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Abstract Background Effective medication adherence is vital for managing acute myocardial infarction (AMI) and enhancing patient well-being. This study aimed to evaluate medication adherence levels and associated factors among AMI patients using standardized assessment tools. Methods Employing a cross-sectional descriptive design, the study involved 210 patients diagnosed with acute myocardial infarction. Participants completed the General Medication Adherence Scale (GMAS), Hospital Anxiety and Depression Scale (HADS), and provided socio-demographic details. Results The study revealed partial adherence to medications among AMI patients, with mean scores of 24.89 (± 3.64) out of 33. Notably, good adherence was observed in non-adherence due to patient behavior (mean ± SD = 11.8 ± 2.3 out of 15) and additional disease burden (mean ± SD = 8.65 ± 2.21 out of 12), while partial adherence was noted in non-adherence due to financial constraints (mean ± SD = 4.44 ± 1.34 out of 6). Patients reported mild anxiety (mean ± SD = 8.38 ± 2.81) and no depressive symptoms (mean ± SD = 7.43 ± 2.42). Multiple linear regression analysis indicated that employed status, younger age, shorter duration of MI, lower anxiety, and depression levels were associated with higher medication adherence. However, factors such as monthly income, gender, educational level, and marital status did not predict medication adherence. Conclusion The study highlights the significance of addressing anxiety and depression levels and considering socio-demographic factors when designing interventions to enhance medication adherence among AMI patients. Further research is needed to explore additional determinants of medication adherence and develop tailored interventions to improve patient outcomes post-AMI.

Abstract Tracer antibodies, which are labelled with fluorescent or other type of reporter molecules, are widely employed in diagnostic immunoassays. Time-resolved fluorescence immunoassay (TRFIA), recognized as one of the most sensitive immunoassay techniques, utilizes tracers labelled with lanthanide ion (Ln) chelates. The conventional approach for conjugating isothiocyanate (ITC) Ln-chelates to antibodies involves random chemical targeting of the primary amino group of Lys residues, requiring typically overnight exposure to an elevated pH of 9–9.3 and leading to heterogeneity. Moreover, efforts to enhance the sensitivity of the assays by introducing a higher number of Ln-chelates per tracer antibody are associated with an elevated risk of targeting critical amino acid residues in the binding site, compromising the binding properties of the antibody. Herein, we report a method to precisely label recombinant antibodies with a defined number of Ln-chelates in a well-controlled manner by employing the SpyTag/SpyCatcher protein ligation technology. We demonstrate the functionality of the method with a full-length recombinant antibody (IgG) as well as an antibody fragment by producing site-specifically labelled antibodies for TRFIA for cardiac troponin I (cTnI) detection with a significant improvement in assay sensitivity compared to that with conventionally labelled tracer antibodies. Overall, our data clearly illustrates the benefits of the site-specific labelling strategy for generating high-performing tracer antibodies for TRF immunoassays.

Background and Objectives: Zinc is an essential trace mineral required by the human body in minute quantities. It plays a crucial role in facilitating around 100 enzymes to perform key chemical reactions. It has a significant role in DNA synthesis, cellular proliferation, protein synthesis, tissue regeneration, and bolstering the immune system. Zinc toxicity primarily arises from the consumption of zinc supplements rather than from dietary sources. The study aimed to evaluate the side effects caused by the misuse of zinc during and after recovery from the coronavirus. Materials and Methods: A case series study design was used to carry out the study. The constructed checklist was applied to 107 patients who recovered from corona disease to determine the causes of the adverse health consequences they still suffer from after recovery, also, they underwent comprehensive laboratory tests in January 2023. Results: Nearby 50% of the study sample had zinc tests higher than the normal range, whereas they were suffering from such physical health disorders that were significantly enhanced due to management undertaken. Conclusions: The misuse of zinc tablets for a long time and in large doses caused such physical problems to be continued for a time among many patients recovering from coronavirus, and when the intake of zinc tablets and multivitamins supplements was stopped for 6 months an obvious improvement in these health symptoms occurred.

Abstract Background Pedestrian traffic injuries are a rising public health concern worldwide. In rapidly urbanizing countries like Saudi Arabia, these injuries account for a considerable proportion of trauma cases and represent a challenge for healthcare systems. The study aims to analyze the key characteristics, seasonality, and outcomes of pedestrian traffic injuries in Riyadh, Saudi Arabia. Methods This study was a retrospective cohort analysis of all pedestrian traffic injuries presented to King Saud Medical City, Riyadh, and included in the Saudi Trauma Registry (STAR) database between August 1, 2017, and December 31, 2022. The analysis of metric and nominal variables was reported as mean (standard deviation, SD) or median (interquartile range, IQR) and frequencies (%), respectively. A logistic regression analysis was performed to examine the influence of patients’ pre-hospital vitals and key characteristics on arrival at the ED on the need for mechanical ventilation and in-hospital mortality. Results During the study period, 1062 pedestrian-injured patients were included in the analysis, mostly males (89.45%) with a mean (SD) age of 33.44 (17.92) years. One-third (35.88%) of the patients were Saudi nationals. Two-thirds (67.04%) of the injuries occurred from 6 p.m. until 6 a.m. Compared to other years, a smaller % of injury events (13.28%) were noticed during the COVID-19 pandemic (2020). Half (50.19%) of the patients were transported to the emergency department by the Red Crescent ambulance, and 19.68% required intubation and mechanical ventilation. Most of the patients (87.85%) were discharged home after completion of treatment, and our cohort had a 4.89% overall mortality. The logistic regression analysis showed the influence of patients’ pre-hospital vitals and key characteristics on arrival at the ED on the need for mechanical ventilation (Chi2 = 161.95, p

Abstract Ischemia-induced retinopathy is a hallmark finding of common visual disorders including diabetic retinopathy (DR) and central retinal artery and vein occlusions. Treatments for ischemic retinopathies fail to improve clinical outcomes and the design of new therapies will depend on understanding the underlying disease mechanisms. Histone deacetylases (HDACs) are an enzyme class that removes acetyl groups from histone and non-histone proteins, thereby regulating gene expression and protein function. HDACs have been implicated in retinal neurovascular injury in preclinical studies in which nonspecific HDAC inhibitors mitigated retinal injury. Histone deacetylase 3 (HDAC3) is a class I histone deacetylase isoform that plays a central role in the macrophage inflammatory response. We recently reported that myeloid cells upregulate HDAC3 in a mouse model of retinal ischemia-reperfusion (IR) injury. However, whether this cellular event is an essential contributor to retinal IR injury is unknown. In this study, we explored the role of myeloid HDAC3 in ischemia-induced retinal neurovascular injury by subjecting myeloid-specific HDAC3 knockout (M-HDAC3 KO) and floxed control mice to retinal IR. The M-HDAC3 KO mice were protected from retinal IR injury as shown by the preservation of inner retinal neurons, vascular integrity, and retinal thickness. Electroretinography confirmed that this neurovascular protection translated to improved retinal function. The retinas of M-HDAC3 KO mice also showed less proliferation and infiltration of myeloid cells after injury. Interestingly, myeloid cells lacking HDAC3 more avidly engulfed apoptotic cells in vitro and after retinal IR injury in vivo compared to wild-type myeloid cells, suggesting that HDAC3 hinders the reparative phagocytosis of dead cells, a process known as efferocytosis. Further mechanistic studies indicated that although HDAC3 KO macrophages upregulate the reparative enzyme arginase 1 (A1) that enhances efferocytosis, the inhibitory effect of HDAC3 on efferocytosis is not solely dependent on A1. Finally, treatment of wild-type mice with the HDAC3 inhibitor RGFP966 ameliorated the retinal neurodegeneration and thinning caused by IR injury. Collectively, our data show that HDAC3 deletion enhances macrophage-mediated efferocytosis and protects against retinal IR injury, suggesting that inhibiting myeloid HDAC3 holds promise as a novel therapeutic strategy for preserving retinal integrity after ischemic insult.

