Responses to COVID-19, small and medium enterprises' corporate social responsibility and psychological capital of employees: From the mediating perspective of affective commitment.

The influence of corporate social responsibility (CSR) on employees' positive psychological capital in stressful situations remains unexplored in the literature for small and medium enterprises (SMEs). This study aims to examine how CSR could assist employees in developing psychological capital during the COVID-19 pandemic. In order to understand the aforesaid relationship, an attempt is made to study the mediation effect of affective commitment. Structural equation modelling (AMOS 21.0) was used for data analysis and hypothesis testing on a sample of 545 employees from 356 Malaysian SMEs. The results of this study showed that SMEs' CSR policies helped to improve the positive psychological capital of their employees during the COVID-19 pandemic. Also, affective commitment complementary mediates the relationship between CSR and psychological capital. During the COVID-19 pandemic, SMEs should come up with a consistent way to implement CSR policies and procedures to improve employees' psychological capital and increase their affective commitment toward the enterprise. There are two main contributions to the literature from this study, in addition to enriching previous empirical research on CSR. As a first contribution to the CSR literature, it examines how CSR impacts employees' psychological capital during a pandemic. COVID-19 is one of the recent pandemics that offers an opportunity to examine its effects on employee psychological state. Secondly, the results of the study add to the growing body of empirical research that supports affective commitment's significant relationship with CSR and enhances employees' psychological capital during a pandemic in a developing market.

Impact of Coronavirus Disease (COVID-19) Pandemic on Psychological Well-Being of the Pakistani General Population.

Background and Objectives: In order to curb the spread of coronavirus disease 2019 (COVID-19), the countries took preventive measures such as lockdown and restrictions of movements. This can lead to effects on mental health of the population. We studied the impact of COVID-19 on psychological well-being and associated factors among the Pakistani general population. Methods: An online cross-sectional survey was conducted between 26th April and 15th May and included participants from all over the Pakistan. Attitudes and worriedness about COVID-19 pandemic were assessed using a structured questionnaire. A validated English and Urdu version of the World Health Organization Well-Being Index (WHO-5) was used to assess the well-being. Factor analysis was done to extract the attitude item domains. Logistic regression was used to assess the factors associated with poor well-being. Results: A total of 1,756 people participated in the survey. Almost half 50% of the participants were male, and a similar proportion was employed. About 41% of the participants were dependent on financial sources other than salary. News was considered a source of fear as 72% assumed that avoiding such news may reduce the fear. About 68% of the population was worried about contracting the disease. The most common coping strategies used during lockdown were spending quality time with family, eating healthy food, adequate sleep, and talking to friends on phone. Prevalence of poor well-being was found to be 41.2%. Female gender, being unemployed, living in Sindh and Islamabad Capital Territory (ICT), fear of COVID-19, and having chronic illness were significantly associated with poor well-being. Similarly, coping strategies during lockdown (doing exercise; spending time with family; eating healthy food; having good sleep; contributing in social welfare work and spending time on hobbies) were also significantly associated with mental well-being. Conclusion: We found a high prevalence 41.2% of poor well-being among the Pakistani general population. We also investigated risk factors of poor well-being which included female gender, unemployment, being resident of ICT and Sindh, fear, chronic illness, and absence of coping strategies. This calls for immediate action at population level in the form of targeted mass psychological support programs to improve the mental health of population during the COVID-19 crises.

Potential medicinal plants involved in inhibiting 3CLpro activity: A practical alternate approach to combating COVID-19.

