Revitalizing oncology medications access in Saudi Arabia: Current challenges and recommendations by the Saudi Oncology Pharmacy Assembly.

BACKGROUND: Cancer care is posing immense challenges to healthcare systems globally. Advances in screening, monitoring, and treating cancer improved patient outcomes and survival rates yet amplified the disease burden. Multiple barriers might impede early access to innovative therapies. We thoroughly examined the current challenges in oncology medication access in Saudi Arabia and provided consensus recommendations to revitalize the process. METHODS: A focus group discussion was conducted. Expert healthcare providers (pharmacists and physicians) were invited to participate based on prespecified criteria. The research team conducted a qualitative analysis of the discussion to identify themes and formulate recommendations. RESULTS: Fourteen experts were equally distributed into two groups, limiting the number in each group to 7. Pharmacists were 12 (∼86%), and physicians were 2 (∼14%). Ten were practicing in governmental hospitals, four representing different sectors; regulatory bodies, including Ministry of Health, National Unified Procurement Company, and Saudi Food and Drug Authority. Five themes were identified: national cancer burden, local data availability, pharmacoeconomic evaluation, patients reported outcomes, administration, and procurement. Consensus recommendations were formulated to optimize the formulary management process, enabling informed decision-making and facilitating early medication access for cancer patients. CONCLUSIONS: The formulary management process can be enhanced by addressing the national cancer burden, promoting local data availability, conducting pharmacoeconomic evaluations, focusing on patient outcomes, and improving administration and procurement procedures. Implementing these recommendations can improve access to oncology medications and improve patient care outcomes in Saudi Arabia.

Patient Satisfaction with Private Community Pharmacies versus Pharmacies in Primary Health Care Centers in Saudi Arabia.

Introduction: Saudi Arabia has begun reforming its government-run health care system to increase efficiency and reduce costs. One effort is the adoption of an electronic prescribing system (Wasfaty) and outsourcing pharmaceutical services from government-run clinics to community pharmacies (CP). This study aims to compare satisfaction with pharmaceutical services offered in the two systems. Materials and methods: This cross-sectional observational study used existing survey data collected from patients (≥15 years of age) visiting government primary health care centers from January 2022 to June 2022. Satisfaction with three pharmaceutical services (availability of medications, pharmacist's explanation of the prescription, and waiting time to get medications) were the main outcomes. Results: The study comprised 91,317 participants, 74.06 % of them were CP/Wasfaty users. CP/Wasfaty patients had lower odds of satisfaction with the three pharmaceutical services: availability of medications (OR = 0.49, 95 % CI = 0.47-0.51), pharmacists' explanation of prescription (OR = 0.55, 95 % CI = 0.53-0.58), and waiting time to get medications (OR = 0.81, 95 % CI = 0.75-0.88). Additional findings showed variations in satisfaction levels based on demographic factors and clinic types. Conclusions: The significant differences observed in satisfaction levels based on demographic characteristics and type of clinics visited emphasize the importance of tailoring pharmaceutical services to meet the specific needs and expectations of different patient populations.

Knowledge and Attitude of Undergraduate Health Professions Students towards Hepatitis B and C.

The current study sought to establish the attitude and knowledge level of medical science students in Tibah University towards hepatitis B and C. A cross-sectional study involving 369 students drawn from the faculties of medicine, dentistry, applied medical sciences, pharmacy, nursing, and medical rehabilitation sciences was conducted where a standardised questionnaire was used to determine the attitude and knowledge level of undergraduate students drawn from the college of medicine in Tibah University, Saudi Arabia, regarding viral infections. With a mean of 0.71, 0.69, and 0.66 and a standard deviation (SD) of 0.24, 0.34, and 0.24 for virology and transmission, symptoms and clinical outcomes, and treatment and prevention, respectively, the knowledge level of the health professions students towards hepatitis B and C infections was significant. The knowledge level about the infections was higher among male students than among female students. Similarly, students in their final years of medical school had significantly higher knowledge levels about hepatitis B and C than their counterparts in their first years of medical school. There was also a positive correlation between the attitude of the health professions students towards the disease and their knowledge levels of the disease. Findings indicate that enhanced instruction on the nature, virology, transmission, symptoms, treatment, clinical outcomes, and prevention of hepatitis B and C can help improve the knowledge levels and attitude of the health professions students towards the disease and its management.

