The Probable Protective Effect of Photobiomodulation on the Immunologic Factor's mRNA Expression Level in the Lung: An Extended COVID-19 Preclinical and Clinical Meta-analysis

Background: Different expression of cytokine genes in the body determines the type of immune response (Th1 or Th2), which can play an important role in the pathogenesis of the COVID-19 disease. Aims: This meta-analysis was conducted to evaluate the probable effect of photobiomodulation (PBMT) therapy on the cytokine's mRNA expression in the lung. Methods: We systematically searched indexing databases, including PubMed/Medline, ISI web of science, Scopus, EMBASE, and Cochrane central, using standard terms without language, study region or type restrictions. Studies on using PBM in lung injury modeling with samples collected from lung tissue to observe IL-1β, TNF-α, IL-10, and IL-6 mRNA expression were included. RevMan 5.3 software was used for data analysis and standardized mean difference as effect size. Results: Of the 438 studies found through initial searches, 17 met the inclusion criteria. The main properties of 13 articles on 384 animals included in this meta-analysis with a wide range of species include rats (n = 10) and rabbits (n = 3). The analysis revealed that PBMT reduced the mRNA expression of TNFα (SMD: −3.70, 95% CI: −6.29, −1.11, P = .005,I2 = 71%) and IL-1β (SMD: −5.85, 95% CI: −8.01, −3.69, P < .00001,I2 = 37%) significantly, but no statistically significant reduction in IL-6 (SMD: −2.89, 95% CI: −5.79, 0.01, P = .05,I2 = 88%) was observed compared with the model controls. Also, PBMT increased IL-10 mRNA expression significantly compared with the model controls (SMD: 1.04, 95% CI: 0.43, 1.64, P = .0008,I2 = 17%). Conclusion: This meta-analysis revealed that the PBMT utilizes beneficial anti-inflammatory effects and modulation of the immune system on lung damage in animal models and clinical studies. However, animal models and clinical studies appear limited considering the evidence's quality;therefore, large clinical trials are still required.

Association of the corona virus (Covid-19) epidemic with environmental risk factors.

The current outbreak of the novel coronavirus SARS-CoV-2 (coronavirus disease 2019; previously 2019-nCoV), epicenter in Hubei Province (Wuhan), People's Republic of China, has spread too many other countries. The transmission of the corona virus occurs when people are in the incubation stage and do not have any symptoms. Therefore, the role of environmental factors such as temperature and wind speed becomes very important. The study of Acute Respiratory Syndrome (SARS) indicates that there is a significant relationship between temperature and virus transmission and three important factors, namely temperature, humidity and wind speed, cause SARS transmission. Daily data on the incidence and mortality of Covid-19 disease were collected from World Health Organization (WHO) website and World Meter website (WMW) for several major cities in Iran and the world. Data were collected from February 2020 to September 2021. Meteorological data including temperature, air pressure, wind speed, dew point and air quality index (AQI) index are extracted from the website of the World Meteorological Organization (WMO), The National Aeronautics and Space Administration (NASA) and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Statistical analysis carried out for significance relationships. The correlation coefficient between the number of infected people in one day and the environmental variables in the countries was different from each other. The relationship between AQI and number of infected was significant in all cities. In Canberra, Madrid and Paris, a significant inverse relationship was observed between the number of infected people in one day and wind speed. There is a significant positive relationship between the number of infected people in a day and the dew point in the cities of Canberra, Wellington and Washington. The relationship between the number of infected people in one day and Pressure was significantly reversed in Madrid and Washington, but positive in Canberra, Brasilia, Paris and Wuhan. There was significant relationship between Dew point and prevalence. Wind speed showed a significant relationship in USA, Madrid and Paris. AQI was strongly associated with the prevalence of covid19. The purpose of this study is to investigate some environmental factors in the transmission of the corona virus.

