In-silico analysis of nsSNPs in human CYP3A4/5 and their effects on drug-enzymes interactions of FDA-approved COVID-19 antiviral drugs: A pharmacogenetic study (preprint)

Single nucleotide polymorphisms (SNPs) represent the prevailing form of genetic variations observed in the human population. Such variations could alter the encoded enzymes’ activities. CYP3A4/5 enzymes have a pivotal role in metabolising drugs, notably antivirals against SARS-CoV-2. In this work we computationally investigated antiviral-enzyme interactions of CYP3A4/5 genetic variants. We also examined the deleterious impact of 751 non-synonymous single nucleotide polymorphisms (nsSNPs) within the CYP3A4/5 genes. An ensemble of bioinformatics tools, [SIFT, PolyPhen, cadd, revel, metaLr, mutation assessor, Panther, SNP&GO, PhD-SNP, SNAP, Meta-SNP, FATHMM, I-Mutante, MuPro, INPS, CONSURF, GPS 5.0, MusiteDeep and NetPhos], identified a total of 94 variants (47 nsSNPs in CYP3A4, 47 nsSNPs in CYP3A5) to potentially impact the structural integrity as well as the activity of the CYP3A4/5 enzymes. Molecular docking was done to recognize the structural stability and binding properties of the CYP3A4/5 protein isoforms with 3 FDA-approved antiviral drugs. It was concluded that for the gene CYP3A4; the variants R418T, I335T and R130P while the CYP3A5 SNPs; I335T, L133P and R130Q are considered the most deleterious nsSNPs, potentially affecting drug-binding. Cataloguing deleterious SNPs is vital for personalized gene-based pharmacotherapy.

Synthesis, Antimicrobial, and Antibiofilm Activities of Some Novel 7-Methoxyquinoline Derivatives Bearing Sulfonamide Moiety against Urinary Tract Infection-Causing Pathogenic Microbes.

A new series of 4-((7-methoxyquinolin-4-yl) amino)-N-(substituted) benzenesulfonamide 3(a-s) was synthesized via the reaction of 4-chloro-7-methoxyquinoline 1 with various sulfa drugs. The structural elucidation was verified based on spectroscopic data analysis. All the target compounds were screened for their antimicrobial activity against Gram-positive bacteria, Gram-negative bacteria, and unicellular fungi. The results revealed that compound 3l has the highest effect on most tested bacterial and unicellular fungal strains. The highest effect of compound 3l was observed against E. coli and C. albicans with MIC = 7.812 and 31.125 µg/mL, respectively. Compounds 3c and 3d showed broad-spectrum antimicrobial activity, but the activity was lower than that of 3l. The antibiofilm activity of compound 3l was measured against different pathogenic microbes isolated from the urinary tract. Compound 3l could achieve biofilm extension at its adhesion strength. After adding 10.0 µg/mL of compound 3l, the highest percentage was 94.60% for E. coli, 91.74% for P. aeruginosa, and 98.03% for C. neoformans. Moreover, in the protein leakage assay, the quantity of cellular protein discharged from E. coli was 180.25 µg/mL after treatment with 1.0 mg/mL of compound 3l, which explains the creation of holes in the cell membrane of E. coli and proves compound 3l's antibacterial and antibiofilm properties. Additionally, in silico ADME prediction analyses of compounds 3c, 3d, and 3l revealed promising results, indicating the presence of drug-like properties.

The Black Swan for Green Supply Chain Management in Pakistan

For the last few decades, the business practices have primarily been focusing on the green and sustainable practices that mainly focus on the preservation of the environment and correspond to corporate social responsibility. But the sudden outbreak of the COVID-19 pandemic has left unprecedented effects on the business world. Against this backdrop, the current study entails investigation of the antecedents and consequences of green supply chain management in the post-COVID-19 era. The term black swan stands true for the event. The term could be believed to be accurate as all aspects of the supply chain have been observed to be influenced by the swan (customers with panic/regulated buying, suppliers with hoarding, inventories witnessing bullwhip effects). The current study, therefore, offers a novel explanation by linking various actors of green supply chain management and how the interplay of those actors can influence the supply chain and overall firm performance post COVID-19.

A new Covid-19 diagnosis strategy using a modified KNN classifier.

