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Background The Kingdom of Saudi Arabia’s (KSA) health sector is undergoing rapid reform in line with the National Transformation Program, as part of Saudi’s vision for the future, Vision 2030. From a nursing human resources for health (HRH) perspective, there are challenges of low nursing school capacity, high employment of expatriates, labor market fragmentation, shortage of nurses in rural areas, uneven quality, and gender challenges. Case presentation This case study summarizes Saudi Ministry of Health (MOH) and Saudi Health Council’s (SHCs) evaluation of the current challenges facing the nursing profession in the KSA. We propose policy interventions to support the transformation of nursing into a profession that contributes to efficient, high-quality healthcare for every Saudi citizen. Key to the success of modernizing the Saudi workforce will be an improved pipeline of nurses that leads from middle and high school to nursing school; followed by a diverse career path that includes postgraduate education. To retain nurses in the profession, there are opportunities to make nursing practice more attractive and family friendly. Interventions include reducing shift length, redesigning the nursing team to add more allied health workers, and introducing locum tenens staffing to balance work-load. There are opportunities to modernize existing nurse postgraduate education, open new postgraduate programs in nursing, and create new positions and career paths for nurses such as telenursing, informatics, and quality. Rural pipelines should be created, with incentives and increased compensation packages for underserved areas. Conclusions Critical to these proposed reforms is the collaboration of the MOH with partners across the healthcare system, particularly the private sector. Human resources planning should be sector-wide and nursing leadership should be strengthened at all levels.

Hypogammaglobulinemia is a heterogeneous group of innate and acquired antibody deficiency with variable disease severity, recurrent pneumonia, and bronchiectasis. The outcome of COVID in patients with hypogammaglobulinemia is variable depending on age, comorbidities, type of immunodeficiency, and use of immunoglobulins. We report the favorable outcome of two family members diagnosed with DNAJC17-related retinitis pigmentosa and hypogammaglobulinemia syndrome and infected with SARS-CoV-2 following contact with their mother who had COVID-19. We describe the different immune dysfunction in these patients and their impact on the course and management of SARS-CoV-2 infection.

Background Research evidence exists that poor prognosis is common in Middle East respiratory syndrome coronavirus (MERS‐CoV) patients. Objectives This study estimates recovery delay intervals and identifies associated factors in a sample of Saudi Arabian patients admitted for suspected MERS‐CoV and diagnosed by rRT‐PCR assay. Methods A multicenter retrospective study was conducted on 829 patients admitted between September 2012 and June 2016 and diagnosed by rRT‐PCR procedures to have MERS‐CoV and non‐MERS‐CoV infection in which 396 achieved recovery. Detailed medical charts were reviewed for each patient who achieved recovery. Time intervals in days were calculated from presentation to the initial rRT‐PCR diagnosis (diagnosis delay) and from the initial rRT‐PCR diagnosis to recovery (recovery delay). Results The median recovery delay in our sample was 5 days. According to the multivariate negative binomial model, elderly (age ≥ 65), MERS‐CoV infection, ICU admission, and abnormal radiology findings were associated with longer recovery delay (adjusted relative risk (aRR): 1.741, 2.138, 2.048, and 1.473, respectively). Camel contact and the presence of respiratory symptoms at presentation were associated with a shorter recovery delay (expedited recovery) (aRR: 0.267 and 0.537, respectively). Diagnosis delay is a positive predictor for recovery delay (r = .421; P = .001). Conclusions The study evidence supports that longer recovery delay was seen in patients of older age, MERS‐CoV infection, ICU admission, and abnormal radiology findings. Shorter recovery delay was found in patients who had camel contact and respiratory symptoms at presentation. These findings may help us understand clinical decision making on directing hospital resources toward prompt screening, monitoring, and implementing clinical recovery and treatment strategies.

