Medicine and Health Sciences Commons^™

Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, Ramakanth Kavuluru

Institute for Biomedical Informatics Faculty Publications

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

METHODS: The Human Phenotype Ontology …

Evaluation Of The United States Covid-19 Vaccine Allocation Strategy, Md Rafiul Islam, Tamer Oraby, Audrey Mccombs, Mohammad Mihrab Chowdhury, Mohammad Al-Mamun, Michael G. Tyshenko, Claus Kadelkai

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background: Anticipating an initial shortage of vaccines for COVID-19, the Centers for Disease Control (CDC) in the United States developed priority vaccine allocations for specific demographic groups in the population. This study evaluates the performance of the CDC vaccine allocation strategy with respect to multiple potentially competing vaccination goals (minimizing mortality, cases, infections, and years of life lost (YLL)), under the same framework as the CDC allocation: four priority vaccination groups and population demographics stratified by age, comorbidities, occupation and living condition (congested or non-congested).

Methods and findings: We developed a compartmental disease model that incorporates key elements of the …

Bisindolylmaleimide Ix: A Novel Anti-Sars-Cov2 Agent Targeting Viral Main Protease 3clpro Demonstrated By Virtual Screening Pipeline And In-Vitro Validation Assays, Yash Gupta, Dawid Maciorowski, Samantha E. Zak, Krysten A. Jones, Rahul S. Kathayat, Saara-Anne Azizi, Raman Mathur, Catherine M. Pearce, David J. Ilc, Hamza Husein, Andrew S. Herbert, Ajay Bharti, Brijesh Rathi, Ravi Durvasula, Daniel P. Becker, Bryan C. Dickinson, John M. Dye, Prakasha Kempaiah

Chemistry: Faculty Publications and Other Works

SARS-CoV-2, the virus that causes COVID-19 consists of several enzymes with essential functions within its proteome. Here, we focused on repurposing approved and investigational drugs/compounds. We targeted seven proteins with enzymatic activities known to be essential at different stages of the viral cycle including PLpro, 3CLpro, RdRP, Helicase, ExoN, NendoU, and 2′-O-MT. For virtual screening, energy minimization of a crystal structure of the modeled protein was carried out using the Protein Preparation Wizard (Schrodinger LLC 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs and investigational molecules (n = …

Understanding Covid-19 Dynamics And The Effects Of Interventions In The Philippines: A Mathematical Modelling Study, Jamie M. Caldwell, Elvira P. De Lara-Tuprio, Timothy Robin Y. Teng, Ma. Regina Justina E. Estuar, Raymond Francis R. Sarmiento, Milinda Abayawardana B. Eng, Robert Neil F. Leong, Richard T. Gray, James G. Wood, Linh-Vi Le, Emma S. Mcbryde, Romain Ragonnet, James M. Trauer

Mathematics Faculty Publications

Background

COVID-19 initially caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with many high-income countries; possibly because of differing demographics; socioeconomics; surveillance; and policy responses. Here; we investigate the role of multiple factors on COVID-19 dynamics in the Philippines; a LMIC that has had a relatively severe COVID-19 outbreak.

Methods

We applied an age-structured compartmental model that incorporated time-varying mobility; testing; and personal protective behaviors (through a “Minimum Health Standards” policy; MHS) to represent the first wave of the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon; Central Visayas; and the National Capital …

Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly

Publications and Research

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 …

Covid-19 And The Impact On Rural And Black Church Congregants: Results Of The C-M-C Project, Lovoria B. Williams, Anita F. Fernander, Tofial Azam, Maria L. Gomez, Junghee Kang, Cassidy L. Moody, Hannah Bowman, Nancy E. Schoenberg

Nursing Faculty Publications

The COVID-19 pandemic has had devastating effects on Black and rural populations with a mortality rate among Blacks three times that of Whites and both rural and Black populations experiencing limited access to COVID-19 resources. The primary purpose of this study was to explore the health, financial, and psychological impact of COVID-19 among rural White Appalachian and Black nonrural central Kentucky church congregants. Secondarily we sought to examine the association between sociodemographics and behaviors, attitudes, and beliefs regarding COVID-19 and intent to vaccinate. We used a cross sectional survey design developed with the constructs of the Health Belief and Theory …

Covid-19 Impact On Radiology Students’ Distance Learning (Summer 2021), Mary Lee, Jason Chan, Cheryann Jackson-Holmes, Renzo Marmolejo, Zoya Vinokur

