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Abstract The study investigates the link between corporate social responsibility (CSR) and sustainability performance (SP) using a multi-case study approach in six Qatari firms from different industries. Specifically, it identifies how CSR practices—across philanthropy, business operations, and product responsibility—enhance environmental, social, and economic sustainability. The findings suggest that companies that adopt CSR practices achieve greater economic, environmental, and social benefits, regardless of factors like product type, business nature, and industry sector. Overall, this study provides a detailed examination of diverse sectors (construction, telecom, banking, etc.), assessing how CSR adoption varies across industries and impacts sustainability, irrespective of operational differences. Furthermore, it contributes to the literature by focusing on Qatar, a rapidly developing economy with a growing emphasis on sustainability and CSR, influenced by Qatar National Vision 2030. Therefore, the findings highlight how CSR can serve as a pathway for companies in developing economies like Qatar to achieve sustainability goals, providing actionable insights for managers to integrate CSR into their business strategies for improved economic, social, and environmental outcomes.

Abstract Background Anomaly detection is crucial in healthcare data due to challenges associated with the integration of smart technologies and healthcare. Anomaly in electronic health record can be associated with an insider trying to access and manipulate the data. This article focuses around the anomalies under different contexts. Methodology This research has proposed methodology to secure Electronic Health Records (EHRs) within a complex environment. We have employed a systematic approach encompassing data preprocessing, labeling, modeling, and evaluation. Anomalies are not labelled thus a mechanism is required that predicts them with greater accuracy and less false positive results. This research utilized unsupervised machine learning algorithms that includes Isolation Forest and Local Outlier Factor clustering algorithms. By calculating anomaly scores and validating clustering through metrics like the Silhouette Score and Dunn Score, we enhanced the capacity to secure sensitive healthcare data evolving digital threats. Three variations of Isolation Forest (IForest)models (SVM, Decision Tree, and Random Forest) and three variations of Local Outlier Factor (LOF) models (SVM, Decision Tree, and Random Forest) are evaluated based on accuracy, sensitivity, specificity, and F1 Score. Results Isolation Forest SVM achieves the highest accuracy of 99.21%, high sensitivity (99.75%) and specificity (99.32%), and a commendable F1 Score of 98.72%. The Isolation Forest Decision Tree also performs well with an accuracy of 98.92% and an F1 Score of 99.35%. However, the Isolation Forest Random Forest exhibits lower specificity (72.84%) than the other models. Conclusion The experimental results reveal that Isolation Forest SVM emerges as the top performer showcasing the effectiveness of these models in anomaly detection tasks. The proposed methodology utilizing isolation forest and SVM produced better results by detecting anomalies with less false positives in this specific EHR of a hospital in North England. Furthermore the proposal is also able to identify new contextual anomalies that were not identified in the baseline methodology.

Abstract This research explores the challenges posed by variations in cystic duct anatomy during laparoscopic cholecystectomy and the potential use of stapler devices to address such complexities. It aims to assess the safety and efficacy of stapler devices, particularly in cases involving short, and wide cystic duct. The study, conducted at King Abdulaziz Medical City in Riyadh, Saudi Arabia, between 2021 and 2023. The study design involved a retrospective cohort approach, and the sample size encompassed all cases meeting the inclusion criteria during the study period. Data was analyzed using SPSS program. The study involving 568 patients, with the predominant technique for ligation being clipping (89.3%). The primary indication for using the Endo GIA stapler was a wide cystic duct (6.2%). Analysis revealed a significant association between stapler device use and hypertension (p = 0.042), diabetes (p = 0.001), CKD (p = 0.011), and obstructive jaundice (p = 0.006). Multivariate regression demonstrated that older patients were 2.1 times more likely to use stapler devices (AOR = 2.125; p = 0.039), while those with obstructive jaundice had a 2.2 times higher likelihood (AOR = 2.168; p = 0.049). Throughout the years, metal clips have shown the best prognosis compared to any other method for securing the cystic duct during closure in laparoscopic cholecystectomy. However, to avoid incomplete sealing of wide, short, or inflamed ducts, other instruments have emerged as possible alternatives for such conditions. Use of Endo-GIA is a safe and effective method for patients with wide, short cystic duct. Selective usage of endo-GIA is considered cost effective and may add a positive impact in decreasing post operative biliary leak.

We consider the controllability of multi-agent dynamical systems modeled by a particular class of bipartite graphs, called chain graphs. Our main focus is related to chain graphs with exactly one repeated degree. We determine all chain graphs with this structural property and derive some properties of their Laplacian eigenvalues and associated eigenvectors. On the basis of the obtained theoretical results, we compute the minimum number of leading agents that make the system in question controllable and locate the leaders in the corresponding graph. Additionaly, we prove that a chain graph with exactly one repeated degree, that is not a star or a regular complete bipartite graph, has the second smallest Laplacian eigenvalue (also known as the algebraic connectivity) in $ (0.8299, 1) $ and we show that the second smallest eigenvalue increases when the number of vertices increases. This result is of a particular interest in control theory, since families of controllable graphs whose algebraic connectivity is bounded from below model the systems with a small risk of power or communication failures.

Abstract The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The ‘cleaning’ factor has the highest weight, and ‘updating’ is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals.

Aunque las universidades juegan un papel crucial en la esfera pública a través de la educación, su impacto en el tejido urbano y social de las comunidades que las acogen es menos claro. Este artículo examina el auge del término “eds and meds” en Estados Unidos, que posiciona a las instituciones educativas y médicas como actores clave en el entorno urbano, y explora los debates intelectuales y de política que ha suscitado. Analiza la transición conceptual y discursiva desde el involucramiento social académico hacia una renovación urbana impulsada por empresas privadas sin fines de lucro, cuestionando la visión a menudo acrítica de las universidades como agentes inherentemente positivos para la comunidad. Al revelar los persistentes desajustes entre las ambiciones institucionales y las necesidades comunitarias, este estudio ofrece un análisis crítico y oportuno sobre un discurso ostensiblemente preocupado por el rol de las universidades en la vida cívica.

Abstract Background Hypodontia is the most prevalent dental anomaly in humans, and is primarily attributed to genetic factors. Although genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNP) associated with hypodontia, genetic risk assessment remains challenging due to population-specific SNP variants. Therefore, we aimed to conducted a genetic analysis and developed a machine-learning-based predictive model to examine the association between previously reported SNPs and hypodontia in the Saudi Arabian population. Our case–control study included 106 participants (aged 8–50 years; 64 females and 42 males), comprising 54 hypodontia cases and 52 controls. We utilized TaqManTM Real-Time Polymerase Chain Reaction and allelic genotyping to analyze three selected SNPs (AXIN2: rs2240308, PAX9: rs61754301, and MSX1: rs12532) in unstimulated whole saliva samples. The chi-square test, multinomial logistic regression, and machine-learning techniques were used to assess genetic risk by using odds ratios (ORs) for multiple target variables. Results Multivariate logistic regression indicated a significant association between homozygous AXIN2 rs2240308 and the hypodontia phenotype (ORs [95% confidence interval] 2.893 [1.28–6.53]). Machine-learning algorithms revealed that the AXIN2 homozygous (A/A) genotype is a genetic risk factor for hypodontia of teeth #12, #22, and #35, whereas the AXIN2 homozygous (G/G) genotype increases the risk for hypodontia of teeth #22, #35, and #45. The PAX9 homozygous (C/C) genotype is associated with an increased risk for hypodontia of teeth #22 and #35. Conclusions Our study confirms a link between AXIN2 and hypodontia in Saudi orthodontic patients and suggests that combining machine-learning models with SNP analysis of saliva samples can effectively identify individuals with non-syndromic hypodontia.

