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Abstract Introduction Abdominal surgical emergencies have a high mortality rate. Effective management primarily relies on the early identification of patients at high risk of postoperative complications. The objective of our study was to determine the prognostic factors associated with poor outcomes from abdominal surgical emergencies in Senegal and to establish a predictive score for mortality for preoperative risk evaluation (NDAR (New Death Assessment Risk) score). Methodology This was a retrospective national cross-sectional study conducted over one year in 14 regions of Senegal. Adult patients (aged > 15 years) who presented with a traumatic or non-traumatic abdominal surgical emergency were included. The studied variables included clinical and paraclinical data. The variable of interest was death within 30 days of the surgery. Logistic regression was used to identify the factors independently associated with mortality. Risk factors identified after logistic regression analysis were weighted using odds ratio (OR) values rounded to the nearest whole number. The predictive capacity of the score was evaluated by analyzing the ROC (Receiver Operating Characteristic) curve based on the area under the curve (AUC). Results A total of 1114 patient records were included, with a mortality rate of 4.4%. Diagnoses were observed in patients included appendicitis in 39.8% of cases (n = 444), followed by peritonitis in 22.3% (n = 249), intestinal obstruction in 18.5% (n = 205), strangulated hernias in 10.5% (n = 117), and abdominal trauma in 6.1%. Logistic regression, established the following scores: age > 40 years (score 2), ASA status grade 2 or higher (score 1), presence of a positive QSIRS score (score 2), diagnosis of peritonitis (score 2), diagnosis of intestinal obstruction (score 1), and the presence of intestinal necrosis (score 3). The score is positive if the total is strictly greater than 5, indicating a 17.7% risk of mortality. This score had a high predictive capacity with an AUC of 0.7397. Conclusion This study enabled the establishment of a score that allows for the early identification of at-risk patients, even in constrained resource settings, facilitating appropriate perioperative management and timely surgical intervention to reduce the risk of complications. This approach, focused on early recognition of high-risk patients, is crucial for improving clinical outcomes in abdominal surgical emergencies.

Abstract Background This study aimed to demonstrate that the genomic material of SARS-CoV-2 can be isolated from strips of COVID-19 rapid diagnostic test cassettes. Method It was a prospective cross-sectional study involving patients admitted to treatment centers and sampling sites in the city of Conakry, Guinea. A total of 121 patients were double sampled, and 9 more patients were tested only for RDT. PCR was conducted according to the protocol of the RunMei kit. Sequencing was performed by using the illumina COVIDSeq protocol. Nine COVID-19 RDTs without nasopharyngeal swabs were in addition tested. Result Among the 130 COVID-19 RDTs, forty-seven were macroscopically positive, whereas seventy-two were positive according to PCR using RDT strip, while among the 121 VTM swabs, sixty-four were positive. Among eighty-three negative COVID-19 RDTs, twenty-seven were positive by PCR using RDT strip with a geometric mean Ct value of 32.49 cycles. Compared to those of PCR using VTM, the sensitivity and specificity of PCR using RDT strip were estimated to be 100% and 85.96%, respectively, with 93.39% test accuracy. Among the fifteen COVID-19 RDT extracts eligible for sequencing, eleven had sequences identical to those obtained via the standard method, with coverage between 75 and 99.6%. Conclusion These results show that COVID-19 RDTs can be used as biological material for the genomic surveillance of SARS-CoV-2.

Abstract Background The microplastic transport of rivers is a complex spatiotemporal process; however, only limited knowledge exists on it, making its monitoring complicated. The study aimed to analyze the spatial and temporal dynamics of suspended sediments and microplastics based on measurements (1) every five days for 2 years at one site and (2) annual repetition at 29 sites along the 750-km-long Tisza River for 3 years. Water samples were taken by pumping (1 m3). Machine learning algorithms were applied to Sentinel images to analyze the spatiality of sediment transport. Results In the Tisza River (Central Europe), the microplastic concentration (MPCmean: 35 ± 27 item/m3) and the suspended sediment concentration (SSCmean: 60 ± 57 g/m3) showed high temporal variations. During low stages, the concentrations dropped as most transported sediments were deposited on the bottom. These sediments, including microplastics, were remobilized during flood waves, thus, higher MPC and SSC were measured. The first flood wave after a low-stage period had the highest concentrations. The increased transport capacity of the river during floods created large-scale suspended sediment and microplastic waves with increased concentrations. The mean MPC gradually increased between 2021 (19 ± 13.6 item/m3) and 2022 (23.7 ± 15.8 item/m3), and then it more than doubled (2023: 57 ± 44.8 item/m3). The tributaries acted as suspended sediment and microplastic conveyors. On the Sentinel images, medium-scale clouds were identified, with the suspended sediment clouds being more pronounced than microplastic clouds. Fewer and longer clouds appeared during low stages, separated by clearer water bodies. During flood waves, shorter clouds were detected. The tributaries with increased suspended sediment and microplastic transport created well-distinguishable clouds in the main river. Conclusions Identifying suspended sediment and microplastic clouds in a river could support more precise monitoring. The hydrological background of the monitoring and the existence of these clouds should be considered, as sampling from clouds with increased SSC and MPC provides different data than sampling from the clearer water bodies between two clouds. Graphical Abstract

