Locating-dominating number of certain infinite families of convex polytopes with applications.

A convex hull of finitely many points in the Euclidean space Rd is known as a convex polytope. Graphically, they are planar graphs i.e. embeddable on R2. Minimum dominating sets possess diverse applications in computer science and engineering. Locating-dominating sets are a natural extension of dominating sets. Studying minimizing locating-dominating sets of convex polytopes reveal interesting distance-dominating related topological properties of these geometrical planar graphs. In this paper, exact value of the locating-dominating number is shown for one infinite family of convex polytopes. Moreover, tight upper bounds on γl-d are shown for two more infinite families. Tightness in the upper bounds is shown by employing an updated integer linear programming (ILP) model for the locating-dominating number γl-d of a fixed graph. Results are explained with help of some examples. The second part of the paper solves an open problem in Khan (2023) [28] which asks to find a domination-related parameter which delivers a correlation coefficient of ρ>0.9967 with the total π-electronic energy of lower benzenoid hydrocarbons. We show that the locating-dominating number γl-d delivers such a strong prediction potential. The paper is concluded with putting forward some open problems in this area.

COVID-ConvNet: A Convolutional Neural Network Classifier for Diagnosing COVID-19 Infection.

The novel coronavirus (COVID-19) pandemic still has a significant impact on the worldwide population's health and well-being. Effective patient screening, including radiological examination employing chest radiography as one of the main screening modalities, is an important step in the battle against the disease. Indeed, the earliest studies on COVID-19 found that patients infected with COVID-19 present with characteristic anomalies in chest radiography. In this paper, we introduce COVID-ConvNet, a deep convolutional neural network (DCNN) design suitable for detecting COVID-19 symptoms from chest X-ray (CXR) scans. The proposed deep learning (DL) model was trained and evaluated using 21,165 CXR images from the COVID-19 Database, a publicly available dataset. The experimental results demonstrate that our COVID-ConvNet model has a high prediction accuracy at 97.43% and outperforms recent related works by up to 5.9% in terms of prediction accuracy.

Salivary Antibody Responses to Two COVID-19 Vaccines following Different Vaccination Regimens.

Background: To date, little is known about the salivary mucosal immune response following different COVID-19 vaccine types or after a booster (3rd) dose of the BNT162b2 (BNT) vaccine. Methods: A total of 301 saliva samples were collected from vaccinated individuals and arranged into two cohorts: cohort 1 (n = 145), samples from individuals who had received two doses against SARS-CoV-2; cohort 2 (n = 156), samples from individuals who had received a booster of BNT vaccine. Cohorts 1 and 2 were sub-stratified into three groups based on the types of first and second doses (homologous BNT/BNT, homologous ChAdOx1/ChAdOx1, or heterologous BNT/ChAdOx1vaccinations). Salivary immunoglobulin G (IgG) response to SARS-CoV-2 spike glycoprotein was measured by ELISA, and clinical demographic data were collected from hospital records or questionnaires. Results: Salivary IgG antibody responses against different vaccines, whether homologous or heterogeneous vaccination regimens, showed similar levels in cohorts 1 and 2. Compiling all groups in cohort 1 and 2 showed significant, albeit weak, negative correlations between salivary IgG levels and time (r = -0.2, p = 0.03; r = -0.27, p = 0.003, respectively). In cohort 2, the durability of salivary IgG after a booster dose of BNT162b2 significantly dropped after 3 months compared to the <1 month and 1-3 months groups. Conclusions: Different COVID-19 vaccine types and regimens elicit similar salivary anti-SARS-CoV-2 IgG with modest waning over time. Boosting with BNT162b2 vaccine did not produce an evident increase in mucosal IgG response whereby COVID-19 recovered subjects show higher salivary IgG than naive, post-vaccination subjects. The ChAdOx1/ChAdOx1 regimen showed better correlation between salivary IgG levels and durability. These findings highlight the importance of developing oral or intra-nasal vaccines to induce stronger mucosal immunity.

Type I interferon autoantibodies in hospitalized patients with Middle East respiratory syndrome and association with outcomes and treatment effect of interferon beta-1b in MIRACLE clinical trial.