Nutritional science is increasingly recognizing the synergistic relationship between essential minerals and plant-derived phenolic in modulating immune health, oxidative stress, and nutrient bioavailability. However, challenges remain in improving mineral bioavailability and leveraging the full functional potential of phenolics in dietary interventions to support immune modulation. The central aim was to understand how mineral–phenolic interactions influence absorption, antioxidant potential, and immune cell activity, and to apply this understanding toward the development and evaluation of a novel functional food ingredient (mineral–phenolic complex) to address micronutrient deficiencies and support immune function. A multidisciplinary approach was taken, through four interconnected research projects, combining food composition analysis, in vitro digestion, bioavailability modeling, analytical characterization techniques, and immune cell assays.The first objective was to review and analyze the biological roles of essential minerals in immune cell metabolism, emphasizing the mechanisms by which minerals such as calcium, magnesium, and iron in regulate energy production, redox status, enzyme activation, and inflammatory responses. This chapter established the physiological foundation of mineral balance emphasizing that mineral deficiencies impair adaptive immunity and increase susceptibility to chronic inflammation; and sets the stage for a series of experimental investigations that follow.In the second study, green leafy vegetables commonly consumed in the United States (arugula, celery, parsley, and lettuce) were analyzed to assess their mineral and phenolic composition across different points of purchase, including small farms and grocery stores of different tiers. Findings revealed that lettuces, parsley, and celery from small farms and premium-tier stores had significantly higher levels of magnesium, iron, and total phenolics. These nutritional differences correlated with stronger antioxidant activity and nitric oxide (NO) suppression in RAW264.7 macrophages, especially in celery, where apiin, a flavone glycoside found abundantly in celery, showed strong correlation with nitric oxide inhibition, positioning it as a key bioactive marker. This study established a link between sourcing, growing practices, food system quality and the immunomodulatory potential of vegetables.The third study focused on 52 urban-grown chili pepper cultivars assessing the distribution of capsaicinoids, phenolics, antioxidant capacity and immune modulation. Significant variation was observed in both nutrient and bioactive profiles across pepper varieties, with strong correlations between phenolics content, radical scavenging activity, and NO inhibition. This finding reinforced the idea that certain plant-derived phenolics may play several roles by enhancing antioxidant defense, modulating immune-related signaling pathways and as ligands to enhance the function of essential minerals. These insights shaped the rationale for selecting ferulic acid as a functional ligand in a mineral complex.Building on this foundation, the final study involved the synthesis, characterization, and biological evaluation of a novel calcium–ferulate complex, integrating the bioactive ferulic acid with calcium to create a dual-function compound. The complex was structurally verified using UV, FTIR, LC-MS, and NMR techniques. Through in vitro simulated gastrointestinal digestion followed by transport studies using Caco-2 intestinal cell, calcium–ferulate complex exhibited higher calcium bioaccessibility, and significantly greater cellular transport efficiency compared to calcium citrate. Notably, calcium–ferulate complex treated cells demonstrated increased viability and mitochondrial activity by around 150% compared to the control. These results position calcium–ferulate complex as a promising next generation calcium supplement with both mineral and bioactive health benefits.Across all four studies, this thesis demonstrates that mineral–phenolic interactions can be used to enhance both nutrient bioavailability and functional immune health outcomes. The research not only provides mechanistic insights into the roles of minerals in immune metabolism but also validates the development of a multifunctional nutritional compound that offers improved bioavailability and correcting micronutrient deficiencies also promote immune resilience and antioxidant support. To sum up, these findings support the use of calcium–ferulate as a novel dietary ingredient in functional food and supplement formulations aimed at improving mineral status and modulating inflammation. This work contributes a new layer of understanding the design of functional foods, supplements, and sustainable nutrition strategies aligned with the principles of preventive health and nutritional precision. In conclusion, this thesis contributes to the growing field of nutritional immunology and functional food design by demonstrating that the combination of plant-derived phenolics with essential minerals and offers a promising strategy for enhancing health-promoting properties. The findings have direct applications in the development of functional foods, fortified products, and nutritional interventions, particularly for populations with increased calcium requirements or inflammatory conditions. Future studies could investigate incorporation of calcium–ferulate into real food systems to evaluate its stability, sensory properties, and functional efficacy under practical conditions. In addition in vivo performance of calcium–ferulate complex, explore its long-term effects on bone and immune health. Expanding this approach to other mineral–phenolic combinations may further extend its potential applications in human and animal nutrition. Ultimately, this work contributes to the growing field of precision nutrition by illustrating how food chemistry, cell biology, and sustainable agriculture can intersect to create personalized, multifunctional nutritional solutions.

