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The second survey of the Saudi Acute Myocardial Infarction Registry Program: Main results and temporal changes in care (STARS-2 program)
Background The Saudi Acute Myocardial Infarction Registry (STARS) program aims to evaluate the clinical characteristics, management, and outcomes of a representative sample of patients with acute myocardial infarction (AMI) in Saudi Arabia. This second phase evaluates temporal changes in patient care, demographics, and the management benchmarks for AMI. Methods and findings We created a 5-year recurring, multi-center prospective registry that utilizes a snapshot design in 50 hospitals from various healthcare sectors in Saudi Arabia. The study’s recruitment phase spanned from September 3, 2021, to January 6, 2023. During these 16 months, 2,690 patients presenting with acute myocardial infarction (AMI) with or without ST-segment elevation (STEMI or NSTEMI, respectively) were enrolled. The mean age (± SD) of the overall population was 57 (±12.4) years, 70% were Saudi citizens, 82% were men, and (48.8%) of the total patients had STEMI. Fifty-eight percent of patients had diabetes mellitus and 58% had hypertension. Of the total population with STEMI, primary percutaneous coronary intervention (PCI) was performed in 619 patients (47.1%), thrombolytics were given to 584 patients (44.5%), and 110 patients had no reperfusion (8.4%). Among patients who presented within 24 h of symptom onset, the door-to-balloon (DTB) time was 63 min (IQR: 43), with 75.6% achieving DTB < 90 min, whereas the door-to-needle (DTN) was 25 min (IQR: 34), with 57% achieving DTN < 60 min. Thirty-nine percent of patients failed lytic reperfusion and 96% of these required rescue PCI. In 52% of instances, the failure to receive reperfusion therapy was attributed to patients’ late presentation. At presentation, only 8.5% of cases were transferred by the Emergency Medical Services. Approximately one-fourth of patients with NSTEMI did not undergo a coronary angiogram. All-cause mortality was 2.4% with no significant difference between sexes or nationalities. Conclusion This nationwide AMI registry revealed younger age at presentation with a high prevalence of risk factors for coronary artery disease. While primary PCI key performance indicators have improved from the previous phase, further progress is needed in EMS utilization and acute revascularization for STEMI and NSTEMI.
Investigating factors influencing injury severity in crashes involving vulnerable road users in Pakistan
AA-Amyloidosis in the Eurasian stone-curlew (Burhinus oedicnemus)
Amyloidosis is a group of protein misfolding diseases and a well-recognized disorder in avian species. However, the knowledge of wild avian amyloid proteome is scarce. We report here gross, histopathological, ultrastructural, immunohistochemical and proteomic findings of systemic amyloidosis in seven Eurasian stone-curlews (Burhinus oedicnemus) necropsied in the Canary Islands. Spleen (5/6–83.33%), liver (3/5–60%), kidney (3/5–60%), proventricle (3/5–60%) and intestine (3/6–50%) were the more severely affected organs. All cases underwent chronic inflammatory processes associated to helminth, bacteria or fungi infection. Verminous chronic ventriculitis was the most frequent associated pathology in 5/7 (71.43%) followed by bumblefoot in 2/7 (28.57%) cases. Electron microscopy revealed a predominantly amorphous substance with 10 nm diameter non-branching amyloid fibrils. AA amyloidosis was characterized by immunohistochemistry and mass spectrometry analysis. By mass spectrometry three amyloid signature proteins were also identified: vitronectin, apolipoprotein A-IV and apolipoprotein A-I in 6/7 (85.71%), 4/7 (57.14%), and 3/7 (42.86%) cases, respectively, contributing with new knowledge about the amyloid proteome of amyloidosis in wild avian species.