Abstract Background Hodgkin’s lymphoma (HL) is an extremely rare cause of ocular inflammation that is usually not considered in the typical workup of uveitis and other eye diseases. A few cases of ocular inflammation were reported previously showcasing HL with absence of typical symptoms of HL at presentation. Acknowledging the potential ocular inflammation associated with HL can prompt ophthalmologists to broaden their diagnostic approach and collaborate with internal medicine departments to investigate this rare yet significant etiology. Case presentation A 17-year-old Caucasian woman presenting unilateral panuveitis was later diagnosed with HL. The ocular findings were non-necrotizing scleritis, anterior uveitis, vitritis, white/yellowish chorioretinal lesions, papillitis and vasculitis. A left supra-clavicular lymph node biopsy confirmed the diagnosis of nodular sclerosing Hodgkin’s lymphoma stage IIB. Other causes of uveitis were excluded. Chemotherapy led to remission of the disease and the ocular lesions became quiescent with persistent pigmented chorioretinal scars. Conclusions Hodgkin's lymphoma should be considered in the differential diagnosis of diseases that can occasionally be revealed by unilateral ocular inflammation. A comprehensive, multidisciplinary approach is key to properly assessing such cases.

The increase in water demand and the scarcity of fresh water in arid regions have contributed to the depletion of groundwater. Artificial Groundwater Recharge (AGR) is an advanced strategy that contributes to combating water shortage issues. Limited efforts have been exerted to evaluate and demarcate AGR potential zones in the United Arab Emirates (UAE). The current study aims to delineate AGR potential zone mapping using the traditional analytical hierarchy process (AHP) and a hybrid deep learning model namely, Convolutional Neural Network-Xtreme Gradient Boosting (CNN-XGB) was used for the optimal prediction-based suitability assessment. A total of nine hydrogeological factors were considered for AGR mapping. First, the influence of each parameter was determined based on expert opinion and literature reviews for the AHP approach (0.007 consistency ratio). Second, a hybrid CNN-XGB model (90.8 % accuracy) predicted the AGR and non-AGR classes as part of binary classification and generated an AGR potential zone map. Moreover, the contributing factors were analyzed deeply for the AGR site selection to understand the intercorrelation, importance, and prediction interaction. Using both approaches, a comparative assessment was conducted in the eastern, central, and western parts of Sharjah. The AGR zone based on the CNN-XGB model achieved a precision of (0.8168), recall (0.7873), and F1-score (0.8018). The critical contributing factors for AGR mapping were found to be geology (20%), geomorphology (15%), rainfall (10%), and groundwater level (10%). The AGR map is expected to help explore new sites with potentially higher favourability to retain water, deal with water scarcity, and improve water management in the UAE.

Background: Type 2 diabetes mellitus (T2DM) and its consequences are a serious global public health issue. By 2030, the number of people with type 2 diabetes is predicted to reach 439 million. The purpose of this study is to evaluate the plasma levels of glucose, HbA1c, insulin, and lipid profile in Sudanese T2DM patients. Methods: This case control study included 165 Sudanese patients with diabetic type 2 and a cardiovascular condition as cases and 165 diabetic type 2 volunteers without a cardiovascular disorder as controls. The concentrations of plasma glucose, HbA1c, and lipid profile were assessed using a Mindray BS-480 auto-chemistry analyzer, and insulin was analyzed using a Cobase 411 auto analyzer. The collected data were analyzed using statistical tools for social science computer programs (SPSS version 21). Results: According to the findings, (59.4%) of patients between the ages of (50-69). Females made up 50.9%. (38.2%) of patients had an illness duration of between (8-15 years). (41.8%) of individuals did not have hypertension. There was a substantial rise in BMI, FBG, HbA1c, HDL-C, and insulin among diabetics with cardiovascular disease compared to diabetics without cardiovascular disease (p-value = 0.001, 0.000, 0.018, and 0.000). Females had significantly higher blood TC, LDL-C, HDL-C, and BMI than males (p-values = 0.000, 0,001, and 0.000, respectively). There were significant positive correlation between FBS, HBA1c, insulin and duration of disease (r=0.155, p, value=0.005) (r=0.160, p, value=0.004)(r=0.103, p. value=0.061)respectively, while there were significant negative correlation between TC, TG,LDL-C, HDL-C and duration of disease (r=-0.152, p, value= 0.006)(r=-0.023, p, value=0.678)(r=-0.113, p, value= 0.040)(r=-0.145, p, value=0.008)respectively. Conclusion: When comparing diabetics with cardiovascular disease to diabetics without cardiovascular disease, there was a substantial rise in BMI, FBG, HbA1c, HDL-C, and insulin. FBS, HBA1c, insulin, and illness duration all had a strong positive connection.

Background: A shortage of images of pathology on diverse skin tones has been recognized for decades in health professions education. Identifying skin manifestations of disease depends on pattern recognition, which is difficult without visual examples. Lack of familiarity with visual diagnosis on skin of color can lead to delayed or missed diagnoses with increased morbidity and mortality. As the United States continues to increase in ethnic and racial diversity, addressing the disparity in health outcomes with education is vital. Case Presentation: At the Hackensack Meridian School of Medicine, students, librarians, and faculty came together to address this problem and develop a database of dermatological conditions in people with darker skin tones. A student group initiated a series of meetings with faculty to determine the best approach to address and enhance the representation of diversity in disease images within the curriculum. With the guidance of faculty and librarians, students performed a literature search and created a database of images of skin pathologies in people with darker skin tones. The database was disseminated to course directors and lecturers, and the noted disparities were corrected for the next cohort of students. The database provides an easily accessible resource for creating lecture slides. Conclusion: This project brought awareness of the need for inclusivity and generated a broad review of the curriculum to be more representative of all patient populations. Most importantly, our experience provides a roadmap for institutional change through student, librarian and faculty collaboration and cultivation of a culture of optimism and acceptance.

Background: Cardiogenic shock (CS) is the leading cause of mortality in acute myocardial infarction (AMI) patients, especially in those with vascular disease. This study aimed to assess the association between extent of polyvascular disease and the in hospital management and outcome of patients with AMI-induced CS. Method: Using the National Inpatient Sample from 2016 to 2019, adult patients with AMI and CS with known vascular disease were identified and stratified by number of diseased vascular beds and into STEMI and NSTEMI subgroups. The study assessed in-hospital major adverse cardiovascular and cerebrovascular events (MACCE), mortality, acute CVA and major bleeding, as well as invasive management by number of diseased vascular beds. Results: Out of 136,245 patients, 57.9 % attributed to STEMI and 42.1 % to NSTEMI. The study revealed that the likelihood of percutaneous coronary intervention (PCI) [(aOR for 2 beds 0.94, CI 0.91–0.96, p-value

Abstract Background We previously described the KINSSHIP syndrome, an autosomal dominant disorder associated with intellectual disability (ID), mesomelic dysplasia and horseshoe kidney, caused by de novo variants in the degron of AFF3. Mouse knock-ins and overexpression in zebrafish provided evidence for a dominant-negative mode of action, wherein an increased level of AFF3 resulted in pathological effects. Methods Evolutionary constraints suggest that other modes-of-inheritance could be at play. We challenged this hypothesis by screening ID cohorts for individuals with predicted-to-be damaging variants in AFF3. We used both animal and cellular models to assess the deleteriousness of the identified variants. Results We identified an individual with a KINSSHIP-like phenotype carrying a de novo partial duplication of AFF3 further strengthening the hypothesis that an increased level of AFF3 is pathological. We also detected seventeen individuals displaying a milder syndrome with either heterozygous Loss-of-Function (LoF) or biallelic missense variants in AFF3. Consistent with semi-dominance, we discovered three patients with homozygous LoF and one compound heterozygote for a LoF and a missense variant, who presented more severe phenotypes than their heterozygous parents. Matching zebrafish knockdowns exhibit neurological defects that could be rescued by expressing human AFF3 mRNA, confirming their association with the ablation of aff3. Conversely, some of the human AFF3 mRNAs carrying missense variants identified in affected individuals did not rescue these phenotypes. Overexpression of mutated AFF3 mRNAs in zebrafish embryos produced a significant increase of abnormal larvae compared to wild-type overexpression further demonstrating deleteriousness. To further assess the effect of AFF3 variation, we profiled the transcriptome of fibroblasts from affected individuals and engineered isogenic cells harboring + / + , KINSSHIP/KINSSHIP, LoF/ + , LoF/LoF or KINSSHIP/LoF AFF3 genotypes. The expression of more than a third of the AFF3 bound loci is modified in either the KINSSHIP/KINSSHIP or the LoF/LoF lines. While the same pathways are affected, only about one third of the differentially expressed genes are common to the homozygote datasets, indicating that AFF3 LoF and KINSSHIP variants largely modulate transcriptomes differently, e.g. the DNA repair pathway displayed opposite modulation. Conclusions Our results and the high pleiotropy shown by variation at this locus suggest that minute changes in AFF3 function are deleterious.