Background: Type I interferons (IFNs) are essential antiviral cytokines induced upon respiratory exposure to coronaviruses. Defects in type I IFN signaling can result in severe disease upon exposure to respiratory viral infection and are associated with worse clinical outcomes. Neutralizing autoantibodies (auto-Abs) to type I IFNs were reported as a risk factor for life-threatening COVID-19, but their presence has not been evaluated in patients with severe Middle East respiratory syndrome (MERS). Methods: We evaluated the prevalence of type I IFN auto-Abs in a cohort of hospitalized patients with MERS who were enrolled in a placebo-controlled clinical trial for treatment with IFN-ß1b and lopinavir-ritonavir (MIRACLE trial). Samples were tested for type I IFN auto-Abs using a multiplex particle-based assay. Results: Among the 62 enrolled patients, 15 (24.2%) were positive for immunoglobulin G auto-Abs for at least one subtype of type I IFNs. Auto-Abs positive patients were not different from auto-Abs negative patients in age, sex, or comorbidities. However, the majority (93.3%) of patients who were auto-Abs positive were critically ill and admitted to the ICU at the time of enrollment compared to 66% in the auto-Abs negative patients. The effect of treatment with IFN-ß1b and lopinavir-ritonavir did not significantly differ between the two groups. Conclusion: This study demonstrates the presence of type I IFN auto-Abs in hospitalized patients with MERS.

Immunogenicity of High-Dose MVA-Based MERS Vaccine Candidate in Mice and Camels.

The Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic pathogen that can transmit from dromedary camels to humans, causing severe pneumonia, with a 35% mortality rate. Vaccine candidates have been developed and tested in mice, camels, and humans. Previously, we developed a vaccine based on the modified vaccinia virus Ankara (MVA) viral vector, encoding a full-length spike protein of MERS-CoV, MVA-MERS. Here, we report the immunogenicity of high-dose MVA-MERS in prime-boost vaccinations in mice and camels. METHODS: Three groups of mice were immunised with MVA wild-type (MVA-wt) and MVA-MERS (MVA-wt/MVA-MERS), MVA-MERS/MVA-wt, or MVA-MERS/MVA-MERS. Camels were immunised with two doses of PBS, MVA-wt, or MVA-MERS. Antibody (Ab) responses were evaluated using ELISA and MERS pseudovirus neutralisation assays. RESULTS: Two high doses of MVA-MERS induced strong Ab responses in both mice and camels, including neutralising antibodies. Anti-MVA Ab responses did not affect the immune responses to the vaccine antigen (MERS-CoV spike). CONCLUSIONS: MVA-MERS vaccine, administered in a homologous prime-boost regimen, induced high levels of neutralising anti-MERS-CoV antibodies in mice and camels. This could be considered for further development and evaluation as a dromedary vaccine to reduce MERS-CoV transmission to humans.

Puberty Induction in Adolescent Males: Current Practice.

Puberty is a developmental stage characterized by the appearance of secondary sexual characteristics which leads to complete physical, psychosocial, and sexual maturation. The current practice of hormonal therapy to induce puberty in adolescent males is based on published consensus and expert opinion. Evidence-based guidelines on optimal timing and regimen in puberty induction in males are lacking, and this reflects some discrepancies in practice among endocrinologists. It is worth mentioning that the availability of various hormonal products in markets, their different routes of administration, and patients/parents' preference also have an impact on clinical decisions. This review outlines the current clinical approach to delayed puberty in boys with an emphasis on puberty induction.

Seroprevalence of COVID-19 in Riyadh city during the early increase of COVID-19 infections in Saudi Arabia, June 2020.