Covid-19 is a very dangerous disease as a result of the rapid and unprecedented spread of any previous disease. It is truly a crisis that threatens the world since its first appearance in December 2019 until our time. Due to the lack of a vaccine that has proved sufficiently effective so far, the rapid and more accurate diagnosis of this disease is extremely necessary to enable the medical staff to identify infected cases and isolate them from the rest to prevent further loss of life. In this paper, Covid-19 diagnostic strategy (CDS) as a new classification strategy that consists of two basic phases: Feature selection phase (FSP) and diagnosis phase (DP) has been introduced. During the first phase called FSP, the best set of features in laboratory test findings for Covid-19 patients will be selected using enhanced gray wolf optimization (EGWO). EGWO combines both types of selection techniques called wrapper and filter. Accordingly, EGWO includes two stages called filter stage (FS) and wrapper stage (WS). While FS uses many different filter methods, WS uses a wrapper method called binary gray wolf optimization (BGWO). The second phase called DP aims to give fast and more accurate diagnosis using a hybrid diagnosis methodology (HDM) based on the selected features from FSP. In fact, the HDM consists of two phases called weighting patient phase (WP2) and diagnostic patient phase (DP2). WP2 aims to calculate the belonging degree of each patient in the testing dataset to class category using naïve Bayes (NB) as a weight method. On the other hand, K-nearest neighbor (KNN) will be used in DP2 based on the weights of patients in the testing dataset as a new training dataset to give rapid and more accurate detection. The suggested CDS outperforms other strategies according to accuracy, precision, recall (or sensitivity) and F-measure calculations that are equal to 99%, 88%, 90% and 91%, respectively, as showed in experimental results.

Association between sociodemographic characteristics and knowledge and practice of COVID-19 measures among households in Mombasa and Kilifi County, Kenya.

BACKGROUND: Coronavirus disease 2019 (COVID-19), declared a global pandemic by the World Health Organization (WHO), is a severe acute respiratory disease. The Kenyan Ministry of Health (MoH) put in place measures that included mandatory face masking, hand and cough hygiene and social and physical distancing to reduce disease transmission and increase prevention efforts. The primary objective of this study was to determine how sociodemographic characteristics affect knowledge and practice of the above measures. METHODS: A cross-sectional study was conducted to assess water, sanitation and hygiene practices for the prevention and control of COVID-19 in Kilifi and Mombasa Counties, Kenya. Data collection was accomplished through a mobile data collection tool. Principal component analysis was used to create a wealth index using data on asset ownership and housing characteristics. Bloom cut-off points of 80-100%, 60-79% and ≤59% were used to determine knowledge and practice. RESULTS: Of the 612 households, 339 (55.4%) were from Kilifi County and 273 (44.6%) were from Mombasa County. A total of 431 (70.4%) were female and the mean age of the household members was 38.2±14.8 y.Almost all (99.2%) respondents were aware of COVID-19, with 60% knowing prevention, symptoms and persons at a higher risk of contracting the virus. Females had the highest knowledge of COVID-19 and were likely to practice prevention and control measures, unlike males. Age was significant (p<0.05) with knowledge and practice. CONCLUSIONS: The sociodemographic characteristics of populations play a key role in behavioural aspects as far as prevention and control of COVID-19 are concerned. There is a need for partnerships between the MoH and county governments to put in place a multisectoral community approach to advance feasible behavioural interventions among targeted populations towards combating the spread of COVID-19.

Rapid One-Pot Microwave Assisted Green Synthesis Nitrogen Doped Carbon Quantum Dots as Fluorescent Precursor for Estimation of Modafinil as Post-Covid Neurological Drug in Human Plasma with Greenness Assessments.

