Voltammetric determination of daclatasvir dihydrochloride at bimetallic Ag/Co nanoparticles modified carbon paste electrode

In this work, a sensitive and cost-effective voltammetric method was proposed for the determination of daclatasvir dihydrochloride (DAC.2HCl) at a bimetallic Ag/Co nanoparticles-modified carbon paste electrode. Potential cyclization was used for the electro-deposition of the nanoparticles. The number of potential cycles needed for deposition was optimized. Surface characterization of the prepared sensor was performed using scanning electron microscope imaging (SEM). The electroanalysis of DAC was performed using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). Results of the scan rate effect indicated a dual diffusion-adsorption mechanism of DAC electrooxidation that involved two electrons. A very wide concentration range, from 5 × 10−9 to 10−4 M, was detected and divided into two segments with a low detection limit of 0.387 nM in 0.1 M phosphate buffer solution/pH 2.6. The electroactivity of the developed sensor toward DAC, sensitivity, reproducibility, repeatability, robustness, and selectivity were investigated. This sensor was successfully applied for the determination of DAC in pharmaceutical and urine samples.

The impact of temporary COVID-19 legislative moves on the ability of food enterprises to pivot in Arizona. (Special Issue: The impact of the covid-19 pandemic and the foodservice industries.)

The COVID-19 pandemic highlighted shortfalls in the U.S. food system, exposing how regulatory processes shape access to the market. This paper builds on ongoing research following the impact of shut-down orders on alcohol retail via small restaurants and breweries in Arizona and examines the impacts of regulatory shifts on the ability of these food enterprises to pivot. We highlight how the concept of the pivot creates expectations of individual businesses ability to be resilient to shocks. Responses within Arizona to COVID-19 induced systemic failures, demonstrate that bottom-up pivots from small businesses can creatively and quickly meet local community needs. However, those efforts were stymied by state government and top-down approaches that proved incapable of pivoting to meet local needs. Through this case study, we highlight the need and opportunity for further examination of the interplay between regulatory agencies and small businesses in times of crisis. We invite others into the work of creating guidelines for pivoting that facilitate bottom-up and top-down collaboration while ensuring the voice and agency of different players.

Understanding Economic Development Organization Efforts to Advance Inclusive Economic Recovery in Virginia

This research incorporates preliminary findings from a survey and case studies of economic development organizations (EDOs) in Virginia as these entities initiate their economic recovery planning processes in the post-COVID-19 pandemic era. The research seeks to understand the extent to which EDOs understand—and engage in conversations about—racial and economic inclusion in the context of economic recovery and to learn more about the strategies being deployed to promote inclusive recovery in the post-COVID era. Though some common characteristics were identified, the results demonstrate significant variation in both the extent to which inclusivity is prioritized and how it is conceived of in recovery planning efforts. The findings suggest that while many economic development organizations are signaling a commitment to inclusivity, albeit, in assorted ways, there remains a need for further dialogue about how inclusivity is defined and how it can best translate into actionable strategies. © The Author(s) 2023.

APPLYING HUNGER GAME SEARCH (HGS) FOR SELECTING SIGNIFICANT BLOOD INDICATORS FOR EARLY PREDICTION OF ICU COVID-19 SEVERITY

This paper introduces an early prognostic model for attempting to predict the severity of patients for ICU admission and detect the most significant features that affect the prediction process using clinical blood data. The proposed model predicts ICU admission for high-severity patients during the first two hours of hospital admission, which would help assist clinicians in decision-making and enable the efficient use of hospital resources. The Hunger Game search (HGS) meta-heuristic algorithm and a support vector machine (SVM) have been integrated to build the proposed prediction model. Furthermore, these have been used for selecting the most informative features from blood test data. Experiments have shown that using HGS for selecting features with the SVM classifier achieved excellent results as compared with four other meta-heuristic algorithms. The model that used the features that were selected by the HGS algorithm accomplished the topmost results (98.6 and 96.5%) for the best and mean accuracy, respectively, as compared to using all of the features that were selected by other popular optimization algorithms © 2023 Author(s). This is an open access publication, which can be used, distributed and reproduced in any medium according to the Creative Commons CC-BY 4.0 License