Abstract Background This study aims to investigate the factors affecting the vitreous levels of pigment epithelium-derived factor (PEDF) and vascular endothelial growth factor (VGEF) among patients with pars plana vitrectomy (PPV). Also, this study correlates the levels of PEDF with RRD characteristics. Methods All patients who were scheduled for PPV for any indication were included in the study. They were divided into a case group which included patients with advanced PDR and a control group which included the remaining diagnoses. During the PPV, an undiluted vitreous sample was taken and the enzyme-linked immunosorbent assay method was utilized to measure the levels of VEGF and PEDF. Results Eighty eyes were involved. Patients diagnosed with advanced PDR and endophthalmitis exhibited higher levels of VEGF. PEDF was affected inversely by the age of the patients and PEDF levels were higher in RRD and endophthalmitis cases. In patients with RRD, the level of PEDF was higher if the tear was found inferiorly, if the macula was detached, and with a longer duration of RRD. Conclusions This study highlights the clinical importance of those biomarkers. Anti-VEGF-based treatment is the mainstay against PDR. PEDF may show a promising predictive values regarding patients with RRD.

Abstract This study aimed to explore the forms and causes of domestic violence against women in Jordan during the COVID-19 pandemic through a systematic literature review. The review yielded eight articles published between April 2020 and November 2022 in the final sample, all of which met the inclusion criteria. The results revealed 11 forms of domestic violence against women in Jordan during and after the full and partial lockdowns due to the pandemic. Physical violence was the most prevalent form of domestic violence, followed by economic, psychological, emotional, verbal, and sexual forms, as well as control and humiliation, bullying, online abuse, harassment and neglect-related violence. The causes were a combination of economic, socio-cultural, and psychological factors emerging because of the pandemic and lockdowns (e.g., poverty, job loss, low wages, gender discrimination, double burden on women [monotonous roles, paid work], male dominance, reduced income, high cost of living). Additionally, effects of the pandemic included psychological, mental, and emotional negative consequences (e.g., anxiety, fear, stress, depression, loneliness, failure, status frustration). Individuals in Jordanian societies employed the norms, ideas, and values of the patriarchal culture to negatively adapt to the economic and psychological effects of the pandemic, which contributed to more domestic violence cases.

Myelodysplastic neoplasm (MDS) is a heterogeneous group of clonal hematological disorders that originate from the hematopoietic and progenitor cells and present with cytopenias and morphologic dysplasia with a propensity to progress to bone marrow failure or acute myeloid leukemia (AML). Genetic evolution plays a critical role in the pathogenesis, progression, and clinical outcomes of MDS. This process involves the acquisition of genetic mutations in stem cells that confer a selective growth advantage, leading to clonal expansion and the eventual development of MDS. With the advent of next-generation sequencing (NGS) assays, an increasing number of molecular aberrations have been discovered in recent years. The knowledge of molecular events in MDS has led to an improved understanding of the disease process, including the evolution of the disease and prognosis, and has paved the way for targeted therapy. The 2022 World Health Organization (WHO) Classification and the International Consensus Classification (ICC) have incorporated the molecular signature into the classification system for MDS. In addition, specific germline mutations are associated with MDS development, especially in pediatrics and young adults. This article reviews the genetic abnormalities of MDS in adults with a brief review of germline predisposition syndromes.

Abstract Background Developmental dysplasia of the hip (DDH) leads to pain, joint instability, and early degenerative joint disease. Incidence, prevalence, and management strategies of DDH have been well-documented in several countries, but not in Saudi Arabia. Objective We synthesized the current evidence regarding incidence, prevalence, risk factors, and clinical treatment for children with DDH in Saudi Arabia. Methods We searched 3 databases to locate studies. Studies that included children with DDH in Saudi Arabia; reported either incidence rate, prevalence, risk factors, and/or clinical practice; and were available in English or Arabic were included. We excluded reviews, case studies, or animal studies. Two independent authors reviewed potential studies and assessed study’s quality. Results Our search yielded 67 potential studies, of which 16 studies were included (total DDH sample = 3,127; age range = 2.5 to 86.4 months). Three studies reported incidence rates ranging from 3.1 to 4.9 per 1000 births, and 3 studies reported prevalence ranging from 6 to 78%. Nine studies reported that female sex, breech position, family history, and age less than 3 years were risk factors associated with DDH. Four studies reported that brace applications and closed reduction were conservative treatments, and 9 studies reported that open hip reduction, adductor tenotomy, and/or pelvic osteotomy were surgical approaches to treat DDH. Conclusions In Saudi Arabia, the Incidence and prevalence rates of DDH are 3.1 to 4.9 per 1,000 births, and 6–78%, respectively (differ from what has been reported in other countries), but the risk factors of DDH in Saudi Arabia appear to be similar in comparison to other countries (female, breech presentation, family history of DDH).

Abstract Non‐alcoholic fatty liver disease (NAFLD) is projected to be the most common chronic liver disease worldwide and is closely linked to obesity, insulin resistance and type 2 diabetes. Currently, no pharmacological treatments are available to treat NAFLD, and lifestyle modification, including dietary interventions, is the only remedy. Therefore, we conducted a study to determine whether supplementation with medium‐chain triglycerides (MCTs), containing a mixture of C8 and C10 (60/40), attenuates NAFLD in obese and insulin‐resistant mice. To achieve that, we fed C57BL/6 male mice a high‐fat diet (HFD) for 12 weeks to induce obesity and hepatic steatosis, after which obese mice were assigned randomly either to remain on the HFD or to transition to an HFD supplemented with MCTs (HFD + MCTs) or a low‐fat diet (LFD) for 6 weeks as another dietary intervention model. Another group of mice was kept on an LFD throughout the study and used as a lean control group. Obese mice that transitioned to HFD + MCTs exhibited improvement in glucose and insulin tolerance tests, and the latter improvement was independent of changes in adiposity when compared with HFD‐fed mice. Additionally, supplementation with MCTs significantly reduced hepatic steatosis, improved liver enzymes and decreased hepatic expression of inflammation‐related genes to levels similar to those observed in obese mice transitioned to an LFD. Importantly, HFD + MCTs markedly lowered hepatic ceramide and diacylglycerol content and prevented protein kinase C‐ε translocation to the plasma membrane. Our study demonstrated that supplementation with MCTs formulated mainly from C8 and C10 effectively ameliorated NAFLD in obese mice.

Abstract Myeloid cells including microglia and macrophages play crucial roles in retinal homeostasis by clearing cellular debris and regulating inflammation. These cells are activated in several blinding ischemic retinal diseases including diabetic retinopathy, where they may exert both beneficial and detrimental effects on neurovascular function and angiogenesis. Myeloid cells impact the progression of retinal pathologies and recent studies suggest that targeting myeloid cells is a promising therapeutic strategy to mitigate diabetic retinopathy and other ischemic retinal diseases. This review summarizes the recent advances in our understanding of the role of microglia and macrophages in retinal diseases and focuses on the effects of myeloid cells on neurovascular injury and angiogenesis in ischemic retinopathies. We highlight gaps in knowledge and advocate for a more detailed understanding of the role of myeloid cells in retinal ischemic injury to fully unlock the potential of targeting myeloid cells as a therapeutic strategy for retinal ischemia.

Parks design relies on understanding user preferences, which are determined through interviews, surveys, and observations. However, previous methods are limited in their capacity to explore user preferences, which necessitates the development of new approaches. Virtual reality (VR) is an effective tool for modeling perceptions and simulating the real world, yet its impact on overcoming previous limitations remains unexplored. This study aims to assess VR's role in addressing challenges and limitations related to people's uses and preferences regarding neighborhood parks. Using an experimental approach, we test factors that influence park visits, using both traditional methods and VR to analyze the extent to which VR can mitigate these challenges. The study reveals that, among individuals in various age groups, perception significantly influences responses. In addition, VR helps overcome issues with traditional research methods, ensuring result validity and interpretation of differences. Ultimately, compared to traditional methods, using VR improves the sense of certainty among individuals regarding their preferences.