The neuro-stimulant anti-narcoleptic drug as modafinil (MOD) is used to treatment neurological conditions caused by COVID-19. MOD was used to treatment narcolepsy, shift-work sleep disorder, and obstructive sleep apnea-related sleepiness. So, an innovative, quick, economical, selective, and ecologically friendly procedure was carried out. A highly sensitive N@CQDs technique was created from green Eruca sativa leaves in about 4 min using microwave synthesis at 700 w. The quantum yield of the synthesized N@CQDs was found to be 41.39%. By increasing the concentration of MOD, the quantum dots' fluorescence intensity was gradually quenched. After being excited at 445 nm, the fluorescence reading was recorded at 515 nm. The linear range was found to be in the range 50 - 700 ng mL-1 with lower limit of quantitation (LOQ) equal to 45.00 ng mL-1. The current method was fully validated and bio analytically according to (US-FDA and ICH) guidelines. Full characterization of the N@CQDs has been conducted by high resolution transmission electron microscope (HRTEM), Zeta potential measurement, fluorescence, UV-VIS, and FTIR spectroscopy. Various experimental variables including pH, QDs concentration and the reaction time were optimized. The proposed study is simply implemented for the therapeutic drug monitoring system (TDMS) and various clinical laboratories for further pharmacokinetic research.

Red piranha optimization (RPO): a natural inspired meta-heuristic algorithm for solving complex optimization problems

An optimization algorithm is a step-by-step procedure which aims to achieve an optimum value (maximum or minimum) of an objective function. Several natural inspired meta-heuristic algorithms have been inspired to solve complex optimization problems by utilizing the potential advantages of swarm intelligence. In this paper, a new nature-inspired optimization algorithm which mimics the social hunting behavior of Red Piranha is developed, which is called Red Piranha Optimization (RPO). Although the piranha fish is famous for its extreme ferocity and thirst for blood, it sets the best examples of cooperation and organized teamwork, especially in the case of hunting or saving their eggs. The proposed RPO is established through three sequential phases, namely;(i) searching for a prey, (ii) encircling the prey, and (iii) attacking the prey. A mathematical model is provided for each phase of the proposed algorithm. RPO has salient properties such as;(i) it is very simple and easy to implement, (ii) it has a perfect ability to bypass local optima, and (iii) it can be employed for solving complex optimization problems covering different disciplines. To ensure the efficiency of the proposed RPO, it has been applied in feature selection, which is one of the important steps in solving the classification problem. Hence, recent bio-inspired optimization algorithms as well as the proposed RPO have been employed for selecting the most important features for diagnosing Covid-19. Experimental results have proven the effectiveness of the proposed RPO as it outperforms the recent bio-inspired optimization techniques according to accuracy, execution time, micro average precision, micro average recall, macro average precision, macro average recall, and f-measure calculations.

Functional, Multivariate Functional and Spatial PCA: Application to Covid-19 Data in the African Continent

Covid-19 pandemic has negatively impacted many areas, including the economy and health care facilities, and has left more than 5 million deaths worldwide. In this paper, we use functional data analysis methods to describe evolution of the number of cases and the number of deaths of Covid-19 in Africa. We perform functional principal component analysis, Multivariate functional component analysis and spatial component analysis to characterize better the phenomena and spatial data to determine the impact of a region's neighborhood on number of cases. The obtained results allow us to have a better knowledge of the evolution of the pandemic in African continent. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

SARS-CoV-2 vaccines from A to Z: A review of the current challenges

COVID-19 pandemic is a major worldwide health disaster firstly reported in December 2019. The Food and Drug Administration (FDA) has offered the public hope of halting it, authorizing vaccinations for emergency use with more than 85% efficacy against serious acute respiratory syndrome (SARS-CoV-2). Recent outbreaks of SARS-CoV-2 variations including spike-protein mutations, the key vaccines viral target for immune response, have prompted a thorough investigation into the vaccine's long-term effectiveness. Consequently, this review assayed the details on SARS-CoV-2 infection mechanism and how to control the infection by different types of SARS-CoV-2 vaccines, and their effectiveness against other mutant strains. Additionally, the review summarized the different complaints which have been recorded after vaccination. In conclusion, these negative effects must be constantly weighed against the predicted advantages in terms of disease prevention. Although COVID-19 vaccination is recommended for everyone aged 5 years and older, SARS-CoV-2 is high likely to continue to be a pandemic infectious as a result of the broadcasting of variants of the virus. Therefore, a booster vaccination, wearing a mask, and social distancing should be maintained. © 2023 Global NEST.

Strategies to save energy in the context of the energy crisis: a review.