Randomized Clinical Trial Comparing Insulin Fast Dissolving Films versus Control Group for Anosmic Patients for Improving Their Health and Social Qualities of Life

Background: Olfactory anomalies are the most common diseases among post-COVID-19 disorders. Only 15% of patients completed their prescribed treatment plans, even though several different treatment strategies were recommended;this had a detrimental effect on the patients' physical, social, and emotional wellbeing.Purpose: The aim of this study was approving intranasal fast-dissolving insulin films as the treatment of choice for anosmia in comparison to the control group, and the innovative treatment for anosmic post-COVID-19 is assessed in terms of the patients' health-related quality of life (HRQoL).Methods: For therapy and evaluation, a randomized clinical trial with forty adult anosmic post-viral patients was performed. The recruited participants were recruited between October 1 and March 8 of 2021 based on predetermined criteria. A validated smell assessment questionnaire concerning the participants' olfactory, physical, and psychological outcomes was given to them. Recruited patients were randomly subdivided into two groups: intervention and control group. Intervention was treated with insulin intranasal films, while control group took plain films (placebo).Results: The physical, emotional, and social health quality of life were significantly (p-value <0.0001) improved after 4 consecutive weeks of treatment with the intervention group compared to the control group. The data were analyzed statistically with the aid of GraphPad Prism 9.1.0.Conclusion: The lowest HRQoLs, which significantly impact their quality of life, are found in post-COVID-19 anosmic patients treated with insulin films. It is advised to employ this new intervention (insulin films) as the main therapy approach and to gather additional industry data for its development and dissemination. Problems with self-hygiene, eating, sense of danger and emotional satisfaction were significantly enhanced with insulin intervention versus placebo.

Dibenzo-18-crown-6-based carbon paste sensors for the nanomolar potentiometric determination of daclatasvir dihydrochloride: An anti-HCV drug and a potential candidate for treatment of SARS-CoV-2.

Daclatasvir dihydrochloride (DAC) is an anti-hepatitis C virus (HCV) drug that has recently proven to be a promising candidate for the treatment of SARS-CoV-2. Still, there is a lack of sensitive potentiometric methods for its determination. In this work, carbon paste sensors based on dibenzo-18-crown-6 (DB18C6) were fabricated and optimized for the sensitive and selective potentiometric determination of DAC in Daclavirocyrl® tablets, serum, and urine samples. The best performance was obtained by two sensors referred to as sensor I and sensor II. Both sensors exhibited a wide linear response range of 5×10-9 - 1×10-3 mol/L, and Nernstian slopes of 29.8 ± 1.18 and 29.5 ± 1.00 mV/decade, with limits of detection, 4.8×10-9 and 3.2×10-9 mol/L, for the sensors I and II, respectively. Sensors I and II displayed fast response times of 5-8 and 5-6 s, respectively, with great reversibility and no memory effect. Moreover, the sensors exhibited a lifetime of 16 days. For the study of sensors morphology and elucidation of the interaction mechanism, the scanning electron microscope (SEM), Fourier-transform infrared spectroscopy (FTIR), and nuclear magnetic resonance (1H NMR) techniques were performed. A selectivity study was performed, and the proposed sensors exhibited good discrimination between DAC and potentially coexisting interferents with sensor II displaying better selectivity. Finally, sensor II was successfully applied for the determination of DAC in the above-mentioned samples, with recovery values ranging from 99.25 to 101.42%, and relative standard deviation (RSD) values ranging from 0.79 to 1.53% which reflected the high accuracy and precision.

Computational Design and Experimental Evaluation of MERS-CoV siRNAs in Selected Cell Lines.

Middle East respiratory syndrome coronavirus (MERS-CoV) is caused by a well-known coronavirus first identified in a hospitalized patient in the Kingdom of Saudi Arabia. MERS-CoV is a serious pathogen affecting both human and camel health globally, with camels being known carriers of viruses that spread to humans. In this work, MERS-CoV genomic sequences were retrieved and analyzed by multiple sequence alignment to design and predict siRNAs with online software. The siRNAs were designed from the orf1ab region of the virus genome because of its high sequence conservation and vital role in virus replication. The designed siRNAs were used for experimental evaluation in selected cell lines: Vero cells, HEK-293-T, and Huh-7. Virus inhibition was assessed according to the cycle threshold value during a quantitative real-time polymerase chain reaction. Out of 462 potential siRNAs, we filtered out 21 based on specific selection criteria without off-target effect. The selected siRNAs did not show any cellular toxicity in the tested cell lines at various concentrations. Based on our results, it was obvious that the combined use of siRNAs exhibited a reduction in MERS-CoV replication in the Vero, HEK-293-T, and Huh-7 cell lines, with the highest efficacy displayed in the Vero cells.