Abstract Purpose The diagnosis and management of prostate cancer (PCa), the second most common cancer in men worldwide, are highly complex. Hence, patients often seek knowledge through additional resources, including AI chatbots such as ChatGPT and Google Bard. This study aimed to evaluate the performance of LLMs in providing education on PCa. Methods Common patient questions about PCa were collected from reliable educational websites and evaluated for accuracy, comprehensiveness, readability, and stability by two independent board-certified urologists, with a third resolving discrepancy. Accuracy was measured on a 3-point scale, comprehensiveness was measured on a 5-point Likert scale, and readability was measured using the Flesch Reading Ease (FRE) score and Flesch–Kincaid FK Grade Level. Results A total of 52 questions on general knowledge, diagnosis, treatment, and prevention of PCa were provided to three LLMs. Although there was no significant difference in the overall accuracy of LLMs, ChatGPT-3.5 demonstrated superiority over the other LLMs in terms of general knowledge of PCa (p = 0.018). ChatGPT-4 achieved greater overall comprehensiveness than ChatGPT-3.5 and Bard (p = 0.028). For readability, Bard generated simpler sentences with the highest FRE score (54.7, p

Abstract Background The purpose of the study was to assess visual outcomes, complications, intraocular lens (IOL) stability, and corneal status after sutured scleral-fixated intraocular lens implantation combined with penetrating keratoplasty (PKP). Methods This retrospective single-arm cohort study included patients who underwent PKP and sutured scleral-fixated intraocular lens implantation between 2013 and 2018 at the Dhahran Eye Specialty Hospital. The eyes were examined postoperatively at 1, 3, 6, 12, and 24 months. Corneal status, complications, and IOL status were also evaluated periodically, and the number of eyes with a BCVA of > 20/200 was recorded. Results Twenty-two eyes from 22 patients were included. The median duration of follow-up was 3 (IQR 1.8; 4.4) years. Reasons for surgery were traumatic globe rupture (six eyes, 27.3%), bullous keratopathy (nine eyes, 40.1%), failed previous graft (five eyes, 22.7%), and corneal scarring (two eyes, 9.1%). Twelve (54.5%) eyes showed a BCVA of > 20/200 (non-blind) at 12 months after surgery and only five (22.7%) before surgery. Twelve months after surgery, 13 patients showed an improvement in BCVA in two lines (59.1%), seven remained the same (31.8%), and 2 deteriorated (9.1%). The indication for surgery (p = 0.2) and the stability of the sutured-scleral fixated IOL (p = 0.8) were not associated with an improvement in BCVA at the final follow-up. The corneal graft remained clear in nine eyes (40.9%) at a median duration of 3 years. The overall average survival period for all corneal grafts was 42.9 months. Conclusions The combination of sutured scleral-fixated intraocular lens implants and PKP is an effective intervention for preserving visual acuity in patients with complex cases. However, the risk of graft failure and then need for repeat transplantation should be taken into consideration.

Women-owned small and medium-sized enterprises (SMEs) may have difficulties in establishing networks and business partnership. This is in particular because they may have limitations in building social interaction, which in turn enhances their entrepreneurial activities and business performance. However, this may differ in matrilineal such as Minangkabau, where women have privileges, including in business activities. They are inherited ancestral properties such as land and houses that can be seen as valuable assets in starting and developing businesses. Therefore, it is interesting to know whether women-owned SMEs in Minangkabau can benefit from social capital, more specifically, bridging social capital. This type of social capital signifies social interaction with weak ties or new people from new places. This paper aims to examine the relationships between social capital, innovation, and performance in the context of women-owned SMEs in Minangkabau. We employed a quantitative approach using smartPLS 4.0. Data were analyzed from 100 women-owned SMEs in Padang, the capital of West Sumatra. It was found that bridging social capital is significantly and positively related to innovation and performance. Additionally, innovation mediated the relationship between bridging social capital and women-owned SME performance. Accordingly, promoting bridging social capital and innovation to women-owned SMEs is an effective way to enhance business performance. This may confirm that women-owned SMEs need to expand their social interaction with new people and from new places. In this case, they can benefit from digital technology facilitating this and increase their degree of innovation.

Abstract Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which can lead to cancer. Machine learning and deep learning methods have emerged as vital tools in identifying mutations associated with cancer. Thyroid cancer ranks as the 5th most prevalent cancer in the USA, with thousands diagnosed annually. This paper presents an ensemble learning model leveraging deep learning techniques such as Long Short-Term Memory (LSTM), Gated Recurrent Units (GRUs), and Bi-directional LSTM (Bi-LSTM) to detect thyroid cancer mutations early. The model is trained on a dataset sourced from asia.ensembl.org and IntOGen.org, consisting of 633 samples with 969 mutations across 41 genes, collected from individuals of various demographics. Feature extraction encompasses techniques including Hahn moments, central moments, raw moments, and various matrix-based methods. Evaluation employs three testing methods: self-consistency test (SCT), independent set test (IST), and 10-fold cross-validation test (10-FCVT). The proposed ensemble learning model demonstrates promising performance, achieving 96% accuracy in the independent set test (IST). Statistical measures such as training accuracy, testing accuracy, recall, sensitivity, specificity, Mathew's Correlation Coefficient (MCC), loss, training accuracy, F1 Score, and Cohen's kappa are utilized for comprehensive evaluation.

Cytochrome c is a vital electron carrier in the mitochondrial respiratory chain. When the outer membrane of mitochondria becomes permeable, cytochrome c is discharged into the cytoplasm, where it initiates the intrinsic apoptosis pathway. The complex interaction between cytochrome c and apoptosis protease-activating factor-1 (Apaf-1) leads to the formation of the apoptosome and activation of a cascade of caspases, highlighting the critical role of cytochrome c in controlling cell death mechanisms. Additionally, cytochrome c undergoes post-translational modifications, especially phosphorylation, which intricately regulate its roles in both respiration and apoptosis. These modifications add layers of complexity to how cytochrome c effectively controls cellular functions. cytochrome c becomes a lighthouse in the intricate web of cancer, its expression patterns providing hints about prognosis and paths toward treatment. Reduced levels of cytochrome c have been observed in cancer tissues, indicating a potential inhibition of apoptosis. For instance, in glioma tissues, cytochrome c levels were lower compared to healthy tissues, and this reduction became more pronounced in advanced stages of the disease. However, the role of cytochrome c in cancer becomes more intricate as it becomes intertwined with the metabolic reprogramming of cancer cells. This suggests that cytochrome c plays a crucial role in tumor progression and resistance to treatment. Viewing cytochrome c as a molecular mosaic reveals that it is not merely a protein, but also a central player in determining cellular fate. This realization opens up exciting avenues for potential advancements in cancer diagnosis and treatment strategies. Despite the advancements made, the narrative surrounding cytochrome c remains incomplete, urging further exploration into its complexities and the biological implications linked to cancer. cytochrome c stands as a beacon of hope and a promising target for therapy in the battle against cancer, particularly due to its significant involvement in tumor metabolism. It holds the potential for a future where innovative solutions can be developed to address the intricate challenges of cellular fate. In this review, we have endeavored to illuminate the multifaceted domain of cytochrome c drawing connections among apoptosis, metabolic reprogramming, and the Warburg effect in the context of cancer.

Land-based livelihoods in Pakistan's high mountain regions are highly vulnerable to climate change due to the complex interactions between people and their natural environment. This study uses a mixed-method approach to explore how climate change affects land-based livelihoods in the high mountain Nagar District, Pakistan. Data were collected using a structured household survey of 430 randomly selected farmers, supplemented by focus group discussions and key informant interviews. The findings reveal that 87.7 % of farmers have observed negative impacts of climate change, such as increased crop diseases, reduced water for irrigation, and lower crop yields. Bivariate results indicate that factors related to farming practices, such as farming experience and cropping zones, significantly influence farmers' perceptions of impacts. The study emphasizes the urgent need for targeted government intervention and agricultural planning to boost the resilience of farmers in Nagar District. It calls for improved irrigation, crop disease management, and support tailored to high-mountain farming practices. The research highlights the importance of developing adaptation strategies to protect vulnerable farming communities from climate change impacts and supports the need for effective autonomous adaptation measures. This research contributes to a better understanding of climate change impacts on high-mountain agriculture and emphasizes the need to safeguard vulnerable farming communities.