The association between different predictive biomarkers and mortality of COVID-19

BackgroundImmunocompromised individuals are expected to be more prone to severe diseases and, subsequently, death. Genetic disorders and polymorphisms in genes involved in the immune system, such as human leukocyte antigen (HLA), inflammatory cytokines, and killer-cell immunoglobulin-like receptors, can be involved in the immune system's response to various pathogens. In the current survey, the data were received from the world health organization, collected around the world.ResultsSpearman's coefficient correlation test for evaluating the relationship between the Daily Death Rates (DDR) and immunological variables showed a statistically significant correlation between the DDR and all immunological variables except TNFa857T, TNFa863A IL2330G, and IL2166T (P < 0.001). Also, there was a statistically significant correlation between the DDR and some HLA markers.ConclusionThis meta-analysis study shows that predictive biomarkers and mortality of COVID-19 are associated with HLA markers. However, these results should be confirmed in a more structured agreement. It is worth noting that the design of new studies should consider potential diseases with poor prognoses because they are related to these immune genetic markers.

Diagnostic utility of antigen detection rapid diagnostic tests for Covid-19: a systematic review and meta-analysis.

BACKGROUND: The early detection of coronavirus disease (COVID-19) infection to improve disease management becomes the greatest challenge. Despite the high sensitivity of RT-PCR, not only it was reported that 20-67% of infected patients had false-negative results. Rapid diagnostic tests (RDTs) are widely used as a point-of-care test for SARS-CoV-2 detection in pharyngeal and blood specimens. It's more appealing since it's less time-consuming, doesn't seem to be as expensive, and doesn't need any specific training, but the poor sensitivity is the major limitation. Several reports indicated the rapid test of blood and pharyngeal samples has the same sensitivity as the RT-PCR, but some reports have lower sensitivity, especially in asymptomatic patients. METHODS: In the present survey, we investigate the eligible studies for the sensitivity and specificity of rapid tests and explore the factors that influence the result to help better diagnose COVID-19 infection. 20 studies met the inclusion criteria which imposed 33 different tests. RESULTS: Our findings showed the type of sample, the type of assay, the time of sampling, and the load of virus influence on the sensitivity of RDTs. CONCLUSION: This research extends our knowledge of how to improve the sensitivity of RDTs to better diagnose the infected patients to address the controlling COVID-19 pandemic.

Global interest in vaccines during the COVID-19 pandemic: Evidence from Google Trends.

COVID-19 (coronavirus disease 2019) vaccines have become available; now, everyone has the opportunity to get vaccinated. We used Google Trends (GT) data to assess the global public interest in COVID-19 vaccines during the pandemic. For the analysis, a period of 17 months was chosen (from Jan 19, 2020, to Jul 04, 2021). Interest in user queries was tracked by keywords (corona vaccine, COVID-19 vaccine development, Sputnik v, Pfizer vaccine, AstraZeneca vaccine, etc.). The geographic analysis of queries was also carried out. The interest of users in the vaccine is significantly increasing. It is focused on the side effects of vaccines, and users pay attention to vaccines' developers from different countries. The correlation between the scientific publications devoted to vaccine development and such requests of users on the internet is absent. This study shows that internet search patterns can be used to gauge public attitudes towards coronavirus vaccination. Safety concerns consistently high follow an interest in vaccine side effects. This data can be used to track and predict attitudes towards vaccination of populations from COVID-19 in different countries before global vaccination becomes available to help mitigate the adverse effects of the pandemic.

The Probable Protective Effect of Photobiomodulation on the Inflammation of the Airway and Lung in COVID-19 Treatment: A Preclinical and Clinical Meta-Analysis.