Severe acute respiratory syndrome coronavirus (SARS-CoV-2) emerged in December 2019 and caused a global pandemic of the Coronavirus Disease 2019 (COVID-19). More than 170 million cases have been reported worldwide with mortality rate of 1-3%. The detection of SARS-CoV-2 by molecular testing is limited to acute infections, therefore serological studies provide a better estimation of the virus spread in a population. This study aims to evaluate the seroprevalence of SARS-CoV-2 in the major city of Riyadh, Saudi Arabia during the sharp increase of the pandemic, in June 2020. Serum samples from non-COVID patients (n = 432), patients visiting hospitals for other complications and confirmed negative for COVID-19, and healthy blood donors (n = 350) were collected and evaluated using an in-house enzyme-linked immunosorbent assay (ELISA). The overall percentage of positive samples was 7.80% in the combined two populations (n = 782). The seroprevalence was lower in the blood donors (6%) than non-COVID-19 patients (9.25%), p = 0.0004. This seroprevalence rate is higher than the documented cases, indicating asymptomatic or mild unreported COVID-19 infections in these two populations. This warrants further national sero-surveys and highlights the importance of real-time serological surveillance during pandemics.

Herpetic Keratitis and Corneal Endothelitis Following COVID-19 Vaccination: A Case Series.

Herpetic corneal disease is the most common infectious cause of corneal blindness in developed countries. The majority of the infections are caused by the reactivation of the latent virus in the trigeminal ganglion. Environmental factors and physical stress are thought to contribute to viral reactivation. The pathognomonic lesion of the herpes simplex virus (HSV) is dendritic keratitis, which is visible on slit-lamp examination after fluorescein dye staining. A potential association between HSV reactivation and coronavirus disease 2019 (COVID-19) vaccines has been reported. In this case series, we present four cases of HSV reactivation in patients who received COVID-19 vaccination in Saudi Arabia from different medical centers. This report emphasizes the necessity of evaluating HSV reactivation as a potential side effect of COVID-19 vaccination. This is important because early diagnosis and timely management of herpetic lesions can potentially reduce the severity of infection.

Safety and immunogenicity of ChAdOx1 MERS vaccine candidate in healthy Middle Eastern adults (MERS002): an open-label, non-randomised, dose-escalation, phase 1b trial.

BACKGROUND: ChAdOx1-vectored vaccine candidates against several pathogens have been developed and tested in clinical trials and ChAdOx1 nCoV-19 has now been licensed for emergency use for COVID-19. We assessed the safety and immunogenicity of the ChAdOx1 MERS vaccine in a phase 1b trial in healthy Middle Eastern adults. METHOD: MERS002 is an open-label, non-randomised, dose-escalation, phase 1b trial. Healthy Middle Eastern adults aged 18-50 years were included in the study. ChAdOx1 MERS was administered as a single intramuscular injection into the deltoid muscle of the non-dominant arm at three different dose groups: 5·0 × 109 viral particles in a low-dose group, 2·5 × 1010 viral particles in an intermediate-dose group, and 5·0 × 1010 viral particles in a high-dose group. The primary objective was to assess the safety and tolerability of ChAdOx1 MERS, measured by the occurrence of solicited and unsolicited adverse events after vaccination for up to 28 days and occurrence of serious adverse events up to 6 months. The study is registered with ClinicalTrials.gov, NCT04170829. FINDINGS: Between Dec 17, 2019, and June 1, 2020, 24 participants were enrolled (six to the low-dose, nine to the intermediate-dose, and nine to the high-dose group) and received a dose; 23 were available for follow-up at 6 months. The one dose of ChAdOx1 MERS vaccine was well tolerated with no serious adverse event reported during the 6 months of follow-up. Most adverse events were mild (67, 74%) and moderate (17, 19%). Six (7%) severe adverse events were reported by two participants in the intermediate-dose group (two feverish, two headache, one joint pain, and one muscle pain). Pain at the injection site was the most common local and overall adverse event, reported by 15 (63%) of the 24 participants. The most common systemic adverse event was headache, reported by 14 (58%), followed by muscle pain reported by 13 (54%). The vaccine induced both antibody and T cell immune responses in all volunteers; antibodies peaked at day 28 and T cell responses peaked at day 14; and continued until the end of follow-up at 6 months. INTERPRETATION: The acceptable safety and immunogenicity data from this phase 1b trial of ChAdOx1 MERS vaccine candidate in Healthy Middle Eastern adults, combined with previous safety and immunogenicity data from a trial in the UK, support selecting the ChAdOx1 MERS vaccine for advancement into phase 2 clinical evaluation. FUNDING: UK Department of Health and Social Care, using UK Aid funding, managed by the UK National Institute for Health Research; and King Abdullah International Medical Research Center.