Background Antimicrobial resistance is increasing at an alarming rate. The use of antibiotics without a prescription by a patient or other family members and their inappropriate storage have caused serious health issues as it would lead to antibiotic resistance and exposure to the risk of harmful adverse effects unnecessarily. Therefore, the study aimed to evaluate the current behaviour of antibiotic usage, storage, re-usage and misuse among the residents of Saudi Arabia. Methods This is a cross-sectional study. Our target study population was the residents of Saudi Arabia. Data were collected by an online questionnaire and analysed by SPSS. Results A total of 738 participants answered the online questionnaire from all ages, genders, nationalities, and socioeconomic backgrounds residing in different regions across the Kingdom of Saudi Arabia. 76.42% knew that an antibiotic is a chemical substance used to treat infections. The participants were questioned about when they started using antibiotics, to which 95.66% (n=706) responded after consulting a physician, 3.25% (n=24) said when they felt ill for any reason, and 1.08% (n=8) replied after first attempting herbal medicine. A total of 147 participants admitted that they store excess pills of antibiotics after being prescribed for an infection and reuse them later on for symptoms like sore throat and fever. Conclusions The results indicated that nearly half of the participants used leftover antibiotics. Participants having children in their homes significantly reuse antibiotics. However, one-third of the participants didn’t complete the antibiotics course. A large portion of the population, regardless of age, level of education, or professional background, have continued to store leftover antibiotics after an infection treatment and reuse them once they think they need them for new symptoms. This advice further revises the current measures to fill those gaps and reduce this habit.

Background/objectivesSaudi Arabia is experiencing a rapid increase in chronic diseases and disabilities. However, there is a dearth of research on these topics in the Arab world. This study aimed to examine the prevalence of multiple long-term chronic conditions (MLTCs) and disabilities and their relationship.MethodsThe survey was conducted in Riyadh, Saudi Arabia, in 2023. Convenient sampling was used to select 324 participants aged 50 years and older, using data on disabilities status. The survey collected information on age, sex, body mass index (BMI), MLTCs or multi-morbidity, and activities of daily living (ADL). Disabilities was measured using Arabic versions of basic ADL and the Barthel index.ResultsThe prevalence of MLTCs among participants was 49.4%. The prevalence of disabilities measured using the ADL and Barthel index was 33.6 and 49.7%, respectively, and these rates increased by 42.5 and 58.1% among participants with MLTCs (n = 160). MLTCs were associated with an increased risk of disabilities using ADL [odds ratio (OR) 1.99, p = 0.037] and the Barthel index (OR 2.27, p = 0.007).ConclusionApproximately half of the participants with disabilities data had MLTCs, and approximately a third to half had a disabilities. MLTCs were significantly associated with various types of disabilities among community-dwelling Saudi adults. Hence, strategies to reduce chronic diseases may result in a reduction in disabilities, and vice versa.

IntroductionAdaptation to climate change (ACC) is imperative to avoid deleterious consequences of climate change in agriculture. However, the uptake of adaptation measures has been slow among farmers because of low adaptive capacity (AC) in developing countries, particularly in Pakistan. Farmers and their supporting institutions have been successful in introducing technological innovations to respond and adapt to environmental challenges. The present study intended to determine the impact of farming technologies, along with human, financial, social, physical, natural, and climate information resources that support AC and hence ACC.MethodsThe study collected data from 360 farmers in Punjab through a multi-stage random sampling technique. A binary logit model and odds ratio were used to identify the factors affecting ACC. The study also utilized correlation tests to show the correlation between each pair of variables included in the analysis.ResultsThe results indicated that physical capital such as ownership of tube wells, transportation, and sowing and harvesting tools by the farmers builds farmers’ AC and consequently determines the ACC such as change crop variety (CCV), change crop type (CCT), change planting date (CPD), soil conservation (SC), water conservation (WC), and diversification strategies (DSs). The findings also revealed that human capital (age, education, family size, and labor), financial capital (off-farm employment, access to the marketing of produce, and agricultural credit), social capital (farmers-to-farmers extensions, access to extension services, and the farm association membership), and natural capital (land ownership, tenancy status, and the location of the farm) were importantly related to farm households’ ACC strategies. The odds (likelihood) of adaptation were higher for the users of farm technology as compared to non-users.DiscussionThe analysis conducted in this study showed that climate information resources amplify the adaptation to climate change: technology allows farming to be much more efficient, while climate change knowledge (CCK) self-motivates farmers to adopt more ACC measures. Our findings provide evidence that suggests the need to provide credits and financial support for farming technologies that speed up the ACC in the long run, while in the short run, climate information should be spread among farming communities.

Abstract Ocular diseases can cause vision problems or even blindness if they are not detected early. Some ocular diseases generate irregular physical changes in the eye; therefore, reliable diagnostic technology for continuous monitoring of the eye is an unmet clinical need. In this study, a pulsed laser (Nd:YAG) was used to create optical nanostructures on a hydrogel-based commercial contact lens. Simulations were used to determine the spacing of the nanostructures, which were then produced and tested on the lens in ambient humidity and fully hydrated environments. The nanostructures produced a 4° diffraction angle difference in response to the environmental changes. Vision obstruction was considered while designing the nanostructure features on the lens. The curved nanostructures exhibited a series of visible rainbow colors with an average range of 8° under normal room light. A spherical surface was also used to simulate the human eye, and application of a force (curvature change) caused the nanostructure spacing to change, influencing the visible color of the contact lenses. A smartphone camera application was used to measure the progress of ocular diseases by analyzing the RGB color values of the visible color. The nanostructures were also responsive to K+ ion variations in artificial tear fluids, with a 12 mmol L−1 sensitivity, which may allow the detection of ocular ionic strength changes.

Abstract Data on the association between social isolation, loneliness, and risk of incident coronary heart disease (CVD) are conflicting. The objective of this study is to determine the relationship between social isolation and loneliness, and the risk of developing cardiovascular disease (CVD) in middle age and elderly using meta-analysis. The purpose of the bibliometric analysis is to systematically evaluate the existing literature on the relationship between social isolation, loneliness, and the risk of developing cardiovascular disease (CVD) in middle-aged and elderly individuals. A comprehensive search through four electronic databases (MEDLINE, Google Scholar, Scopus, and Web of Science) was conducted for published articles that determined the association between social isolation and/or loneliness and the risk of developing coronary heart disease from June 2015 to May 2023. Two independent reviewers reviewed the titles and abstracts of the records. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline to conduct the systematic review and meta-analysis. Data for the bibliometric analysis was obtained from the Scopus database and analyzed using VOSviewer and Bibliometrix applications. Six studies involving 104,511 patients were included in the final qualitative review and meta-analysis after screening the records. The prevalence of loneliness ranged from 5 to 65.3%, and social isolation ranged from 2 to 56.5%. A total of 5073 cardiovascular events were recorded after follow-up, ranging between 4 and 13 years. Poor social relationships were associated with a 16% increase in the risk of incident CVD (Hazard Ratio of new CVD when comparing high versus low loneliness or social isolation was 1.16 (95% Confidence Interval (CI) 1.10–1.22). The bibliometric analysis shows a rapidly growing field (9.77% annual growth) with common collaboration (6.37 co-authors/document, 26.53% international). The US leads research output, followed by the UK and Australia. Top institutions include University College London, Inserm, and the University of Glasgow. Research focuses on "elderly," "cardiovascular disease," and "psychosocial stress," with recent trends in "mental health," "social determinants," and "COVID-19". Social isolation and loneliness increase the risk of and worsen outcomes in incident cardiovascular diseases. However, the observed effect estimate is small, and this may be attributable to residual confounding from incomplete measurement of potentially confounding or mediating factors. The results of the bibliometric analysis highlight the multidimensional nature of CVD research, covering factors such as social, psychological, and environmental determinants, as well as their interplay with various demographic and health-related variables.

Purpose: Holmium laser enucleation of the prostate (HoLEP) showed higher efficacy than transurethral resection for treating benign prostatic hyperplasia (BPH). The present study aims to report the outcome of BPH treatment by HoLEP in a tertiary center. Patients and Methods: An observational prospectively collected data for consecutive symptomatic BPH patients undergoing HoLEP between January 2020 and December 2021. Demographic and perioperative data were collected with the International Prostate Symptom Score (IPSS), quality of life, peak flow rate (Qmax), residual urine postvoid residual (PVR), and prostate-specific antigen (PSA) changes, in addition to perioperative and late adverse events. Results: One hundred patients were included with a median age of 73 years (range 65–80). The IPSS improved by 80% postoperatively (25 vs. 5, P < 0.001). Similarly, Qmax significantly improved. Seven patients were found to have incidental prostate cancer. No patient needed a perioperative blood transfusion. Compared to its preoperative values, follow-up PSA has been reduced by 75% (P < 0.001). Urethral stricture and bladder neck contracture were noted in < 2% of the patients. Conclusions: HoLEP is feasible for all prostate sizes and a safe and effective treatment for BPH patients; our results are consistent with the reported data in the literature regarding functional outcomes, complication rates, and urinary incontinence rates.

