Encapsulation of Vitamins Using Nanoliposome: Recent Advances and Perspectives.

Nowadays the importance of vitamins is clear for everyone. However, many patients are suffering from insufficient intake of vitamins. Incomplete intake of different vitamins from food sources due to their destruction during food processing or decrease in their bioavailability when mixing with other food materials, are factors resulting in vitamin deficiency in the body. Therefore, various lipid based nanocarriers such as nanoliposomes were developed to increase the bioavailability of bioactive compounds. Since the function of nanoliposomes containing vitamins on the body has a direct relationship with the quality of produced nanoliposomes, this review study was planned to investigate the several aspects of liposomal characteristics such as size, polydispersity index, zeta potential, and encapsulation efficiency on the quality of synthesized vitamin-loaded nanoliposomes.

Executive protocol designed for new review study called: systematic review and artificial intelligence network meta-analysis (RAIN) with the first application for COVID-19.

Artificial intelligence (AI) as a suite of technologies can complement systematic review and meta-analysis studies and answer questions that cannot be typically answered using traditional review protocols and reporting methods. The purpose of this protocol is to introduce a new protocol to complete systematic review and meta-analysis studies.In this work, systematic review, meta-analysis, and meta-analysis network based on selected AI technique, and for P < 0.05 are followed, with a view to responding to questions and challenges that the global population is facing in light of the COVID-19 pandemic.Finally, it is expected that conducting reviews by following the proposed protocol can provide suitable answers to some of the research questions raised due to COVID-19.

Global prevalence of chronic fatigue syndrome among long COVID-19 patients: A systematic review and meta-analysis.

BACKGROUND: Chronic fatigue syndrome is a persistent and debilitating disorder. According to several studies, chronic fatigue syndrome has been identified among recovered COVID-19 patients as the most common symptom of long COVID. The aim of this systematic review and meta-analysis study was to obtain the prevalence of chronic fatigue syndrome in long COVID cases. METHODS: In this systematic review and meta-analysis, we analysed reported results of studies that assessed the occurrence of chronic fatigue syndrome among COVID-19 patients four weeks after the onset of symptoms. The study selection was commenced by searching PubMed, Web of Science, Science Direct, Scopus, Embase, and Google scholar using the keywords of Chronic fatigue syndrome, COVID-19, and post-COVID-19 syndrome. The searches were without a lower time limit and until April 2022. Heterogeneity of studies was assessed using the I2 index, and a random effects model was used for analysis. Data analysis was performed within the Comprehensive Meta-Analysis software (version 2). RESULTS: The pooled prevalence of chronic fatigue syndrome four weeks after the onset of COVID-19 symptoms, in 52 studies with a sample size of 127,117, was 45.2% (95% CI: 34.1-56.9%). Meta-regression analysis in examining the effects of the two factors of sample size, and year of study on the changes in the overall prevalence, showed that with increasing sample size, and year of study, the prevalence of chronic fatigue syndrome among long COVID patients (p < 0.05). CONCLUSION: Our results show that the overall prevalence of chronic fatigue syndrome as a long COVID symptom is 45.2%. Chronic fatigue after infection with COVID-19 can negatively affect personal and social lives. Given such significant negative consequences caused by the syndrome, it is recommended that health policymakers allocate funds to reduce the adverse effects of this syndrome, by creating programs to support long COVID patients.

Identification of Suitable Drug Combinations for Treating COVID-19 Using a Novel Machine Learning Approach: The RAIN Method.

COVID-19 affects several human genes, each with its own p-value. The combination of drugs associated with these genes with small p-values may lead to an estimation of the combined p-value between COVID-19 and some drug combinations, thereby increasing the effectiveness of these combinations in defeating the disease. Based on human genes, we introduced a new machine learning method that offers an effective drug combination with low combined p-values between them and COVID-19. This study follows an improved approach to systematic reviews, called the Systematic Review and Artificial Intelligence Network Meta-Analysis (RAIN), registered within PROSPERO (CRD42021256797), in which, the PRISMA criterion is still considered. Drugs used in the treatment of COVID-19 were searched in the databases of ScienceDirect, Web of Science (WoS), ProQuest, Embase, Medline (PubMed), and Scopus. In addition, using artificial intelligence and the measurement of the p-value between human genes affected by COVID-19 and drugs that have been suggested by clinical experts, and reported within the identified research papers, suitable drug combinations are proposed for the treatment of COVID-19. During the systematic review process, 39 studies were selected. Our analysis shows that most of the reported drugs, such as azithromycin and hydroxyl-chloroquine on their own, do not have much of an effect on the recovery of COVID-19 patients. Based on the result of the new artificial intelligence, on the other hand, at a significance level of less than 0.05, the combination of the two drugs therapeutic corticosteroid + camostat with a significance level of 0.02, remdesivir + azithromycin with a significance level of 0.03, and interleukin 1 receptor antagonist protein + camostat with a significance level 0.02 are considered far more effective for the treatment of COVID-19 and are therefore recommended. Additionally, at a significance level of less than 0.01, the combination of interleukin 1 receptor antagonist protein + camostat + azithromycin + tocilizumab + oseltamivir with a significance level of 0.006, and the combination of interleukin 1 receptor antagonist protein + camostat + chloroquine + favipiravir + tocilizumab7 with corticosteroid + camostat + oseltamivir + remdesivir + tocilizumab at a significant level of 0.009 are effective in the treatment of patients with COVID-19 and are also recommended. The results of this study provide sets of effective drug combinations for the treatment of patients with COVID-19. In addition, the new artificial intelligence used in the RAIN method could provide a forward-looking approach to clinical trial studies, which could also be used effectively in the treatment of diseases such as cancer.