At present, a variety of vaccines have been approved, and existing antiviral drugs are being tested to find an effective treatment for coronavirus disease 2019 (COVID-19). However, no standardized treatment has yet been approved by the World Health Organization. The virally encoded chymotrypsin-like protease (3CLpro) from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which facilitates the replication of SARS-CoV in the host cells, is one potential pharmacological target for the development of anti-SARS drugs. Online search engines, such as Web of Science, Google Scholar, Scopus and PubMed, were used to retrieve data on the traditional uses of medicinal plants and their inhibitory effects against the SARS-CoV 3CLpro. Various pure compounds, including polyphenols, terpenoids, chalcones, alkaloids, biflavonoids, flavanones, anthraquinones and glycosides, have shown potent inhibition of SARS-CoV-2 3CLpro activity with 50% inhibitory concentration (IC50) values ranging from 2-44 µg/mL. Interestingly, most of these active compounds, including xanthoangelol E (isolated from Angelica keiskei), dieckol 1 (isolated from Ecklonia cava), amentoflavone (isolated from Torreya nucifera), celastrol, pristimerin, tingenone and iguesterin (isolated from Tripterygium regelii), tannic acid (isolated from Camellia sinensis), and theaflavin-3,3'-digallate, 3-isotheaflav1in-3 gallate and dihydrotanshinone I (isolated from Salvia miltiorrhiza), had IC50 values of less than 15 µg/mL. Kinetic mechanistic studies of several active compounds revealed that their mode of inhibition was dose-dependent and competitive, with Ki values ranging from 2.4-43.8 µmol/L. Given the significance of plant-based compounds and the many promising results obtained, there is still need to explore the phytochemical and mechanistic potentials of plants and their products. These medicinal plants could serve as an effective inexpensive nutraceutical for the general public to help manage COVID-19.

Assessment of COVID-19 vaccine booster dose acceptance, reluctance and concerns among elderly diabetes patients in Pakistan.

People around the globe rumored so many things about the safety and efficacy of initial two doses and booster dose of Covid-19 vaccine, which eventually affected the acceptance of the only tool available against the fight between humans and virus. The aim of current study is to evaluate the acceptance and reluctance level among the population specifically elderly diabetes patients. The cross-sectional study was conducted during a time period of 3 months i.e. from July 2021 until September 2021. A 16-item questionnaire was used to assess the acceptance, reluctance and concerns of the Covid-19 vaccine booster dose among elderly diabetes patients. A 16-item questionnaire was used to assess the acceptance, reluctance and concerns of the Covid-19 vaccine booster dose among elderly diabetes patients. A total of 497 responses were collected and analyzed. Approximately 32% of respondents believed that they need additional information about the Covid-19 vaccine booster dose will be ineffective due to not enough information about the potential side effects of the vaccine dose, while around 80% of respondents showed concerns about safety, efficacy, newness and not enough information about vaccine contents. Around 47.1% of respondents expressed robust concerns about possible side effects of the Covid-19 vaccine booster dose.

Investigating underlying human immunity genes, implicated diseases and their relationship to COVID-19.

Aim: A human immunogenetics variation study was conducted in samples collected from diverse COVID-19 populations. Materials & methods: Whole-genome and whole-exome sequencing (WGS/WES), data processing, analysis and visualization pipeline were applied to identify variants associated with genes of interest. Results: A total of 2886 mutations were found across the entire set of 13 genomes. Functional annotation of the gene variants revealed mutation type and protein change. Many variants were found to be biologically implicated in COVID-19. The involvement of these genes was also found in multiple other diseases. Conclusion: The analysis determined that ACE2, TMPRSS4, TMPRSS2, SLC6A20 and FYCOI had functional implications and TMPRSS4 was the gene most altered in virally infected patients.

The quest to establish an understanding of the genetics underlying COVID-19 is a central focus of life sciences today. COVID-19 is triggered by SARS-CoV-2, a single-stranded RNA respiratory virus. Several clinical-genomics studies have emerged positing different human gene mutations occurring due to COVID-19. A global analysis of these genes was conducted targeting major components of the immune system to identify possible variations likely to be involved in COVID-19 predisposition. Gene-variant analysis was performed on whole-genome sequencing samples collected from diverse populations. ACE2, TMPRSS4, TMPRSS2, SLC6A20 and FYCOI were found to have functional implications and TMPRSS4 may have a role in the severity of clinical manifestations of COVID-19.

Forecasting COVID-19 Testing Load Using Google Trends: Experience from a Lower Middle-Income Country with over 10 Million Diagnostic Tests.