Aloe species are known for the treatment of various conditions including diabetes mellitus, hypocholesteremia, and glycation end products. Nevertheless, the biological activity of Aloe armatissima is yet to be reported. It is a first-time report to evaluate the Aloe armatissima leaves (AAL) extract for its antioxidant, anti-glycation, anti-hyperglycemic, and anti-hyperlipidemic potential. In vitro tests of 1,1-diphenyl-2-picrylhydrazyl for the antioxidant and HSA for the antiglycation activity whereas in vivo models were used to assess the toxicity, antihyperglycemic, and anti-hypercholesteremic effects. The volatile profile was determined via gas chromatography-mass spectrometry. The IC50 values of 116 ± 0.66 (μg/mL) for antioxidant activity and 0.21 ± 0.009 (mg/mL) for antiglycation activity were observed for the AAL extract. The acute toxicity in the animal model revealed a lack of toxicity for the extract. The in vivo models exhibited a dose-dependent hypoglycemic and anti-hyperglycemic effects with significant (P < 0.01) blood glucose levels reduction. Moreover, a profound decrease in serum cholesterol, triglyceride, and LDL along with a significant (P < 0.05) increase in HDL and serum insulin levels was recorded. The statistical analysis demonstrated the values of F (24,125) = 23.95, P = 0.001, effect size = 1.95 (normoglycemic mice), F (24,125) = 143.21, P = 0.001, effect size = 4.79 (glucose loaded mice), and F (24,125) = 82.69, P = 0.001, effect size = 3.6 (diabetic model). GCMS showed the presence of eleven compounds with tetratetracontane (100%), β-sitosterol (27.76), and vitamin E (18.68) in major amounts. The results underscore the extract’s capacity to effectively combat various ailments; however, the active phytochemicals need to be isolated and the pharmacological activities may be established at the molecular level.

Abstract Background Healthcare programs and insurance initiatives play a crucial role in ensuring that people have access to medical care. There are many benefits of healthcare insurance programs but fraud in healthcare continues to be a significant challenge in the insurance industry. Healthcare insurance fraud detection faces challenges from evolving and sophisticated fraud schemes that adapt to detection methods. Analyzing extensive healthcare data is hindered by complexity, data quality issues, and the need for real-time detection, while privacy concerns and false positives pose additional hurdles. The lack of standardization in coding and limited resources further complicate efforts to address fraudulent activities effectively. Methodolgy In this study, a fraud detection methodology is presented that utilizes association rule mining augmented with unsupervised learning techniques to detect healthcare insurance fraud. Dataset from the Centres for Medicare and Medicaid Services (CMS) 2008-2010 DE-SynPUF is used for analysis. The proposed methodology works in two stages. First, association rule mining is used to extract frequent rules from the transactions based on patient, service and service provider features. Second, the extracted rules are passed to unsupervised classifiers, such as IF, CBLOF, ECOD, and OCSVM, to identify fraudulent activity. Results Descriptive analysis shows patterns and trends in the data revealing interesting relationship among diagnosis codes, procedure codes and the physicians. The baseline anomaly detection algorithms generated results in 902.24 seconds. Another experiment retrieved frequent rules using association rule mining with apriori algorithm combined with unsupervised techniques in 868.18 seconds. The silhouette scoring method calculated the efficacy of four different anomaly detection techniques showing CBLOF with highest score of 0.114 followed by isolation forest with the score of 0.103. The ECOD and OCSVM techniques have lower scores of 0.063 and 0.060, respectively. Conclusion The proposed methodology enhances healthcare insurance fraud detection by using association rule mining for pattern discovery and unsupervised classifiers for effective anomaly detection.

Sign language serves as a sophisticated means of communication vital to individuals who are deaf or hard of hearing, relying on hand movements, facial expressions, and body language to convey nuanced meaning. American Sign Language (ASL) exemplifies this linguistic complexity with its distinct grammar and syntax. The advancement of real-time ASL gesture recognition has explored diverse methodologies, including motion sensors and computer vision techniques. This study specifically addresses the recognition of ASL alphabet gestures using computer vision through Mediapipe for hand movement tracking and YOLOv8 for training the deep learning model. The model achieved notable performance metrics: precision of 98%, recall rate of 98%, F1 score of 99%, mean Average Precision (mAP) of 98%, and mAP50-95 of 93%, underscoring its exceptional accuracy and sturdy capabilities.

Background: The carbapenem-resistant Klebsiella pneumoniae poses a serious threat to public health because carbapenems are used as a final resort to treat K. pneumoniae-mediated infections in humans. Methods: Samples were collected from various clinical specimens including skin swabs, anal swabs, wound swabs, oral swabs, and sputum by the standard method and K. pneumoniae strains were isolated. Biofilm-forming characters were determined. The antibiotic resistance pattern was analyzed by the Kirby–Bauer disk diffusion method. Carbapenem resistance properties were tested using the imipenem and meropenem antibiotics. The carbapenemase genes (blaKPC and blaNDM) were determined. Results: A total of 11 cephalosporin-resistant K. pneumoniae (CRKP) strains were isolated from the samples. The screened CRKP strains exhibited multi-drug resistance and non-susceptible to imipenem, ceftazidime, piperacillin, ceftriaxone, cefazolin, ampicillin, aztreonam, and cefotetan antibiotics. A total of 79.4 % K. pneumoniae isolates showed positive results on String-forming test. About 82.1 % of isolates showed mucoid colonies and 59 % of K. pneumoniae strains formed biofilm (p

The main consequence of climate change on temperature is global warming. Over the past century, worldwide temperature has increased, rising by about 0.14 degrees Fahrenheit every year. Rising temperature negatively affects morphology, physiology, and yield of crops. Over the last 5 years, agriculture production in Pakistan affected due to temperature increase. Pakistan is an agriculture based developing country. About 2.2% GDP of Pakistan depends on wheat crop which is 1st major cereal crop and ranked as staple food. Nutritionally it provides proteins, dietary fibers, carbohydrates, calcium, and other important compounds but because of the harmful effects of a high temperature, yield of wheat crop in Pakistan has reduced to lowest levels in the last few years. Heat stress affects wheat plants by reducing growth, raised reactive oxygen species (ROS) production, denature cell membranes, and enzymes activity, decreasing photosynthetic activity and disturbing respiration processes. Improving wheat crop productivity is urgently needed to feed the rapidly growing population. Several techniques like Quantitative Trait Locus mapping, omics techniques, and application of nutrients have been used in the past to mitigate high temperature effect on wheat and other different crop plants. This review critically analyzes the response of wheat towards heat stress and its impacts on wheat crop as well as provides critical information on advanced strategies and techniques for the mitigation of heat stress.

ABSTRACT Outbreaks of influenza A viruses are generally seasonal and cause annual epidemics worldwide. Due to their frequent reassortment and evolution, annual surveillance is of paramount importance to guide vaccine strategies. The aim of this study was to explore the molecular epidemiology of influenza A virus and nasopharyngeal microbiota composition in infected patients in Saudi Arabia. A total of 103 nasopharyngeal samples from 2015 and 12 samples from 2022 were collected from patients positive for influenza A. Sequencing of influenza A as well as metatranscriptomic analysis of the nasopharyngeal microbiota was conducted using Oxford Nanopore sequencing. Phylogenetic analysis of hemagglutinin, neuraminidase segments, and concatenated influenza A genomes was performed using MEGA7. Whole-genome sequencing analysis revealed changing clades of influenza A virus: from 6B.1 in 2015 to 5a.2a in 2022. One sample containing the antiviral resistance-mediating mutation S247N toward oseltamivir and zanamivir was found. Phylogenetic analysis showed the clustering of influenza A strains with the corresponding vaccine strains in each period, thus suggesting vaccine effectiveness. Principal component analysis and alpha diversity revealed the absence of a relationship between hospital admission status, age, or gender of infected patients and the nasopharyngeal microbial composition, except for the infecting clade 5a.2a. The opportunistic pathogens Staphylococcus aureus, Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis were the most common species detected. The molecular epidemiology appears to be changing in Saudi Arabia after the COVID-19 pandemic. Antiviral resistance should be carefully monitored in future studies. In addition, the disease severity of patients as well as the composition of the nasopharyngeal microbiota in patients infected with different clades should also be assessed.IMPORTANCEIn this work, we have found that the clade of influenza A virus circulating in Riyadh, KSA, has changed over the last few years from 6B.1 to 5a.2a. Influenza strains clustered with the corresponding vaccine strains in our population, thus emphasizing vaccine effectiveness. Metatranscriptomic analysis showed no correlation between the nasopharyngeal microbiome and the clinical and/or demographic characteristics of infected patients. This is except for the 5a.2a strains isolated post-COVID-19 pandemic. The influenza virus is among the continuously evolving viruses that can cause severe respiratory infections. Continuous surveillance of its molecular diversity and the monitoring of anti-viral-resistant strains are thus of vital importance. Furthermore, exploring potential microbial markers and/or dysbiosis of the nasopharyngeal microbiota during infection could assist in the better management of patients in severe cases.