Development and validation of a methylation-specific droplet digital PCR multiplex for lung cancer detection
An intelligent diagnosis method for cardiovascular diseases based on the CNN-CBAM-GRU model
Early diagnosis of cardiovascular diseases (CVDs) is essential for improving patient outcomes. As a primary diagnostic modality, electrocardiogram (ECG) signals pose challenges for automatic classification due to their complex temporal and morphological characteristics. This study proposes a CNN-CBAM-GRU model that integrates Convolutional Neural Networks (CNN), the Convolutional Block Attention Module (CBAM), and Gated Recurrent Units (GRU) to enhance both spatial feature representation and temporal sequence modeling. The model is evaluated on two public ECG datasets—MIT-BIH and PTB-XL—under five-class classification settings. Unlike many existing approaches that report only a limited set of metrics, this study conducts a comprehensive evaluation across multiple performance indicators, including accuracy, precision, recall, sensitivity, and F1-score, providing a more complete view of classification effectiveness. Experimental results demonstrate that the proposed model achieves a strong balance between predictive performance and computational efficiency. Specifically, it achieves 98.17% accuracy and 98.91% F1-score on MIT-BIH, and 99.21% accuracy and 99.47% F1-score on PTB-XL, with a compact parameter size of 2.45 million. These findings validate the proposed model as a practical and robust solution for intelligent ECG classification and automated cardiovascular disease diagnosis.
In situ decoration of Pd NPs over methotrexate encapsulated CoFe2O4 as a recyclable catalyst for the reduction of nitroarenes and synthesis of diaryl sulfide derivatives
Assessing the potential of seaweed extracts to improve vegetative, physiological and berry quality parameters in Vitis vinifera cv. Chardonnay under cool climatic conditions
Seaweed extracts are promising plant biostimulants for viticulture, but their effects on white winegrape cultivars grown under cool climates remain fairly undocumented. Furthermore, information is limited on the biostimulant potential of some brown seaweed species like Ecklonia maxima. This study evaluated the impact of two commercial extracts (derived from Ascophyllum nodosum and Ecklonia maxima) on Vitis vinifera cv. Chardonnay in Belgium during the 2021 and 2022 growing seasons. The extracts, alongside a water‑control and an NPK‑reference (NPK‑Ref) treatment (with nitrogen, phosphorus, and potassium levels comparable to the extracts), were applied as foliar sprays five times at regular intervals, from flowering to ripening. In 2021 and 2022, A. nodosum significantly increased individual leaf area (+12% and +15%), while in 2021 A. nodosum‑treated vines had an increased chlorophyll content index (+12% CCI) and photosystem II (PSII) reaction centre density (+6%) relative to control vines. This corresponded with a small, but significant, improvement (+1.5%) in PSII maximum quantum yield (Fv∕Fm), whereas PSII electron transport efficiency (ΦE0) remained unchanged. Furthermore, increased berry size, mass, and sugar content were observed in A. nodosum‑treated vines during ripening in 2022, comparable to NPK‑Ref vines. Conversely, the E. maxima extract had limited effects on vegetative growth, physiology, and subsequent berry development. Yield increase from 2021 to 2022 varied by treatment, with a significant increase observed for E. maxima (+60%) and NPK‑Ref vines (+80%), relative to control vines. Our results indicate that seaweed extracts, specifically A. nodosum‑based, can enhance grapevine leaf area, CCI, and Fv∕Fm under cool climatic conditions. A. nodosum treatment was also associated with increased berry size and sugar content, while E. maxima treatment was associated with increased yield in the subsequent, warmer season. Altogether, our study highlights that the differential effects of seaweed extracts on grapevine development are modulated by species and environmental conditions.
A risk analysis method for potential failure modes in the lithium-ion battery assembly process based on optimized FMEA and DHHFLTS
Charantin targets HMGCR-PCSK9 axis and activates PPAR-α signaling to ameliorate hyperlipidemia: Mechanistic insights from bioinformatics and in-vivo studies
Plant-derived compounds have recently gained attention owing to their better safety profile and multi-targeted actions. Charantin, a plant-based natural compound known for its diverse pharmacological properties, was investigated for its anti-hyperlipdemic activity using both in-silico and in-vivo approaches. A detailed network pharmacology analysis was used to predict charantin-related targets, cross-referenced with hyperlipidemia-associated genes from GeneCards, DisGeNET, and CTD. Shared targets were subjected to protein-protein interaction analysis and functional enrichment using STRING, Cytoscape, and ShinyGO. Molecular docking studies assessed charantin’s binding interactions with key lipid-regulating proteins (HMGCR, PCSK9, LDLR, PPAR-α, PI3K). In-vivo efficacy of charantin (100 and 200 mg/kg) was evaluated in Sprague-Dawley rats fed with high-lipid diet (HLD) for 12 days. Lipid profiles, liver enzymes and transcript levels of lipid-regulating genes were analyzed. A total of 242 overlapping genes were identified between charantin targets and hyperlipidemia-associated genes, with enrichment analyses highlighting key lipid metabolic and inflammatory pathways. Molecular docking revealed that charantin exhibited stronger binding affinities than simvastatin across multiple targets. In HLD animal model, charantin significantly reduced total cholesterol, triglycerides, LDL, and VLDL, while increasing HDL levels in a dose-dependent manner. Liver function remained preserved, accompanied by downregulation of HMGCR, PCSK9, and APOB, and upregulation of LDLR and PPAR-α at both gene and protein levels. Charantin exerts potent lipid-lowering effects through modulation of multiple pathways, including cholesterol biosynthesis, lipoprotein metabolism, and nuclear receptor activation. Its efficacy and hepatoprotective properties reiterate its potential as a safe, effective alternative or adjunct to conventional therapies for hyperlipidemia.