New technologies, systems, societal organization and policies for energy saving are urgently needed in the context of accelerated climate change, the Ukraine conflict and the past coronavirus disease 2019 pandemic. For instance, concerns about market and policy responses that could lead to new lock-ins, such as investing in liquefied natural gas infrastructure and using all available fossil fuels to compensate for Russian gas supply cuts, may hinder decarbonization efforts. Here we review energy-saving solutions with a focus on the actual energy crisis, green alternatives to fossil fuel heating, energy saving in buildings and transportation, artificial intelligence for sustainable energy, and implications for the environment and society. Green alternatives include biomass boilers and stoves, hybrid heat pumps, geothermal heating, solar thermal systems, solar photovoltaics systems into electric boilers, compressed natural gas and hydrogen. We also detail case studies in Germany which is planning a 100% renewable energy switch by 2050 and developing the storage of compressed air in China, with emphasis on technical and economic aspects. The global energy consumption in 2020 was 30.01% for the industry, 26.18% for transport, and 22.08% for residential sectors. 10-40% of energy consumption can be reduced using renewable energy sources, passive design strategies, smart grid analytics, energy-efficient building systems, and intelligent energy monitoring. Electric vehicles offer the highest cost-per-kilometer reduction of 75% and the lowest energy loss of 33%, yet battery-related issues, cost, and weight are challenging. 5-30% of energy can be saved using automated and networked vehicles. Artificial intelligence shows a huge potential in energy saving by improving weather forecasting and machine maintenance and enabling connectivity across homes, workplaces, and transportation. For instance, 18.97-42.60% of energy consumption can be reduced in buildings through deep neural networking. In the electricity sector, artificial intelligence can automate power generation, distribution, and transmission operations, balance the grid without human intervention, enable lightning-speed trading and arbitrage decisions at scale, and eliminate the need for manual adjustments by end-users.

Medium-Term Outcomes in COVID-19.

COVID-19 causes severe illness that results in morbidity and mortality. Electrocardiographic features, including QT prolongation, have been associated with poor acute outcomes; data on the medium-term outcomes remain scarce. This study evaluated the 1-year outcomes of patients who survived the acute COVID-19 infection. METHODS AND MATERIALS: Data of the 159 patients who survived the COVID-19 illness during the first wave (1 March 2020-18 May 2020) were collected. Patient demographics, laboratory findings and electrocardiography data were evaluated. Patients who subsequently died within 1-year of the index illness were compared to those who remained well. RESULTS: Of the 159 patients who had survived the index illness, 28 (17.6%) subsequently perished within 1-year. In comparison to the patients that were alive after 1-year, the deceased were older (68 vs. 83 years, p < 0.01) and equally male (60.4% vs. 53.6%, p = 0.68), with a similar proportion of hypertension (59.5% vs. 57.1%, p = 0.68), diabetes (25.2% vs. 39.2%, p = 0.096) and ischaemic heart disease (11.5% vs. 7.1%, p = 0.54). The QTc interval for the alive and deceased patients shortened by a similar degree from the illness to post-COVID (-26 ± 33.5 vs. -20.6 ± 30.04 milliseconds, p = 0.5); the post-COVID R-R interval was longer in the alive patients compared to the deceased (818.9 ± 169.3 vs. 761.1 ± 61.2 ms, p = 0.02). A multivariate Cox regression analysis revealed that age (HR1.098 [1.045-1.153], p < 0.01), diabetes (HR3.972 [1.47-10.8], p < 0.01) and the post-COVID R-R interval (HR0.993 [0.989-0.996], p < 0.01) were associated with 1-year mortality. CONCLUSIONS: The COVID-19-associated mortality risk extends to the post-COVID period. The QTc does recover following the acute illness and is not associated with outcomes; the R-R interval is a predictor of 1-year mortality.

COVID-19 and a trade-off between health and economics: an extended inoperability model for Italy

