Computer Vision Syndrome in Undergraduate and Medical Students During the COVID-19 Pandemic.

Purpose: The purpose of this study was to evaluate Computer Vision Syndrome (CVS) in undergraduate and medical students since transitioning to online learning during the COVID-19 pandemic. Patients and Methods: This was a cross-sectional single center survey-based study using a validated CVS questionnaire (CVS-Q). The survey was distributed to 20,080 undergraduate students and 680 medical students at the University of Illinois at Chicago. The primary outcome measures were prevalence of CVS (based on CVS severity score of 6 or more), frequency of CVS and intensity of CVS symptoms. Results: The survey was completed by 2300 undergraduate students (11.4% response rate) and 154 medical students (22.6% response rate). The prevalence of CVS was 77.1% in undergraduate students and 69.1% in medical students. CVS-Q severity scores were highest for headaches and eye dryness, with over half of students reporting worsening of symptoms since March 2020. Increased time spent on online learning (undergraduate: P <0.001, medical: P = 0.018), blue light glasses usage (undergraduate: P <0.001, medical: P = 0.0015), and increased number of device usage were associated with higher CVS severity scores (undergraduate: P <0.001, medical: P = 0.0032). Conclusion: CVS among undergraduate and medical students has increased since the start of the COVID-19 pandemic. More focus should be placed on the management of CVS for students in higher education. Physicians should be cognizant of the consequences of online learning and be proactive about providing advice regarding preventative measures.

Effect of covid-19 pandemic on the urban heat island: A multi-city case study in india

Urban Heat Island (UHI) is defined as an urban area that is warmer than its rural counterpart due to excessive human activities. The temperature difference is significantly more during the night than during the daytime and is noticed around the year, except for during the monsoon. COVID-19 pandemic and the subsequent lockdown closed all the outside activities and forced the people to remain inside their houses. In India, the first national lockdown started on 24th March 2020 and lasted till November 2020 with phased unlock from June 2020. Further, in 2021, a second lockdown was imposed due to the second wave of the pandemic. The lockdown in the second phase started in April 2021 and lasted till July 2021, while easing some restrictions from June. Due to these lockdowns, whereas the air quality improved on account of less vehicular and other pollution, people staying in their houses increased the consumption/use of electricity for cooling/heating resulting in an increase in the Land Surface Temperature (LST) and subsequently the Urban Heat Island for the residential areas. To study the effect of lockdown on the change in UHI in metro and state capital cities of India, the authors have calculated the variation in the day UHI for 5 cities across different states in India for pre- and post-lockdowns of 2020 and 2021. The day LST has been calculated using LANDSAT 8 for 5 cities spread across different states in different climate zones of India. The LST and UHI of the cities have also been compared with the earlier values. The chapter details the different LST/UHI calculation methodologies, the use of cloud platforms such as Google Earth Engine (GEE) for the calculation of LST/UHI, and the relationship between LST, UHI with the human activities and air pollution. After analysis of 4 cities across different parts of India, the results indicate that there is a positive effect of the COVID-19 lockdown on the Urban Heat Islands. There was an increasing pattern of temperatures observed in the residential areas and a decreasing pattern in the industrial areas during the lockdown. © 2022 by Nova Science Publishers, Inc.

Neurogenesis is disrupted in human hippocampal progenitor cells upon exposure to serum samples from hospitalized COVID-19 patients with neurological symptoms.

Coronavirus disease 2019 (COVID-19), represents an enormous new threat to our healthcare system and particularly to the health of older adults. Although the respiratory symptoms of COVID-19 are well recognized, the neurological manifestations, and their underlying cellular and molecular mechanisms, have not been extensively studied yet. Our study is the first one to test the direct effect of serum from hospitalised COVID-19 patients on human hippocampal neurogenesis using a unique in vitro experimental assay with human hippocampal progenitor cells (HPC0A07/03 C). We identify the different molecular pathways activated by serum from COVID-19 patients with and without neurological symptoms (i.e., delirium), and their effects on neuronal proliferation, neurogenesis, and apoptosis. We collected serum sample twice, at time of hospital admission and approximately 5 days after hospitalization. We found that treatment with serum samples from COVID-19 patients with delirium (n = 18) decreased cell proliferation and neurogenesis, and increases apoptosis, when compared with serum samples of sex- and age-matched COVID-19 patients without delirium (n = 18). This effect was due to a higher concentration of interleukin 6 (IL6) in serum samples of patients with delirium (mean ± SD: 229.9 ± 79.1 pg/ml, vs. 32.5 ± 9.5 pg/ml in patients without delirium). Indeed, treatment of cells with an antibody against IL6 prevented the decreased cell proliferation and neurogenesis and the increased apoptosis. Moreover, increased concentration of IL6 in serum samples from delirium patients stimulated the hippocampal cells to produce IL12 and IL13, and treatment with an antibody against IL12 or IL13 also prevented the decreased cell proliferation and neurogenesis, and the increased apoptosis. Interestingly, treatment with the compounds commonly administered to acute COVID-19 patients (the Janus kinase inhibitors, baricitinib, ruxolitinib and tofacitinib) were able to restore normal cell viability, proliferation and neurogenesis by targeting the effects of IL12 and IL13. Overall, our results show that serum from COVID-19 patients with delirium can negatively affect hippocampal-dependent neurogenic processes, and that this effect is mediated by IL6-induced production of the downstream inflammatory cytokines IL12 and IL13, which are ultimately responsible for the detrimental cellular outcomes.