ABSTRACT: The effects of traditional and on-farm hatching systems on broiler performance and health under a subclinical necrotic enteritis (NE) challenge were evaluated in this study. A 2×2 factorial study explored the effects of place of hatch (on-farm hatched [OFH] vs. hatchery hatched [HH]) and NE challenge (nonchallenged vs. challenged) on broilers. Cobb 500 eggs (∼E19) were acquired from a commercial hatchery; 840 eggs were placed in pens on clean shavings in prewarmed floor pens and allowed to hatch out, while 927 eggs were placed in a hatcher set under standard practices. On day (d) of hatch, all chicks were weighed and randomly distributed to 4 treatments (8 replicate pens each and 30 birds/pen). The OFH birds were placed immediately after sorting while HH birds were placed back in the hatcher overnight to simulate commercial hatchery procedures. After placing HH birds, feed and litter in the challenge group pens were sprayed with a live oocyst coccidia vaccine as a predisposing factor to NE. The small intestines of 3 male chicks per pen were scored for NE lesions (n = 24) on d 8 (peak NE challenge) and jejunal samples were collected from 1 bird per pen for RNA extraction and qPCR on d 8 and d 14. Data were analyzed using JMP Pro17 and significance between treatments was identified by LSD (P ≤ 0.05). Regardless of the hatching system, the subclinical NE challenge caused a significant reduction in average daily gain (ADG) and average daily feed intake (ADFI), and increased feed conversion ratio (FCR) until d 28 (P ≤ 0.05). Moreover, OFH birds exhibited significantly better growth (P ≤ 0.05) through d 28 but had similar performance to HH birds by d 42. There were no significant differences in NE lesion scores between HH and OFH groups. In conclusion, OFH system resulted in better broiler performance compared to HH system under both no-challenge and challenge conditions during the starter and grower periods. This practice may hold potential for further exploration by the industry as an alternative to traditional hatching, aiming to improve the welfare and productivity of broilers.

Background: Research comparing artificial intelligence and machine learning (AI/ML) methods with classical statistical methods applied to large population health databases is limited. Objectives: This retrospective cohort study aimed to compare the predictive performance of AI/ML algorithms against conventional multivariate logistic regression models using linked health administrative data. Methods: Using Ontario's population health databases, we created a cohort of residents of the city of Ottawa, Ontario, who underwent a PCR test for COVID-19 between March 10, 2020, and May 13, 2021. Using demographic, socio-economic and health data (including COVID-19 PCR test results and available, symptom data), we developed predictive models for the purpose of COVID-19 case identification using the following approaches: classical multivariate logistic regression (LR); deep neural network (DNN); random forest (RF); and gradient boosting trees (GBT). Model performance comparisons were made using the area under the curve (AUC) swarm plot for 10-fold cross-validation. Results: The cohort consisted of n = 351,248 Ottawa residents tested for COVID-19 during the study period. Among whom, a total of n = 883,879 unique COVID-19 tests were performed (2.6 % positive test results). Inclusion of COVID-19 symptoms data in the analysis improved model performance and variable predictive value across all tested models (p

ABSTRACT: In this comparative study, the differential responses of heritage (ACRB; Athens Canadian Random Bred) and modern (Cobb) broilers to a necrotic enteritis (NE) challenge were evaluated. The design was a 2×2 factorial with breed (ACRB and Cobb) and challenge (non-challenged and NE-challenged) as main factors. On day (d) of hatch, 96 male chicks (48 ACRB and 48 Cobb) were allocated to 4 experimental groups with 8 replicate cages and 3 birds/cage. On d 14, birds in the NE-challenged groups were orally gavaged with 3,000 Eimeria maxima sporulated oocysts followed by 2 doses of ∼1×108 CFU of Clostridium perfringens on d 19 and 20. On d 21, 2 birds/cage were necropsied to score NE lesions, and spleen and cecal tonsils (CT) samples were collected from 1 bird/cage for assessing mRNA abundance. Challenged ACRB birds exhibited reduced growth performance and relative growth performance compared to challenged Cobb birds. There was no significant interaction between breed and challenge during the challenge period (d 14–21) for mortality. However, there was a challenge main effect (P ≤ 0.05) on mortality as manifested by greater NE-associated mortality compared to non-challenged birds. No significant breed × challenge interaction or breed main effect on lesion scores were observed in the duodenum, jejunum, and ileum. NE-challenged Cobb birds exhibited greater mRNA abundance of IL-18, TNFα, TLR1.2, TLR2.1, CCR5, CCR6, CCL20, and AvBD1 in CT compared to NE challenged ACRB birds. There was a significant breed × challenge interaction effect on mRNA abundance of IL-10, AvBD13, NK-Lysin, and LEAP2 in the spleen. Moreover, a main effect of breed was observed in IL-1β, IL-18, TNFα, TLR2.1, CCR5, CCL20, and NK-Lysin where ACRB birds had higher mRNA abundance than Cobb birds (P ≤ 0.05). The observed differences in performance, pathology, and mRNA abundance between ACRB and Cobb broilers during the NE challenge highlight the distinct immune response profiles of heritage and modern breeds, emphasizing the need for breed-specific nutritional, managerial, and genetic selection programs for modulating immune responses during enteric disease challenges.

Mechanical and Corrosion characteristics of composite materials made from Aluminum alloys (AA) 6063 supplanting as the material of choice for automotive, aerospace, and marine applications by systematically varying ceramic reinforcements developed through controlled stir cast technique ensuring uniform dispersion are explored. The hardness, density, impact and tensile strength, corrosion resistance, and microstructural characteristics of Aluminum Matrix Composites (AMCs) reinforced with titanium diboride (TiB2) at 7.5, 10, and 12.5 wt% and chromium oxide (Cr2O3) at 3, 6, and 9 wt% were assessed according to ASTM standards. The microstructural analysis revealed a reduction in the growth of reinforcement clusters within acceptable limits. The addition of reinforcements to the matrix resulted in improved tensile strength, ranging from 124.6 to 188.7 MPa, and hardness, increasing from 71.5 to 144.32 VHN. This improvement is attributed to the strengthening or load transfer mechanism facilitated by the reinforcements. Additionally, the impact strength of the composites increased from 11.845 to 21.16 J, while the density showed slight variations. Consistent corrosion tests demonstrated that the chemical and interfacial interactions between the matrix material and the reinforcements significantly enhanced the corrosion resistance, reducing the corrosion rate from 570 to 499 mm/year.

The crisis in Jordan has had disastrous effects on the national economy, particularly impacting the hospitality sector. Confronted with dramatic uncertainty, hospitality leaders must rapidly nurture responsibility and resilience. To enhance our understanding of how responsible and resilient leadership responds to such shocks, we aim to investigate if responsible and resilient leadership styles can foster crisis management in the hospitality sector through the mediating path of knowledge management, and the moderating role of digital transformation using the conservation of resources (COR) theory to support our hypotheses. This theory asserts that organizational resources facilitate effective crisis management, implying that adequate resources and support systems enable organizations to navigate and recover from crises effectively. Data was gathered from 154 owners and senior managers in the hospitality sector, and the proposed relationships were evaluated using partial least squares structural equation modeling (PLS-SEM). These findings imply that responsible and resilient leadership styles significantly influence crisis management. Furthermore, knowledge sharing mediates the relationship between these leadership styles and effective crisis management. Finally, the study identifies digital transformation as a significant moderator between knowledge sharing and crisis management. This research contributes to the existing literature on leadership and crisis management by demonstrating that, during times of crisis, leadership characterized by responsibility and resilience enhances crisis management within the hospitality sector.