Machine-Learning-Assisted Cyclostationary Spectral Analysis for Joint Signal Classification and Jammer Detection at the Physical Layer of Cognitive Radio.

Cognitive radio technology was introduced as a possible solution for spectrum scarcity by exploiting dynamic spectrum access. In the last two decades, most researchers focused on enabling cognitive radios for managing the spectrum. However, due to their intelligent nature, cognitive radios can scan the radio frequency environment and change their transmission parameters accordingly on-the-fly. Such capabilities make it suitable for the design of both advanced jamming and anti-jamming systems. In this context, our work presents a novel, robust algorithm for spectrum characterisation in wideband radios. The proposed algorithm considers that a wideband spectrum is sensed by a cognitive radio terminal. The wideband is constituted of different narrowband signals that could either be licit signals or signals jammed by stealthy jammers. Cyclostationary feature detection is adopted to measure the spectral correlation density function of each narrowband signal. Then, cyclic and angular frequency profiles are obtained from the spectral correlation density function, concatenated, and used as the feature sets for the artificial neural network, which characterise each narrowband signal as a licit signal with a particular modulation scheme or a signal jammed by a specific stealthy jammer. The algorithm is tested under both multi-tone and modulated stealthy jamming attacks. Results show that the classification accuracy of our novel algorithm is superior when compared with recently proposed signal classifications and jamming detection algorithms. The applications of the algorithm can be found in both commercial and military communication systems.

TinyML-Sensor for Shelf Life Estimation of Fresh Date Fruits.

Fresh dates have a limited shelf life and are susceptible to spoilage, which can lead to economic losses for producers and suppliers. The problem of accurate shelf life estimation for fresh dates is essential for various stakeholders involved in the production, supply, and consumption of dates. Modified atmosphere packaging (MAP) is one of the essential methods that improves the quality and increases the shelf life of fresh dates by reducing the rate of ripening. Therefore, this study aims to apply fast and cost-effective non-destructive techniques based on machine learning (ML) to predict and estimate the shelf life of stored fresh date fruits under different conditions. Predicting and estimating the shelf life of stored date fruits is essential for scheduling them for consumption at the right time in the supply chain to benefit from the nutritional advantages of fresh dates. The study observed the physicochemical attributes of fresh date fruits, including moisture content, total soluble solids, sugar content, tannin content, pH, and firmness, during storage in a vacuum and MAP at 5 and 24 ∘C every 7 days to determine the shelf life using a non-destructive approach. TinyML-compatible regression models were employed to predict the stages of fruit development during the storage period. The decrease in the shelf life of the fruits begins when they transition from the Khalal stage to the Rutab stage, and the shelf life ends when they start to spoil or ripen to the Tamr stage. Low-cost Visible-Near-Infrared (VisNIR) spectral sensors (AS7265x-multi-spectral) were used to capture the internal physicochemical attributes of the fresh fruit. Regression models were employed for shelf life estimation. The findings indicated that vacuum and modified atmosphere packaging with 20% CO2 and N balance efficiently increased the shelf life of the stored fresh fruit to 53 days and 44 days, respectively, when maintained at 5 ∘C. However, the shelf life decreased to 44 and 23 days when the vacuum and modified atmosphere packaging with 20% CO2 and N balance were maintained at room temperature (24 ∘C). Edge Impulse supports the training and deployment of models on low-cost microcontrollers, which can be used to predict real-time estimations of the shelf life of fresh dates using TinyML sensors.

Revolutionizing Urban Mobility: IoT-Enhanced Autonomous Parking Solutions with Transfer Learning for Smart Cities.