Sleep in COVID-19 recovery period and its impacts on Quality Of Life

Introduction: According to the World Health Organization (WHO), the COVID-19 infection became a worldwide devastating health issue starting in December 2019 in China and then gradually was a global pandemic. PTSD after recovery from COVID-19 has been correlated to sleep problems, high anxiety level and depressive manifestations. These sleep problems have their drastic effect on the recovered patients' quality of life including physical, psychological and social domains. Objective(s): 1-To investigate the sleep in the post Coronavirus -19 period 2-If has an impact on the different items of patients' quality of life. Method(s): 1-Socio-demographic characteristics of 500 recovered COVID-19 patients 2-Insomnia Severity index a brief scale evaluating the patient's insomnia. The ISI evaluates the subjective complaints and results of insomnia as well as the level of dysfunctions from these sleep disturbances 3-Pittsburgh sleep quality index (PSQI):The Pittsburgh Sleep Quality Index (PSQI) is a scale that study the subjective sleep quality and different domains of sleep over a period of 1-month 4-Quality Of Life (QOL) by the SF36 Health Survey is a 36-item -report survey that evaluate eight domains of physical and mental wellbeing ranging from 0 to 100. Result(s): The mean score of insomnia severity index was 13.01+/-4.9. Regarding Pittsburgh sleep quality index , Sum of seven component scores was 15.37+/-4.43.Also QOL SF36 showed higher scores of the 8 domains including physical and mental Conclusion(s): High score of insomnia and sleep disturbances during the recovery period of COVID-19 infection which affecting the Quality Of Life.

To assess autism spectrum disorder parental quality of life during covid 19 in Taif, KSA

Background: Considering the fact that family members necessarily spend more time together during the pandemic, this study aims to assess autism spectrum disorder parental quality of life during covid 19. Method: Descriptive community base study was conducted at the city of Al-Taif using semi-structured questionnaire during Feb. 2022. A total of 76 parents living in Al-Taif participated in the study. Results: The study found that the most frequent effect of the emerging corona virus (Covid 19) on isolating the lives of children with autism was to some extent, the percentage 31, and the most frequent effect of the emerging corona virus (Covid 19) on health condition of children with autism was disagree, the percentage 32.8, the most frequency. Conclusion: The Corona epidemic has compounded the suffering of children with special needs, as the quarantine period and restrictions on their ability to go to school and move have been incomprehensible to them, and it has been difficult for them to comprehend the risks, and their health has deteriorated as a result of their failure to attend treatment and follow-up sessions in the Autism House and clinics for months. Children in this category are unable to articulate how they feel about the ongoing trends of people wearing masks and social isolation, which has been imposed in varied degrees for weeks, months, or even a short amount of time.

Deep Neural Network for Virus Mutation Prediction: A Comprehensive Review

Artificial intelligence (AI) and Deep Learning Algorithms are potential methods for preventing the alarmingly widespread RNA viruses and ensuring pandemic safety, they have become an integrative part of the modern scientific methodology, offering automated procedures for the prediction of a phenomenon based on past observations, unraveling underlying patterns in data and providing insights about the problem. With the continuous growth in the number of RNA Virus COVID-19 patients, likely, doctors and healthcare personnel won’t be helpful in treating every case. Thus, data scientists can help in the battle against RNA Viruses Mutations by implementing more innovative solutions in order to accomplish controlling severe acute respiratory syndrome quickly RNA Viruses are viruses that are made up of strands of RNA. This work studies the induction of machine learning models and motivating their design and purpose whenever possible. In the second part of this work, we analyze and discuss the biological data in the eyes of deep learning models. The core of our contributions rests in the role of machine learning in viruses pandemics. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Stress effect of COVID-19 pandemic among Egyptian children and adolescents with malignancy: a single-center experience

