Search Results (2,339)

The growing sophistication of cyber threats has posed significant challenges for organizations in terms of accurately detecting and responding to incidents in a coordinated manner. Despite advances in the application of machine learning and automation, many solutions still face limitations such as high false positive rates, low scalability, and difficulties in interorganizational cooperation. This study presents MICRA (Modular Intelligent Cybersecurity Response Architecture), a modular conceptual proposal that integrates dynamic data acquisition, cognitive threat analysis, multi-layer validation, adaptive response orchestration, and collaborative intelligence sharing. The architecture consists of six interoperable modules and incorporates techniques such as supervised learning, heuristic analysis, and behavioral modeling. The modules are designed for operation in diverse environments, including corporate networks, educational networks, and critical infrastructures. MICRA seeks to establish a flexible and scalable foundation for proactive cyber defense, reconciling automation, collaborative intelligence, and adaptability. This proposal aims to support future implementations and research on incident response and cyber resilience in complex operational contexts. Full article

The incidence and prevalence of obesity and related cardio-metabolic diseases are on the rise, posing a critical health care challenge to systems across the globe. Bariatric surgery is a therapeutic cornerstone for morbidly obese patients, besides novel medical treatments, partly by ameliorating metabolic inflammation, a hallmark of metabolic diseases. Acyl-CoA Binding Protein (ACBP), also known as diazepam-binding inhibitor (DBI), is a regulator of autophagy and metabolism, and has recently been shown to increase in individuals undergoing voluntary fasting and in patients with cancer cachexia-induced malnutrition. By analyzing a prospectively collected study with matched serum and liver samples from patients undergoing laparoscopic adjustable gastric banding at baseline and six months after surgery, we here demonstrate that ACBP serum levels significantly increase following bariatric surgery. Hepatic ACBP expression at baseline predicted weight loss six months after the procedure. The predictive value of ACBP warrants further study, as it could identify patients who benefit most from metabolic surgery in the future. Full article

Ferroptosis, a distinct form of programmed cell death characterized by iron-dependent lipid peroxidation, has emerged as a critical factor in the pathogenesis of various diseases. Given the increasing prevalence of osteoporosis worldwide and the increasing incidence of osteoporosis, understanding the molecular mechanisms underlying bone loss is imperative for developing targeted therapies. Recent evidence suggests that ferroptosis plays a pivotal role in osteoporosis by influencing the balance between osteoblast and osteoclast activity. This review examines the mechanistic basis of ferroptosis and its pathological implications in osteoporosis. By delineating the interplay between ferroptosis and skeletal remodeling, we highlight potential therapeutic strategies aimed at modulating ferroptosis to mitigate osteoporosis progression. Full article

Pulmonary carcinoids (PCs) are rare neoplasms involving typical and atypical carcinoids (TCs and ACs), defined histologically by absent or focal necrosis and mitotic counts (<2/mm² vs. 2–10/mm²), respectively. Although uncommon overall, TCs and ACs represent the most frequent non-hematologic malignancies in the pediatric population. However, significantly less is known about PC in AYAs, a population often overlooked or analyzed within pediatric or adult cohorts. In this critical review, we analyzed existing literature on PCs in the AYA population using a question-and-answer format, emphasizing the substantial gap in current knowledge in this field and the urgent unmet clinical need for future scientific proposals. First, we analyzed epidemiology and the data availability about the association between PCs in AYA patients and genetic syndromes that typically reach the maximal diagnostic incidence within this age group. We then reviewed the available literature about the pathologic characteristics, clinical presentation, and treatment strategies for localized and metastatic disease in PC AYA patients. According to our findings, a significant lack of age-specific evidence and the need for international collaboration and prospective, AYA-focused clinical studies were underscored. Advancing research in this area is essential to improve understanding and develop tailored, evidence-based therapeutic approaches for this peculiar population. Full article