Ascorbic acid as an adjunctive therapy in critically ill patients with COVID-19: a propensity score matched study.

Ascorbic acid represents an appealing option for clinicians to utilize in the context of the global COVID-19 pandemic due to its proposed clinical efficacy, relative safety, and low cost. The aim of this study was to evaluate the efficacy and safety of using ascorbic acid in supplemental doses as adjunctive therapy for patients critically ill with COVID-19. This was a two-center, non-interventional, retrospective cohort study. All critically ill adult patients admitted to ICU with a confirmed COVID-19 diagnosis between March 1st and December 31st, 2020, were included in the final analysis. The study was conducted at two large governmental tertiary hospitals in Saudi Arabia. The purpose was to investigate the clinical outcomes of low-dose ascorbic acid as adjunctive therapy in COVID-19 after propensity score matching using baseline severity scores, systematic use of corticosteroids, and study centers. A number of 739 patients were included in this study, among whom 296 patients were included after propensity score matching. There was no association between the administration of ascorbic acid and in-hospital mortality or the 30-day mortality [OR (95% CI) 0.77 (0.47, 1.23), p value = 0.27 and OR (95% CI) 0.73 (0.43, 1.20), p value = 0.21, respectively]. Using ascorbic acid was associated with a lower incidence of thrombosis compared with the non-ascorbic-acid group [6.1% vs. 13% respectively; OR (95% CI) 0.42 (0.184, 0.937), p value = 0.03]. Low dose of ascorbic acid as an adjunctive therapy in COVID-19 critically ill patients was not associated with mortality benefits, but it was associated with a lower incidence of thrombosis. Further studies are required to confirm these findings.

A Comparative Study of Traffic Classification Techniques for Smart City Networks.

Smart city networks involve many applications that impose specific Quality of Service (QoS) requirements, thus representing a challenging scenario for network management. Solutions aiming to guarantee QoS support have not been deployed in large-scale networks. Traffic classification is a mechanism used to manage different aspects, including QoS requirements. However, conventional traffic classification methods, such as the port-based method, are inefficient because of their inability to handle dynamic port allocation and encryption. Traffic classification using machine learning has gained research interest as an alternative method to achieve high performance. In fact, machine learning embeds intelligence into network functions, thus improving network management. In this study, we apply machine learning algorithms to predict network traffic classification. We apply four supervised learning algorithms: support vector machine, random forest, k-nearest neighbors, and decision tree. We also apply a port-based method of traffic classification based on applications' popular assigned port numbers. Then, we compare the results of this method to those obtained from the machine learning algorithms. The evaluation results indicate that the decision tree algorithm provides the highest average accuracy among the evaluated algorithms, at 99.18%. Moreover, network traffic classification using machine learning provides more accurate results and higher performance than the port-based method.

Nationwide Seroprevalence of SARS-CoV-2 in Saudi Arabia.

BACKGROUND: Estimated seroprevalence of Coronavirus Infectious Disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) is a critical evidence for a better evaluation of the virus spread and monitoring the progress of COVID-19 pandemic in a population. In the Kingdom of Saudi Arabia (KSA), SARS-CoV-2 seroprevalence has been reported in specific regions, but an extensive nationwide study has not been reported. Here, we report a nationwide study to determine the prevalence of SARS-CoV-2 in the population of KSA during the pandemic, using serum samples from healthy blood donors, non-COVID patients and healthcare workers (HCWs) in six different regions of the kingdom, with addition samples from COVID-19 patients. METHODS: A total of 11,703 serum samples were collected from different regions of the KSA including; 5395 samples from residual healthy blood donors (D); 5877 samples from non-COVID patients collected through residual sera at clinical biochemistry labs from non-COVID patients (P); and 400 samples from consented HCWs. To determine the seroprevalence of SARS-CoV-2, all serum samples, in addition to positive control sera from RT-PCR confirmed COVID-19 patients, were subjected to in-house ELISA with a sample pooling strategy, which was further validated by testing individual samples that make up some of the pools, with a statistical estimation method to report seroprevalence estimates. RESULTS: Overall (combining D and P groups) seroprevalence estimate was around 11% in Saudi Arabia; and was 5.1% (Riyadh), 1.5% (Jazan), 18.4% (Qassim), 20.8% (Hail), 14.7% (ER; Alahsa), and 18.8% in Makkah. Makkah samples were only D group and had a rate of 24.4% and 12.8% in the cities of Makkah and Jeddah, respectively. The seroprevalence in Saudi Arabia across the sampled areas would be 12 times the reported COVID-19 infection rate. Among HCWs, 7.5% (4.95-10.16 CI 95%) had reactive antibodies to SARS-CoV-2 without reporting any previously confirmed infection. This was higher in HCWs with hypertension. The study also presents the demographics and prevalence of co-morbidities in HCWs and subset of non-COVID-19 population. INTERPRETATION: Our study estimates the overall national serological prevalence of COVID-19 in Saudi Arabia to be 11%, with an apparent disparity between regions. This indicates the prevalence of asymptomatic or mild unreported COVID-19 cases.