Smart cities have emerged as a specialized domain encompassing various technologies, transitioning from civil engineering to technology-driven solutions. The accelerated development of technologies, such as the Internet of Things (IoT), software-defined networks (SDN), 5G, artificial intelligence, cognitive science, and analytics, has played a crucial role in providing solutions for smart cities. Smart cities heavily rely on devices, ad hoc networks, and cloud computing to integrate and streamline various activities towards common goals. However, the complexity arising from multiple cloud service providers offering myriad services necessitates a stable and coherent platform for sustainable operations. The Smart City Operational Platform Ecology (SCOPE) model has been developed to address the growing demands, and incorporates machine learning, cognitive correlates, ecosystem management, and security. SCOPE provides an ecosystem that establishes a balance for achieving sustainability and progress. In the context of smart cities, Internet of Things (IoT) devices play a significant role in enabling automation and data capture. This research paper focuses on a specific module of SCOPE, which deals with data processing and learning mechanisms for object identification in smart cities. Specifically, it presents a car parking system that utilizes smart identification techniques to identify vacant slots. The learning controller in SCOPE employs a two-tier approach, and utilizes two different models, namely Alex Net and YOLO, to ensure procedural stability and improvement.

Low uptake of seasonal influenza vaccination in Al-Jouf region of Saudi Arabia.

Introduction: Seasonal influenza is a contagious viral respiratory condition typically occurring in the fall to early spring months of the year globally. The risk of infection from seasonal influenza can be greatly reduced with vaccination. Unfortunately, research has indicated that the seasonal influenza vaccination rate in Saudi Arabia is low. This study assessed the uptake of seasonal influenza vaccination among adults residing in Al-Jouf region, Saudi Arabia. Materials and Methods: A cross-sectional survey targeting adults (20-80 years) residing in Al-Jouf region, Saudi Arabia, was conducted to gather information about their sociodemographic characteristics, chronic conditions, knowledge about periodic health examinations (PHE), regular use of PHE, and uptake of seasonal influenza vaccination. Comparative statistics and a multivariate logistic regression analysis were conducted to determine characteristics associated with the uptake of seasonal influenza vaccination. Results: A total of 624 respondents completed the survey and participated in this study. Among the participants, 27.4% indicated they visited their primary healthcare centers or hospitals every year to get a seasonal influenza vaccination. The regression analysis showed that the odds of getting a seasonal influenza vaccination were higher among employed respondents (Odds Ratio [OR] = 1.73; P = 0.039), respondents who were employees of the healthcare sector (OR = 2.31; P = 0.001), and those with a higher PHE Knowledge Score (OR = 1.22; P = 0.008), compared to their counterparts. Conclusions: Seasonal influenza is a serious condition warranting appropriate prevention measures, including vaccination. However, this study confirmed low rates of seasonal influenza vaccination in Al-Jouf Region of Saudi Arabia. Interventions to boost vaccination uptake, in particular among unemployed individuals, those not working in the healthcare sector, and those with lower PHE knowledge Scores, are therefore recommended.

Nurses' readiness to prescribe under supervision in Saudi Arabia: A cross-sectional study.

Aim: To explore nurses' readiness to prescribe medications under supervision and identify associations between prescribing practices under supervision and demographic characteristics in Saudi Arabia. Design: A cross-sectional study. Methods: Using convenience sampling, this study used a 32-item survey to collect data on nurses prescribing medications under supervision between December 2022 and March 2023. Results: A total of 379 nurses were recruited from different regions in Saudi Arabia. Approximately 7% (n = 30) of the participants were prescribing medications independently, and 70% (n = 267) expressed their likelihood of becoming prescribers. The highest motivating factors to become prescribers were improvement of patient care (52.2%) and contribution to the multidisciplinary team (52.0%). Most participants (60%-81%) agreed that prescribing medications under supervision would improve potential outcomes at the system, nurse, and patient levels. Availability of appropriate mentors or supervisors (72.9%) was the highest rated facilitating factor, followed by support of nursing colleagues (72%). Based on demographic characteristics, findings revealed significant differences in the: a) likelihood and motivators of becoming prescribers; b) required minimum qualification, years of experience, and continuing professional education hours to become prescribers; and c) type of organizations delivering educational programs for nurse prescribing. Conclusion: Majority of nurses in Saudi Arabia favored becoming prescribers, and motivating factors were mostly relevant to optimizing patient care outcomes. Having the proper supervision was rated as the most facilitating factor for nurse prescribing. Nurses' views on potential outcomes, facilitating factors, and possible motivators varied based on nurses' demographical characteristics. Implications for the professional and/or patient care: Nurses favored prescribing under supervision to improve patient care outcomes, which is an opportunity to expand the benefits of health services, including easy access to healthcare. Impact: Results revealed that nurses support the implementation of prescribing practice under supervision. Thus, the findings may inform practice change in Saudi Arabia to allow prescribing under supervision, which was perceived to have a positive impact on patient care outcomes. Reporting Method: This study adhered to STROBE guidelines.