IMPACT OF IMMUNOSUPPRESSIVE THERAPIES ON ANTIBODY DECAY FOLLOWING MRNA VACCINATION TO SARS-COV-2 IN A PROSPECTIVE COHORT OF PATIENTS WITH CHRONIC INFLAMMATORY DISEASES

Background: Waning levels of anti-SARS-CoV-2 Spike (S) antibodies, particularly neutralizing, are associated with the risk of breakthrough infections. The impact of immunosuppression on antibody decay kinetics is unclear. We have previously reported a strong correlation between total anti-S antibodies and neutralization titers. Here, we report the decay kinetics in anti-S IgG antibodies across various immunosuppressive medications used in patients with CID. Methods: We recruited a volunteer sample of adults with confirmed CID eligible for SARS-CoV-2 vaccination in a prospective observational cohort study at two United States CID referral centers. All study participants received two doses of mRNA vaccine to SARSCoV- 2. To assess the durability of immunogenicity, anti-S IgG were measured at 7 (visit 3), 90 (visit 5), and 120 (visit 6) days after the 2nd dose of mRNA vaccine. The impact of various medications was assessed in repeated measures mixed model with the patient as a random effect, adjusting for gender and age, and using the group of patients on sulfasalazine, NSAIDs, or on no medications as a reference, using STATA. The half-life of anti-S IgG for a 50 percent reduction in titers at visit 3 was calculated for each medication class. Results: A total of 316 CID patients were recruited of which 148 (46.8%) had inflammatory bowel disease (IBD). Durability was assessed in 495 samples obtained in 293 patients. The arithmetic mean of anti-S IgG antibodies for each medication class at visits 3, 5, and 6 is shown in Figure 1. Overall, a 2-fold reduction in titers was observed from 7 to 90 days and 90 to 120 days (Table 1). The strongest decline was observed among patients on B cell depleting/ modulating therapies followed by those on combinations of biologics and/or small molecules and antimetabolites (methotrexate, leflunomide, thiopurines, mycophenolate mofetil, and teriflunomide). There was modest decline seen with TNFi (half-life 430.5 days, -2.15, 95% CI - 4.31 to - 1.07, p = 0.03). There was also a modest, but not significant, decline seen with Janus Kinase inhibitor (JAKi). No decline was seen with anti-IL-23 or anti-integrin medication classes. Conclusions: Antibody decay in patients with CID is not observed in patients on anti-integrins or anti-IL-23 while it is seen among patients on TNFi, JAKi, antimetabolites, and combinations of biologics and/or small molecules. Our data and those from other cohorts may be used to prioritize medication classes for boosting immunogenicity with additional doses of vaccination against SARS-CoV-2. Collection of antibody titers after booster doses is currently ongoing.(Table Presented) (Figure Presented) Figure 1: Durability of anti-spike IgG antibodies after vaccination against SARS-CoV-2 in patients with Chronic Inflammatory Disease

Awareness of health care workers regarding COVID-19 vaccine in a tertiary care hospital-a knowledge, attitude, and practice study

Inactivated COVID Vaccine;COVID 19;Healthcare Worker;Vaccination;Knowledge;Attitude and Practices INTRODUCTION Severe acute respiratory syndrome (SARS) coronavirus-2novel coronavirus termed as COVID 19 is a major outbreak which was deleterious globally created a fast spreading respiratory infectious disease that caused the SARS. MATERIALS AND METHODS Study Site and Design This is a hospital-based, Observational cross-sectional study done in Hassan Institute of Medical Sciences, Teaching hospital, Hassan, Karnataka. [...]knowing the acceptability and willingness to take the vaccines becomes an important factor for the better usage of vaccines. [2] mentioned that developing a vaccine quickly requires a new pandemic protocol, with a prompt start and many steps executed in parallel before confirming a result of another step, hence might elevate financial risk. Since China confirmed the outbreak of disease in Wuhan the vaccine procurement was necessary and needed a fast production.