Purpose: The recent COVID-19 has obliged governments to enact large-scale policies to contain it. A topic of economic debate is the quantification of the impact that these policies can create in the economy, with the aim of activating regulatory mechanisms to minimize this impact. In this vein, this study aims to propose a quantification of the effects of the Italian government policy that blocks nonessential production activities. Design/methodology/approach: The authors use a multisectoral extended inoperability model on the social accounting matrix of Italy. The analysis identifies the pandemic's impact on outputs, endogenous demands, value-added and disposable incomes of institutional sectors. Findings: The construction and real estate sectors revealed a significant contraction followed by the retail trade and hotel and catering services sectors. The output contraction further impacts the value-added generation, disposable income and final demand components. Originality/value: The current pandemic is alleged to have a greater impact than the epidemics of the past century, considering the present dimension of the world economy and the increasing interconnections between industries and institutions. In this scenario, it is challenging to safeguard not only human health and life but also the economy. Hence, there is a need to establish a trade-off between health and economics;and in this regard, the current study empirically quantifies the impact of health measures on the economy. The findings of this study help identify the sectors that are more prone to disaster effects and also present the structure of income circular flow in the Italian economy. © 2021, Emerald Publishing Limited.

Investigating COVID-19 spillovers in the US economy with a dynamic CGE model

PurposeThe recent COVID-19 is forcing governments to implement policies on a large scale to counter its spread. A central issue in the economic debate is the effective quantification of the impact that the policies may implicitly have on the economy. This study quantifies the effects of lockdown in the United States.Design/methodology/approach The study uses a dynamic computable general equilibrium (DCGE) model calibrated on a social accounting matrix (SAM). The lockdown policy is applied on the supply side, by using a reduction in the production according to the closing time of each industry. The reduction in the demand is also applied, throughout the contraction of the household consumption that is diversified by the commodities. In order to analyse the pure effect of the lockdown policy, the interventions by the policy makers are not considered in this study.FindingsThe results show an important contraction of productivity in the food industry, the real estate activities, the constructions and the general services.Originality/valueThe contraction produces a fall of the GDP for the whole period analysed, traced by the investments, which includes repercussions on the whole productive system, employment and income of the institutional sectors.

Mutations in SARS-CoV-2: Insights on structure, variants, vaccines, and biomedical interventions.

COVID-19 is a worldwide pandemic caused by SARS-coronavirus-2 (SARS-CoV-2). Less than a year after the emergence of the Covid-19 pandemic, many vaccines have arrived on the market with innovative technologies in the field of vaccinology. Based on the use of messenger RNA (mRNA) encoding the Spike SARS-Cov-2 protein or on the use of recombinant adenovirus vectors enabling the gene encoding the Spike protein to be introduced into our cells, these strategies make it possible to envisage the vaccination in a new light with tools that are more scalable than the vaccine strategies used so far. Faced with the appearance of new variants, which will gradually take precedence over the strain at the origin of the pandemic, these new strategies will allow a much faster update of vaccines to fight against these new variants, some of which may escape neutralization by vaccine antibodies. However, only a vaccination policy based on rapid and massive vaccination of the population but requiring a supply of sufficient doses could make it possible to combat the emergence of these variants. Indeed, the greater the number of infected individuals, the faster the virus multiplies, with an increased risk of the emergence of variants in these RNA viruses. This review will discuss SARS-CoV-2 pathophysiology and evolution approaches in altered transmission platforms and emphasize the different mutations and how they influence the virus characteristics. Also, this article summarizes the common vaccines and the implication of the mutations and genetic variety of SARS-CoV-2 on the COVID-19 biomedical arbitrations.

Remdesivir.

Remdesivir, marketed under the brand name Veklury, is an antiviral drug with a broad spectrum of activity. There were various countries where the use of Remdesivir for the treatment of COVID-19 was authorized during the pandemic. Remdesivir was first designed to treat hepatitis C, but it was later tested for Ebola virus sickness and Marburg virus infections. Remdesivir is a prodrug designed to facilitate the intracellular transport of GS-441524 monophosphate and its subsequent biotransformation into GS-441524 triphosphate, a ribonucleotide analogue inhibitor of viral RNA polymerase. The objective of this chapter is to provide a comprehensive review of Remdesivir (GS-5734), including its nomenclature, physiochemical properties, preparation methods, identification procedures, numerous qualitative and quantitative analytical techniques, ADME profiles, and pharmacological effects. In addition, the chapter provides a variety of chromatographic and spectroscopic techniques for separating brimonidine from other drugs in combination formulations.

COVID-19 Vaccine Uptake and Hesitancy among Pregnant and Lactating Women in Saudi Arabia.