Background Thoughts and feelings of stress and worry are common for any person facing the challenges of a serious illness. Aim The aim was to assess the effect of COVID-19 on the psychological well-being of patients with malignancy compared with age-matched and sex-matched controls and to compare the psychological effect of COVID-19 with the psychological effect of malignancy among the patient group. Patients and methods This case-control study included 46 participants diagnosed with malignancy who were compared with 45 healthy age-matched and sex-matched individuals serving as a control group. Their ages were more than 8 years. All patients and controls were subjected to history taking with an emphasis on age, sex, educational level, history of chronic medical illness in the family, disease status, physical symptoms during the last 14 days, and data about COVID-19 infection. The psychological effect was measured using the Children's Revised Impact of Event Scale Crises-13. Results Mean age of the patient group was 11.76 +/- 3.31 years. There were 30 male and 16 female in the case group, who were compared with 45 age-matched and sex-matched healthy children and adolescents. There was a significantly higher prevalence of psychological stressful effect among the healthy children group than the oncological pediatric patients. The psychological effect related to malignancy diagnosis was significantly higher than the psychological effect related to COVID-19. Conclusion COVID-19 pandemic is a stressful event;however, the psychological effect related to cancer diagnosis among the oncological patients showed a higher stressful effect. (C) 2021 The Egyptian Journal of Haematology

Next Generation Sequence Prediction Intelligent System for SARS-COV-2 Using Deep Learning Neural Network

Viral mutations can occur that prevent antibody neutralization, an event known as viral escape, which can disrupt vaccine manufacturing. Viruses' potential to develop and escape the body's immune system, as well as the infection cause, is known as viral escape, and it continues to be a stumbling block in the development of treatments and vaccines. Understanding the rules of virus mutations can help in the development of a therapeutic plan. Using machine learning algorithms that designed for natural language processing was emulated for viral escape. The mutations that protect viral infectivity, but make a virus show up distinctive from the immune system, comparable to word changes that protect the language structure of a sentence, but change its meanings. In this work the seq2seq LSTM neural network language models applied on two datasets of different viruses like SARS-CoV-2 and HIV. The prediction model achieves accuracy 97 % for HIV validation dataset and 99.6% for coronavirus strain validation dataset. It shows superior results over other prediction techniques as well. © 2021 IEEE.

Examining the Effectiveness of Using Adaptive AI-Enabled e-Learning during the Pandemic of COVID-19.

This study aimed to identify the effect of using adaptive AI-enabled e-learning on developing digital content creative design skills among postgraduate students. The research tools included an achievement test and an observation checklist for rating the practical performance. Research results concluded that, regardless of learning styles, the proposed adaptive e-learning environment had a positive effect on developing both cognitive achievement and practical performance of digital content creative design skills. The results also indicated that there is a significant difference at the 0.01 level between the mean scores of the first experimental group's students using the global learning style-based adaptive e-learning environment and the second experimental group's students using the sequential learning style-based adaptive AI-enabled e-learning environment in the achievement test and observation checklist after measurement of digital content creative design skills in favor of the second experimental group's students. The study provided a number of suggestions and recommendations for making the utmost use of various design layouts of adaptive AI-enabled e-learning environments in developing different cognitive and performance aspects of learning as well as taking full advantage of digital content creative design skills mastery in producing a plethora of advanced electronic educational applications in the foreseeable future.

Natural Products Homoharringtonine and Emetine Alkaloids as SARS-CoV-2 Treatment Options.

BACKGROUND: Viruses are known as the major causative agents for infectious diseases globally. The coronaviruses are one of the serious pathogens to cause serious diseases in humans. Recently identified SARSCoV- 2 from Wuhan City, China, has emerged as a serious threat to human health and caused a global pandemic. Bats have been confirmed as a primary source of infection. The vaccination of the human population and animals serving as a potential reservoir is a straightforward strategy to control the transmission of any pathogen to humans. Natural products from many herbal plants are well known to have novel antiviral properties and evaluated against various viral diseases. There are many alkaloids that have shown to be effective against coronaviruses. METHODS: Recently, the antiviral efficacy of natural alkaloids known as Homoharringtonine (HTT) and Emetine has been evaluated and provided promising results against coronaviruses, including SARS-CoVs. These alkaloids may be very useful and can be used as antivirals against SARS-CoV-2 because they have already been reported to inhibit the replication of SASRS-CoV and other viruses in cell lines. CONCLUSION: This review specifically focuses on the recent findings of these alkaloids against coronaviruses and possible treatment options for SARS-CoV-2. It is expected that natural products as alkaloids from herbal plants could be considered as novel and valuable candidates for the new antiviral drugs against SARS-CoV-2.