Hybrid Approach for Improving the Performance of Data Reliability in Cloud Storage Management.

The digital transformation disrupts the various professional domains in different ways, though one aspect is common: the unified platform known as cloud computing. Corporate solutions, IoT systems, analytics, business intelligence, and numerous tools, solutions and systems use cloud computing as a global platform. The migrations to the cloud are increasing, causing it to face new challenges and complexities. One of the essential segments is related to data storage. Data storage on the cloud is neither simplistic nor conventional; rather, it is becoming more and more complex due to the versatility and volume of data. The inspiration of this research is based on the development of a framework that can provide a comprehensive solution for cloud computing storage in terms of replication, and instead of using formal recovery channels, erasure coding has been proposed for this framework, which in the past proved itself as a trustworthy mechanism for the job. The proposed framework provides a hybrid approach to combine the benefits of replication and erasure coding to attain the optimal solution for storage, specifically focused on reliability and recovery. Learning and training mechanisms were developed to provide dynamic structure building in the future and test the data model. RAID architecture is used to formulate different configurations for the experiments. RAID-1 to RAID-6 are divided into two groups, with RAID-1 to 4 in the first group while RAID-5 and 6 are in the second group, further categorized based on FTT, parity, failure range and capacity. Reliability and recovery are evaluated on the rest of the data on the server side, and for the data in transit at the virtual level. The overall results show the significant impact of the proposed hybrid framework on cloud storage performance. RAID-6c at the server side came out as the best configuration for optimal performance. The mirroring for replication using RAID-6 and erasure coding for recovery work in complete coherence provide good results for the current framework while highlighting the interesting and challenging paths for future research.

A Novel Integration of Face-Recognition Algorithms with a Soft Voting Scheme for Efficiently Tracking Missing Person in Challenging Large-Gathering Scenarios.

The probability of losing vulnerable companions, such as children or older ones, in large gatherings is high, and their tracking is challenging. We proposed a novel integration of face-recognition algorithms with a soft voting scheme, which was applied, on low-resolution cropped images of detected faces, in order to locate missing persons in a challenging large-crowd gathering. We considered the large-crowd gathering scenarios at Al Nabvi mosque Madinah. It is a highly uncontrolled environment with a low-resolution-images data set gathered from moving cameras. The proposed model first performs real-time face-detection from camera-captured images, and then it uses the missing person's profile face image and applies well-known face-recognition algorithms for personal identification, and their predictions are further combined to obtain more mature prediction. The presence of a missing person is determined by a small set of consecutive frames. The novelty of this work lies in using several recognition algorithms in parallel and combining their predictions by a unique soft-voting scheme, which in return not only provides a mature prediction with spatio-temporal values but also mitigates the false results of individual recognition algorithms. The experimental results of our model showed reasonably good accuracy of missing person's identification in an extremely challenging large-gathering scenario.

Tracking Missing Person in Large Crowd Gathering Using Intelligent Video Surveillance.

Locating a missing child or elderly person in a large gathering through face recognition in videos is still challenging because of various dynamic factors. In this paper, we present an intelligent mechanism for tracking missing persons in an unconstrained large gathering scenario of Al-Nabawi Mosque, Madinah, KSA. The proposed mechanism in this paper is unique in two aspects. First, there are various proposals existing in the literature that deal with face detection and recognition in high-quality images of a large crowd but none of them tested tracking of a missing person in low resolution images of a large gathering scenario. Secondly, our proposed mechanism is unique in the sense that it employs four phases: (a) report missing person online through web and mobile app based on spatio-temporal features; (b) geo fence set estimation for reducing search space; (c) face detection using the fusion of Viola Jones cascades LBP, CART, and HAAR to optimize the results of the localization of face regions; and (d) face recognition to find a missing person based on the profile image of reported missing person. The overall results of our proposed intelligent tracking mechanism suggest good performance when tested on a challenging dataset of 2208 low resolution images of large crowd gathering.