INTRODUCTION: Pregnant and breastfeeding women comprise a high-risk group for the development of severe COVID-19. Therefore, vaccination is highly recommended for perinatal women; however, vaccination levels for this group remain inadequate. This study explores the percentage of COVID-19 vaccination among Saudi pregnant and lactating women, as well as their attitudes toward it. METHODS: We conducted a cross-sectional questionnaire-based survey on a sample of Saudi pregnant and breastfeeding women. The study included pregnant and lactating women. RESULTS: The percentage of COVID-19 vaccine uptake was 78.2%. A total of 45 (21.8%) out of 206 women did not receive the vaccine. The overall vaccine hesitancy was 21.8%. Breastfeeding women were 2.86 more likely not to receive the vaccine as compared to pregnant women. Being a mother of over five children increased the vaccine uptake among our participating women (n = 20, 90%; p < 0.01). The majority of the subjects had taken the Pfizer vaccine (81.98%, 132/161). The availability of the COVID-19 vaccine was the most common factor for choosing a particular vaccine. Protection from infection (60.2%, 97/161) was reported as the main driver for vaccine uptake. The most common reason perceived for delaying COVID-19 vaccination was being worried about the side effects (176, 85.44%) on one's own body and the effects on the unborn child (130, 63.1%). CONCLUSION: We uncovered high levels of hesitancy, primarily induced by concerns about adverse effects and social media-related misinformation. These high levels of vaccine uptake are likely due to the large-scale obligatory vaccination program provided in Saudi Arabia, which was well-structured and far reaching. Our results provide further support for the so-called "protection motivation theory" in boosting vaccine acceptance. Counseling and educating pregnant and breastfeeding women about COVID-19 vaccination is the need of the hour.

A Mathematical Model of the Ongoing Coronavirus Disease (COVID-19) Pandemic: a Case Study in Turkey

Turkey reported the first case of COVID-19 on 11 March 2020 since the outbreak of the deadly coronavirus pandemic. COVID-19 spread rapidly in Turkey, where about a total of 3,208,173 cases of infected persons were registered by 29 March 2021 with 2,957,093 cases of recovered persons and 31,076 reported deaths. A new mathematical COVID-19 model containing six classes is presented. Also, the positive invariant region of the solutions, basic reproductive number, disease-free equilibrium, and its stability are highlighted. Afterward, the disease-free equilibrium is locally asymptotically stable when R0 < 1. Moreover, the proposed model was further generalized to the fractional-order derivative in the AtanganaBaleanu (ABC) context for a more successful realization. Besides, the existence and uniqueness of solutions via techniques of Schaefer's and Banach fixed point theorems were established. Based on the publicly recorded number of infected people from 1-31 July 2020 in Turkey and least-squares curve fitting techniques with fminsearch function the fractionalorders model has been validated and can better fit the data compared with the integer-order model. Also, using the Atangana-Toufik scheme, numerical solutions, as well as simulations, are presented for different values of fractional order. © 2022, Thammasat University. All rights reserved.

Radium 223 audit in Southend Hospital from the implementation of treatment in January 2018

Category: Prostate Background to the audit: On top of conventional chemotherapy and hormonal manipulation, radium 223 treatment, which is given over six cycles, has been shown to improve symptoms and survival for castration-resistant metastatic prostate cancer in a previous alpharadin in symptomatic prostate cancer (ALSYMPCA) study. Standard: Inclusion and exclusion criteria were set out as per the original study. Indicator: The indication of this audit is to compare the safety and efficacy of our Mid and South Essex patients who received radium 223 treatment since the implementation of treatment in our trust in January 2018. Target: All the patients who received radium 223 treatment between January 2018 and November 2021 were included. Methodology: It was a retrospective cohort study. Results of first audit round: Our audit had fewer patients (n=36) compared with the original study (n=614). It demonstrated comparable inclusion and exclusion criteria for the treatment. However, we had lower overall survival of 13.5 months for the patients who completed six cycles of radium 223 compared with 14.9 months in the ALSYMPCA study. Being a single-centre audit, having older patients with poorer performance status, less bisphosphonate use and the global COVID pandemic during the time of our audit could have affected the survival outcome. However, when we compared our results with another UK study done in Mount Vernon and Lister Hospitals, they had comparable overall survival (13.1 months) for patients who completed all six doses of radium 223. First action plan: To continue current practice of careful patient selection for radium 223 treatment. To encourage use of bisphosphonate to help improve bony pain. References: 1. Parker C, Nilsson S, Heinrich D et al. Alpha emitter radium-223 and survival in metastatic prostate cancer. N Engl J Med 2013;369(3): 213-223. 2. Dadhania S, Alonzi R, Douglas S et al. Single-centre experience of use of radium 223 with clinical outcomes based on number of cycles and bone marrow toxicity. Anticancer Res 2018;38(9): 5423-5427. 3. Saad F, Sternberg CN, Mulders PF, Niepel D, Tombal BF. The role of bisphosphonates or denosumab in light of the availability of new therapies for prostate cancer. Cancer Treat Rev 2018;68: 25-37. Copyright © 2022