BACKGROUND: The ability to forecast changing trends of COVID-19 can help drive efforts to sustain the increasing burden on the healthcare system, specifically the clinical laboratories. We aimed to assess whether the trends of SARS-CoV-2 testing in Pakistan can be predicted using COVID-19 symptoms as search terms and analyzing the data from Google Trends. METHODS: The number of weekly SARS-CoV-2 tests performed were retrieved from online COVID-19 data resource. Google Trends data for the search terms with most common COVID-19 symptoms was analyzed for cross-correlation with the number of tests performed nationally. RESULTS: A total of 10,066,255 SARS-CoV-2 diagnostic tests were analyzed. Search terms of fever, headache, and shortness of breath displayed a statistically significant correlation with total number of tests performed with a 1-week time lag. CONCLUSIONS: Google Trends data can be used to forecast the changing trends in COVID-19 testing. This information can be used for careful planning and arrangements to meet increased diagnostic and healthcare demands in difficult times.

Blended learning using augmented reality glasses during the COVID-19 pandemic: the present and the future

Background: The COVID-19 pandemic has caused major disruption to a normal way of life. It has also affected medical education, and traditional methods of delivering learning have not been possible because of various restrictions. We devised novel methods of teaching and endeavoured to provide as much clinical exposure as possible to medical students, keeping the safety of all parties involved paramount. Methods: We incorporated augmented reality glasses into our teaching to provide clinical exposure to final year medical students. Most students were present in a remote location while the teaching was imparted. Following the teaching sessions, students were emailed a survey requesting their feedback on the experience. Statistical analysis of the responses was done to formulate an objective assessment of the effectiveness of the blended learning. Results: The overall response was satisfactory, with the majority of students satisfied with the new techniques. There were reservations regarding technological setbacks we experienced with the equipment and delivery. It was also noted that most students preferred ward-based traditional teaching compared to augmented reality learning. Conclusion: We concluded that augmented reality blended learning provides an alternate to traditional teaching, especially at times when the latter is not logistically feasible. There is scope for further utility of this technology in medical education, and further trials and refinements are necessary to make its use widespread.

Insights into the evolutionary and prophylactic analysis of SARS-CoV-2: A review.

In late 2019, following the emergence of a ß-originated SARS-CoV-2, phylogenetic and evolutionary approaches have been demonstrated to strengthen the diagnostic and prophylactic stratagem of COVID-19 at an unprecedented level. Despite its clinical prominence, the SARS-CoV-2 gene set remains largely irrefutable by impeding the dissection of COVID-19 biology. However, many pieces of molecular and serological evidence have predicted that SARS-CoV-2 related viruses carry their roots from bats and pangolins of South East Asia. Analysis of viral genome predicts that point mutations at a rate of 10-4 nucleotides per base in the receptor-binding domain allow the emergence of new SARS-CoV-2 genomic variants at regular intervals. Research in the evolution of molecular pathways involved in emergence of pandemic is critical for the development of therapeutics and vaccines as well as the prevention of future zoonosis. By determining the phyletic lineages of the SARS-CoV-2 genomic variants and those of the conserved regions in the accessory and spike proteins of all the SARS-related coronaviruses, a universal vaccine against all human coronaviruses could be formulated which would revolutionize the field of medicine. This review highlighted the current development and future prospects of antiviral drugs, inhibitors, mesenchymal stem cells, passive immunization, targeted immune therapy and CRISPR-Cas-based prophylactic and therapeutic strategies against SARS-CoV-2. However, further investigations on Covid-19 pathogenesis is required for the successful fabrication of successful antivirals.

The Mediating Effect of Coping Strategies Between Psychological Capital and Small Tourism Organization Resilience: Insights From the COVID-19 Pandemic, Malaysia.