EDTD-SC: An IoT Sensor Deployment Strategy for Smart Cities.

A smart city is a geographical area that uses modern technologies to facilitate the lives of its residents. Wireless sensor networks (WSNs) are important components of smart cities. Deploying IoT sensors in WSNs is a challenging aspect of network design. Sensor deployment is performed to achieve objectives like increasing coverage, strengthening connectivity, improving robustness, or increasing the lifetime of a given WSN. Therefore, a sensor deployment method must be carefully designed to achieve such objective functions without exceeding the available budget. This study introduces a novel deployment algorithm, called the Evaluated Delaunay Triangulation-based Deployment for Smart Cities (EDTD-SC), which targets not only sensor distribution, but also sink placement. Our algorithm utilizes Delaunay triangulation and k-means clustering to find optimal locations to improve coverage while maintaining connectivity and robustness with obstacles existence in sensing area. The EDTD-SC has been applied to real-world areas and cities, such as Midtown Manhattan in New York in the United States of America. The results show that the EDTD-SC outperforms random and regular deployments in terms of area coverage and end-to-end-delay by 29.6% and 29.7%, respectively. Further, it exhibits significant performance in terms of resilience to attacks.

Factors associated with the presence of diabetic ketoacidosis: A retrospective analysis of patients with type 1 diabetes in Saudi Arabia.

BACKGROUND AND AIMS: To Investigate the factors associated with Diabetic Ketoacidosis (DKA) among patients with type 1 diabetes (T1D). METHODS: This was a descriptive, retrospective study conducted among 1118 patients with T1D, at the Prince Sultan Military Medical City, Riyadh, Saudi Arabia. After, exclusion process, 336 patients were selected for analysis. Among these, 105 patients with T1D were hospitalized for DKA, whereas 231 patients without DKA were outpatients who visited the hospital for T1D follow-up treatment. RESULTS: Bivariate analysis between patients with DKA and those without DKA revealed significant relationships in terms of gender (p = 0.014), age (p = 0.0001), body mass index (BMI) (p = 0.017), hemoglobin A1c (HbA1c) (p = 0.0001), duration of diabetes (p = 0.001) and clinic appointments (p = 0.001). From the logistic regression analysis, it was clear that females (OR 1.88; p = 0.038) had a higher risk for DKA. As compared to the age group of ≥30 years, those in the age category of 20-29 years (OR 1.35; p = 0.001) and teenagers (OR 3.64; p = 0.001) faced a higher risk of having DKA episodes. Compared with patients having HbA1c levels <8%, those showing HbA1c levels 8-9.9% (OR 1.77; p = 0.224) and ≥10% (OR 4.06; p = 0.003) revealed higher risk for DKA. Likewise, in comparison with the patients who were compliant to clinic appointments, those who were non-compliant to clinic appointments exhibited higher than six times the risk (OR 6.38; p = 0.0001) of being more prone to experiencing the DKA episodes. CONCLUSION: Patients with higher risk for DKA comprise, those having high HbA1c levels, longer period of diabetes duration, teenagers, female gender and non-compliant to clinic appointments.