Perirenal fat thickness may be a significant predictor of prognosis and postoperative renal function in renal cancer surgery patients
Willingness to use long-acting injectable pre-exposure prophylaxis (LAI-PrEP) among black cisgender women in the Southern United States
Background Long-acting injectable pre-exposure prophylaxis (LAI-PrEP) for HIV prevention may improve adherence for those with concerns with daily pills. Limited data exist on LAI-PrEP acceptability among Black women in the U.S., a population vulnerable to HIV. We assessed willingness to use LAI-PrEP among Black women eligible for PrEP in the Southern U.S. Methods We conducted a cross-sectional online survey of HIV-negative Black women from March to June 2022 in the U.S. South. Participants provided information on sociodemographic characteristics, HIV knowledge, PrEP awareness, and use, stigma, risk perception, medical mistrust, and healthcare access. Multivariate logistic regression models determined factors associated with willingness to use LAI-PrEP. Results Of 491 women, the mean (SD) age was 40.1 (17.5), 53% of participants had a college degree or lower, 79% were single, and 80% resided in urban/suburban settings. Thirty-nine percent were aware of PrEP before the study and 36.7% of women were willing to use LAI-PrEP. In multivariate analyses, PrEP awareness [adjusted odds ratio (aOR=2.37, 95% CI 1.40, 3.73, p < 0.001), having a personal clinician (aOR=2.01, 95% CI 1.10, 3.68, p = 0.02), HIV worried (aOR=1.78, 95% CI 1.09, 2.89, p = 0.02), and medical trust (aOR=1.41, 95% CI 1.03, 1.93, p = 0.04) were statistically associated with willingness to use LAI-PrEP. However, the healthcare stereotype (beliefs that healthcare is biased) had lower odds of using LAI-PrEP (aOR=0.94, 95% CI 0.89, 0.99, p = 0.04). Conclusion Black women at risk for HIV are more likely to consider injectable PrEP when they understand HIV risk factors, are aware of PrEP, have a clinician, and trust the medical care. Implementing client-centered care interventions could effectively address medical mistrust and enhance engagement in HIV prevention services among Black women.
Assessing the spatial risk of wild birds in avian influenza transmission using global risk score
Ethical implications of neurotechnology in industry-academia partnerships: Insights from patient and research participant interviews
Background Neurotechnologies often advance through industry-academia (IA) partnerships and offer insight into brain and nervous system functions, bringing improved diagnosis and treatment options to patients. Both neurotechnology and IA partnerships pose ethical challenges that can impact research participation experiences, patient treatment, and health outcomes. Methods Investigators conducted interviews with 16 patients who used neurotechnology devices in therapeutic or research settings. Interviews explored participants’ experiences using neurotechnology, perspectives on IA partnerships, preferences for neural data use and long-term care, and advice for future neurotechnology device users. Data were analyzed using inductive thematic analysis. Results Participants were generally supportive of IA partnerships. However, they also recognized that these relationships could unduly influence research and clinical decisions. While participants appreciated the information shared with them prior to using the neurotechnology, informational gaps were still identified regarding the impact of devices on daily living, disclosure of relationships with industry, plans for data use and sharing, and plans for long-term care and upkeep of the device. Participants generally supported neural data sharing to advance research or improve patient care, although for some this depended on data sensitivity and how privacy would be protected. Participants advocated for post-trial access to experimental neurotechnologies and felt that responsibility for long-term care and device maintenance is best shared among companies, doctors, academic researchers, insurance companies, and patients themselves. Future device users were advised to self-advocate, maintain realistic expectations, and learn about a device before engaging with it. Conclusion Given current and future capabilities of neurotechnologies and the data they generate, IA partnerships that develop and commercialize neurotechnologies require careful consideration and implementation of practices that meaningfully consider patient perspectives, needs, and safety. Such practices include bias management in the design, conduct, and reporting of neurotechnology research, neural data sharing and use, post-trial device access, and informed consent processes.