Amid difficulty, the psychological capital of small tourism firm owners/managers has been given less attention. In the coronavirus disease-2019 (COVID-19) pandemic, this research examined how psychological capital (self-efficacy, hope, optimism, and resilience) affects organizational resilience. By structural equation modeling (AMOS 21.0), 644 small tourism firm owners in Malaysia were randomly selected to investigate the relationship between psychological capital and organizational resilience, and the mediating effect of problem-focused and emotion-focused coping strategies on this relationship. The findings of the study supported hypothesized relationships, as the psychological capital of small tourism firm owners in Malaysia significantly affects organizational resilience. Furthermore, the study discovered that problem-focused and emotion-focused coping strategies have partial mediating effects on the association between psychological capital and organizational resilience. In the context of small tourism businesses sector, the findings of the study have implications, as the firms identify the recovery procedure in the COVID-19 pandemic.

Intelligent health system for the investigation of consenting COVID-19 patients and precision medicine.

Advancing frontiers of clinical research, we discuss the need for intelligent health systems to support a deeper investigation of COVID-19. We hypothesize that the convergence of the healthcare data and staggering developments in artificial intelligence have the potential to elevate the recovery process with diagnostic and predictive analysis to identify major causes of mortality, modifiable risk factors and actionable information that supports the early detection and prevention of COVID-19. However, current constraints include the recruitment of COVID-19 patients for research; translational integration of electronic health records and diversified public datasets; and the development of artificial intelligence systems for data-intensive computational modeling to assist clinical decision making. We propose a novel nexus of machine learning algorithms to examine COVID-19 data granularity from population studies to subgroups stratification and ensure best modeling strategies within the data continuum.

THE IMPACT OF CORONA VIRUS DISEASE-19(COVID-19) ON POSTGRADUATE PAEDIATRIC RESIDENTS

ABSTRACT Objective: To explore the impact of corona virus disease-19 pandemic on postgraduate paediatric residents. Study Design: Mixed method study. Place and Duration of Study: Pak Emirates Military Hospital Rawalpindi, from Apr to May 2020. Methodology: Post graduate paediatric residents working in Pak Emirates Military Hospital and Combined Military Hospital Rawalpindi, Pakistan were included by purposive sampling technique. Sample size was predetermined, included all(forty total) residents of two hospitals. Participant‘s written response was obtained on an open ended self administered-questionnaire distributed in person. All enrolled participants responded. Thematic analysis of data was done. Results: The participants were predominantly female(n: 30, 75%) of age range 31-35(50%) years. The first theme category was Impact on personal life The residents reported an unprecedented physical, psychological and social stress. The second category was Family life during COVID-19 Residents had to share extra family/ financial/health responsibilities of their families. Professional duties and training was another theme category. Residents worked in new context of environment, fear of contagion, managing interpersonal / interprofessional relationships, less volume of patients/clinical experience / skills and new e-learning modalities. Challenges and suggestions to cope is another category, where residents suggested strategies and sources to improve patient care, their well being and training during pandemic. Conclusion: The residents had experienced intensive physically, emotional and social stress. Most of them behaved with resilience and extreme professional dedication. Different competencies of training are being affected. Concerned authorities must adopt new strategies to support resident‘s training and personal life.

VERTICAL TRANSMISSION OF CORONA VIRUS DISEASE-19 (COVID-19) FROM INFEECTED PREGNANT MOTHERS TO NEONATES

ABSTRACT Objective: To assess the vertical transmission of Corona Virus disease (COVID-19) from infected pregnant mothers to neonates. Study Design: Cross sectional study. Place and Duration of Study: Department of Obstetrics and Gynaecology, Pak Emirates Military Hospital Rawalpindi, from May 2020 to Jun 2020. Methodology: A total of 90 pregnant patients reported in Pak Emirates Military Hospital during the pandemic of COVID-19 with COVID-19 test positive from 01 May 2020 to 30 June 2020. Diagnosis was confirmed with reverse transcriptase polymerase chain reaction (RT-PCR) of nasal and throat swabs. Clinical, analytical, laboratory and radiographic findings were then recorded. The (RT-PCR) for COVID-19 of all the babies who were delivered to these mothers was also done on throat and nasal swabs. The neonatal blood was also sent for serology (IgM/IgG). Results: Out of 90 patients studied, 46 were delivered either through a Caesarean section or by vaginal delivery. The patients were categorized as asymptomatic 51 (55.66%) and symptomatic 39 (43.33%). Out of those symptomatic, patients with mild to moderate disease were 33 (84.61%), patients with severe disease 05 (12.82%) and critically ill patient was 01 (2.56%). All the patients who delivered were COVID-19 test positive at the time of delivery and later when the babies of all these mothers were tested, they were all found to be COVID-19 negative on RT-PCR and no immunoglobulins were found in the serum of these neonates. The possibility for transplacental transmission could only be checked by these two methods (RT-PCR and Serology) since RT-PCR of amniotic fluid, high vaginal swab and breast milk was not available. Conclusion: In our study we did not find any evidence of vertical transmission of corona virus disease-19 (COVID-19) from infected pregnant mothers to neonates.