In an era where artificial intelligence (AI) is reshaping educational paradigms, this study explores AI-based chatbot adoption in higher education among students and educators. Employing a Structural Equation Modeling (SEM) approach, the research focuses on developing and validating a comprehensive model to understand the multifaceted factors impacting the acceptance and use of these chatbots. The methodology integrates an extensive literature review, construction of a theoretical model, administration of a detailed questionnaire to a representative sample from the higher education sector, coupled with advanced SEM techniques for data analysis and interpretation. The SEM analysis validates the model's robustness and highlights the relationships between several key factors affecting users' perspectives and chatbots adoption. Results reveal a predominantly positive perception towards AI-chatbots among both students and educators, underscoring the potential to substantially enrich their educational journey. However, it also uncovers critical concerns pertaining to trust, privacy, response bias, and information accuracy. Moreover, the study offers valuable insights into how moderators such as technological proficiency, user roles, and gender influence the adoption model relationships. This emphasizes the need for customizing AI-chatbots deployment to meet the diverse needs of users effectively. Contributing a robust framework for understanding users' perceptions towards AI-chatbots and their adoption patterns, this study offers actionable insights for educational leaders, policymakers, and technology developers. It also lays the groundwork for future research, including longitudinal studies to evaluate the long-term impact of these technologies, investigations into their effect on learning outcomes, and explorations of the ethical and privacy considerations involved.

Achieving net carbon neutrality is a global goal toward mitigating climate change presumed consequences. The building and construction sector, responsible for approximately 40 % of greenhouse gas emissions, requires innovative zero-carbon technologies. This paper investigates the synergistic potential of combining 3D concrete printing (3DCP) and carbon capture and sequestration (CCS) to advance net carbon neutrality in construction. By implementing different CO2 spraying regimes, this study demonstrates improved carbon dioxide (CO2) uptake and the crystallinity of precipitated calcium carbonate (CaCO3). The findings indicate that the method's effectiveness heavily relies on appropriate printing parameters and curing conditions. Chamber-cured samples exhibit the highest CO2 uptake but the lowest mechanical strength, while ambient-cured samples show the opposite trend. It is also important to note that the duration of CO2 exposure in this study was relatively short, resulting in limitations in both CO2 uptake and strength gain. Nevertheless, this study highlights the potential of synergistically combining 3DCP and CCS technologies for net carbon neutrality, emphasizing the critical role of the construction sector in achieving global emission reduction targets.

Background: Inflammation plays a central role in atherogenesis. The major neutrophilic peptide alpha-defensin is a promising evolving risk factor for atherosclerosis. The aim of the present study was to examine the role of alpha-defensin in predicting future major adverse cardiovascular events (MACE) occurrence in fully revascularized patients with stable CAD under optimal medical therapy. Methods and results: We retrospectively examined the prognostic value of baseline plasma alpha-defensin levels in predicting MACE occurrence in 174 fully revascularized patients for stable CAD between March 2016 and January 2017. Alpha-defensin levels were found 20 % higher among demised patients (10,859 pg/ml, IQR [6,920 to 23,320] vs. 9,020 pg/ml, IQR [5,540 to 16,180] pg/ml, P = 0.15). The absolute increase in mortality risk in patients with alpha-defensin levels greater than the median values was 72.5 % (P = 0.33). Log-rank analysis proved both recurrent PCI for de novo lesions (14.9 % and 2.3 %) and the composite of mortality and recurrent PCI for de novo lesions (27.6 % vs. 9.2 %) were significantly related to alpha-defensin values greater than the median (>9200 pg/ml). Conclusion: Baseline plasma alpha-defensin is an independent predictor of mortality and recurrent PCI among patients with stable CAD. Alpha-defensin may evolve as a promising factor in cardiovascular risk assessment beyond traditional risk factors. Targeting alpha-defensin to ameliorate MACE occurrence should be addressed in future studies.

Background Type 2 diabetes is prevalent in cardiovascular disease and contributes to excess morbidity and mortality. We sought to investigate the effect of glycemia on functional cardiac improvement, morbidity, and mortality in durable left ventricular assist device (LVAD) recipients. Methods and Results Consecutive patients with an LVAD were prospectively evaluated (n=531). After excluding patients missing pre‐LVAD glycated hemoglobin (HbA1c) measurements or having inadequate post‐LVAD follow‐up, 375 patients were studied. To assess functional cardiac improvement, we used absolute left ventricular ejection fraction change (ΔLVEF: LVEF post‐LVAD−LVEF pre‐LVAD). We quantified the association of pre‐LVAD HbA1c with ΔLVEF as the primary outcome, and all‐cause mortality and LVAD‐related adverse event rates (ischemic stroke/transient ischemic attack, intracerebral hemorrhage, gastrointestinal bleeding, LVAD‐related infection, device thrombosis) as secondary outcomes. Last, we assessed HbA1c differences pre‐ and post‐LVAD. Patients with type 2 diabetes were older, more likely men suffering ischemic cardiomyopathy, and had longer heart failure duration. Pre‐LVAD HbA1c was inversely associated with ΔLVEF in patients with nonischemic cardiomyopathy but not in those with ischemic cardiomyopathy, after adjusting for age, sex, heart failure duration, and left ventricular end‐diastolic diameter. Pre‐LVAD HbA1c was not associated with all‐cause mortality, but higher pre‐LVAD HbA1c was shown to increase the risk of intracerebral hemorrhage, LVAD‐related infection, and device thrombosis by 3 years on LVAD support (P

A previously healthy man presented in shock due to incessant tachycardia. He ultimately required extracorporeal membrane oxygenation for support and clipping of his appendage for arrhythmia control. This case highlights the importance of early recognition of cardiogenic shock, aggressive hemodynamic support, and a multidisciplinary approach to managing these challenging arrhythmias.

ABSTRACT: Transfer of Salmonella to internal organs of broilers over a 35 d grow-out period was evaluated. A total of 360 one-day old chicks were placed in 18 floor pens of 3 groups with 6 replicate pens each. On d 0, broilers were orally challenged with a cocktail of Salmonella (equal population of marked serovars; nalidixic acid-resistant S. Typhimurium, rifampicin-resistant S. Infantis, and kanamycin-resistant S. Reading) to have 3 groups: L (low; ∼2 log CFU/bird); M (medium; ∼5 log CFU/bird); and H (High; ∼8 log CFU/bird). On d 2, 7 and 35, 4 birds/pen were euthanized and ceca, liver, and spleen samples were collected aseptically. Gizzard samples (4/pen) were collected on d 35. The concentration of Salmonella in liver and spleen were transformed to binary outcomes (positive and negative) and fitted in glm function of R using cecal Salmonella concentrations (log CFU/g) and inoculation doses (L, M, and H) as inputs. On d 2, H group showed greater (P ≤ 0.05) cecal colonization of all 3 serovars compared to L and M groups. However, M group showed greater (P ≤ 0.05) colonization of all 3 serovars in the liver and spleen compared to L group. Salmonella colonization increased linearly in the ceca and quadratically in the liver and spleen with increasing challenge dose (P ≤ 0.05). On d 35, L group had greater (P ≤ 0.05) S. Infantis colonization in the ceca and liver compared to M and H groups (P ≤ 0.05). Moreover, within each group on d 35, the concentration of S. Reading was greater than those of S. Typhimurium and S. Infantis for all 3 doses in the ceca and high dose in the liver and gizzard (P ≤ 0.05). Salmonella colonization diminished in the ceca, liver, and spleen during grow-out from d 0 to d 35 (P ≤ 0.05). On d 35, birds challenged with different doses of Salmonella cocktail showed a similar total Salmonella spp. population in the ceca (ca. 3.14 log CFU/g), liver (ca. 0.54 log CFU/g), spleen (ca. 0.31 log CFU/g), and gizzard (ca. 0.42 log CFU/g). Estimates from the fitted logistic model showed that one log CFU/g increase in cecal Salmonella concentration will result in an increase in relative risk of liver and spleen being Salmonella-positive by 4.02 and 3.40 times (P ≤ 0.01), respectively. Broilers from H or M group had a lower risk (28 and 23%) of being Salmonella-positive in the liver compared to the L group when the cecal Salmonella concentration is the same (P ≤ 0.05). Oral challenge of broilers with Salmonella spp. with various doses resulted in linear or quadratic increases in Salmonella colonization in the internal organs during early age and these populations decreased during grow-out (d 35). This research can provide guidance on practices to effectively mitigate the risk of Salmonella from chicken parts and enhance public health.