Assessment of health-related quality of life in transfusion dependent beta thalassemia
Psychometric evaluation of the Persian nursing students’ learning self-efficacy instrument
The preparedness of the nursing workforce is a critical determinant of patient safety and healthcare quality, with academic performance serving as a key contributor to this preparedness. Self-efficacy plays a significant role in shaping the motivation and success of nursing students, necessitating the availability of valid and reliable instruments for its assessment. This study aimed to translate a multidimensional learning self-efficacy instrument for nursing students into Persian and evaluate its psychometric properties within the Iranian context. Employing a methodological design, the study recruited 450 nursing students through convenience sampling between September and December 2024. The instrument underwent translation/back-translation, with face validity (Impact Score > 1.5), content validity ratio (CVR = 0.8–1), and content validity index (CVI = 80–100%) established. Psychometric evaluation included construct, convergent, and discriminant validity, internal consistency, and test-retest reliability. Students from all academic years participated in construct validity testing through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) using SPSS 24.0 and AMOS 24.0. EFA identified a five-factor structure explaining 73.43% of variance, supported by strong sampling adequacy (Kaiser-Meyer-Olkin = 0.87) and significant Bartlett’s test (p < 0.001). CFA confirmed model fit for the 21-item Nursing Learning Self-Efficacy (NLSE) instrument, with robust indices: Parsimonious Comparative Fit Index (PCFI = 0.75), Parsimonious Normed Fit Index (PNFI = 0.72), Incremental Fit Index (IFI = 0.93), and Comparative Fit Index (CFI = 0.93). Internal consistency (Cronbach’s α = 0.93) and test-retest reliability (Intraclass Correlation Coefficient = 0.89) were excellent. These findings establish the Persian version of the NLSE as a valid and reliable self-report instrument. By providing a culturally adapted instrument, this study equips nursing educators and researchers with a practical means to assess and enhance self-efficacy among nursing students, ultimately contributing to improved educational outcomes and a more competent nursing workforce capable of addressing Iran’s evolving healthcare demands.
Efficacy of combined undenatured type II collagen and hydrolysed collagen supplementation in knee osteoarthritis: a randomised controlled trial
Analysis of global, regional, and national burden and attributable risk factors of acute lymphoblastic leukemia and acute myeloid leukemia from 1990 to 2021
Background Acute Leukemia (AL) is a prevalent subtype of leukemia, mainly including acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). The disease burden of acute leukemia has significantly shifted in recent years. The aim of this study was to evaluate global trends in the burden of disease for ALL and AML from 1990 to 2021. Methods Data on ALL and AML, encompassing incidence, mortality, disability-adjusted life-years (DALYs), and associated risk factors from 1990 to 2021, were extracted from the Global Burden of Disease (GBD) 2021 database. Estimated annual percentage changes (EAPC) were calculated to assess the changes in age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR). The associations between cancers burden and socio-demographic index (SDI) were also analyzed. Results Compared with 1990, the global incidence of ALL and AML in 2021 is 5.69% and 82.25% higher, respectively. During the period from 1990 to 2021, ASMR in ALL showed a large decline, while AML remained stable. The ASDR of both showed a downward trend (EAPC = −2.11% and −0.84%). Regions and countries with higher SDI also have higher rates of acute leukemia. The burden of AML is mainly distributed in the elderly population, while the burden of ALL is heavier in children. Smoking, high BMI, and occupational exposure to benzene and formaldehyde are major risk factors for AML and ALL-related deaths. Conclusion Acute leukemia remains one of the major global public health challenges, but there are different trends in different regions and countries. Acute myeloid leukemia has had a higher disease burden in recent years than acute lymphoblastic leukemia. Policy makers should develop targeted public health policies to further reduce the global burden of acute leukemia.