A cross sectional evaluation of the corona-score for swift identification of SARS-CoV-2 infection at a tertiary care hospital in Pakistan.

BACKGROUND: The Corona-Score is one of the first and most widely used predictive model for coronavirus 2 (SARS-CoV-2) infection. The purpose of this study was to validate the performance of Corona-Score in a cohort of Pakistani patients pursuing care for suspected infection. METHODS: After seeking institution's ethical committee exemption, results of serum lactate dehydrogenase (LDH), C-reactive protein (CRP), ferritin, absolute lymphocyte and neutrophil counts, chest x-ray findings and demographics of suspected COVID-19 cases with respiratory symptoms were recouped from electronic medical record. The pre-validated score as proposed by Kurstjens S et al., was calculated. The subjects were divided into SARS-CoV-2 positive and negative on the basis of reverse transcription-polymerase chain reaction (RT-PCR) findings. Median and interquartile range (IQR) was calculated for the score in the two groups and the difference was assessed using the independent sample median test. Receiver operating characteristics (ROC) curve analysis was plotted. Statistical analyses were carried out using SPSS 26, with statistical significance set at p value < 0.05. RESULTS: A total of sixty cases, 30 (50%) RT-PCR positive and 30 (50%) negative with a median Corona-Score of 3.5 (IQR: 0-6) and 1.5 (IQR: 0-4) respectively, were evaluated. A p-value of 0.61 showing no statistically significant between group differences was observed. The area under the curve of Corona-Score in our population of patients was 0.59 (95% CI: 0.45-0.74). Using the cut-off values of four originally identified by Kurstjens et al. the model displayed 43.3% sensitivity and 70% specificity with an overall accuracy of 56.67%. CONCLUSION: Corona-Score displayed a lower diagnostic accuracy which may be attributable to the different genetic framework, viral strain and severity of the disease in Pakistanis compared to the population where this score was originally validated. However, large multi-center studies across the country are dire need of time to evaluate the score in overly exhausted health care setup and limited availability of PCR testing.

Evaluation of serum ferritin for prediction of severity and mortality in COVID-19- A cross sectional study.

BACKGROUND: Ferritin even though widely recognized as a representative of total body iron stores, its prognostic utility is linked with COVID-19. This study was aimed at evaluation of the association of ferritin with severity in Coronavirus disease 2019 (COVID-19), hospitalized patients and to test the hypothesis that it is an independent predictor of mortality. MATERIAL AND METHODS: This study was conducted at Chemical Pathology, Department of Pathology and Laboratory Medicine, Aga Khan University (AKU), Karachi. Medical records of all in-patients including both genders, and all age groups with documented COVID-19 from 1st March to 10th August 2020 were reviewed. The subjects were divided into two categories severe and non-severe COVID-19; and survivors and non-survivors. The details were recorded on a pre-structured performa. Between-group differences were tested using the Mann-Whitney's U-test. The receiver operating characteristic curve was plotted for ferritin with severity and mortality. A binary logistic regression was used to identify variables independently associated with mortality. The data was analyzed using Statistical Package for the Social Sciences (SPSS). RESULTS: A total of 336 in patients were reviewed as declared COVID-19 positive during the study duration, and 157 were included in the final analysis including 108 males and 49 females. Statistically significant difference in ferritin was found in the two categories based on severity and mortality. Binary logistic regression showed ferritin to be an independent predictor of all-cause mortality supplemented with an AUC of 0.69 on ROC analysis. CONCLUSIONS: Serum ferritin concentration is a promising predictor of mortality in COVID-19 cases.