Knowledge, Attitude and Practice toward COVID-19 among the Population attending primary healthcare centers in Makkah Al-Mukarramah Saudi Arabia 2022

Background: Since the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) as a pandemic, it has become a major challenging public health problem worldwide. This pandemic has affected all aspects of Population life in almost all nations and among all socioeconomic groups. Population of all types are facing an unprecedented crisis with the rapid spread of COVID-19 and severity of the disease in many infected individuals. As such many healthcare systems have been overwhelmed and HCWs presented with work load . There is a potential shortage of physical resources, such as ventilators and intensive care unit beds, needed to care for surges of critically ill patients, however, additional medical supplies and beds will be of limited help unless there is an adequate medical workforce, as the Middle East respiratory syndrome coronavirus (MERS-CoV) continues to occur in small outbreaks in Saudi Arabia. Aim of the study: To assessment the Knowledge, Attitude and Practice toward COVID-19 among the Population attending primary healthcare centers in Makkah Al-Mukarramah Saudi Arabia 2022. Method(s): Cross sectional study, was conducted among Saudi Arabia population in primary health care center in Makkah Al-Mukarramah. The questionnaire collected socio-demographic characteristics, assessment of Knowledge, Attitude and Practice toward COVID-19 Our total participants were(200). Result(s): show the relation of participant to Attitude, knowledge, Practice score towards COVID-19 regarding the Attitude the most of participants high attitude were (78.0) heave a significant relation were P-value <0.001 and X2187.240, regarding the knowledge the most of participants high knowledge were (61.0%) P-value <0.001 and X270.360, the Practice the most of participants high Practice were (77.0%) a significant relation were P-value <0.001 and X2174.040. Conclusion(s): Study participants from KSA, not adequate knowledge, positive attitude, and acceptable practices towards COVID-19 Knowledge. Electronic and social media should be effectively utilized to spread awareness of COVID-19 among the public, the Population worry levels regarding transmitting for COVID-19 during the early stage of the COVID-19 pandemic, and subsequent awareness campaigns that were conducted were associated with increased knowledge, adherence to protective hygienic practices and reduction of anxiety toward the COVID-19 pandemic. Copyright © 2022 Ubiquity Press. All rights reserved.

An Analysis of Aesthetic Concerns Identified by Video Conferencing.

Background During and after the coronavirus disease 2019 (COVID-19) pandemic, there was a significant increase in the demand for aesthetic procedures nationwide. We believe that one of the factors contributing to this increase was the use of video conferencing apps. Therefore, the purpose of this study was to analyze the aesthetic concerns that were identified by video conferencing. Methodology In Saudi Arabia, an observational, cross-sectional study was conducted from February to April, 2022. An online survey was used to assess the aesthetic concerns raised by video conferencing. The survey addressed multiple aspects, including demographic data, information on video call utilization, the attentional focus of the participants during video calls, and new appearance concerns identified on video calls. Results The survey successfully captured 432 adult participants. More than 85% of participants disliked at least one character of their appearance during video conferencing. The skin color type (based on the Fitzpatrick scale), time spent on video calls, and visual focus during the virtual meeting were significantly correlated with self-perception of new disliked features. Conclusion Video conferencing showed a significant statistical correlation with identified disliked facial/body features in both genders. People with skin color type III were less likely to perceive a disliked feature through video conferencing applications. The likelihood of having a disliked feature was significantly higher among individuals who spent up to one hour per day using video calls. Additionally, those who mainly paid attention to their face or body during virtual meetings were more likely to have disliked features.