Global prevalence of polypharmacy among the COVID-19 patients: a comprehensive systematic review and meta-analysis of observational studies.

BACKGROUND: Polypharmacy has traditionally been defined in various texts as the use of 5 or more chronic drugs, the use of inappropriate drugs, or drugs that are not clinically authorized. The aim of this study was to evaluate the prevalence of polypharmacy among the COVID-19 patients, and the side effects, by systematic review and meta-analysis. METHODS: This study was performed by systematic review method and in accordance with PRISMA 2020 criteria. The protocol in this work is registered in PROSPERO (CRD42021281552). Particular databases and repositories have been searched to identify and select relevant studies. The quality of articles was assessed based on the Newcastle-Ottawa Scale checklist. Heterogeneity of the studies was measured using the I2 test. RESULTS: The results of meta-analysis showed that the prevalence of polypharmacy in 14 studies with a sample size of 189,870 patients with COVID-19 is 34.6% (95% CI: 29.6-40). Studies have shown that polypharmacy is associated with side effects, increased morbidity and mortality among patients with COVID-19. The results of meta-regression analysis reported that with increasing age of COVID-19 patients, the prevalence of polypharmacy increases (p < 0.05). DISCUSSION: The most important strength of this study is the updated search to June 2022 and the use of all databases to increase the accuracy and sensitivity of the study. The most important limitation of this study is the lack of proper definition of polypharmacy in some studies and not mentioning the number of drugs used for patients in these studies. CONCLUSION: Polypharmacy is seen in many patients with COVID-19. Since there is no definitive cure for COVID-19, the multiplicity of drugs used to treat this disease can affect the severity of the disease and its side effects as a result of drug interactions. This highlights the importance of controlling and managing prescription drugs for patients with COVID-19.

Virus load and incidence of olfactory, gustatory, respiratory, gastrointestinal disorders in COVID-19 patients: A retrospective cohort study.

OBJECTIVES: This study investigated the relationship between viral load and the incidence of olfactory and gustatory dysfunction (OD and GD), the incidence of respiratory and gastrointestinal symptoms and the recovery of OD and GD in COVID-19 patients. DESIGN: A retrospective cohort study. SETTING AND PARTICIPANTS: This study was conducted on 599 outpatients' cases in Golestan province between February and June 2020. MAIN OUTCOME MEASURES: The incidence, severity (complete or partial) and recovery time of OD and GD and their associations with cycle threshold (CT) values of SARS-CoV-2 polymerase chain reaction were assessed. RESULTS: The mean age of patients was 38.27 ± 13.62 years. The incidence of general symptoms included myalgia 70.1%, headache 51.8%, fever 47.7% and dyspnoea 21.4%. 41.9% of patients had gastrointestinal symptoms, including abdominal pain 26.5%, diarrhoea 25.2%, nausea 20.5% and vomiting 12.9%. 12.2% of patients had comorbidity. The trimester recovery rates of OD and GD were 93.94% and 94.74% respectively. The mean recovery time of OD and GD was 14.56 ± 13.37 and 13.8 ± 3.77 days respectively. The mean CT value in all patients was 27.45 ± 4.55. There were significant associations between the mean of CT value with headache (p = 0.04), GD (p = 0.002) and OD (p = 0.001). CONCLUSIONS: The finding of this study indicates a possible association between viral load with incidence of OD and GD in COVID-19 patient's cases and assures the recovery of OD/GD in these patients.

Contradictions in the promotion of publishing academic and scientific journal articles, and the inability to cope with the new coronavirus (COVID-19).

BACKGROUND: Translating research into practice is a central priority within the National Institutes of Health (NIH) Roadmap. The underlying aim of the NIH Roadmap is to accelerate the movement of scientific findings into practical health care provisions through translational research. MAIN TEXT: Despite the advances in health sciences, emerging infectious diseases have become more frequent in recent decades. Furthermore, emerging and reemerging pathogens have led to several global public health challenges. A question, and to an extent a concern, arises from this: Why our health care system is experiencing several challenges in encountering the coronavirus outbreak, despite the ever-growing advances in sciences, and the exponential rise in the number of published articles in the first quartile journals and even the ones among the top 1%? CONCLUSION: Two responses could be potentially provided to the above question: First, there seems to be a significant gap between our theoretical knowledge and practice. And second that many scholars and scientists publish papers only to have a longer list of publications, and therefore publishing is viewed as a personal objective, rather than for improving communities' public health.

The prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients: a systematic review and meta-regression.