COVID-19 and comorbidities: Deleterious impact on infected patients.

The pandemic situation with the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from China has endangered human lives. Coronavirus disease 2019 (COVID-19) is presented with asymptomatic, mild, or severe pneumonia-like symptoms. COVID-19 patients with diabetes, chronic obstructive pulmonary disease (COPD), cardiovascular diseases (CVD), hypertension, malignancies, HIV, and other comorbidities could develop a life-threatening situation. SARS-CoV-2 utilizes ACE-2 receptors found at the surface of the host cells to get inside the cell. Certain comorbidities are associated with a strong ACE-2 receptor expression and higher release of proprotein convertase that enhances the viral entry into the host cells. The comorbidities lead to the COVID-19 patient into a vicious infectious circle of life and are substantially associated with significant morbidity and mortality. The comorbid individuals must adopt the vigilant preventive measure and require scrupulous management. In this review, we rigorously focused on the impact of common morbidities in COVID-19 patients and recapitulated the management strategies with recent directions. We found limited resources describing the association of comorbidities in COVID-19; however, our review delineates the broader spectrum of comorbidities with COVID-19 patients.

Food as medicine: A possible preventive measure against coronavirus disease (COVID-19).

The recent and ongoing outbreak of coronavirus disease (COVID-19) is a huge global challenge. The outbreak, which first occurred in Wuhan City, Hubei Province, China and then rapidly spread to other provinces and to more than 200 countries abroad, has been declared a global pandemic by the World Health Organization. Those with compromised immune systems and/or existing respiratory, metabolic or cardiac problems are more susceptible to the infection and are at higher risk of serious illness or even death. The present review was designed to report important functional food plants with immunomodulatory and anti-viral properties. Data on medicinal food plants were retrieved and downloaded from English-language journals using online search engines. The functional food plants herein documented might not only enhance the immune system and cure respiratory tract infections but can also greatly impact the overall health of the general public. As many people in the world are now confined to their homes, inclusion of these easily accessible plants in the daily diet may help to strengthen the immune system and guard against infection by SARS-CoV-2. This might reduce the risk of COVID-19 and initiate a rapid recovery in cases of SARS-CoV-2 infection.

Practicing precision medicine with intelligently integrative clinical and multi-omics data analysis.

Precision medicine aims to empower clinicians to predict the most appropriate course of action for patients with complex diseases like cancer, diabetes, cardiomyopathy, and COVID-19. With a progressive interpretation of the clinical, molecular, and genomic factors at play in diseases, more effective and personalized medical treatments are anticipated for many disorders. Understanding patient's metabolomics and genetic make-up in conjunction with clinical data will significantly lead to determining predisposition, diagnostic, prognostic, and predictive biomarkers and paths ultimately providing optimal and personalized care for diverse, and targeted chronic and acute diseases. In clinical settings, we need to timely model clinical and multi-omics data to find statistical patterns across millions of features to identify underlying biologic pathways, modifiable risk factors, and actionable information that support early detection and prevention of complex disorders, and development of new therapies for better patient care. It is important to calculate quantitative phenotype measurements, evaluate variants in unique genes and interpret using ACMG guidelines, find frequency of pathogenic and likely pathogenic variants without disease indicators, and observe autosomal recessive carriers with a phenotype manifestation in metabolome. Next, ensuring security to reconcile noise, we need to build and train machine-learning prognostic models to meaningfully process multisource heterogeneous data to identify high-risk rare variants and make medically relevant predictions. The goal, today, is to facilitate implementation of mainstream precision medicine to improve the traditional symptom-driven practice of medicine, and allow earlier interventions using predictive diagnostics and tailoring better-personalized treatments. We strongly recommend automated implementation of cutting-edge technologies, utilizing machine learning (ML) and artificial intelligence (AI) approaches for the multimodal data aggregation, multifactor examination, development of knowledgebase of clinical predictors for decision support, and best strategies for dealing with relevant ethical issues.