Elevated levels of circulating branched-chain amino acids (BCAAs) and their associated metabolites have been strongly linked to insulin resistance and type 2 diabetes. Despite extensive research, the precise mechanisms linking increased BCAA levels with these conditions remain elusive. In this review, we highlight the key organs involved in maintaining BCAA homeostasis and discuss how obesity and insulin resistance disrupt the intricate interplay among these organs, thus affecting BCAA balance. Additionally, we outline recent research shedding light on the impact of tissue-specific or systemic modulation of BCAA metabolism on circulating BCAA levels, their metabolites, and insulin sensitivity, while also identifying specific knowledge gaps and areas requiring further investigation. Finally, we summarize the effects of BCAA supplementation or restriction on obesity and insulin sensitivity.

BackgroundThe effect of Ramadan intermittent fasting (RIF) on the metabolic profile, anthropometry and blood pressure has been investigated in multiple studies. However, it is still unknown to what extent changes in nutrient intakes contribute to these changes.MethodsThis observational study was conducted in London (UK) in 2019. The study collected diverse data from a community-based sample in London before and during/after Ramadan. Collected data included a 3-day food diary (before and during Ramadan), as well as blood samples, anthropometric measurements and blood pressure (before and after Ramadan). The food diary was translated into nutritional data using nutrition software “Nutritics.” The changes in nutrient intakes were investigated using a mixed-effects regression model. The impact of adjusting for nutrient intake change was investigated on the absolute difference of metabolites (Nightingale platform), systolic/diastolic blood pressure and anthropometric measures.ResultsThe study collected data on food intake before and during Ramadan from 56 participants; the mean age was 44.7 ± 17.3, and 51.8% (n = 29) were females. We found a change in the intake of 11 nutritional factors, glucose, fructose, betaine, sugars, sugars as monosaccharide equivalents, lutein/zeaxanthin, starch, starch as monosaccharide equivalents, proline, glutamic acid and lycopene. No changes in quantities or proportions of macronutrients, carbohydrates, protein and fat. Mainly, the changes in diet during Ramadan are characterized by more consumption of sugars (62%, p

هدفت الدراسة إلى تعرّف واقع التربية الإعلامية في مدارس الحلقة الثانية من التعليم الأساسي في مدينة اللاذقية. ولتحقيق أهداف الدراسة اسُتخِدمَ المنهج الوصفي، حيث تكونت عينة الدراسة من (112) معلماً ومعلمةً من معلمي الحلقة الثانية من مرحلة التعليم الأساسي تم اختيارهم بطريقة العينة العشوائية البسيطة. اعتمدت الدراسة على استبانة واقع التربية الإعلامية من إعداد الباحث، حيث تكونت من (37) بنداً توزعوا على أربعة أبعاد رئيسية، وبعد التحقق من الخصائص السيكومترية للأداة من صدق وثبات؛ أظهرت نتائج الدراسة: أن درجة إدراك معلمي مدارس الحلقة الثانية من مرحلة التعليم الأساسي لأهمية التربية الإعلامية جاء بدرجة مرتفعة، كما أظهرت أن درجة تطبيق المعلمين لأنشطة التربية الإعلامية ودرجة ممارستهم لمهارات التربية الإعلامية جاء بدرجة منخفضة، أما فيما يتعلق بمعوقات تطبيق التربية الإعلامية في مدارس الحلقة الثانية فقد جاءت بدرجة مرتفعة. وتأسيساً لذلك يوصي الباحث في ضوء نتائج الدراسة بضرورة تشجيع الإدارات التربوية المسؤولة عن تطوير المناهج الدراسية على إدخال التربية الإعلامية ضمن المناهج التعليمية، عن طريق دمج مفاهيم ومهارات التربية الإعلامية ضمن بعض المواد الدراسية كأنشطة صفية أو لاصفية، وذلك بالاستناد إلى العديد من تجارب بعض الدول العربية والعالمية.

Date palm plantations in the United Arab Emirates (UAE) are under threat from soil salinity, drought, and date palm weevils. Accordingly, monitoring and conserving date palms are crucial to preserving a vital component of the country’s agricultural heritage, economy, food security, and ecological balance. Previous studies have effectively identified date palm trees using RGB-based aerial and UAV imagery utilizing diverse deep learning methods. However, the utilization of very high-resolution satellite data for delineating individual date palm crowns remains unexplored due to the limited spatial resolution capabilities of existing satellite systems. This study primarily aimed to achieve precise and comprehensive mapping of date palm trees using WorldView-3 (WV-3) satellite data by leveraging the high representational power of the state-of-the-art vision transformers (ViT) in capturing global information from the input data. First, an in-depth analysis assessment of the various transformer-based semantic segmentation architectures, including UperNet with vision transformer and Swin transformer, SegFormer, Mask2Former, and UniFormer, was conducted. Second, the integration of spectral data on the performance of ViTs was evaluated. Moreover, the models’ generalizability and complexity effect on the segmentation effectiveness were assessed. Accordingly, a postprocessing strategy was developed to aid in delineating and counting date palm trees from semantic segmentation outputs. Results demonstrated that integration of WV-3 spectral data into the analysis resulted in a marked improvement in segmentation quality. The UniFormer, UperNet-Swin, and Mask2Former models demonstrated considerable improvements in multispectral data analysis, with increases in mean intersection over union (mIoU) of 2.17% (77.88% mIoU, 86.01% mean F-score [mF-score]), 2% (78.10% mIoU, 86.18% mF-score), and 1.15% (77.36% mIoU, 85.59% mF-score), respectively, compared with their RGB-based results. Evaluations of model transferability also indicated that Mask2Former, UniFormer, and UperNet-Swin transformers efficiently adapted to multispectral data in the Dibba region. These models achieved mIoU scores of 84.36%, 84.25%, and 83.17% and mF-scores of 90.95%, 90.87%, and 90.13%, highlighting their effectiveness and potential for broader regional application. This research highlights the efficacy and feasibility of using ViTs with WV-3 multispectral data for accurate and comprehensive surveying of date palm plantations, enabling the development of palm tree inventories and continuously updating geospatial databases.

Abstract Workplace cyberbullying has harmful psychological, social, and behavioral consequences for employees and employers. This study investigates workplace cyberbullying among academic staff of both sexes at Jordanian universities, to explore their exposure to workplace cyberbullying by colleagues and employers and its correlation with social capital and self-esteem. Data were collected through an anonymous online survey involving Jordanian academic staff. The findings revealed that workplace cyberbullying reduces with increasing social capital. No relationship was detected between workplace cyberbullying and self-esteem. A positive correlation was found between self-esteem and structural social capital. Age, sex, and university sector do not predict academic workplace cyberbullying levels. The results indicate that administrators and policymakers in the Jordanian higher education sector should improve social capital among academics, given its positive implications for self-esteem, organizational life, and the prevention of distress. This strategy is appropriate in the turbulent conditions confronting academics working in a context with an increasingly dominant digital culture.

In this study, our focus is on stabilizing a competitive game involving an original equipment manufacturer (OEM) and a third-party remanufacturer (TPR). To assess the presence of chaos within the dynamics of this game, we employ various analytical tools, including spectral entropy (SE), bifurcation diagrams, and Lyapunov exponents. The unpredictable nature of chaotic dynamics significantly influences the market and has negative implications for the strategic decisions of both firms. Our approach to counteracting this chaotic behaviour and stabilizing the system revolves around the implementation of the Ott, Grebogi, and Yorke (OGY) method. Crucially, our analysis highlights that the marginal costs ($ c_n $ and $ c_r $) incurred by the OEM and TPR emerge as pivotal factors in achieving stabilization within the game. To provide a tangible demonstration of the effectiveness of our proposed stabilization strategy in the context of this competitive environment, we conducted numerical simulations.

This study proposes a passive human identification system based on wireless signals. The proposed system comprises three phases; preprocessing and standardization of recorded channel state information (CSI) signals and the extraction of relevant data using principal component analysis (PCA), transformation of the signals into feature vectors, and finally construction of classification models. To evaluate the proposed approach, we collected data from ten subjects in an indoor environment while performing a set of activities. The proposed approach was tested using three different activities: walking, sitting/standing, and picking up a pen, achieving subject identification accuracy of 97.3%, 99.75%, and 65.5%, respectively. The results suggest that activity-based identification systems can serve as an effective alternative to traditional methods such as passwords and smart cards.