Indirect-Neural-Approximation-Based Fault-Tolerant Integrated Attitude and Position Control of Spacecraft Proximity Operations.

In this paper, a neural adaptive fault-tolerant control scheme is proposed for the integrated attitude and position control of spacecraft proximity operations in the presence of unknown parameters, disturbances, and actuator faults. The proposed controller is made up of a relative attitude control law and a relative position control law. Both the relative attitude control law and relative position control law are designed by adopting the neural networks (NNs) to approximate the upper bound of the lumped unknowns. Benefiting from the indirect neural approximation, the proposed controller does not need any model information for feedback. In addition, only two adaptive parameters are required for the indirect neural approximation, and the online calculation burden of the proposed controller is therefore significantly reduced. Lyapunov analysis shows that the overall closed-loop system is ultimately uniformly bounded. The proposed controller can ensure the relative attitude, angular velocity, position, and velocity stabilize into the small neighborhoods around the origin. Lastly, the effectiveness and superior performance of the proposed control scheme are confirmed by a simulated example.

In-Depth Review of Augmented Reality: Tracking Technologies, Development Tools, AR Displays, Collaborative AR, and Security Concerns.

Augmented reality (AR) has gained enormous popularity and acceptance in the past few years. AR is indeed a combination of different immersive experiences and solutions that serve as integrated components to assemble and accelerate the augmented reality phenomena as a workable and marvelous adaptive solution for many realms. These solutions of AR include tracking as a means for keeping track of the point of reference to make virtual objects visible in a real scene. Similarly, display technologies combine the virtual and real world with the user's eye. Authoring tools provide platforms to develop AR applications by providing access to low-level libraries. The libraries can thereafter interact with the hardware of tracking sensors, cameras, and other technologies. In addition to this, advances in distributed computing and collaborative augmented reality also need stable solutions. The various participants can collaborate in an AR setting. The authors of this research have explored many solutions in this regard and present a comprehensive review to aid in doing research and improving different business transformations. However, during the course of this study, we identified that there is a lack of security solutions in various areas of collaborative AR (CAR), specifically in the area of distributed trust management in CAR. This research study also proposed a trusted CAR architecture with a use-case of tourism that can be used as a model for researchers with an interest in making secure AR-based remote communication sessions.

A Novel Mutation in a Gene Causes Sclerosteosis in a Family of Mediterranean Origin.

Background and Objectives: Sclerostin is an SOST gene product that inhibits osteoblast activity and prevents excessive bone formation by antagonizing the Wnt signaling pathway. Sclerosteosis has been linked to loss of function mutations in the SOST gene. It is a rare autosomal recessive disorder characterized by craniotubular hyperostosis and can lead to fatal cerebellar herniation. Our aim is to describe the clinical and radiological features and the new underlying SOST mutation in a patient with sclerosteosis. Case: A 25-year-old female who was referred to the endocrine clinic for suspected excess growth hormone. The patient complained of headaches, progressive blurred vision, hearing disturbances, increased size of feet, proptosis, and protrusion of the chin. She had normal antenatal history except for syndactyly. Images showed diffuse osseous thickening and high bone mineral density. Biochemical and hormonal tests were normal. Due to progressive compressive optic neuropathy, optic nerve fenestration with decompression hemicraniotomy was performed. Sclerosteosis was suspected due to the predominant craniotubular hyperostosis with syndactyly. Using peripheral leucocyte DNA, genomic sequencing of the SOST gene was performed. This identified a novel deletion homozygous mutation in the SOST gene (c.387delG, p.Asp131ThrfsTer116) which disrupts sclerostin function, causing sclerosteosis. Conclusions: Discovery of the molecular basis of sclerosteosis represents an important advance in the diagnosis and management of this fatal disease.

A novel claudin-10 mutation with a unique mechanism in two unrelated families with HELIX syndrome.