Publications and Research

The Radiological Technology students have adjusted from the urgent distance learning that was enacted in the Spring of 2020, to the hybrid distance learning that is currently in place. This hybrid distance learning is the same way the incoming class of radiological technology students were taught. Both cohorts of students were tracked over the year by online anonymous surveys. We wanted to know how students were adapting to distance learning, if their focus and motivation varied over the course of the year due to changing pandemic conditions. For the students that were working, what impact did it have on their …

Tocilizumab And Covid-19: A Meta-Analysis Of 2120 Patients With Severe Disease And Implications For Clinical Trial Methodologies, Azza Sarfraz, Zouina Sarfraz, Muzna Sarfraz, Hinna Aftab, Zainab Pervaiz

Department of Paediatrics and Child Health

Background/aim: Since the outbreak of the COVID-19, numerous therapies to counteract this severe disease have emerged. The benefits of Tocilizumab for severely infected COVID-19 patients and the methodologies of ongoing clinical trials are explored.
Materials and methods: A systematic search adhering to PRISMA guidelines was conducted in PubMed, Cochrane Central, medRxiv, and bioRxiv using the following keywords: “Tocilizumab,” “Actemra,” “COVID-19.” An additional subsearch was conducted on Clinicaltrials.gov to locate ongoing tocilizumab trials.
Results: A total of 13 studies were included in the meta-analysis comprising 2120 patients. The treatment group had lower mortality compared to the control group (OR = 0.42, …

Adapting An Agent-Based Model Of Infectious Disease Spread In An Irish County To Covid-19, Elizabeth Hunter, John D. Kelleher

Articles

The dynamics that lead to the spread of an infectious disease through a population can be characterized as a complex system. One way to model such a system, in order to improve preparedness, and learn more about how an infectious disease, such as COVID-19, might spread through a population, is agent-based epidemiological modelling. When a pandemic is caused by an emerging disease, it takes time to develop a completely new model that captures the complexity of the system. In this paper, we discuss adapting an existing agent-based model for the spread of measles in Ireland to simulate the spread of …

A Comparison Of Prospective Space-Time Scan Statistics And Spatiotemporal Event Sequence Based Clustering For Covid-19 Surveillance, Fuyu Xu, Kate Beard

Teaching, Learning & Research Documents

The outbreak of the COVID-19 disease was first reported in Wuhan, China, in December 2019. Cases in the United States began appearing in late January. On March 11, the World Health Organization (WHO) declared a pandemic. By mid-March COVID-19 cases were spreading across the US with several hotspots appearing by April. Health officials point to the importance of surveillance of COVID-19 to better inform decision makers at various levels and efficiently manage distribution of human and technical resources to areas of need. The prospective space-time scan statistic has been used to help identify emerging COVID-19 disease clusters, but results from …

Covid-19_Umaine News_Wvii Talks With Lieberthal About Disease Superspreader Prediction, University Of Maine Division Of Marketing And Communications

Division of Marketing & Communications

Screenshot of UMaine in the News regarding WVII (Channel 7) speaking with Brandon Lieberthal, a University of Maine research associate in the School of Biology and Ecology, about the development of a mathematical model that can be used to identify potential superspreader locations and to predict the efficacy of mitigation strategies.

Knowledge And Anxiety About Covid-19 In The State Of Qatar, And The Middle East And North Africa Region—A Cross Sectional Study, Sathyanarayanan Doraiswamy, Sohaila Cheema, Maisonneuve Patrick, Amit Abraham, Ingmar Weber, Jisun An, Albert B. Lowenfels, Ravinder Mamtani

Research Collection School Of Computing and Information Systems

While the coronavirus disease 2019 (COVID-19) pandemic wreaked havoc across the globe, we have witnessed substantial mis- and disinformation regarding various aspects of the disease. We conducted a cross-sectional study using a self-administered questionnaire for the general public (recruited via social media) and healthcare workers (recruited via email) from the State of Qatar, and the Middle East and North Africa region to understand the knowledge of and anxiety levels around COVID-19 (April–June 2020) during the early stage of the pandemic. The final dataset used for the analysis comprised of 1658 questionnaires (53.0% of 3129 received questionnaires; 1337 [80.6%] from the …