Cities face continuous challenges in maintaining and operating reliable water supply systems. Management strategies are needed to support both water conservation and cost reduction of infrastructure operations. New pricing policies can be used as an instrument of water demand management to reduce the cost of operating, maintaining, and expanding water distribution networks. As utilities adopt advanced metering infrastructure (AMI), new data that describe water consumption at high temporal resolution and accuracy are available and can be used to evaluate demand management policies. In this research, dynamic pricing strategies are developed and evaluated as a tool to enhance the performance and life of water distribution systems (WDSs). This research investigates the performance of a dynamic pricing framework designed to flatten the daily demand curve by reducing peak demand. Demand changes reduce peak flows within the WDS to mitigate the cost of energy. Several criteria are used to evaluate the effects of dynamic pricing on drinking water infrastructure management, including the cost of water for consumers and the hydraulic performance of the network, based on water loss, peak flow, energy consumption, energy cost, and water age. AMI data collected at nearly 20,000 accounts at Lakewood City in California are used to develop a model of expected water use and simulate changes in consumption and innetwork metrics. This research developed four dynamic pricing policies with different parameters and levels of constraints to test the model. Analysis is conducted to explore reductions in the peak demand, reduction in total water demands, and hydraulic performance. Results demonstrate that reductions in peak demand ranging from 8% to 20% lead to a 40% reduction in peak energy demands and a 10-11% reduction in total energy, with a maximum of 13% reduction in energy cost. Cost savings reflect the importance of dynamic pricing as a demand-side strategy to manage infrastructure. Operational costs can be lowered without new infrastructure investment or expansion, while continuing to meet urban water demands.

We introduce RadGame, an AI-powered gamified platform for radiology education that targets two core skills: localizing findings and generating reports. Traditional radiology training is based on passive exposure to cases or active practice with real-time input from supervising radiologists, limiting opportunities for immediate and scalable feedback. RadGame addresses this gap by combining gamification with large-scale public datasets and automated, AI-driven feedback that provides clear, structured guidance to human learners. In RadGame Localize, players draw bounding boxes around abnormalities, which are automatically compared to radiologist-drawn annotations from public datasets, and visual explanations are generated by vision-language models for user missed findings. In RadGame Report, players compose findings given a chest X-ray, patient age and indication, and receive structured AI feedback based on radiology report generation metrics, highlighting errors and omissions compared to a radiologist's written ground truth report from public datasets, producing a final performance and style score. In a prospective evaluation, participants using RadGame achieved a 68% improvement in localization accuracy compared to 17% with traditional passive methods and a 31% improvement in report-writing accuracy compared to 4% with traditional methods after seeing the same cases. RadGame highlights the potential of AI-driven gamification to deliver scalable, feedback-rich radiology training and reimagines the application of medical AI resources in education.

This study describes the epidemiology of Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia. Epidemiological analysis was performed on data from all MERS-CoV cases recorded by the Saudi Ministry of Health between June 6, 2013 and May 14, 2014. The frequency of cases and deaths was calculated and adjusted by month, sex, age group, and region. The average monthly temperature and humidity of infected regions throughout the year was also calculated. A total of 425 cases were recorded over the study period. The highest number of cases and deaths occurred between April and May 2014. Disease occurrence among men (260 cases [62%]) was higher than in women (162 cases [38%]), and the case fatality rate was higher for men (52%) than for women (23%). In addition, those in the 45-59 years and ≥60 years age groups were most likely to be infected, and the case fatality rate for these people was higher than for other groups. The highest number of cases and deaths were reported in Riyadh (169 cases; 43 deaths), followed by Jeddah (156 cases; 36 deaths) and the Eastern Region (24 cases; 22 deaths). The highest case fatality rate was in the Eastern Region (92%), followed by Medinah (36%) and Najran (33%). MERS-CoV infection actively causes disease in environments with low relative humidity (<20%) and high temperature (15°C-35°C). MERS-CoV is considered an epidemic in Saudi Arabia. The frequency of cases and deaths is higher among men than women, and those above 45 years of age are most affected. Low relative humidity and high temperature can enhance the spread of this disease in the entire population. Further analytical studies are required to determine the source and mode of infection in Saudi Arabia.