This study focuses on the synthesis, characterization, and use of zinc oxide nanoparticles (ZnONPs) derived from W. bifurcata fruit peel extract. ZnONPs are frequently synthesized utilizing a green technique that is both cost-effective and ecologically friendly. ZnONPs were characterized utilizing analytical techniques. Ultra Violet visible (UV-Vis) spectra showed peaks at 364 nm, confirming the production of ZnONPs. Scanning Electron Microscope analysis indicated that the nanoparticles generated were spherical/agglomerated, with diameters ranging from 11 to 25 nm. FTIR spectroscopy was used to identify the particular functional groups responsible for the nanoparticles’ reduction, stabilization, and capping. Phytochemical analysis of the extract revealed that flavonoids, saponins, steroids, triterpenoids, and resins were present. The antibacterial activity of W. bifurcata synthesised nanoparticles was evaluated against pathogenic bacteria. The ZnONPs antioxidant activity was assessed using DPPH assay. The in vitro cytotoxicity was assessed against prostate cancer PC3 cells. The wound healing potential was assessed by employing in vitro scratch assay and in vivo excision model in Wistar rats. Because of its environmentally benign production, low toxicity, and biocompatibility, ZnONPs exhibited potential antibacterial, antioxidant, anticancer, and wound healing activities, indicating that they could be used in cancer treatment and wound management. Further study is required to examine the fundamental mechanisms and evaluate the safety and effectiveness of the test sample in clinical situations.

Urban stormwater drains in Kurunegala City collect runoff and untreated wastewater, leading to public health problems. The Greater Kurunegala Sewage Treatment Plant (GKSTP) was commissioned in 2018 and currently operates at 73% of its capacity to combat public health issues. This study assessed the water quality of canals, comparing it with standards and pre-GKSTP conditions. Water samples were collected from seven sites during dry and wet seasons, and physicochemical parameters were measured. The data underwent spatial and temporal analysis using the general linear model (GLM). Additionally, cluster analysis and distance-based redundancy analysis were employed. The water quality index (WQI) was employed to evaluate the effectiveness of the treatment plant. The study revealed significant spatial and temporal variations in physicochemical parameters along the canals (p < 0.05, GLM), with higher pollution levels during wet months. The WQI improved from 35 (2005) to 49 at present, indicating enhanced water quality (p < 0.05, ANOVA), although it remains unsatisfactory. This study provides novel insights into the limitations of conventional wastewater treatment practices, demonstrating that merely treating wastewater and discharging it back into canals is insufficient. Research underscores the importance of rethinking treated wastewater reuse in achieving multiple sustainable development goals (SDGs). This approach offers a pragmatic path forward for enhancing water security and environmental sustainability globally.

The current thermal slip and Magnetohydrodynamic analysis plays prominent importance in heat insulation materials, polishing of artificial heart valves, heat exchangers, magnetic resonance imaging and nanoburning processes. The main objective of the existing article is to deliberate the impact of thermal slip, thermal radiation and viscous dissipation on magnetized cone embedded in a porous medium under reduced gravitational pressure. Convective heating characteristics are used to increase the rate of heating throughout the porous cone. For viscous flow along a heated and magnetized cone, the conclusions are drawn. The simulated nonlinear partial differential equations are transformed into a dimensionless state by means of suitable non-dimensional variables. The technique of finite differences is implemented to solve the given model with Gaussian elimination approach. The FORTRAN language is used to make uniform algorithm for asymptotic results according to the boundary conditions. The influence of controlling parameters, such as thermal radiation parameter Rd, Prandtl number Pr, porosity parameter Ω, viscous dissipation parameter Ec, δ thermal slip parameter, Rg reduced gravity parameter and mixed convection parameter λ is applied. Graphical representations were created to show the consequences of various parameters on velocity, temperature and magnetic field profiles along with fluctuating skin friction, fluctuating heat and oscillatory current density. It is found that velocity and temperature profile enhances as radiation parameter enhances. It is noted that the amplitude and oscillations in heat transfer and electromagnetic waves enhances as magnetic Prandtl factor increases.

Objectives: The present study explored the ability of lignin-degrading enzyme-producing fungal isolates, Cladosporium uredinicola GRDBF21 (Accession No. KJ913698) and Bipolaris maydis GRDBF23 (Accession No. KJ913699) in the biodegradation of structurally complex chlorpyrifos (CPS). Methodology: Axenic cultures of the test isolates were acclimatised to CPS in Czapek Dox broth (CDB) containing 50 mgL−1 followed by 100 mgL−1 of CPS and subsequently with 200 mgL−1 of CPS as the only carbon source. A comparative evaluation of biomass production by the isolates in the presence and absence of CPS was made. The biodegradation of CPS by the isolates was evaluated by Gas Chromatography-Mass Spectrometry (GC–MS). Results: The Minimum Inhibitory Concentrations (MICs) of CPS against C. uredinicola GRDBF21 and B. maydis GRDBF23 were 700 mg/L and 1300 mg/L, respectively. In the presence of CPS, C. uredinicola GRDBF21 and B. maydis GRDBF23 exhibited biomass production and maximum laccase activity of 4.2 g/L & 5.15 g/L and 290.14 U L−1 & 164.91 U L−1, respectively. The GC–MS analysis proved an effective biodegradation of CPS, as only a negligible and unquantifiable amount of CPS was present after 20 d of incubation. Conclusion: These results are indicative that the test isolates could be effectively used in the bioremediation of recalcitrant environmental pollutants, especially organophosphate pesticides like CPS.

The combination of nickel (Ni) and titanium alloy (Ti) with silicon carbide (SiC) reinforcement offers promising avenues for research and applications due to their exceptional resistance to heat, oxidation, and corrosion properties. These studies investigate the influence of silicon carbide (SiC) on Ni-Ti matrix materials, focusing on Ni-Ti-SiC composites fabricated through the microwave sintering method. The microstructure analysis reveals uniform dispersion of Ni and Ti, indicating desirable properties. This study utilized the Taguchi methodology to optimize the wear rate of Ni-Ti-SiC composites by examining sliding distance, load, and sliding velocity as essential variables. The experimental findings showed a minimum wear rate of 0.014 mg/m under certain conditions and a maximum of 0.052 mg/m under other conditions. The optimal wear rate was determined using the signal-to-noise ratio (SN ratio) at a sliding distance of 1500 m, load of 20N, and sliding velocity of 1 m/s. Sliding distance was found to be the most significant factor affecting wear rate (55%), followed by load (32%) and sliding velocity (7.3%) according to the variance analysis. Scanning electron microscope (SEM) analysis showed increased wear grooves and a smoother surface in the specimen with the lower wear rate. Atomic force microscopy was used to analyze the worn surfaces, revealing detailed 3D image patterns. Surface parameters showed significant variations between surfaces with higher and lower wear rates. Surfaces with lower wear rates exhibited minimum average roughness (6.69 nm) and maximum peak-to-valley roughness (88.65 nm).