Spatially Refined Time-Varying Reproduction Numbers Of Covid-19 By Health District In Georgia, Usa, March–December 2020, Chigozie A. Ogwara, Arshpreet Kaur Mallhi, Xinyi Hua, Kamalich Muniz-Rodriguez, Jessica S. Schwind, Xiaolu Zhou, Jeffery A. Jones, Joanne Chopak-Foss, Gerardo Chowell, Isaac Chun-Hai Fung

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, Rt of SARS-CoV-2 in Georgia and its 18 public health districts, we apply the R package ‘EpiEstim’ to the time series of historical daily incidence of confirmed cases, 2 March–15 December 2020. The epidemic curve is shifted backward by nine days to account for the incubation period and delay to testing. Linear regression is performed between log10-transformed per capita cumulative case count and log10-transformed population size. We observe …

Social Distancing And Testing As Optimal Strategies Against The Spread Of Covid-19 In The Rio Grande Valley Of Texas, Kristina P. Vatcheva, Josef A. Sifuentes, Tamer Oraby, Jose Campo Maldonado, Timothy Huber, Cristina Villalobos

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

At the beginning of August 2020, the Rio Grande Valley (RGV) of Texas experienced a rapid increase of coronavirus disease 2019 (abbreviated as COVID-19) cases and deaths. This study aims to determine the optimal levels of effective social distancing and testing to slow the virus spread at the outset of the pandemic. We use an age-stratified eight compartment epidemiological model to depict COVID-19 transmission in the community and within households. With a simulated 120-day outbreak period data we obtain a post 180-days period optimal control strategy solution. Our results show that easing social distancing between adults by the end of …

Covid-19_Umaine News_Education Week Talks With Ferrini-Mundy About Stem Teaching During The Pandemic, University Of Maine Division Of Marketing And Communications

Division of Marketing & Communications

Screenshot of UMaine in the News regarding Education Week report on a symposium at the American Educational Research Association's virtual annual meeting featuring Joan Ferrini-Mundy, University of Maine System vice chancellor for research and innovation and president of the University of Maine.

Covid-19 And Preparing Planetary Health For Future Ecological Crises: Hopes From Glycomics For Vaccine Innovation, Xueqing Wang, Zhaohua Zhong, Wei Wang

Research outputs 2014 to 2021

A key lesson emerging from COVID-19 is that pandemic proofing planetary health against future ecological crises calls for systems science and preventive medicine innovations. With greater proximity of the human and animal natural habitats in the 21st century, it is also noteworthy that zoonotic infections such as COVID-19 that jump from animals to humans are increasingly plausible in the coming decades. In this context, glycomics technologies and the third alphabet of life, the sugar code, offer veritable prospects to move omics systems science from discovery to diverse applications of relevance to global public health and preventive medicine. In this expert …

Digital Sustainability And Its Implications For Finance And Climate Change, Gerard George, Simon J.D. Schillebeeckx

Research Collection Lee Kong Chian School Of Business

As the pandemic forced the entire world to a virtual standstill, nature revived a little. The US emitted 10.3% less CO2 in 2020 than in 2019 and other regions similarly experienced emission declines. Depending on the source, global carbon emissions were down between 4 and 8% in 2020.2 Consumers globally have expressed more concern about sustainability, an observation confirmed by large survey research by Accenture, Kantar, Boston Consulting Group (BCG), and Ipsos.3 In its latest Emissions Gap Report4 , the UN Environment Programme (UNEP) explicitly connected the pandemic to climate change, nature loss, and pollution. Besides the acceleration of business …

A University Forest Fire: Examining The Spread Of The Coronavirus Through College Social Networks Using A Modified Forest Fire Probabilistic Model, Raechel Griffin

Senior Honors Projects

No abstract provided.

Sars-Cov-2 Transmission In Alberta, British Columbia, And Ontario, Canada, December 25, 2019, To December 1, 2020, Isaac Chun-Hai Fung, Yuen Wai Hung, Sylvia Ofori, Kamalich Muniz-Rodriguez, Po-Ying Lai, Gerardo Chowell

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Objective:

This study aimed to investigate coronavirus disease (COVID-19) epidemiology in Alberta, British Columbia, and Ontario, Canada.

Methods:

Using data through December 1, 2020, we estimated time-varying reproduction number, R t , using EpiEstim package in R, and calculated incidence rate ratios (IRR) across the 3 provinces.