Preliminary studies also show that many of the fatalities of COVID-19 are due to over-activity of the immune system, and photobiomodulation (PBM) therapy mainly accelerates wound healing and reduces pain and inflammation. Therefore, this systematic review and meta-analysis was conducted to evaluate the probable effect of the PBM therapy on the lung inflammation or ARDS and accelerate the regeneration of the damaged tissue. We systematically searched major indexing databases, including PubMed/Medline, ISI web of science (WOS), Scopus, Embase, and Cochrane central, using standard terms without any language, study region, or type restrictions. Of the 438 studies found through initial searches, 13 met the inclusion criteria. After applying the exclusion criteria, the main properties of 13 articles on 384 animals included in this meta-analysis with a wide range of species include rat (n = 10) and rabbit (n = 3). The analysis revealed that PBM therapy reduced TNFα (SMD:-3.75, 95% CI: -4.49, -3.02, P < 0.00001, I2 = 10%), IL-1ß (SMD:-4.65, 95% CI: -6.15, -3.16, P < 0.00001, I2 = 62%), and IL-6 (SMD:-4.20, 95% CI: -6.42, -1.97, P = 0.0002, I2 = 88%) significantly compared with the model controls. Hence, PBM therapy increased IL-10 significantly compared with the model controls (SMD:-4.65, 95% CI: -6.15, -3.16, P < 0.00001, I2 = 62%). PBM therapy also reduced MPO activity (SMD:-2.13, 95% CI: -3.38, -0.87, P = 0.0009, I2 = 64%) and vascular permeability (SMD:-2.59, 95% CI: -4.40, -0.77, P = 0.0052, I2 = 71%) in the lung using the Evans blue extravasation technique significantly compared with the model controls. This systematic review and meta-analysis revealed that the PBM therapy does utilize beneficial anti-inflammatory effect, modulation of the immune system, lung permeability, or bronchoalveolar lavage on lung damage in both animal models and clinical studies. However, animal model and clinical studies appear limited considering the quality of the included evidences; therefore, large clinical trials are still required.

Global Scientific Research on SARS-CoV-2 Vaccines: A Bibliometric Analysis.

OBJECTIVE: We performed this bibliometric analysis to identify global scientific research on the SARS-CoV-2 vaccines. MATERIALS AND METHODS: This bibliometric analysis study inclusive search of English-language publications related to the SARS-CoV-2 vaccines was conducted in the Scopus, PubMed, and Dimensions databases without year limitations. The results of bibliometric analysis comprised a time-dependent citation density trend, the name of the journal, journal impact factor (IF), year of publication, type of article, category, subscription or affiliation, co-authorship, and cooccurrence network. RESULTS: A study of the scientific literature from three databases (Scopus, PubMed, Dimensions) shows that investigators have focused more on studying the structure of the coronavirus at different levels (organismic, cellular, and molecular). In addition, the method of virus penetration into the cell and features of the influence of coronavirus on animals are well-studied. Various methods and strategies are being used to develop the vaccines, including both animal-tested methods and computer models. The Dimensions database is the most representative in terms of coverage of research on development of the SARS-CoV-2 vaccines. CONCLUSION: This research is a scientific investigation based on bibliometric analysis of papers related to the SARS-CoV-2 vaccines. The Dimensions database provides the most representative research coverage on the creation of a vaccine against coronavirus. It is characterized by a large number of formed verbose terms (length of more than four words) related to coronavirus, which makes it possible to track trends in the development of methods for creating a vaccine.

The association between various indicators of hospital capacity, age category, and the number of screening tests performed with case fatality rate and recovery rate during the COVID-19 disease pandemic.

BACKGROUND: The COVID-19-related deaths are growing rapidly around the world, especially in Europe and the United States. PURPOSE: In this study we attempt to measure the association of these variables with case fatality rate (CFR) and recovery rate (RR) using up-to-date data from around the world. METHODS: Data were collected from eight global databases. According to the raw data of countries, the CFR and RR and their relationship with different predictors was compared for countries with 1,000 or more cases of COVID-19 confirmed cases. RESULTS: There were no significant correlation between the CFR and number of hospital beds per 1,000 people, proportion of population aged 65 and older ages, and the number of computed tomography per one million inhabitants. Furthermore, based on the continents-based subgroup univariate regression analysis, the population (R2 = 0.37, P = 0.047), GPD (R2 = 0.80, P < 0.001), number of ICU Beds per 100,000 people (R2 = 0.93, P = 0.04), and number of CT per one million inhabitants (R2 = 0.78, P = 0.04) were significantly correlated with CFR in America. Moreover, the income-based subgroups analysis showed that the gross domestic product (R2 = 0.30, P = 0.001), number of ICU Beds per 100,000 people (R2 = 0.23, P = 0.008), and the number of ventilator (R2 = 0.46, P = 0.01) had significant correlation with CFR in high-income countries. CONCLUSIONS: The level of country's preparedness, testing capacity, and health care system capacities also are among the important predictors of both COVID-19 associated mortality and recovery. Thus, providing up-to-date information on the main predictors of COVID-19 associated mortality and recovery will hopefully improve various countries hospital resource allocation, testing capacities, and level of preparedness.