Literature reporting on the outcomes of the different procedures of nephrectomies (open vs laparoscopic vs robotic) in Saudi Arabia remains limited. Compare surgical and oncological outcomes between open and minimally invasive nephrectomies. A retrospective cohort study. The present study included all adult patients who underwent nephrectomies between January 1, 2015 and January 31, 2023. We collected demographic, preoperative, intraoperative, and postoperative data on 408 adult cancer patients who underwent nephrectomies at our center between January 2015 and January 2023. Statistical differences were calculated between procedure types. Overall survival was calculated using Kaplan–Meier curves with log-rank tests. P

IntroductionMental health among medical students is an area that has been increasingly garnering world-wide attention. Yet, despite this increased attention, research related to anxiety disorders in Saudi Arabia remain limited. This study aims to address this gap by assessing the prevalence of generalized anxiety disorder (GAD) as well as explore its association with students’ sociodemographic factors and academic performance among medical students in a Saudi Arabian institute that has a diverse, multicultural student body.MethodsThe study takes place in a unique educational environment: a privately funded institute in Riyadh, the capital of Saudi Arabia, with 32% of its student body comprising international students from over 40 countries, during the COVID-19 pandemic. The study deploys the use of a survey that was sent to the students at this institute via their institutional emails. A survey containing 33 items assessing demographics, GAD using GAD-7 questionnaire, stress-relief measures, online learning experience during the pandemic, mental disorders, anxiety associated with the pandemic, two open-ended questions, and one item assessing sleep difficulty.ResultsThe results of the survey showed that a significant majority of the responders’ scores in the GAD-7 assessment were in the range of moderate to severe anxiety. The results also suggest that low cGPA and the first academic years are significantly associated with higher GAD-7 scores. Students found severe time constraints, difficult educational content, and lack of psychological support to be major sources of stress. Furthermore, students suggested providing an in-house psychologist, personalized feedback, and guidance on study tactics as methods to reduce anxiety.ConclusionThese findings, among others, suggest a need for further studies and research in this field to uncover broader patterns and inform targeted mental health support strategies.

PURPOSEProstate cancer has emerged as a significant public health challenge in the Middle East, characterized by rising incidence rates and a concerning mortality-to-incidence ratio. Yet, despite these alarming trends, data regarding prostate cancer awareness in the region remain limited. To address this critical knowledge gap, this study investigates prostate cancer awareness within the Middle East.MATERIALS AND METHODSA cross-sectional survey was performed among 5,913 men age 40 years and older across 14 Middle Eastern countries between January 1, 2022, and July 31, 2023. Excluding those with a history of prostate cancer, a validated questionnaire assessed prostate cancer awareness. Data were analyzed using frequencies and percentages for categorical variables, medians and ranges for continuous variables, and Pearson chi-square analysis for relationships between education levels and awareness of prostate cancer.RESULTSThe survey achieved a 74.9% response rate, with 4,431 male participants. Regarding prostate cancer awareness, 83.8% of participants had heard of the disease. However, only 31.0% correctly identified it as the most common malignancy in men, and 21.8% believed it affects both sex. Awareness of screening was limited, with just 19.1% recognizing the prostate-specific antigen test's role. Additionally, participants had a pessimistic view, with a mean perception that 75% of patients with prostate cancer die from the disease, rather than from other causes. Higher education levels were associated with significantly increased awareness of prostate cancer (P < .001).CONCLUSIONThis study reveals that while general awareness of the disease exists, crucial knowledge deficits regarding risk factors, screening, and prognosis are evident. Addressing these knowledge gaps through culturally tailored education may improve early detection rates, treatment outcomes, and ultimately reduce the burden of prostate cancer in the Middle East.

Biodegradable mulch (BDMs) films are ecologically safe substitutes for polyethylene mulches (PEMs) in agricultural systems. However, since it is an innovative technology on the market, it is not easy for farmers to adopt it. Understanding farmers' familiarity with BDM and their willingness to adopt it in the future could play a crucial role in the design and implementation of effective agricultural interventions for promoting the adoption of BDM to reduce environmental pollution. Therefore, a study was undertaken to assess farmers' familiarity with BDM and their willingness to adopt it in the future. Data were collected from fruit and vegetable growers located in Al-Kharj, Saudi Arabia, using a simple random sampling approach with the help of a pre-tested paper-based questionnaire. The findings revealed that most of the farmers were not familiar with BDM. Despite the lack of awareness, a considerable portion indicated their willingness to adopt BDM in the future. The farmers' education level, farm size, and membership in agricultural cooperatives significantly influenced their familiarity with BDM. Education level, farming experience, and membership in agricultural cooperatives also showed significant relationships with their willingness to adopt BDM in the future. Moreover, the farmers were not aware of the potential benefits of this new innovation. The study recommends that extension education programs through the active involvement of agricultural cooperatives should be implemented to make farmers aware of the advantages of BDM over PEM. In addition, the government should facilitate the adoption of this promising innovation by enhancing its availability on the market and affordability to farmers.

Introduction Traumatic rib fractures present a considerable risk to patient well-being, contributing to morbidity and mortality in trauma patients. To address the risks associated with rib fractures, evidence-based interventions have been implemented, including effective pain management, pulmonary hygiene, and early walking. Vancouver General Hospital, a level 1 trauma center in British Columbia, Canada, developed a comprehensive multidisciplinary chest trauma clinical practice guideline (CTCPG) to optimize the management of patients with rib fractures. This prospective cohort study aimed to assess the impact of the CTCPG on pain management interventions and patient outcomes.Methods The study involved patients admitted between January 1, 2021 and December 31, 2021 (post-CTCPG cohort) and a historical control group admitted between November 1, 2018 and December 31, 2019 (pre-CTCPG cohort). Patient data were collected from patient charts and the British Columbia Trauma Registry, including demographics, injury characteristics, pain management interventions, and relevant outcomes.Results Implementation of the CTCPG resulted in an increased use of multimodal pain therapy (99.4% vs 96.1%; p=0.03) and a significant reduction in the incidence of delirium in the post-CTCPG cohort (OR 0.43, 95% CI 0.21 to 0.80, p=0.0099). There were no significant differences in hospital length of stay, ICU (intensive care unit) days, non-invasive positive pressure ventilation requirement, ventilator days, pneumonia incidence, or mortality between the two cohorts.Discussion Adoption of a CTCPG improved chest trauma management by enhancing pain management and reducing the incidence of delirium. Further research, including multicenter studies, is warranted to validate these findings and explore additional potential benefits of the CTCPG in the management of chest trauma patients.Level of evidence IIb.

Background: Bacterial meningitis is an infectious condition associated with high rates of morbidity and mortality. Streptococcus pneumoniae is the most common cause of bacterial meningitis in adults. It is a highly fatal disease that often leaves survivors with serious neurologic damage if left untreated. Cerebral vasculitis is a rare but recognized complication of bacterial meningitis as seen in the literature. Patient and methods: We report a 55-year-old woman diagnosed with pneumococcal meningitis who developed cerebral vasculitis during her stay at the hospital. It was confirmed by cerebral magnetic resonance imaging (MRI) that showed multifocal ischemic lesions of the brain and the patient’s neurologic symptoms resolved after the administration of corticosteroids and the patient made a full recovery. In addition to MRI, many investigations were done to rule out other possible causes of these lesions and confirm cerebral vasculitis post pneumococcal meningitis as a diagnosis in this case. Conclusion: Cerebral vasculititis should be considered in patients who deteriorate on treatment, with MRI remaining the mainstay of diagnosis. However, with the absence of a specific MRI sequence that could confirm the diagnosis of vasculitis, it remains a diagnosis of exclusion. Some patients experience rapid onset of neurological deterioration shortly after meningitis, while others show delayed symptoms. Steroids are found to be the mainstay of treatment for vasculitis in the majority of cases. More research to determine the dosage, timing and duration is required.

We describe a case report of a 13 year-old a gymnastic athlete who was diagnosed with an olecranon stress fracture associated with mild medial epicondyle apophysitis, Following a brief review of the literature on this case, the researchers call attention to the significance of and imaging assessment especially MR in determining the correct diagnosis and identifying concomitant injuries. MRI findings concluded firstly a marked bone marrow edema seen at the posterior medial aspect of the olecranon with linear low signal traversing the olecranon related to a stress fracture. Secondly, subchondral linear low signal and bone marrow edema at the radial head related to another stress fracture/reaction injury. Thirdly, bone marrow edema at the medial apophysis with overlying soft tissue edema suggestive for medial epicondylitis.