Trends in philadelphia asthma encounters and pollution during the COVID-19 pandemic

Rationale: The COVID-19 pandemic dramatically changed daily routines as well as healthcare utilization and delivery patterns in the United States. We sought to identify changes in pediatric asthma-related healthcare utilization and levels of air pollution i.e. particulate matter (PM2.5, PM10) and gaseous chemicals (NO2, O3) during the COVID-19 pandemic in Philadelphia. We hypothesized that declining utilization of asthma care and changed pollution levels during the early stages of the pandemic rebounded after the relaxation of COVID-19-related public health measures. Methods: For the time period Mar 17 to Dec 17 during the years 2015-2020, asthmarelated encounters and weekly summaries of respiratory viral testing data were extracted from Children's Hospital of Philadelphia (CHOP) electronic health records. Daily average estimates of PM2.5, PM10, O3, and NO2 for the same time period were obtained from AirData, an EPA resource that provides quality-assured summary air pollution measures collected from outdoor regulatory monitors across the United States. Patterns in encounter characteristics and viral testing in Philadelphia from Mar 17 to Dec 17, 2020, were compared to data from 2015-2019 as a historical reference. Encounter pattern results were summarized as percentage changes. Controlled interrupted time series regression models were created to identify statistically significant differences in pollution levels that differed in 2020 compared with historical time periods. Results: We present data on asthma encounters, viral testing, and air pollution from Mar 2020 through Dec 2020. Contrary to the early stages of the pandemic when in-person asthma encounters decreased by 87% (outpatient) and 84% (emergency + inpatient), asthma-related encounters rebounded with the relaxation of COVID-19-related public health measures. During the initial months of the pandemic, the daily average of PM2.5, PM10, and NO2 levels decreased by 29.0% (2.17 μg/m3), 18.2% (3.13 μg/m3), and 44.1% (6.75 ppb), respectively, whereas ozone levels increased by 43.4% (10.08 ppb), changes that were not statistically significantly different compared to historical trends. Levels of all pollutants considered remained similar during subsequent 2020 months compared to the 2015-2019 reference period. Conclusion: The COVID-19 pandemic in Philadelphia was accompanied by initial decreases in pediatric asthma healthcare activity. Concurrent with the relaxation of COVID-19-related public health measures, there was a subsequent increase in asthma healthcare activity. No substantial change in air pollution levels compared with historical patterns was observed during the time period considered, suggesting that other factors influenced changes in asthma trends during the COVID-19 pandemic.

Evaluation of a Pseudovirus Neutralization Assay for SARS-CoV-2 and Correlation with Live Virus-Based Micro Neutralization Assay.

The unusual cases of pneumonia outbreak were reported from Wuhan city in late December 2019. Serological testing provides a powerful tool for the identification of prior infection and for epidemiological studies. Pseudotype virus neutralization assays are widely used for many viruses and applications in the fields of serology. The accuracy of pseudotype neutralizing assay allows for its use in low biosafety lab and provides a safe and effective alternative to the use of wild-type viruses. In this study, we evaluated the performance of this assay compared to the standard microneutralization assay as a reference. The lentiviral pseudotype particles were generated harboring the Spike gene of SARS-CoV-2. The generated pseudotype particles assay was used to evaluate the activity of neutralizing antibodies in 300 human serum samples from a COVID-19 sero-epidemiological study. Testing of these samples resulted in 55 positive samples and 245 negative samples by pseudotype viral particles assay while microneutralization assay resulted in 64 positive and 236 negative by MN assay. Compared to the MN, the pseudotyped viral particles assay showed a sensitivity of 85.94% and a specificity of 100%. Based on the data generated from this study, the pseudotype-based neutralization assay showed a reliable performance for the detection of neutralizing antibodies against SARS-CoV-2 and can be used safely and efficiently as a diagnostic tool in a biosafety level 2 laboratory.