COVID-19 Pathology on Various Organs and Regenerative Medicine and Stem Cell-Based Interventions.

Severe acute respiratory syndrome-coronavirus 2, a novel betacoronavirus, has caused the global outbreak of a contagious infection named coronavirus disease-2019. Severely ill subjects have shown higher levels of pro-inflammatory cytokines. Cytokine storm is the term that can be used for a systemic inflammation leading to the production of inflammatory cytokines and activation of immune cells. In coronavirus disease-2019 infection, a cytokine storm contributes to the mortality rate of the disease and can lead to multiple-organ dysfunction syndrome through auto-destructive responses of systemic inflammation. Direct effects of the severe acute respiratory syndrome associated with infection as well as hyperinflammatory reactions are in association with disease complications. Besides acute respiratory distress syndrome, functional impairments of the cardiovascular system, central nervous system, kidneys, liver, and several others can be mentioned as the possible consequences. In addition to the current therapeutic approaches for coronavirus disease-2019, which are mostly supportive, stem cell-based therapies have shown the capacity for controlling the inflammation and attenuating the cytokine storm. Therefore, after a brief review of novel coronavirus characteristics, this review aims to explain the effects of coronavirus disease-2019 cytokine storm on different organs of the human body. The roles of stem cell-based therapies on attenuating cytokine release syndrome are also stated.

The diagnostic accuracy of Artificial Intelligence-Assisted CT imaging in COVID-19 disease: A systematic review and meta-analysis.

Artificial intelligence (AI) systems have become critical in support of decision-making. This systematic review summarizes all the data currently available on the AI-assisted CT-Scan prediction accuracy for COVID-19. The ISI Web of Science, Cochrane Library, PubMed, Scopus, CINAHL, Science Direct, PROSPERO, and EMBASE were systematically searched. We used the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool to assess all included studies' quality and potential bias. A hierarchical receiver-operating characteristic summary (HSROC) curve and a summary receiver operating characteristic (SROC) curve have been implemented. The area under the curve (AUC) was computed to determine the diagnostic accuracy. Finally, 36 studies (a total of 39,246 image data) were selected for inclusion into the final meta-analysis. The pooled sensitivity for AI was 0.90 (95% CI, 0.90-0.91), specificity was 0.91 (95% CI, 0.90-0.92) and the AUC was 0.96 (95% CI, 0.91-0.98). For deep learning (DL) method, the pooled sensitivity was 0.90 (95% CI, 0.90-0.91), specificity was 0.88 (95% CI, 0.87-0.88) and the AUC was 0.96 (95% CI, 0.93-0.97). In case of machine learning (ML), the pooled sensitivity was 0.90 (95% CI, 0.90-0.91), specificity was 0.95 (95% CI, 0.94-0.95) and the AUC was 0.97 (95% CI, 0.96-0.99). AI in COVID-19 patients is useful in identifying symptoms of lung involvement. More prospective real-time trials are required to confirm AI's role for high and quick COVID-19 diagnosis due to the possible selection bias and retrospective existence of currently available studies.

Estimating Case Fatality and Case Recovery Rates of COVID-19: is this the right thing to do?

Introduction: Case fatality rates (CFRs) and case recovery rates (CRRs) are frequently used to define health consequences related to specific disease epidemics, including the COVID-19 pandemic. This study aimed to compare various methods and models for calculating CFR and CRR related to COVID-19 based on the global and national data available as of April 2020. Methods: This analytical epidemiologic study was conducted based on detailed data from 210 countries and territories worldwide in April 2020. We used three different formulas to measure CFR and CRR, considering all possible scenarios. Results: We included information for 72 countries with more than 1,000 cases of COVID-19. Overall, using first, second, and third estimation models, the CFR were 6.22%, 21.20%, and 8.67%, respectively; similarly, the CRR was estimated as 23.21%, 78.86%, 32.23%, respectively. We have shown that CFRs vary so much spatially and depend on the estimation method and timing of case reports, likely resulting in overestimation. Conclusions: Even with the more precise method of CFRs estimation, the value is overestimated. Case fatality and recovery rates should not be the only measures used to evaluate disease severity, and the better assessment measures need to be developed as indicators of countries' performance during COVID-19 pandemic.