Neurological complications related to coronavirus disease 2019 (COVID-19) infection have been increasingly reported. One of the most serious neurological complications is encephalitis, which could be due either to direct viral invasion or an immune-mediated inflammatory reaction. In this study, we conducted a systematic review of reported cases of autoimmune encephalitis mediated by N-methyl-ᴅ-aspartate receptor antibodies in conjunction with or after diagnosis of COVID-19 infection.

Wireless Sensor Networks (WSNs) play a critical role in numerous applications, and accurate localization of sensor nodes is vital for their effective operation. In recent years, optimization algorithms have garnered significant attention as a means of enhancing the WSN node localization. This paper presents an in-depth exploration of the necessity of localization in WSN nodes, and offers a comprehensive review of the optimization algorithms used for this purpose. This review encompasses a diverse range of optimization techniques, including evolutionary algorithms, swarm intelligence, and metaheuristic approaches. Key factors such as localization accuracy, scalability, computational complexity, and robustness were systematically evaluated and compared across various optimization algorithms. Additionally, the study sheds light on the strengths and limitations of each optimization approach and discusses their applicability in different WSN deployment scenarios. The insights provided in this review serve as valuable resources for researchers and practitioners seeking to optimize WSN node localization, thus promoting the efficient and reliable operation of WSNs in diverse real-world applications.

The widespread adoption of electric cars (EVs) can be attributed to their many advantages over conventional gas-powered automobiles. However, there may be difficulties in incorporating EVs into the grid due to increased energy demand and peak load. We propose a blockchain-based federated learning scheme using different linear regression algorithms for energy demand prediction for EVs. The information gathered from EVs is stored on the blockchain network. Only those with the proper credentials can decrypt the data from its encrypted storage. Data from EVs is utilized to train a machine learning model with the use of a federated learning algorithm. Each EV is used to train a model, and then the models’ parameters are distributed throughout the blockchain. Our approach is innovative in analyzing of BCFL communications overhead and latency issues, while delving deeper into its dynamics to measure and reduce communication delays to maximize system efficiency. The implementation results verify the effectiveness of our system in anticipating EVs’ energy requirements. For the training of the BCFL model, a huge real-world dataset was used from over 60,000 transactions at EV charging stations in Boulder city, Colorado. The results show that the framework is reliable, since all the models have R2 values above 0.91, which indicates a high degree of accuracy in predicting energy use.

Training neural networks by using conventional supervised backpropagation algorithms is a challenging task. This is due to significant limitations, such as the risk for local minimum stagnation in the loss landscape of neural networks. That may prevent the network from finding the global minimum of its loss function and therefore slow its convergence speed. Another challenge is the vanishing and exploding gradients that may happen when the gradients of the loss function of the model become either infinitesimally small or unmanageably large during the training. That also hinders the convergence of the neural models. On the other hand, the traditional gradient-based algorithms necessitate the pre-selection of learning parameters such as the learning rates, activation function, batch size, stopping criteria, and others. Recent research has shown the potential of evolutionary optimization algorithms to address most of those challenges in optimizing the overall performance of neural networks. In this research, we introduce and validate an evolutionary optimization framework to train multilayer perceptrons, which are simple feedforward neural networks. The suggested framework uses the recently proposed evolutionary cooperative optimization algorithm, namely, the dynamic group-based cooperative optimizer. The ability of this optimizer to solve a wide range of real optimization problems motivated our research group to benchmark its performance in training multilayer perceptron models. We validated the proposed optimization framework on a set of five datasets for engineering applications, and we compared its performance against the conventional backpropagation algorithm and other commonly used evolutionary optimization algorithms. The simulations showed the competitive performance of the proposed framework for most examined datasets in terms of overall performance and convergence. For three benchmarking datasets, the proposed framework provided increases of 2.7%, 4.83%, and 5.13% over the performance of the second best-performing optimizers, respectively.

Abstract Diabetes mellitus (DM) is a prevalent chronic metabolic disorder linked to increased morbidity and mortality. With a significant portion of cases remaining undiagnosed, particularly in the Middle East North Africa (MENA) region, more accurate and accessible diagnostic methods are essential. Current diagnostic tests like fasting plasma glucose (FPG), oral glucose tolerance tests (OGTT), random plasma glucose (RPG), and hemoglobin A1c (HbA1c) have limitations, leading to misclassifications and discomfort for patients. The aim of this study is to enhance diabetes diagnosis accuracy by developing an improved predictive model using retinal images from the Qatari population, addressing the limitations of current diagnostic methods. This study explores an alternative approach involving retinal images, building upon the DiaNet model, the first deep learning model for diabetes detection based solely on retinal images. The newly proposed DiaNet v2 model is developed using a large dataset from Qatar Biobank (QBB) and Hamad Medical Corporation (HMC) covering wide range of pathologies in the the retinal images. Utilizing the most extensive collection of retinal images from the 5545 participants (2540 diabetic patients and 3005 control), DiaNet v2 is developed for diabetes diagnosis. DiaNet v2 achieves an impressive accuracy of over 92%, 93% sensitivity, and 91% specificity in distinguishing diabetic patients from the control group. Given the high prevalence of diabetes and the limitations of existing diagnostic methods in clinical setup, this study proposes an innovative solution. By leveraging a comprehensive retinal image dataset and applying advanced deep learning techniques, DiaNet v2 demonstrates a remarkable accuracy in diabetes diagnosis. This approach has the potential to revolutionize diabetes detection, providing a more accessible, non-invasive and accurate method for early intervention and treatment planning, particularly in regions with high diabetes rates like MENA.

Abstract Background Catheter-associated urinary tract infection is a global problem but it can be prevented with the appropriate implementation of evidence-based guidelines. This study was conducted to assess the level of compliance of healthcare workers with the catheter-associated urinary tract infection prevention guidelines during the insertion of a urinary catheter. Methods An observational study using a descriptive cross-sectional design was conducted at Sana’a City hospitals, Yemen. All the nurses and physicians from the governmental, teaching, and private hospitals were eligible to participate in the study. The data collection was performed through convenience sampling from March 2020 to December 2020, using a structured observational checklist prepared specifically for this study. Results The majority of the urinary catheter insertions were performed by nurses. There were no written policy or procedures for an urinary catheter insertion and no in-service education or training departments in the majority of the hospitals. The overall mean score of compliance was 7.31 of 10. About 71% of the healthcare workers had a high or acceptable level of compliance and 29% had an unsafe level of compliance. Compliance was low for maintaining aseptic technique throughout the insertion procedure, using a single use packet of lubricant jelly, performing hand hygiene immediately before insertion, and securing the urinary catheter once inserted. Factors affecting the healthcare workers compliance were gender, the working ward/unit of the healthcare workers, the availability of a written policy/procedure and a department or unit for in-service education. Conclusion Yemeni healthcare workers’ overall compliance was acceptable but it was unsafe in several critical measures. There is an urgent need for developing, implementing, and monitoring national guidelines and institutional policy and procedures for catheter-associated urinary tract infection prevention. Periodical in-service education and training programs and adequate access to the necessary materials and supplies are paramount.

This study explores the representation of radical and anti-radical ideologies among German Islamic TikTok creators, analyzing 2983 videos from 43 accounts through qualitative content analysis. The results reveal two main content clusters: religious practice involving social/lifestyle issues and political activism around Muslim grievances. Victimization, found in 150 videos, was the most common indicator associated with radicalization and emerged as a source of political activism and subversive discourse. Overall, indicators of radicalism were scarce, suggesting that visible mainstream Islamic creators do not exhibit high levels of radical ideology. However, this also reflects a selection bias in the design of this study, which systematically overlooks fringe actors. In addition, religious advocacy was the most common topic (1144 videos), serving as a source of guidance and motivation, but was occasionally linked to sectarianism and rigid religious interpretations. Male creators posted more religious/theological videos; female creators posted more lifestyle videos. However, gender distinctions are limited due to the low representation of female creators (6). Some topics, such as the hijab, served as an intersection between religious practice and politicized narratives. This study highlights TikTok’s role in promoting diverse ideological views and shaping community engagement, knowledge sharing, and political mobilization within Germany’s Muslim digital landscape.