BACKGROUND: Stress, anxiety, and depression are some of the most important research and practice challenges for psychologists, psychiatrists, and behavioral scientists. Due to the importance of issue and the lack of general statistics on these disorders among the Hospital staff treating the COVID-19 patients, this study aims to systematically review and determine the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. METHODS: In this research work, the systematic review, meta-analysis and meta-regression approaches are used to approximate the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. The keywords of prevalence, anxiety, stress, depression, psychopathy, mental illness, mental disorder, doctor, physician, nurse, hospital staff, 2019-nCoV, COVID-19, SARS-CoV-2 and Coronaviruses were used for searching the SID, MagIran, IranMedex, IranDoc, ScienceDirect, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases. The search process was conducted in December 2019 to June 2020. In order to amalgamate and analyze the reported results within the collected studies, the random effects model is used. The heterogeneity of the studies is assessed using the I2 index. Lastly, the data analysis is performed within the Comprehensive Meta-Analysis software. RESULTS: Of the 29 studies with a total sample size of 22,380, 21 papers have reported the prevalence of depression, 23 have reported the prevalence of anxiety, and 9 studies have reported the prevalence of stress. The prevalence of depression is 24.3% (18% CI 18.2-31.6%), the prevalence of anxiety is 25.8% (95% CI 20.5-31.9%), and the prevalence of stress is 45% (95% CI 24.3-67.5%) among the hospitals' Hospital staff caring for the COVID-19 patients. According to the results of meta-regression analysis, with increasing the sample size, the prevalence of depression and anxiety decreased, and this was statistically significant (P < 0.05), however, the prevalence of stress increased with increasing the sample size, yet this was not statistically significant (P = 0.829). CONCLUSION: The results of this study clearly demonstrate that the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients is high. Therefore, the health policy-makers should take measures to control and prevent mental disorders in the Hospital staff.

The prevalence of sleep disturbances among physicians and nurses facing the COVID-19 patients: a systematic review and meta-analysis.

BACKGROUND: In all epidemics, healthcare staff are at the centre of risks and damages caused by pathogens. Today, nurses and physicians are faced with unprecedented work pressures in the face of the COVID-19 pandemic, resulting in several psychological disorders such as stress, anxiety and sleep disturbances. The aim of this study is to investigate the prevalence of sleep disturbances in hospital nurses and physicians facing the COVID-19 patients. METHOD: A systematic review and metanalysis was conducted in accordance with the PRISMA criteria. The PubMed, Scopus, Science direct, Web of science, CINHAL, Medline, and Google Scholar databases were searched with no lower time-limt and until 24 June 2020. The heterogeneity of the studies was measured using I2 test and the publication bias was assessed by the Egger's test at the significance level of 0.05. RESULTS: The I2 test was used to evaluate the heterogeneity of the selected studies, based on the results of I2 test, the prevalence of sleep disturbances in nurses and physicians is I2: 97.4% and I2: 97.3% respectively. After following the systematic review processes, 7 cross-sectional studies were selected for meta-analysis. Six studies with the sample size of 3745 nurses were examined in and the prevalence of sleep disturbances was approximated to be 34.8% (95% CI: 24.8-46.4%). The prevalence of sleep disturbances in physicians was also measured in 5 studies with the sample size of 2123 physicians. According to the results, the prevalence of sleep disturbances in physicians caring for the COVID-19 patients was reported to be 41.6% (95% CI: 27.7-57%). CONCLUSION: Healthcare workers, as the front line of the fight against COVID-19, are more vulnerable to the harmful effects of this disease than other groups in society. Increasing workplace stress increases sleep disturbances in the medical staff, especially nurses and physicians. In other words, increased stress due to the exposure to COVID-19 increases the prevalence of sleep disturbances in nurses and physicians. Therefore, it is important for health policymakers to provide solutions and interventions to reduce the workplace stress and pressures on medical staff.

Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis.

BACKGROUND: The COVID-19 pandemic has had a significant impact on public mental health. Therefore, monitoring and oversight of the population mental health during crises such as a panedmic is an immediate priority. The aim of this study is to analyze the existing research works and findings in relation to the prevalence of stress, anxiety and depression in the general population during the COVID-19 pandemic. METHOD: In this systematic review and meta-analysis, articles that have focused on stress and anxiety prevalence among the general population during the COVID-19 pandemic were searched in the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases, without a lower time limit and until May 2020. In order to perform a meta-analysis of the collected studies, the random effects model was used, and the heterogeneity of studies was investigated using the I2 index. Moreover. data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software. RESULTS: The prevalence of stress in 5 studies with a total sample size of 9074 is obtained as 29.6% (95% confidence limit: 24.3-35.4), the prevalence of anxiety in 17 studies with a sample size of 63,439 as 31.9% (95% confidence interval: 27.5-36.7), and the prevalence of depression in 14 studies with a sample size of 44,531 people as 33.7% (95% confidence interval: 27.5-40.6). CONCLUSION: COVID-19 not only causes physical health concerns but also results in a number of psychological disorders. The spread of the new coronavirus can impact the mental health of people in different communities. Thus, it is essential to preserve the mental health of individuals and to develop psychological interventions that can improve the mental health of vulnerable groups during the COVID-19 pandemic.