Corrigendum: Virus-Induced Maternal Immune Activation as an Environmental Factor in the Etiology of Autism and Schizophrenia.

[This corrects the article DOI: 10.3389/fnins.2022.834058.].

EARLY TREATMENT WITH PREDNISOLONE AND ACYCLOVIR IN SARS-COV-2 COMPLICATED BELL'S PALSY: A CASE REPORT

Bell's palsy is an idiopathic, unilateral, acute weakness of the face in a pattern consistent with peripheral facial nerve dysfunction and may be partial or complete, occurring with equal frequency on either side of the face. The incidence is about 20 in 100,000 people a year, with about 1 in 60-lifetime risks. Bell's palsy has a peak incidence between the ages of 15 and 40 years. Viral infections are commonly associated with facial nerve pathology, which leads to peripheral facial paralysis. A potential cause of peripheral facial paralysis might be COVID-19 and neurological symptoms could be the first and only manifestation of the disease. Possible mechanisms related to nerve damage in idiopathic facial nerve paralysis include ischemia of vasa nervorum and demyelination induced by an inflammatory process. Direct viral damage or an autoimmune reaction toward the nerve-producing inflammation would be alternative or contributing mechanisms to dysfunction. Acyclovir (aciclovir) is a nucleoside analogue antiviral drug active against some of the herpes virus groups of DNA viruses and RNA viruses. The mechanism of prednisolone may involve modulation of the immune response to the causative agent or direct reduction of edema around the facial nerve within the facial canal. Prednisolone and acyclovir are commonly prescribed separately and in combination, although evidence of their effectiveness is weak. We report a case diagnosed with COVID-19 after presenting with isolated peripheral facial palsy.

Wastewater-based epidemiology for novel Coronavirus detection in wastewater

The entire world is reeling under the worst pandemic of last 100 years. Over 128 million people have been infected with it and 2.8 million deaths have already taken place, till 30th March 2021. The identification of materials positive cases is the first step towards its containment and treatment. However, testing of individuals is an extensive, expensive and time-consuming exercise. In addition, societal taboos are also associated with infected individuals resulting in very few people volunteering for testing, esp. in the developing and under-developed world. An alternative approach that circumvents individual testing is the wastewater-based epidemiology. A state-of-the-art review of this method is provided in context of its utility for COVID-19 detection. This technique relies on collecting and testing samples from sewers and/or wastewater treatment plants for the presence of pathogens and then using that data to determine and predict the spread of the infection, thereby allowing the provision of appropriate containment and treatment steps. The study covers key aspects of wastewater-based epidemiology application for COVID-19 detection including its need, detailed process of detection and assessment, data analysis, economics and challenges to its application. Findings from a number of case studies are presented to elucidate the utility of this technique. It is clearly seen that WBE-based approach is a much better strategy as compared to individual testing and can be adopted to prevent further spread of Covid-19. The work is expected to further emphasize the application of this method for COVID (and other pandemic) detection and implementing containment strategies. This is clearly a much more economical and non-intrusive approach as compared to the individual testing.

Fake News in Health and Medicine

With the rise of social media, the world is faced with the challenge of increasing health-related fake news more than ever before. We are constantly flooded with health-related information through various online platforms, many of which turn out to be inaccurate and misleading. This chapter provides an overview of various health fake news and related studies which have been reported in various news articles and scientific journals. Some of the studies conducted on health misinformation identified a prominence of vaccine- and cancer-related fake news. The popularity of so-called unproven natural cures for cancer and other diseases is alarming. The chapter also highlights the importance of maintaining accurate and effective scientific communication in this COVID-19 pandemic-hit world to safeguard public health. The current pandemic has also proved fertile ground for spreading misinformation. The chapter brings the audience’s attention to the consequences of health misinformation, ranging from giving false hope to patients to the hurdles it poses to effective medical care. Finally, the chapter addresses some of the possible strategies to keep health misinformation in check. © 2021, Springer Nature Switzerland AG.

