capital markets. However, mismatches between the liability of the hedger and the hedging instrument cause longevity basis risk. Therefore, an appropriate two-population model to measure and assess longevity basis risk is required. In this paper, we aim to construct a two-population mortality model to provide an effective hedge against the basis risk. The reference population is modelled by using the Lee–Carter model with the renewal process and exponential jumps, and the dynamics of the book population are specified. The analysis based on the U.K. mortality data indicate that the proposed model for the reference population and the common age effect model for the book population provide a better fit compared to the other models considered in the paper. Different two-population models are used to investigate the impact of sampling risk on the index-based hedge, as well as to analyse the risk reduction regarding hedge effectiveness. The results show that the proposed model provides a significant risk reduction when mortality jumps and sampling risk are taken into account.

scholarly journals Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

2020 ◽  
Vol 6 ◽  
pp. 205520762096835
Author(s):  
C Blease ◽  
C Locher ◽  
M Leon-Carlyle ◽  
M Doraiswamy
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Medical Profession ◽  
Descriptive Analysis ◽  
Psychiatric Practice ◽  
Limited Attention ◽  
Written Responses ◽  
Future Technology ◽  
Qualitative Descriptive ◽  
The Impact

Background The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics. Objective This study aimed to explore psychiatrists’ opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice Methods In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descriptive analysis of written responses (“comments”) to three open-ended questions in the survey. Results Comments were classified into four major categories in relation to the impact of future technology on: (1) patient-psychiatrist interactions; (2) the quality of patient medical care; (3) the profession of psychiatry; and (4) health systems. Overwhelmingly, psychiatrists were skeptical that technology could replace human empathy. Many predicted that ‘man and machine’ would increasingly collaborate in undertaking clinical decisions, with mixed opinions about the benefits and harms of such an arrangement. Participants were optimistic that technology might improve efficiencies and access to care, and reduce costs. Ethical and regulatory considerations received limited attention. Conclusions This study presents timely information on psychiatrists’ views about the scope of artificial intelligence and machine learning on psychiatric practice. Psychiatrists expressed divergent views about the value and impact of future technology with worrying omissions about practice guidelines, and ethical and regulatory issues.

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