The Pfizer-BioNTech COVID-19 vaccine has recently received emergency approval from the US FDA. The mRNA technology was used to manufacture the Pfizer vaccine; however, as a pioneering technology that has never been used in the manufacture of vaccines, many people have concerns about the vaccine's side effects. Thus, the current study aimed to track the short-term side effects of the vaccine. The information in this study was gathered by a Google Form-questionnaire (online survey). The results included the responses of 455 individuals, all of whom are Saudi Arabia inhabitants. Adverse effects of the vaccine were reported after the first and the second doses. The most common symptoms were injection site pain, headaches, flu-like symptoms, fever, and tiredness. Less common side effects were a fast heartbeat, whole body aches, difficulty breathing, joint pain, chills, and drowsiness. Rare side effects include Bell's palsy and lymph nodes swelling and tenderness. Flu-like symptoms were more common among those under 60 years of age, while injection site pain was more frequent among recipients who were 60 years and older. The study revealed a significant increase in the number of females who suffered from the vaccine side effects compared to males. Difficulty of breathing was more reported among recipients who had been previously infected with the coronavirus compared to those who had not been previously infected. Most of the side effects reported in this study were consistent with Pfizer's fact sheet for recipients and caregivers. Further studies are required to determine the long-term side effects.

Gestational diabetes mellitus (GDM) is a condition characterized by glucose intolerance that develops during pregnancy. It is associated with adverse maternal and fetal outcomes and has long-term health implications for both the mother and the child. This study aimed to estimate the prevalence of adverse pregnancy outcomes in women with and without GDM in the Al-Baha region, Saudi Arabia. A cross-sectional study was conducted in the Al-Baha region from April 2023 to November 2023. The study included mothers residing in the Al-Baha region who were willing to participate and had access to a social media account. A simple random sampling technique was used, and the estimated sample size was 422. A self-administered electronic questionnaire was used to collect data on socio-demographic and lifestyle factors, as well as the pregnancy outcomes of diabetic and non-diabetic mothers. Descriptive and inferential statistical analyses were performed using IBM SPSS Statistics for Windows, Version 28.0 (Released 2012; IBM Corp., Armonk, New York, United States). We included 422 women in the study with the majority of participants in the age group of 36-40 years(15.4%, n=74). Most participants (66.6%, n=321) had attained a university degree, and a significant proportion resided in Al-Baha City (52.3%, n=252). Maternal outcomes indicated a significant association between GDM and the development of eclampsia (OR = 8.296, 95%CI: 4.353-15.810, p < 0.001), as well as an increased risk of thyroid diseases (OR = 2.723, 95%CI: 1.428-5.193, p = 0.002). Fetal outcomes revealed a significant association between GDM and respiratory distress/lack of oxygen in newborns (OR = 2.032, 95%CI: 1.085-3.805, p = 0.024), and infants of GDM patients had a higher risk of hypoglycemia (OR = 8.099, 95%CI: 3.350-19.581, p < 0.001). We found that GDM increased the risk of complications such as eclampsia, thyroid problems, and postpartum hemorrhage. GDM was also associated with shorter pregnancy durations, higher cesarean section rates, and an increased risk of developing type 2 diabetes post pregnancy. The study emphasized the importance of comprehensive GDM therapy and monitoring.

The integration of artificial intelligence (AI) into oncology drug discovery is redefining the traditional pipeline by accelerating discovery, optimizing drug efficacy, and minimizing toxicity. AI has enabled groundbreaking advancements in molecular modeling, simulation techniques, and the identification of novel compounds, including anti-tumor and antibodies, while elucidating mechanisms of drug toxicity. Additionally, AI has emerged as a critical tool in precision medicine, driving the formulation and release of targeted therapies and improving the development of treatments for oncology and central nervous system diseases. Furthermore, AI-assisted clinical trial designs have further optimized the recruitment and stratification of patients, reducing the time and cost of trials. Despite these advancements, challenges such as data integration, transparency, and ethical considerations persist. By synthesizing current innovations, this manuscript provides a comprehensive analysis of AI-driven approaches in drug discovery and their potential to advance oncology therapeutics and precision medicine. It examines the transformative role of AI across the drug development continuum, with a focus on its applications in computer-aided drug design (CADD), generative artificial intelligence (GAI), and high-throughput screening (HTS).