Analyzing social distancing policy effectiveness using Computational Fluid Dynamics inside a bus to prevent COVID-19 airborne transmission

Coronavirus disease (COVID-19) is a kind of disease that transmits from one body to another through air by the moist particles caused during sneezing and coughing. As a result, to reduce the virus spreading accordingly, 1.83 m of social distancing has been advised to be followed among the humans. Also, it is not well studied that whether the ambient wind and relative humidity (RH) will cause COVID-19 laden cough droplets to transport farther in the air, and make the current social distancing practice ineffective. In this study, computational fluid dynamics simulations are carried out to analyze the transient transport, condensation/evaporation, and deposition of COVID laden droplets emitted by coughs, with the different environmental conditions, cough velocities and Relative Humidity using the developed bus model of size 12 m x 3.5 m x 3.2 m. Different conditions of sneezing and coughing from the human’s i.e., the laminar and the turbulent flows of the laden droplets in the air inside the bus were also examined. The distance between the two virtual humans is set as 6 m for a 12 m bus length in order to track the distance covered by cough particles. The facial covering effect on reducing the airborne transmission of the cough droplets has also been evaluated. It is found that due to the ambient air and humidity, the generation of secondary laden droplets occur which travels far and accumulates on the ground or any other third human being around and causes a strong potential risk to their health. The secondary droplets are transforming into large droplets due to high humidity and the hygroscopic effect is evaluated. The 6 feet social distancing is found to be ineffective for halting the spread of viruses among human beings because the micro-laden droplets caused during the sneezing and coughing are influenced by the convection effects and transport from one body to another within 5 s. It is thus recommended to wear masks for both infected and healthy humans to reduce the airborne cough droplets.

ReSCo-CC: Unsupervised Identification of Key Disinformation Sentences

Disinformation is often presented in long textual articles, especially when it relates to domains such as health, often seen in relation to COVID-19. These articles are typically observed to have a number of trustworthy sentences among which core disinformation sentences are scattered. In this paper, we propose a novel unsupervised task of identifying sentences containing key disinformation within a document that is known to be untrustworthy. We design a three-phase statistical NLP solution for the task which starts with embedding sentences within a bespoke feature space designed for the task. Sentences represented using those features are then clustered, following which the key sentences are identified through proximity scoring. We also curate a new dataset with sentence level disinformation scorings to aid evaluation for this task;the dataset is being made publicly available to facilitate further research. Based on a comprehensive empirical evaluation against techniques from related tasks such as claim detection and summarization, as well as against simplified variants of our proposed approach, we illustrate that our method is able to identify core disinformation effectively. © 2020 ACM.

ReSCo-CC: Unsupervised Identification of Key Disinformation Sentences (preprint)

Disinformation is often presented in long textual articles, especially when it relates to domains such as health, often seen in relation to COVID-19. These articles are typically observed to have a number of trustworthy sentences among which core disinformation sentences are scattered. In this paper, we propose a novel unsupervised task of identifying sentences containing key disinformation within a document that is known to be untrustworthy. We design a three-phase statistical NLP solution for the task which starts with embedding sentences within a bespoke feature space designed for the task. Sentences represented using those features are then clustered, following which the key sentences are identified through proximity scoring. We also curate a new dataset with sentence level disinformation scorings to aid evaluation for this task; the dataset is being made publicly available to facilitate further research. Based on a comprehensive empirical evaluation against techniques from related tasks such as claim detection and summarization, as well as against simplified variants of our proposed approach, we illustrate that our method is able to identify core disinformation effectively.

Webinar Education in Ophthalmology during the COVID-19 Pandemic: A Survey Study (preprint)

Background: Ophthalmology education is changing amidst the COVID-19 pandemic. The purpose of this study is to describe and evaluate the implementation of webinars combined with online resources for review for ophthalmology trainees. Methods: This is a single-center descriptive survey study. A validated survey tool was distributed 2 months after implementation of webinar education. The survey population comprised residents, fellows, and faculty in a Chicago ophthalmology training program.Results: Eighteen residents (100% response rate), 9 fellows (81.8% response rate) and 20 faculty members (44.4% response rate) responded to the survey. Barriers to webinar education and limitations to learning during webinars were rated as low in both groups (avg. 1.98 ± 2.04 and 2.16 ± 1.82, respectively). The educational value of the webinars was moderately well rated (avg. 7.35 ± 1.66). Interest in webinars replacing in-person lectures was neutral (avg. 5.45 ± 2.54). Faculty expressed fewer barriers (p = 0.005), and a higher preference to use webinar education frequently (p = 0.003) and instead of in-person lectures (p = 0.009), compared to trainees.  Conclusions: The findings of this survey suggest that webinars in ophthalmology education are effective and feasible, with some perceived limitations.