Background: With the spread of coronavirus disease 2019 (COVID-19), most countries rushed to take early measures to control this disease. Aims: This paper describes and evaluates the Saudi Arabian strategic preparedness and response plan on COVID-19 up to 31 December 2020. Methods: Saudi Arabia adopted the World Health Organization’s guidelines on response to COVID-19, which are based on nine pillars of public health preparedness and response. The measures Saudi Arabia took are assessed against these pillars. Results: In response to COVID-19, Saudi Arabia prepared public and private institutions to deal with the pandemic. Saudi authorities established a governance system comprised of responsible committees to continuously monitor national and international updates, trace contacts, screen the population, raise awareness and take proper actions to contain the spread of this disease. After the announcement of the first case in Saudi Arabia, all schools, social events, sports activities, domestic travel and international flights were suspended. Restrictions on social movement, social and religious gatherings, travel and businesses were imposed ahead of the first 100 confirmed COVID-19 cases. The Hajj pilgrimage for 2020 was scaled down to limit participants and no cases of COVID-19 were detected among pilgrims. The country maintained all basic health services and immunization programmes and supported all proposals for COVID-19 drugs and vaccines. The country is working to develop its capacity to produce these products and achieve self-sufficiency. Conclusion: Saudi Arabia took extreme measures to respond to COVID-19 which contributed to limiting the spread and effect of the disease.

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It is tempting to suggest that consumption of tropical pigmented fruits and vegetables could be an effective strategy to combat prostate cancer.

The D3 system provides an early-warning framework for augmenting knowledge of known DDIs and deducing unknown DDIs. It shows promise in suggesting interaction pathways of research and evaluation interest and aiding clinicians in evaluating and adjusting courses of drug therapy.

Background/Aim: hERG potassium channels enhance tumor invasiveness and breast cancer proliferation. MicroRNA (miRNA) dysregulation during cancer controls gene regulation. The objective of this study was to identify miRNAs that regulate hERG expression in breast cancer. Materials and Methods: Putative miRNAs targeting hERG were identified by bioinformatic approaches and screened using a 3'UTR luciferase assay. Functional assessments of endogenous hERG regulation were made using whole-cell electrophysiology, proliferation assays, and cell-cycle analyses following miRNA, hERG siRNA, or control transfection. Results: miR-362-3p targeted hERG 3'UTR and was associated with higher survival rates in patients with breast cancer (HR=0.39, 95%CI=0.18-0.82). Enhanced miR-362-3p expression reduced hERG expression, peak current, and cell proliferation in cultured breast cancer cells (p<0.05). Conclusion: miR-362-3p mediates the transcriptional regulation of hERG and is associated with survival in breast cancer. The potential for miR-362-3p to serve as a biomarker and inform therapeutic strategies warrants further investigation.

Implantation of ICL for the correction of myopia was a safe procedure with good visual and refractive results from the early postoperative period to 1 year. Long-term follow-up is required to confirm the long-term safety of this implant.

The population models allow for a better understanding of the dynamical interactions with the environment and hence can provide a way for understanding the population changes. They are helpful in studying the biological invasions, environmental conservation and many other applications. These models become more complicated when accounting for the stochastic and/or random variations due to different sources. In the current work, a spectral technique is suggested to analyze the stochastic population model with random parameters. The model contains mixed sources of uncertainties, noise and uncertain parameters. The suggested algorithm uses the spectral decompositions for both types of randomness. The spectral techniques have the advantages of high rates of convergence. A deterministic system is derived using the statistical properties of the random bases. The classical analytical and/or numerical techniques can be used to analyze the deterministic system and obtain the solution statistics. The technique presented in the current work is applicable to many complex systems with both stochastic and random parameters. It has the advantage of separating the contributions due to different sources of uncertainty. Hence, the sensitivity index of any uncertain parameter can be evaluated. This is a clear advantage compared with other techniques used in the literature.

Background The COVID-19 pandemic remains an immediate and present concern, yet as of now there is still no approved therapeutic available for the treatment of COVID-19.This study aimed to investigate and report evidence concerning demographic characteristics and currently-used medications that contribute to the ultimate outcomes of COVID-19 ICU patients. Methods A retrospective cohort study was conducted among all COVID-19 patients in the Intensive Care Unit (ICU) of Asir Central Hospital in Saudi Arabia between the 1st and 30th of June 2020. Data extracted from patients’ medical records included their demographics, home medications, medications used to treat COVID-19, treatment durations, ICU stay, hospital stay, and ultimate outcome (recovery or death).Descriptive statistics and regression modelling were used to analyze and compare the results. The study was approved by the Institutional Ethics Committees at both Asir Central Hospital and King Khalid University. Results A total of 118 patients with median age of 57 years having definite clinical and disease outcomes were included in the study. Male patients accounted for 87% of the study population, and more than 65% experienced at least one comorbidity. The mean hospital and ICU stay was 11.4 and 9.8 days, respectively. The most common drugs used were tocilizumab (31.4%), triple combination therapy (45.8%), favipiravir (56.8%), dexamethasone (86.7%), and enoxaparin (83%). Treatment with enoxaparin significantly reduced the length of ICU stay (p = 0.04) and was found to be associated with mortality reduction in patients aged 50−75 (p = 0.03), whereas the triple regimen therapy and tocilizumab significantly increased the length of ICU stay in all patients (p = 0.01, p = 0.02 respectively). Conclusion COVID-19 tends to affect males more significantly than females. The use of enoxaparin is an important part of COVID-19 treatment, especially for those above 50 years of age, while the use of triple combination therapy and tocilizumab in COVID-19 protocols should be reevaluated and restricted to patients who have high likelihood of benefit.