Abstract Background Cardiovascular diseases (CVDs) are common chronic conditions that lead to morbidity and mortality worldwide. However, there are no recent national or regional reports about CVDs in Saudi Arabia. Therefore, this study aimed to estimate the national and regional prevalence rates of CVDs among the Saudi population. Methods This study used data from an ongoing household health survey conducted by the General Authority for Statistics in 2017. The survey sample comprised 24,012 homes that were determined to be a representative sample of the population and dispersed throughout the 13 administrative areas. A self-reported diagnosis of CVD was collected by asking subjects if they had been diagnosed by a physician. Results The prevalence of CVDs among the Saudi population aged 15 years and older was 1.6% (n = 236,815). The prevalence is higher in males at 1.9% compared to females at 1.4%. Age is a significant factor, with a gradual increase in CVD prevalence until the age of 50, followed by a sharp rise. The prevalence among the age group (≥ 65 years) was the highest, recording 11% (n = 93,971), followed by the age group (60–64 years) which reached 6.5% (n = 31156.71), and the lowest prevalence was found in the age group (

Background: Acetaminophen overdose is a common clinical condition, often leading to liver toxicity. Current treatments involve the three-infusion N-Acetylcysteine (NAC) regimen (FDA-labeled), which may be complex, time-consuming, and need to be changed. An alternative uses two infusions instead, which offers possible advantages regarding simplicity and administration errors. This study sought to compare the respective efficacies and safety outcomes when treating acute acetaminophen overdose among children and adolescents. Methods: At Montreal Children’s Hospital, a retrospective study was conducted comparing pre-2003 FDA-labelled three-infusion NAC therapy with a two-infusion regimen. Information was collected regarding patient demographics, NAC administration details, errors, rates of hepatotoxicity, and adverse reactions, and the statistical test Chi-square test was employed to obtain the results. Results: A total of 126 patients met the inclusion criteria. Of these patients, 65 received a two-infusion regimen, and 61 patients received the FDA-labeled regimen. The two-infusion group experienced significantly fewer administration errors (4 errors vs. 23 errors; p < 0.001), while the rates of hepatotoxicity between them were similar. There were no instances of liver transplantation or mortality due to either regimen. Adverse reactions occurred equally frequently between both regimens with no discernible difference—the meantime to administer NAC was 9 h for the two-infusion regimen and 8.5 h for FDA-labeled regimen groups, respectively. Three cases of hepatitis were successfully treated with timely NAC therapy, and no liver transplantation or mortality occurred. Adverse reactions, including anaphylactoid reactions, were observed in both groups but were resolved when temporarily stopped and restarted at a slower infusion rate. Conclusions: The two-infusion NAC regimen proved similar efficacy at protecting liver damage and improving patient outcomes compared to its FDA-labeled three-stage counterpart, with significantly fewer administration errors for this version of NAC treatment, suggesting potential advantages in terms of safety and simplicity. Future research should investigate larger cohorts and more variables to validate these results further and optimize the management of acetaminophen overdose cases; further investigation should focus on dosing strategies, personalized approaches, and long-term patient care in this context.

Abstract Background Despite the efficacy and safety of DIGIFab, it is relatively expensive and has limited availability. In addition, alternative interventions, such as therapeutic plasma exchange, may need to be considered in massive digoxin overdoses. Although few case reports describe its efficacy. Case presentation We report a case of a 17-year-old white male patient brought by family members to our emergency department in Riyadh, Saudi Arabia. After intentionally ingesting 48 mg of digoxin tablets to commit suicide, the patient’s initial digoxin serum level was 8.04 ng/mL. The patient was resuscitated in the emergency department. After admission to the intensive care unit, the patient underwent therapeutic plasma exchange, because of insufficient DIGIFab doses. Afterward, the serum digoxin levels drastically decreased, and his symptoms reverted. The patient was successfully managed and discharged 7 days after admission. Conclusion Despite insufficient evidence and a limited number of case reports describing the use of extracorporeal treatment in digoxin overdose, we noted the significant impact of therapeutic plasma exchange on our patient. However, therapeutic plasma exchange’s use in routine treatment requires stronger evidence to confirm its benefits.

The Internet of Things (IoT) market is experiencing exponential growth, with projections increasing from 15 billion dollars to an estimated 75 billion dollars by 2025. Quantum computing has emerged as a key enabler for managing the rapid expansion of IoT technology, serving as the foundation for quantum computing support. However, the adoption of quantum computing also introduces numerous privacy and security challenges. We delve into the critical realm of quantum-level security within a typical quantum IoT. To achieve this objective, we identified and precisely analyzed security attributes at various levels integral to quantum computing. A hierarchical tree of quantum computing security attributes was envisioned, providing a structured approach for systematic and efficient security considerations. To assess the impact of security on the quantum-IoT landscape, we employed a unified computational model based on Multi-Criteria Decision-Making (MCDM), incorporating the Analytical Hierarchy Process (AHP) and the Technique for Ordering Preferences by Similarity to Ideal Solutions (TOPSIS) within a fuzzy environment. Fuzzy sets were used to provide practical solutions that can accommodate the nuances of diverse and ambiguous opinions, ultimately yielding precise alternatives and factors. The projected undertaking was poised to empower practitioners in the quantum-IoT realm by aiding in the identification, selection, and prioritization of optimal security factors through the lens of quantum computing.

Summary: Background & aims: Severe obesity is a serious health condition defined as a body mass index (BMI) of 40 kg/m2 and more. It was found that individuals with severe obesity had a greater chance of getting nutritional deficiencies related to unhealthy or low nutritional value diets. Therefore, the assessment of nutritional status is highly essential in pre-bariatric surgeries. The study aimed to determine the dietary intake and biochemical parameters of Omani adult subjects with severe obesity who are about to undergo bariatric surgeries and to identify gender-specific differences in dietary and biochemical characteristics. Subjects & methods: A retrospective hospital-based study at the Royal Hospital, Ministry of Health, Muscat, Oman, included 104 Omani adult subjects (35 males and 69 females) diagnosed with severe obesity (BMI ≥ 40 kg/m2). A semi-quantitative food frequency questionnaire and blood tests were the study tools used to collect the data. The dietary intake was analyzed using the Cronometer software, while the biochemical parameters were analyzed using automated analyzers. Results: The majority of macro- and micro-nutrients were statistically significant from the recommended dietary intake (RDI) except for vitamin K and cholesterol for both genders. Among the males, the dietary intake of zinc, potassium, calcium, magnesium, vitamin B12 and vitamin B6 did not differ significantly from the RDI. Meanwhile, in females only pantothenic acid and zinc met the RDI. Macro- and micronutrient deficiencies were abundant among females with severe obesity as compared with males with severe obesity. The biochemical parameters measured in the sera of all study participants were within the normal range, except for serum phosphorus and low density lipoprotein (LDL), which were higher than the normal ranges. The study also revealed statistically significant differences in dietary and biochemical characteristics between males and females except in cholesterol, hemoglobin, LDL and vitamin B12, and vitamin D. Conclusion: This study concludes that the nutritional and biochemical assessment at pre-bariatric surgeries is vital to optimize long-term success and prevent further nutritional or related metabolic complications during the post-bariatric surgeries period.

The cohesion of an object-oriented class refers to the relatedness of its methods and attributes. Constructors, destructors, and access methods are special types of methods featuring unique characteristics that can artificially affect class cohesion quantification. Methods within a class can also directly or transitively invoke each other, representing another cohesion aspect not considered by most existing cohesion measures. The impact of considering special methods (SPs) and transitive relations (TRs) in cohesion measurement on the abilities of the measures to predict inheritance reusability has yet to be investigated. In this paper, we empirically explored this effect. We applied a statistical technique to test the significance of the cohesion value changes across seven scenarios of ignoring or considering SPs and TRs. In addition, we applied a machine learning-based technique to build inheritance reusability prediction models using each of the considered measures and scenarios, evaluated the classification performance of the prediction models, and statistically compared the inheritance reusability prediction results. The results show that for most of the considered measures, the ignorance/consideration of SPs and TRs changed the cohesion values and the corresponding prediction significantly. Based on the study findings, when building inheritance reusability prediction models, software engineers are advised to 1) combine cohesion with other quality factors; 2) exclude the TRs from cohesion quantification; and 3) decide whether to consider or ignore SPs in cohesion quantification based on the selected measure(s) to be used in the prediction model, as this decision differs from one measure to another.