BACKGROUND: Testicular cancer poses a substantial health burden globally, and early detection through testicular self-examination (TSE) is vital for improving prognosis. The study aims to assess the perception, awareness, knowledge, and factors associated with TSE among Saudi nursing students. MATERIALS AND METHODS: A structured questionnaire was distributed to 418 participants. Data analysis included descriptive statistics, Chi-square tests, and t-tests. RESULTS: On average, the participants’ self-confidence in their knowledge to perform TSE was 6.18 (±3.3) out of 10. The majority of participants held misconceptions about TSE, perceiving it as painful (91.86%) and embarrassing (52.39%). The mean of correct awareness and knowledge levels of participants about steps in performing TSE was 9.2 (SD = ±3.6) out of 21. On average, the correct perception of TC and TSE was 11.73 (±4.11) out of 20. Significant relationships emerged between TSE performance and factors such as being married (P = 0.043), having good or less health status (P = 0.015), being a tobacco user (P = 0.039), having a medical problem with testicles (P = 0.005) or family history of TC (P = 0.007), has been learned about TSE (P = 0.002), high-grade point average (P = 0.012), had high self-confidence to perform TSE (P = 0.033), and had correct perception about TC and TSE (P = 0.037), had correct awareness about TSE (P = 0.021), had motivated factors that influencing to practice of TSE (P = 0.003), and had correct awareness and knowledge levels of participants about steps in performing TSE (P = 0.002). CONCLUSION: The study underscores the need for targeted educational interventions and curriculum enhancements to dispel misconceptions, improve awareness, and promote accurate TSE practices among nursing students. Public health campaigns are recommended to address barriers and normalize TSE.

BACKGROUND: The COVID-19 pandemic has significantly impacted the psychological well-being of healthcare providers (HCPs) worldwide. Understanding the prevalence and associated factors of depression, generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD) among these providers is crucial. Assess the prevalence of major depression, GAD, and PTSD symptoms among HCPs in the United Arab Emirates (UAE) during the COVID-19 pandemic. Additionally, this study sought to identify demographic, work-related, and health-related factors associated with these psychological symptoms. MATERIALS AND METHODS: A cross-sectional survey involving 992 HCPs across various healthcare institutions in the UAE was conducted. Participants were administered standardized assessment tools, including the Patient Health Questionnaire-9 (PHQ-9) for depression, the GAD-7) for GAD, and the Impact of Event Scale-Revised (IES-R) for PTSD. Independent t-tests and one-way analysis of variance (ANOVA) were employed to assess the prevalence and associated factors. RESULTS: The findings revealed that approximately 19% of the participants exhibited significant symptoms of major depression (PHQ-9 ≥10), while 57.1% reported no significant anxiety symptoms, and 54.4% displayed minimal or no significant PTSD symptoms. Participants with COVID-19, family infections, and work overload showed higher depression, GAD, and PTSD symptoms. Married in-hospital workers significantly differed from single prehospital workers in psychological symptoms. Occupation, level of education, working department, and age significantly influenced the perceived severity of depression, GAD, and PTSD symptoms. Specifically, the ANOVA test revealed significant differences in depression (F = 3.01, P < 0.05), GAD (F = 11.4, P < 0.001), and PTSD symptoms (F = 3.6, P < 0.05) based on occupation. Nurses had higher depression (5.8 ± 7.4) and GAD (7.4 ± 6.6) scores, while physicians had elevated PTSD symptoms (22.4 ± 21.0). Participants with a bachelor’s degree had significantly higher depression (7.0 ± 8.4), GAD (7.2 ± 7.4), and PTSD symptoms (22.9 ± 24.6) than those with diplomas or postgraduate degrees. In the intensive care unit (ICU), higher levels of depression (9.3 ± 9.1), GAD (7.6 ± 7.5), and PTSD symptoms (24.7 ± 25.4) were reported. Participants at the screening center had higher depression (5.4 ± 4.7) and PTSD symptoms (15.2 ± 16.8) than those in other prehospital departments. However, participants in PHCs reported higher levels of GAD symptoms (5.8 ± 7.1) compared to those at screening centers, and EMTs. Concerning age groups, participants between 50 and 60 years old experienced more depressive symptoms (8.3 ± 6.7), while those aged 40-49 reported higher GAD (8.5 ± 7.3) and PTSD symptoms (27.0 ± 19.0). CONCLUSION: This study underscores the importance of proactive mental health support and tailored interventions for HCPs. It highlights the need for workload management and work-life balance, as well as personalized support for those directly affected by COVID-19. Moreover, it emphasizes the significance of pandemic preparedness and comprehensive training for HCPs. The study findings contribute to a deeper understanding of the diverse factors influencing the psychological well-being of HCPs during public health crises.

Early fire identification is critical to saving lives and property. One viable strategy for improving fire detection systems’ efficacy and precision is the use of Internet of Things (IoT) technology. This article details research into the conception and development of an IoT, ESP32-based, Arduino MEGA-connected smart pre-alert detection system for fires. Because of its flexible nature, the Arduino microcontroller can easily exchange data with various sensors for real-time monitoring and analysis. This study surveys the existing literature to provide insight into many approaches to early fire detection (forecasting), such as sensor fusion methods and the use of the intelligence concept as a pre-predictor. The research highlights the need to set up sophisticated fire monitoring and alarm systems and to develop predictive models based on sensor data. This study illustrates how embedded systems via IoT technology and the ESP32 architecture may improve the efficiency and dependability of very early fire detection systems. This research adds to the expanding corpus of information that may be used to improve fire safety in contemporary settings. The proposal’s sensors include an Arduino MEGA, an ESP32, a MAX6675 module, an MQ-Smoke, and an MQ-Natural Gas for collecting data, which are then processed using Cloud Firebase and a sleek mobile interface that can be reached overseas at any time.

BackgroundRecent studies reported a link between high salt diet (HSD) and clinical exacerbation in mouse models of autoimmune diseases, mainly through the induction of pathogenic Th17 cells and/or HSD-induced dysbiosis. However, the topic remains controversial and not fully understood.PurposeIn this study, we investigated the effects of HSD on the development of experimental autoimmune uveitis (EAU) in C57BL/6J mice.Methods and resultsUnexpectedly, our data showed a significant attenuating effect of HSD on disease severity of native EAU, induced by direct immunization with IRBP peptide. That said, HSD had no effect on EAU disease severity induced by adoptive transfer of semi-purified auto-reactive IRBP-specific T lymphocytes. Accordingly, HSD did not affect IRBP-specific systemic afferent immune response as attested by no HSD-linked changes in T lymphocytes proliferation, cytokine production and Treg proportion. Gut microbiota analysis from cecal samples in naïve and EAU mice demonstrated that HSD affected differentially α-diversity between groups, whereas β-diversity was significantly modified in all groups. Unknown Tannerellaceae was the only taxon associated to HSD exposure in all treatment groups. Interestingly, a significantly higher abundance of unknown Gastranaerophilales, with potential anti-inflammatory properties, appeared in HSD-fed native EAU mice, only.DiscussionIn conclusion, our study suggests a possible impact of HSD on gut microbiota composition and consequently on development and clinical severity of EAU. Further studies are required to investigate the potential beneficial role of Gastranaerophilales in EAU.

This paper adopts a holistic approach to the integrated water supply chain system, considering water-related aspects including production, technology selection, distribution routes, and storage, among others. It also introduces a multi-period comprehensive mathematical model that assists decision makers in jointly optimizing a multitude of decisions pertaining to the water supply chain, ranging from strategic to tactical ones. In particular, the former address the installation of new desalination plants along with their operational capacity, capacity expansion of existing plants and infrastructure assets (storage and distribution), as well as the selection of the best-suited desalination technologies. On the other hand, tactical decisions consider issues such as the allocation of water resources among end users, production level of desalinated water at the different plants, and storage levels across various demand zones. All these decisions are being optimized in every period towards minimizing financial and environmental costs throughout the planning horizon. To illustrate the model’s practical relevance and assess its validity, a case study focused on an Emirate in the United Arab Emirates (UAE). Results highlight the need for increased desalination capacity over the next 15 years to match growing demand. The study pinpoints the timings for desalination facility expansions, compensating for decreased capacity due to degradation or retirement. The study underscores the superiority of reverse osmosis technology over other desalination options.