COVID-19 Patients: A Systematic Review and Meta-Analysis of Laboratory Findings, Comorbidities, and Clinical Outcomes Comparing Medical Staff versus the General Population.

This review compared coronavirus disease 2019 (COVID-19) laboratory findings, comorbidities, and clinical outcomes in patients from the general population versus medical staff to aid diagnosis of COVID-19 in a more timely, efficient, and accurate way. Electronic databases were searched up to 23rd March, 2020. The initial search yielded 6,527 studies. Following screening, 24 studies were included [18 studies (11,564 cases) of confirmed COVID-19 cases in the general public, and 6 studies (394 cases) in medical staff] in this review. Significant differences were observed in white blood cell counts (p < 0.001), lymphocyte counts (p < 0.001), platelet counts (p = 0.04), procalcitonin levels (p < 0.001), lactate dehydrogenase levels (p < 0.001), and creatinine levels (p = 0.03) when comparing infected medical staff with the general public. The mortality rate was higher in the general population than in medical staff (8% versus 2%). This review showed that during the early stages of COVID-19, laboratory findings alone may not be significant predictors of infection and may just accompany increasing C-reactive protein levels, erythrocyte sedimentation rates, and lactate dehydrogenase levels. In the symptomatic stage, the lymphocyte and platelet counts tended to decrease. Elevated D-dimer fibrin degradation product was associated with poor prognosis.

Environmental concern regarding the effect of humidity and temperature on 2019-nCoV survival: fact or fiction.

The new coronavirus, called 2019-nCoV, is a new type of virus that was first identified in Wuhan, China, in December 2019. Environmental conditions necessary for survival and spread of 2019-nCoV are somewhat transparent but unlike animal coronaviruses. We are poorly aware of their survival in environment and precise factors of their transmission. Countries located in east and west of globe did not have a significant impact on prevalence of disease among communities, and on the other hand, north and south have provided a model for relative prediction of disease outbreaks. The 2019-nCoV can survive for up to 9 days at 25 °C, and if this temperature rises to 30 °C, its lifespan will be shorter. The 2019-nCoV is sensitive to humidity, and lifespan of viruses in 50% humidity is longer than that of 30%. Also, temperature and humidity are important factors influencing the COVID-19 mortality rate and may facilitate 2019-nCoV transmission. Thus, considering the available and recent evidence, it seems that low temperatures, as well as dry and unventilated air, may affect stability and transmissibility of 2019-nCoV.

Cross-Country Comparison of Case Fatality Rates of COVID-19/SARS-COV-2.

OBJECTIVES: Case fatality rates (CFR) and recovery rates are important readouts during epidemics and pandemics. In this article, an international analysis was performed on the ongoing coronavirus disease 2019 (COVID-19) pandemic. METHODS: Data were retrieved from accurate databases according to the user's guide of data sources for patient registries, CFR and recovery rates were calculated for each country. A comparison of CFR between countries with total cases ≥ 1,000 was observed for 12th and 23rd March. RESULTS: Italy's CFR was the highest of all countries studied for both time points (12th March, 6.22% versus 23rd March, 9.26%). The data showed that even though Italy was the only European country reported on 12rd March, Spain and France had the highest CFR of 6.16 and 4.21%, respectively, on 23rd March, which was strikingly higher than the overall CFR of 3.61%. CONCLUSION: Obtaining detailed and accurate medical history from COVID-19 patients, and analyzing CFR alongside the recovery rate, may enable the identification of the highest risk areas so that efficient medical care may be provided. This may lead to the development of point-of-care tools to help clinicians in stratifying patients based on possible requirements in the level of care, to increase the probabilities of survival from COVID-19 disease.