Results:

In Ontario, 76% (92 745/121 745) of cases were in Toronto, Peel, York, Ottawa, and Durham; in Alberta, 82% (49 878/61 169) in Calgary and Edmonton; in British Columbia, 90% (31 142/34 699) in Fraser and Vancouver Coastal. Across 3 provinces, R t dropped to ≤ 1 after April. …

Lag Effects Of Ozone, Pm2.5, And Meteorological Factors On Covid-19 New Cases At The Disease Epicenter In Queens, New York, Atin Adhikari, Jingjing Yin

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

The influences of environmental factors on COVID-19 may not be immediate and could be lagged for days to weeks. This study investigated the choice of lag days for calculating cumulative lag effects of ozone, PM2.5, and five meteorological factors (wind speed, temperature, relative humidity, absolute humidity, and cloud percentages) on COVID-19 new cases at the epicenter of Queens County, New York, before the governor’s executive order on wearing of masks in public places (1 March to 11 April 2020). Daily data for selected air pollutants and meteorological factors were collected from the US EPA Air Quality System, weather observation station …

Predictive Modeling And Estimation Of The Doubling Time Of Confirmed Cases Of Covid-19 In Niger, Ibrahim Sidi Zakari, Hadiza Galadima

Community & Environmental Health Faculty Publications

Modeling is increasingly used to assess scenarios and make projections on the future course of new coronavirus disease. This allows for better planning of care as well as a relaxation or tightening of the restrictive measures decreed by the government and the health authorities. The data analyzed in this study covers the period from March 19 to June 05, 2020 and allowed predictions of new cases of COVID-19 based on a growth model with a growth rate that changes linearly over time. In addition, we calculated and predicted the doubling time of the number of positive cases in each region …

Modeling The Effect Of Lockdown Timing As A Covid‑19 Control Measure In Countries With Differing Social Contacts, Tamer Oraby, Michael G. Tyshenko, Jose Campo Maldonado, Kristina Vatcheva, Susie Elsaadany, Walid Q. Alali, Joseph C. Longenecker, Mustafa Al‑Zoughool

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed a stochastic continuous-time Markov chain (CTMC) model with eight states including the environment (SEAMHQRD-V), and derived a formula for the basic reproduction number, R0, for that model. Applying the R 0 formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible R 0 for the 152 countries and chose one …

Covid-19 Pandemic In Brazil: Clinical Manifestation And Effect Of Comorbidities On Outcomes Of Hospitalized Sari Cases, Mario Keko, Karl E. Peace

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Hospitalized SARI cases of 2020 reported to the Ministry of Health of Brazil through the SIVEP Gripe system are subject to our analysis. They are classified as COVID-19 and non-COVID-19 and clinical manifestations and comorbidities are reported for each group. The time trend in the number of cases reported in 2020 is compared to the previous year and the performance of the PCR test is explored in each group. The proportion of death is reported among different subgroups of the patients by epidemiological week. Logistic and Poisson regression models are used to check the effect of comorbidities on clinical outcomes.

Modes Of Transmission Of Severe Acute Respiratory Syndrome-Coronavirus-2 (Sars-Cov-2) And Factors Influencing On The Airborne Transmission: A Review, Mahdieh Delikhoon, Marcelo I. Guzman, Ramin Nabizadeh, Abbas Norouzian Baghani

Chemistry Faculty Publications

The multiple modes of SARS-CoV-2 transmission including airborne, droplet, contact, and fecal–oral transmissions that cause coronavirus disease 2019 (COVID-19) contribute to a public threat to the lives of people worldwide. Herein, different databases are reviewed to evaluate modes of transmission of SARS-CoV-2 and study the effects of negative pressure ventilation, air conditioning system, and related protection approaches of this virus. Droplet transmission was commonly reported to occur in particles with diameter >5 µm that can quickly settle gravitationally on surfaces (1–2 m). Instead, fine and ultrafine particles (airborne transmission) can stay suspended for an extended period of time (≥2 h) …

Gut Microbiota Interplay With Covid-19 Reveals Links To Host Lipid Metabolism Among Middle Eastern Populations, Mohammad Tahseen Al Bataineh, Andreas Henschel, Mira Mousa, Marianne Daou, Fathimathuz Waasia, Hussein Kannout, Mariam Khalili, Mohd Azzam Kayasseh, Abdulmajeed Alkhajeh, Maimunah Uddin, Nawal Alkaabi, Guan K. Tay, Samuel F. Feng, Ahmed F. Yousef, Habiba S. Alsafar, Uae Covid-19 Collaborative Partnership