Smart devices in smart cities face the dual challenge of requiring real-time data processing and storing that data permanently on the cloud for future use. This creates a significant conflict between the need for immediate responsiveness and the demands of long-term storage. While Cloud Computing (CC) offers a viable platform for processing and storing this data, it introduces delays, longer response times, and network congestion issues. Internet of Things (IoT) devices require real-time responses, but their data must also be available for subsequent analysis and decision-making. Although edge and fog computing paradigms have been developed to address these issues, they suffer from limited resources and scalability challenges, making them inadequate for the above needs. A hybrid paradigm is often proposed to address the limitations of both cloud and edge computing. However, synchronization between cloud and edge can introduce delays, negatively affecting overall performance. The proposed framework, Regional Computing (RC), addresses big data challenges in smart cities by providing an intermediate solution between edge (limited power) and cloud (distant) computing. RC manages data during peak hours, alleviating congestion on the public network. The collected data is subsequently offloaded to cloud servers for long-term storage and detailed analysis. Preliminary findings are very encouraging, indicating substantial enhancements in reducing network congestion, minimizing delays, and lowering costs.

The versatility and diverse applications of IoT-based Heterogeneous WSN (HWSN) technologies make them valuable tools for achieving sustainability goals in Sustainable Smart Cities (SSCs). Proper management of underlying heterogeneous architecture is crucial for the successful operation of smart applications. To prolong the WSN’s lifespan and avoid failures, effective energy management is essential. Although researchers are continually exploring heterogeneity in WSN, it gets more and more important to create cost-effective paradigms that cover multiple facets of SSC while ensuring their stability and reliability. The concept of Dominating Sets (DS) in a graph can be leveraged to minimize resource utilization in WSNs by arranging nodes into disjoint DS, with only one set executing duties at any given time. In this work, we propose a novel technique for IoT-based HWSNs-enabled SSC, called EADDSA, utilizing the DS concept to plan the sleep-and-awake scheme for heterogeneous nodes, based on their resource capabilities. We propose a new algorithm, called the Energy Attentive Algorithm (EAA), to find disjoint DSs that are energy-aware. EAA algorithm attentively tries to form the set that maximizes lifespan while adhering to DS conditions in each iteration. EADDSA further incorporates an effective DS scheduling strategy to enhance the HWSN lifetime by establishing operational guidelines for each round, taking into account the estimated lifetimes and the designated number of working rounds for each DS. This enables efficient allocation of data sensing and gathering tasks across the network minimizes resource usage, and extends network lifetime.

MITRE ATT&CK is a comprehensive knowledge-base of adversary tactics, techniques, and procedures (TTP) based on real-world attack scenarios. It has been used in different sectors, such as government, academia, and industry, as a foundation for threat modeling, risk assessment, and defensive strategies. There are valuable insights within MITRE ATT&CK knowledge-base that can be applied to various fields and applications, such as risk assessment, threat characterization, and attack modeling. No previous work has been devoted to the comprehensive collection and investigation of statistical insights of the MITRE ATT&CK dataset. Hence, this work aims to extract, analyze, and represent MITRE ATT&CK statistical insights providing valuable recommendations to improve the security aspects of Enterprise, Industrial Control Systems (ICS), and mobile digital infrastructures. For this purpose, we conduct a hierarchical analysis starting from MITRE ATT&CK threat profiles toward the list of techniques in the MITRE ATT&CK database. Finally, we summarize our key findings while providing recommendations that will pave the way for future research in the area.

Background: Supernumerary teeth numerical anomalies and the early diagnosis of supernumerary teeth is very important to avoid potential complications. The study aim was to determine the prevalence, occurrence, and characteristics of supernumerary teeth among the Arabian population. Methods: A retrospective radiographic study was performed using panoramic radiographs of patients attending a teaching hospital from January 2018 to December 2020. Only healthy patients with clear radiographs were included in the study, and patients with syndromes, cleft lip, and palate, and unclear radiographs were excluded from the study. The details include the patient’s age and gender, supernumerary tooth number, location, orientation, and position. Only a single examiner was involved in the data collection and analysis. Results: Overall, 38 (2%) patients were observed with 47 supernumerary teeth. Among them, 76% were males and 24% were females, with a mean age of 16.1 ± 9.7 years. Mesiodens (87%) are the common type of supernumerary tooth, and the majority of the supernumerary teeth were impacted (66%). The majority of the patients presented with a single supernumerary tooth, while 24% of the patients presented with two supernumerary teeth. Sixty percent of the supernumerary teeth were conical in morphology, followed by a tuberculate morphology. In the study population, most of the supernumerary teeth were normal in orientation. Conclusions: The prevalence of supernumerary teeth was 2%. Among them, the majority were observed at the anterior region of the maxillary arch with a conical shape of normal orientation. The gender-based comparison of location, orientation, morphology, eruption, and number of supernumerary teeth showed male predilection.

Mucormycosis is a rare, severe fungal infection mainly affecting immunocompromised individuals. Because of limited data on its epidemiology in Oman, we present this national, multicentric, retrospective review that includes all cases of proven mucormycosis between 2006 and 2022 in Oman. There were 51 cases of mucormycosis reported in Oman. The annual incidence of mucormycosis was 0.38–0.69 cases per million population before COVID-19. During the pandemic, the incidence rose significantly to 1.76 in 2020, 5.31 in 2021, then decreased to 0.87 per million population in 2022. Diabetes was observed in 82.4% (n = 42) of the cases, COVID-19 in 47.1% (n = 24), and other chronic diseases in 72.6%. The use of steroids was reported in 33.3% (n = 17) and many patients (64.7%, n = 33) had multiple risk factors. The overall mortality rate was 41.2% (n = 21) and most deaths occurred within a month of diagnosis. Mortality rate among patients diagnosed with COVID-19 was 58.3% (14/24). Survival analysis showed a statistically significant association between COVID-19 status and patient survival (p = 0.024). Annual incidence of mucormycosis in Oman rose during the pandemic. This study highlights the epidemiological features of mucormycosis and emphasizes the importance of its inclusion in the national notifiable communicable diseases priority list as well as the importance of enhancing diagnostic capacities to detect and improve patient outcomes.

Background: Early cancer detection is crucial for improving patient outcomes. Molecular imaging biomarkers offer the potential for non-invasive, early-stage cancer diagnosis. Objectives: To evaluate the effectiveness and accuracy of molecular imaging biomarkers for early cancer detection across various imaging modalities and cancer types. Methods: A comprehensive search of PubMed/MEDLINE, Embase, Web of Science, Cochrane Library, and Scopus was performed, covering the period from January 2010 to December 2023. Eligibility criteria included original research articles published in English on molecular imaging biomarkers for early cancer detection in humans. The risk of bias for included studies was evaluated using the QUADAS-2 tool. The findings were synthesized through narrative synthesis, with quantitative analysis conducted where applicable. Results: In total, 50 studies were included. Positron emission tomography (PET)-based biomarkers showed the highest sensitivity (mean: 89.5%, range: 82–96%) and specificity (mean: 91.2%, range: 85–100%). Novel tracers such as [68Ga]-PSMA for prostate cancer and [18F]-FES for breast cancer demonstrated promising outcomes. Optical imaging techniques showed high specificity in intraoperative settings. Conclusions: Molecular imaging biomarkers show significant potential for improving early cancer detection. Integration into clinical practice could lead to earlier interventions and improved outcomes. Further research is needed to address standardization and cost-effectiveness.

Aim: To assess the feasibility of video game-based trunk exercises using the Valedo® system in a chronic stroke population. Method: Ten chronic stroke survivors (eight males and two females, mean age 63 ± 15 years) were asked to complete 18 intervention sessions, each lasting 45 min., over 6–8 weeks. Feasibility was evaluated quantitatively using the Psychosocial Impact of Assistive Devices Scale (PIADS) as well as through recruitment, retention, adherence, and safety measures. Qualitative data on feasibility were collected through post-intervention semi-structured interviews. Descriptive analysis was used to summarize participant characteristics, recruitment, retention, and adherence. Qualitative data were analyzed using thematic analysis of the interviews. Results: Twelve stroke survivors were recruited from Southampton (United Kingdom) and Riyadh (Kingdom of Saudi Arabia), with two participants dropping out after the baseline assessment session. The remaining ten participants completed the study with a mean adherence of 96.11% to the planned sessions. No serious adverse effects were reported, however, four participants did experience trunk muscle tightness and fatigue. Post-intervention interviews revealed that participants encountered some physical and cognitive challenges while playing the Valedo video games. However, they felt that the implementation of trunk exercises using video games was safe, as the exercises were performed in a secure environment and in safe positions. Conclusions: The findings suggest that the Valedo system is feasible for delivering trunk exercises to chronic stroke survivors. Several factors should be considered when implementing this type of intervention in the future.