Abstract This study investigates the effects of laser power, scan speed, and hatch distance on the features of aluminium specimens produced using direct metal laser sintering (DMLS). By systematically varying these parameters, we identified optimal combinations for producing high-quality metal components. Our findings were validated through reproducible printing processes. Analysis of variance (ANOVA) and grey relational analysis (GRA) were employed to optimize the production parameters further. We found a significant trade-off between laser power, tensile strength, and fatigue resistance, with laser power having the most substantial impact on mechanical properties, microstructure, and surface roughness. Statistical analysis confirmed that higher laser power improves mechanical characteristics but may increase surface roughness. These insights are crucial for enhancing the efficiency and quality of DMLS-produced metal components.

Background: Machine learning models can provide quick and reliable assessments in place of medical practitioners. With over 50 million adults in the United States suffering from osteoarthritis, there is a need for models capable of interpreting musculoskeletal ultrasound images. However, machine learning requires lots of data, which poses significant challenges in medical imaging. Therefore, we explore two strategies for enriching a musculoskeletal ultrasound dataset independent of these limitations: traditional augmentation and diffusion-based image synthesis. Methods: First, we generate augmented and synthetic images to enrich our dataset. Then, we compare the images qualitatively and quantitatively, and evaluate their effectiveness in training a deep learning model for detecting thickened synovium and knee joint recess distension. Results: Our results suggest that synthetic images exhibit some anatomical fidelity, diversity, and help a model learn representations consistent with human opinion. In contrast, augmented images may impede model generalizability. Finally, a model trained on synthetically enriched data outperforms models trained on un-enriched and augmented datasets. Conclusions: We demonstrate that diffusion-based image synthesis is preferable to traditional augmentation. Our study underscores the importance of leveraging dataset enrichment strategies to address data scarcity in medical imaging and paves the way for the development of more advanced diagnostic tools.

The central aim of my research is to investigate the third language learning processes of L1 Hungarian high-school learners learning L2 English and L3 German. More specifically, I aim at revealing to what extent Hungarian learners rely on their knowledge of their L1 and L2 as well as on the learning strategies they have developed while learning their L2.

Background Chronic kidney disease (CKD) poses a significant public health challenge globally while impacting patients’ physical function and quality of life. Addressing the issues of physical inactivity and pain management is essential during treatment to improve health-related quality of life. The present study investigated the effect of an aerobic training program with core stabilization exercises for hemodialysis (HD) patients on a transplant waiting list and renal transplant (RTx) patients.Methods A total of 45 patients with CKD were included in the 12-week study: 25 patients receiving HD (12 HD treatment group, 13 HD control group) and 20 patients with RTx (9 RTx treatment group, 11 RTx control group). Functional capacity was measured using the 6-min walk test, pain was measured using the visual analog scale, and health-related quality of life was measured using the Kidney Disease Quality of Life–Short Form 12 questionnaire. Nonparametric statistical tests were performed at a significance level of 0.05.Results Both the HD and RTx treatment groups showed significantly reduced times for the 6-min walking test (p = 0.002 and p = 0.008, respectively), significantly reduced pain severity (p = 0.002 and p = 0.008, respectively), and significantly improved quality of life scores (p = 0.006 and p = 0.041, respectively) by the end of the study compared with control groups.Conclusion Based on the results, structured exercise programs could be effective therapies in CKD management. Therefore, health providers should promote their integration into routine care practices to enhance patient outcomes and well-being.