Research outputs 2014 to 2021

The interplay between the compositional changes in the gastrointestinal microbiome, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) susceptibility and severity, and host functions is complex and yet to be fully understood. This study performed 16S rRNA gene-based microbial profiling of 143 subjects. We observed structural and compositional alterations in the gut microbiota of the SARS-CoV-2-infected group in comparison to non-infected controls. The gut microbiota composition of the SARS-CoV-2-infected individuals showed an increase in anti-inflammatory bacteria such as Faecalibacterium (p-value = 1.72 × 10–6) and Bacteroides (p-value = 5.67 × 10–8). We also revealed a higher relative abundance of the highly …

Active Learning Strategy For Covid-19 Annotated Dataset, Amril Nazir, Ricky Maulana Fajri

All Works

The efficient diagnosis of COVID-19 plays a key role in preventing its spread. Recently, many artificial intelligence techniques, such as the deep neural network approach, have been implemented to help efficient diagnosis of COVID-19. However, the accurate performance of deep learning depends on the tuning of many hyperparameters and a large amount of labeled data. This COVID-19 data bottleneck also leads to insufficient human resources for data labeling, which presents a challenging obstacle. In this paper, a novel discriminative batch-mode active learning (DS3) is proposed to allow faster and more effective COVID-19 data annotation. The framework specifically designed to suit …

Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic triggered a large-scale work-from-home trend globally in recent months. In this paper, we study the phenomenon of “work-from-home” (WFH) by performing social listening. We propose an analytics pipeline designed to crawl social media data and perform text mining analyzes on textual data from tweets scrapped based on hashtags related to WFH in COVID-19 situation. We apply text mining and NLP techniques to analyze the tweets for extracting the WFH themes and sentiments (positive and negative). Our Twitter theme analysis adds further value by summarizing the common key topics, allowing employers to gain more insights on areas of …

Impact Of Covid-19 On The Us And Texas Economy: A General Equilibrium Approach, Lirong Liu, Steven S. Shwiff, Stephanie A. Shwiff, Maryfrances Miller

USDA Wildlife Services: Staff Publications

This paper examines the impact of COVID-19 on the US and Texas economy using a computable general equilibrium model, REMI PI+. We consider three scenarios based on economic forecasts from various sources, including the University of Michigan’s RSQE (Research Seminar in Quantitative Economics), IMF, and the Wi orld Bank. We report a GDP loss of $106 million (a 6% decline) with 1.2 million jobs lost (6.6%) in Texas in 2020. At the national level, GDP loss is $996 billion (a 5% decline) with 11.5 million jobs lost (5.5%) in the same year. By 2026, the aggregate total GDP loss in …

"Who Can Help Me?'': Knowledge Infused Matching Of Support Seekers And Support Providers During Covid-19 On Reddit, Manas Gaur, Kaushik Roy, Aditya Sharma, Biplav Srivastava, Amit Sheth

Publications

During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with varying professions and experiences with diverse perspectives on care (support providers - SPs). Currently, knowledgeable human moderators match an SS with a user with relevant experience, i.e, an SP on these subreddits. This unscalable process defers timely care. We present a medical knowledge-infused approach to efficient matching of SS and SPs validated by experts for the users affected by anxiety and depression, in the context of with COVID-19. After matching, each SP to …

Nutritional Approach For Increasing Public Health During Pandemic Of Covid-19: A Comprehensive Review Of Antiviral Nutrients And Nutraceuticals, Vahideh Ebrahimzadeh-Attari, Ghodratollah Panahi, James R. Hébert Scd, Alireza Ostadrahimi, Maryam Saghafi-Asl, Neda Lotfi-Yaghin, Behzad Baradaran

Faculty Publications

Background: The novel coronavirus (COVID-19) is considered as the most life-threatening pandemic disease during the last decade. The individual nutritional status, though usually ignored in the management of COVID-19, plays a critical role in the immune function and pathogenesis of infection. Accordingly, the present review article aimed to report the effects of nutrients and nutraceuticals on respiratory viral infections including COVID-19, with a focus on their mechanisms of action.

Methods: Studies were identified via systematic searches of the databases including PubMed/ MEDLINE, ScienceDirect, Scopus, and Google Scholar from 2000 until April 2020, using keywords. All relevant clinical and experimental studies …