Echinacea purpurea ameliorates Bleomycin-induced pulmonary fibrosis in rats through modulating NADPH oxidase-4 and endothelin-1/connective tissue growth factor/matrix metalloproteinases signalling axis
Abstract Idiopathic pulmonary fibrosis (IPF) is one of the rapidly progressing interstitial lung illnesses. Bleomycin (Bleo) is used as a chemotherapeutic agent for the treatment of lymphoma patients. The major side effects of Bleo include lung fibrosis, characterized by the accumulation of inflammatory cells. Echinacea purpurea (ECH) possesses immune-modulating, antiviral, antimicrobial and anti-inflammatory activities. The current study aims to evaluate the possible protective effects of ECH against Bleomycin-induced pulmonary fibrosis. Forty rats were divided into four groups (n = 10). Group I represented the normal-control group. Group II represented the Bleo-control group. Groups III and IV received intra-tracheal Bleo followed by oral ECH (25 and 50 mg/kg); respectively, for 1 month. Lung tissue contents of reduced glutathione (GSH), malondialdehyde (MDA), transforming growth factor-beta (TGF-β), matrix metalloproteinases (MMP-2 & MMP-9), tissue inhibitor of metalloproteinase 1 (TIMP-1), MMP-9/TIMP-1 ratio, collagen-1 and alpha-Smooth muscle actin (α-SMA) were measured. NADPH oxidase 4 (NOX4), connective tissue growth factor (CTGF) and endothelin-1 (ET-1) genes were quantified using PCR. Moreover, lung tissue histopathological changes were screened. Intra-tracheal Bleo instillation resulted in significant increments in the lung tissue contents of MDA, TGF-β, MMP-2 & MMP-9, TIMP-1, MMP-9/TIMP-1 ratio, collagen-1 and α-SMA. Moreover, Bleo significantly elevated the PCR expression of NOX4, CTGF and ET-1 genes in lung tissues and caused apparent lung tissue histopathological fibrotic changes. ECH treatment ameliorated all the aforementioned parameters and mitigated the lung tissue histopathological fibrotic changes induced by Bleo. The study highlighted for the first time the anti-oxidant, anti-inflammatory and anti-fibrotic effects of ECH against Bleo-induced pulmonary fibrosis in rats. The study suggests that these effects are mainly mediated via the modulation of Gelatinases, NOX4, ET-1 and CTGF. Accordingly, ECH is anticipated as a potential therapy to be added to the treatment regimen of pulmonary fibrosis.
A machine learning approach for detecting WPA3 downgrade attacks in next-generation Wi-Fi systems
This paper presents a hybrid adaptive approach based on machine learning (ML) for classifying incoming traffic, feature selection and thresholding, aimed at enhancing downgrade attack detection in Wi-Fi Protected Access 3 (WPA3) networks. The fast proliferation of WPA3 is regarded critical for securing modern Wi-Fi systems, which have become integral to 5G and Beyond (5G&B) Radio Access Networks (RAN) architecture. However, the wireless communication channel remains inherently susceptible to downgrade attacks, where adversaries intentionally cause networks to revert from WPA3 to WPA2, with the malicious intent of exploiting known security flaws. Traditional Intrusion Detection Systems (IDS), which rely on fixed-threshold statistical methods, often fail to adapt to changing network environments and new, sophisticated attack strategies. To address this limitation, we introduce a novel ML-based Feature Selection and Thresholding for Downgrade Attacks Detection (MFST-DAD) approach, which comprises three stages: traffic data preprocessing, baseline adaptive feature selection, and real-time detection and prevention using ML algorithms. Experimental results on a specially generated dataset demonstrate that the proposed approach detects downgrade attacks in WPA3 networks, achieving 99.8% accuracy with a Naive Bayes classifier in both WPA3 personal and enterprise transition modes. These findings confirm the effectiveness of our proposed approach in securing next-generation Wi-Fi systems.