Biodiesel has emerged as a compelling substitute for conventional diesel fuel, providing a sustainable and eco-friendly choice for fueling compression ignition engines. This comprehensive study investigates the influence of biodiesel, specifically derived from sunflower oil, through the esterification method, on crucial engine performance parameters and environmental effects. The study examines the impact of varying engine torque on the performance of a single-cylinder, four-stroke compression ignition engine, encompassing parameters such as brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC), as well as exhaust emissions, including unburned hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx). Four distinct biodiesel blends (B10, B20, B30, B40) with varying sunflower oil content are systematically compared to pure diesel (B0). The engine operates at a consistent speed of 1700 rpm, while the torque undergoes controlled adjustments from 0 to 10 Nm. Subsequently, this study explores the application of an alternating model tree (AMT) machine learning algorithm to establish relationships between independent factors, specifically torque and biodiesel volume (%vol), and dependent variables, including BTE, BSFC, CO, and NOx in a combustion engine. Additionally, the study employs a multi-objective ameliorative whale optimization algorithm (AWOA) to optimize the model's output. The objective is to identify optimal values for torque and%vol that maximize engine performance (BTE) while minimizing engine emissions (CO and NOx) and reducing fuel consumption (BSFC). The optimization process yields noteworthy results, with AWOA achieving peak BTE at 29.714 %, BSFC at 0.262 kg.kWh-1, and NOx emissions at 992 ppm at torque 7.3 N.m and 13% vol. In contrast, particle swarm optimization (PSO) secured the minimum CO level at 0.123 %, with torque set at 7.6 N.m and 26% vol. The AMT models demonstrate high prediction accuracy, with coefficient of determination (R2) values exceeding 0.98.

Neovascularization is implicated in the pathology of retinopathy of prematurity (ROP), diabetic retinopathy (DR), and age-related macular degeneration (AMD), which are the leading causes of blindness worldwide. In our work, we analyzed how heme released during hemorrhage affects hypoxic response and neovascularization. Our retrospective clinical analysis demonstrated, that hemorrhage was associated with more severe retinal neovascularization in ROP patients. Our heme-stimulated human retinal pigment epithelial (ARPE-19) cell studies demonstrated increased expression of positive regulators of angiogenesis, including vascular endothelial growth factor-A (VEGFA), a key player of ROP, DR and AMD, and highlighted the activation of the PI3K/AKT/mTOR/VEGFA pathway involved in angiogenesis in response to heme. Furthermore, heme decreased oxidative phosphorylation in the mitochondria, augmented glycolysis, facilitated HIF-1α nuclear translocation, and increased VEGFA/GLUT1/PDK1 expression suggesting HIF-1α-driven hypoxic response in ARPE-19 cells without effecting the metabolism of reactive oxygen species. Inhibitors of HIF-1α, PI3K and suppression of mTOR pathway by clinically promising drug, rapamycin, mitigated heme-provoked cellular response. Our data proved that oxidatively modified forms of hemoglobin can be sources of heme to induce VEGFA during retinal hemorrhage. We propose that hemorrhage is involved in the pathology of ROP, DR, and AMD.

An accurate histopathologic diagnosis on surgical biopsy material is necessary for the clinical management of patients and has important implications for research, clinical trial design/enrollment, and public health education. This study used a mixed methods approach to isolate sources of diagnostic error while residents and attending pathologists interpreted digitized breast biopsy slides. Ninety participants, including pathology residents and attending physicians at major United States medical centers reviewed a set of 14 digitized whole-slide images of breast biopsies. Each case had a consensus-defined diagnosis and critical region of interest (cROI) representing the most significant pathology on the slide. Participants were asked to view unmarked digitized slides, draw their participant region of interest (pROI), describe its features, and render a diagnosis. Participants review behavior was tracked using case viewer software and an eye-tracking device. Diagnostic accuracy was calculated in comparison to the consensus diagnosis. We measured the frequency of errors emerging during 4 interpretive phases: (1) detecting the cROI, (2) recognizing its relevance, (3) using the correct terminology to describe findings in the pROI, and (4) making a diagnostic decision. According to eye-tracking data, trainees and attending pathologists were very likely (∼94% of the time) to find the cROI when inspecting a slide. However, trainees were less likely to consider the cROI relevant to their diagnosis. Pathology trainees (41% of cases) were more likely to use incorrect terminology to describe pROI features than attending pathologists (21% of cases). Failure to accurately describe features was the only factor strongly associated with an incorrect diagnosis. Identifying where errors emerge in the interpretive and/or descriptive process and working on building organ-specific feature recognition and verbal fluency in describing those features are critical steps for achieving competency in diagnostic decision making.

BACKGROUND: Percutaneous left atrial appendage occlusion (LAAO) has proved to be a safer alternative for long-term anticoagulation; however, patients with a history of intracranial bleeding were excluded from large randomized clinical trials. OBJECTIVE: The purpose of this study was to determine outcomes in atrial fibrillation (AF) patients with a history of intracranial bleeding undergoing percutaneous LAAO. METHODS: National Inpatient Sample and International Classification of Diseases, Tenth Revision, codes were used to identify patients with AF who underwent LAAO during the years 2016-2020. Patients were stratified based on a history of intracranial bleeding vs not. The outcomes assessed in our study included complications, in-hospital mortality, and resource utilization. RESULT: A total of 89,300 LAAO device implantations were studied. Approximately 565 implantations (0.6%) occurred in patients with a history of intracranial bleed. History of intracranial bleeding was associated with a higher prevalence of overall complications and in-patient mortality in crude analysis. In the multivariate model adjusted for potential confounders, intracranial bleeding was found to be independently associated with in-patient mortality (adjusted odds ratio [aOR] 4.27; 95% confidence interval [CI] 1.68-10.82); overall complications (aOR 1.74; 95% CI 1.36-2.24); prolonged length of stay (aOR 2.38; 95% CI 1.95-2.92); and increased cost of hospitalization (aOR 1.28; 95% CI 1.08-1.52) after percutaneous LAAO device implantation. CONCLUSION: A history of intracranial bleeding was associated with adverse outcomes after percutaneous LAAO. These data, if proven in a large randomized study, can have important clinical consequences in terms of patient selection for LAAO devices.