HELIX syndrome, characterized by hypohidrosis, electrolyte imbalance, lacrimal gland dysfunction, ichthyosis, and xerostomia due to claudin-10 (CLDN10) mutations, was recognized in 2017. Here we describe two unrelated Saudi families with this syndrome due to a novel CLDN10 mutation with a unique mechanism of CLDN10 inactivation. The two consanguineous families include 12 affected individuals (three siblings in family 1 and nine members in family 2). They presented with hypokalemia and the above-mentioned features of HELIX syndrome. The underlying mutation was detected by whole exome sequencing, confirmed by Sanger sequencing and functionally indicated by RT-PCR, electrophysiological studies and immunohistochemical staining of transfected HEK293 and MDCK C7 cells, and skin and kidney biopsy tissues. A novel biallelic single nucleotide deletion was identified in exon 5 of CLDN10 (NM_182848.3: c.647delC, p.P216Lfs∗19 for CLDN10a or NM_006984.4: c.653delC, p.P218Lfs∗21 for CLDN10b). The mutation led to frameshift and extension of the original termination codon by nine amino acids with loss of the C-terminus pdz-binding motif. Functional studies showed mRNA degradation and protein retention in intracellular compartments and that the pdz-binding motif is crucial for proper localization of claudin-10 in tight junctions. In the kidney, claudin-10 was replaced by translocation of claudin-2 (proximal tubule) and claudin-19 (thick ascending limb), and in the sweat gland by claudin-3 and occludin. However, these claudins did not functionally compensate for loss of claudin-10. Thus, this novel CLDN10 mutation identified in these two families disrupted the C-terminus pdz-binding motif of claudin-10 causing HELIX syndrome.

How Does The AJCC/TNM Staging System Eighth Edition Perform in Thyroid Cancer at A Major Middle Eastern Medical Center?

OBJECTIVE: The American Joint Committee on Cancer tumor node metastasis (TNM) staging system eighth edition (TNM-8) for differentiated thyroid cancer (DTC) has been introduced as a replacement for tumor node metastasis staging system seventh edition (TNM-7). We present the first study from a Middle Eastern population comparing these 2 versions of the TNM staging system. METHODS: We compared TNM-8 with TNM-7 in 701 patients with DTC seen during a 3-year period with a median age of 37 years (6-83) and a female-to-male ratio of 558 (79.6%) to 143 (20.4%). RESULTS: The number (%) of patients within each stage in TNM-7 and TNM-8, respectively, are as follows: stage I = 503 (71.6%) and 583 (83.2%), stage II = 52 (7.4%) and 81 (11.4%), stage III = 53 (7.6%) and 6 (0.9%), and stage IV = 93 (13.2%) and 31 (4.6%). Overall, 172 patients (24.5%) were downstaged in TNM-8 compared to that in TNM-7, as follows: 26, 30, and 24 patients from stages II, III, and IV in TNM-7 to stage I in TNM-8; 23 and 32 patients from TNM-7 stages III and IV to TNM-8 stage II; 6 patients from stage IVa in TNM-7 to stage III in TNM-8; and 31 patients from stage IVc in TNM-7 to stage IVb in TNM-8. TNM-7 and TNM-8 predicted the long-term outcome well (median follow-up, 7.9 years), but Kaplan-Meier analysis showed better separation of cancer-specific survival in TNM-8 compared to TNM-7. CONCLUSIONS: Compared with TNM-7, TNM-8 approximately downstaged a quarter of DTC patients and was more robust in separating the outcome of different stages over time.

The Impact of COVID-19 Viral Infection on the Hypothalamic-Pituitary-Adrenal Axis.

OBJECTIVE: To study the adrenocortical response to an acute coronavirus disease-2019 (COVID-19) infection. METHODS: Morning plasma cortisol, adrenocorticotropic hormone (ACTH), and dehydroepiandrosterone sulfate levels were measured in 28 consecutive patients with COVID-19 (16 men, 12 women, median age 45.5 years, range 25-69 years) on day 1 to 2 of hospital admission. These tests were repeated twice in 20 patients and thrice in 15 patients on different days. The hormone levels were correlated with severity of the disease. RESULTS: The median morning cortisol level was 196 (31-587) nmol/L. It was <100 nmol/L in 8 patients (28.6%), <200 nmol/L in 14 patients (50%), and <300 nmol/L in 18 patients (64.3%). The corresponding ACTH values had a median of 18.5 ng/L (range 4-38 ng/L), and the ACTH level was <10 ng/L in 7 patients (26.9%), <20 ng/L in 17 patients (60.7%), and <30 ng/L in 23 patients (82.1%). The repeated testing on different days showed a similar pattern. Overall, if a cutoff level of <300 nmol/L is considered abnormal in the setting of acute disease, 9 patients (32%) had cortisol levels below this limit, regardless of whether the test was done only once (3 patients) or 3 times (6 patients). When the disease was more severe, the patients had lower cortisol and ACTH levels, suggesting a direct link between the COVID-19 infection and impaired glucocorticoid response. CONCLUSION: Unexpectedly, the adrenocortical response in patients with COVID-19 infection was impaired, and a significant percentage of the patients had plasma cortisol and ACTH levels consistent with central adrenal insufficiency.