Patients with leukemia are at an increased risk for infective endocarditis secondary to their immunocompromised state, chemotherapy, and specific risk factors such as the presence of indwelling central venous catheters. There is a paucity of data regarding temporal trends and clinical outcomes of infective endocarditis in leukemia patients. Previous studies have shown a high rate of complications related to surgical valve procedures for treatment of infective endocarditis in patients with hematological malignancies. In this study, we aimed to analyze the contemporary trends and clinical outcomes of treatment in infective endocarditis patients with and without leukemia based on data available from the Nationwide Inpatient Sample, which is a publicly accessible, large sample-sized national dataset of hospitalized patients across the US. We present key findings on baseline characteristics, microbiological profile, outcomes, rates of valve surgical procedures, and mortality in infective endocarditis patients with and without leukemia between 2002 and 2017 in the US.

Background and Objectives: Alternative medicine (AM) encompasses all forms of therapies that fall outside the mainstream of medical practice. Its popularity is on the increase. Because previous surveys were limited and not generalizable, we estimated the prevalence, pattern and factors associated with use of AM in the community. Subjects and Methods: A multistage cluster cross-sectional household survey was conducted among Saudi residents of the Riyadh region. Data were collected in 2003 by trained interviewers from primary health care centers using a specially designed questionnaire. Results: Of 1408 individuals participating in the study, 39% were men. The mean (±SD) age for the study pop--ulation was 35.5 (±13.9) years. Sixty-eight percent of the respondents had used AM during the last 12 months. The Holy Quran as a therapy was the most frequently used AM (50.3%), followed by honey (40.1%), black seed (39.2%) and myrrh (35.4%). The health belief model was found to be the most important determinant of AM use. Factors independently associated with AM use included perceived failure of medical treatment, the perceived success of AM, a preference for natural materials, and long appointment intervals to see physicians. Conclusions and Recommendations: There is a high prevalence of AM use in the Riyadh region and the most important determinant of AM use was the perceived failure of medical treatment. The study results call for intensive health education campaigns in the media addressing wrong beliefs regarding AM and modern medicine. The popularity of AM in this community should alert decision makers to look at the difficult accessibility to the health system.

Abstract The prevalence of Tuberculosis (TB) serves as a pivotal metric, reflecting the TB burden within a specific demographic. It quantifies the number of individuals affected by either active TB disease or latent TB (LTBI). Such data is crucial for assessing the efficacy of TB control interventions and determining the demand for diagnostic and treatment services. This study aims to consolidate data on TB infection prevalence in Saudi Arabia from existing literature. Additionally, we stratify this prevalence based on age, professional involvement in healthcare, gender, and region. Our search was conducted in PubMed, Scopus, Cochrane Library, and Web of Science databases to determine relevant studies. The pooled prevalence of TB infection among the total population residing in Saudi Arabia was estimated using a random-effect meta-analysis approach and Comprehensive Meta-Analysis software. The protocol was registered in the PROSPERO International Prospective Register of Systematic Reviews, No: CRD42023400984. We included 21 studies, 11 of which were pooled in the analysis. The overall prevalence was 17%. Regarding the specific population, we found that the prevalence of TB in Saudi Arabia was 9.8% and 26.7% in the general population and the healthcare workers, respectively. Stratifying by age, the highest prevalence was observed in individuals over 50 years (33.0%), while the lowest was in the 10–19 age group (6.4%). In terms of gender, men had a higher prevalence (12.0%) compared to women (9.4%). The prevalence of TB in Riyadh was 6.4%, and 3.6% in Mecca and Medina. Among healthcare workers, nurses and physicians had a prevalence of 14.7% and 15.0%, respectively. Our study found a TB prevalence of 17.0% in Saudi Arabia, higher than the worldwide average of 12.0%. Men had a higher prevalence than women, and healthcare workers had a relatively low prevalence compared to other countries. Age was a significant risk factor, with the highest prevalence in individuals above 50 years. Standardized protocols for screening and diagnosis and targeted interventions are needed to combat TB effectively in the country.