Penetrating chest injury afflicting coronary artery fistula-A delayed and asymptomatic occurrence.

We present here a case of a symptomatic chest injury with a nail gun causing a delayed occurrence of coronary artery fistula to the left pulmonary artery presenting with unstable angina 4 years after the initial injury, three of which were symptom-free. The patient underwent successful surgical closure of the fistula and removal of the foreign body.

PI3K/Akt/mTOR inhibitors in cancer: At the bench and bedside.

Phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway is one of the major cellular signaling pathways that plays an important role in basic intracellular functions. The PI3K/Akt/mTOR pathway regulates cell proliferation, growth, cell size, metabolism, and motility. Component genes of this pathway have been extensively studied and found to be commonly activated in human cancer. Inhibition of this pathway has been shown to lead to regression of human tumors and has been studied in preclinical setup and evaluated in many clinical trials at various levels. Some inhibitors of this pathway are approved by the Food and Drug Administration after their potency and safety have been shown in clinical trials. This review discusses the recent trends in exploiting the PI3K/Akt/mTOR pathway towards the molecular targeted therapy using small molecule inhibitors in human cancer.

NOVEL VDR MUTATIONS IN PATIENTS WITH VITAMIN D-DEPENDENT RICKETS TYPE 2A: A MILD DISEASE PHENOTYPE CAUSED BY A NOVEL CANONICAL SPLICE-SITE MUTATION.

Objective: Vitamin D-dependent rickets type 2A (VDDR2A) is a rare autosomal recessive disorder caused by mutations in the vitamin D receptor gene (VDR), leading to end-organ resistance to 1,25-dihydroxyvitamin D3 (1,25[OH]2D3). The objective of this study was to investigate VDR mutations in 11 patients from 8 Turkish-Arab families. Methods: All coding exons and intron-exon boundaries of the VDR gene were amplified by polymerase chain reaction from peripheral leukocyte DNA and sequenced. The effect of splice-site mutations on mRNA splicing was evaluated by a customized VDR mini-gene assay. Results: Homozygous VDR mutations were found in all the patients, including four novel mutations: c.473G>T (p.R158L), c.1-4A>G (IVS3-2A>G), c.755+1G>T, and c.352_356delGACAG (p.D118Sfs*7). The c.1-4A>G mutation was located in the canonical splice acceptor site and 4 base pairs from the original ATG start codon. The mutation resulted in both complete (60% of transcripts) and partial exon 4 skipping (15% of transcripts). The latter was due to activation of a cryptic splice acceptor site and did not disrupt the open reading frame. Both c.755+1G>T and c.352_356delGACAG resulted in frameshifts and a premature stop codon. Clinically, all the patients required continued treatment, except for patient IV-3, who presented with alopecia, hypocalcemia, and increased 1,25(OH)2D3 at 1.5 years of age as a result of the c.1-4A>G mutation. He stopped taking medication at 6 years of age and still maintained normal height and biochemical profile. Conclusion: We have identified four novel VDR mutations. Although canonical splice-site mutations cause premRNA splicing errors that usually lead to a severe disease phenotype, mild disease can also occur due to activation of a cryptic splice site. Abbreviations: 1,25(OH)2D3 = 1,25-dihydroxyvitamin D3 (calcitriol); 25OHD3 = 25-hydroxyvitamin D3; PCR = polymerase chain reaction; PTH = parathyroid hormone; VDDR2A = vitamin D-dependent rickets type 2A; VDR = vitamin D receptor.