Modelling of linear accelerators using the Monte Carlo method is critical for precise radiotherapy planning. In addition, detailed and accurate dose estimation to the organ at risk can be assessed and optimized. In this study, EGSnrc Monte Carlo code was utilized to model, tune, and validate a 10 MV photon head model of a Varian Clinac iX linear accelerator for different field sizes, including flattening and flattening-free modes. Gamma analysis was utilized to compare the model with measured data to determine the best parameters for the incident electron on the target. The main results revealed that, for both flattening and flattening-free modes, the incident electron’s optimal energy is 9.5 MeV, with a 0.1 cm circular full width half maximum (FWHM) and a 0.07° angular divergence. The model is suitable for field sizes extending from 1 × 1 to 30 × 30 cm². The comparison of large field sizes, which includes both 20 × 20 and 30 × 30 cm², reflects the accuracy of the geometrical model of the flattening filter. Altering the FWHM has a notable effect on the profile, particularly in the penumbral region, although adjusting the angular divergence has little effect. The dose rate for the flattening filter-free beam compared to the flattening filter beam increased by a factor of four. The validated model demonstrates excellent agreement with measured data. Thus, it can provide accurate dose calculations and can be used in future studies to test treatment accuracy and patient safety, especially for advanced radiotherapy techniques. Full article

Over the past two decades, patient safety and clinical risk management have become strategic priorities for healthcare systems worldwide. In this context, the London Protocol has emerged as one of the most influential methodologies for investigating adverse events through a systemic, non-punitive lens. The 2024 edition, curated by Vincent, Adams, Bellandi, and colleagues, represents a significant evolution of the original 2004 framework. It integrates recent advancements in safety science, human factors, and digital health, while placing a stronger emphasis on resilience, proactive learning, and stakeholder engagement. This article critically examines the structure, key principles, and innovations of the London Protocol 2024, highlighting its departure from incident-centered analysis toward a broader understanding of both failures and successes. The protocol encourages fewer but more in-depth investigations, producing actionable and sustainable recommendations rather than generic reports. It also underscores the importance of involving patients and families as active partners in safety processes, recognizing their unique perspectives on communication, care pathways, and system failures. Beyond its strengths—holistic analysis, multidisciplinary collaboration, and cultural openness—the systemic approach presents challenges, including methodological complexity, resource requirements, and cultural resistance in blame-oriented environments. This paper discusses these limitations and explores how leadership, staff engagement, and digital technologies (including artificial intelligence) can help overcome them. Ultimately, the London Protocol 2024 emerges not only as a methodological tool but as a catalyst for cultural transformation, fostering healthcare systems that are safer, more resilient, and committed to continuous learning. Full article

Background and Objectives: Romania has experienced the highest measles incidence rate in the European Union since late 2023, driven by suboptimal measles–mumps–rubella (MMR) uptake. Contemporary data on bedside predictors of clinical deterioration are scarce. The objective was to characterise demographic, clinical and laboratory differences between severe and non-severe measles and derive a multivariable model for intensive-care-unit (ICU) admission. Methods: We undertook a retrospective cohort study at the “Victor Babeș” University Hospital for Infectious Diseases, Timișoara. All admissions from 1 November 2023 to 15 May 2025 with serological or RT-PCR confirmation and a complete baseline laboratory panel were included. Descriptive statistics compared ward-managed versus ICU-managed patients; independent predictors of ICU transfer were identified through logistic regression that incorporated age, vaccination status, leukocyte count, C-reactive protein (CRP) and interleukin-6 (IL-6). Results: Among 455 patients (median age 3.0 y, interquartile range [IQR] 1.0–7.0), 17 (3.7%) required ICU care. Vaccine coverage was 18.0% overall and 0% among ICU cases. Compared with ward peers, ICU patients exhibited higher leukocyte counts (8.1 × 10⁹ L vs. 6.0 × 10⁹ L; p = 0.003) and a near-five-fold elevation in IL-6 (18 pg mL vs. 4 pg mL; p < 0.001), while CRP, procalcitonin and fibrinogen were similar. ICU admission prolonged median length of stay from 5 days (IQR 4–7) to 8 days (5–12; p = 0.004). In multivariable modelling, IL-6 remained the sole independent predictor (odds ratio [OR] 1.07 per pg mL; 95% confidence interval [CI] 1.03–1.12; p = 0.001); the model’s AUC was 0.83, indicating good discrimination. Complete separation precluded reliable estimation of the protective effect of vaccination, but no vaccinated child required ICU care. Conclusions: A simple admission panel centred on IL-6 accurately identified Romanian measles patients at risk of critical deterioration, whereas traditional markers such as CRP and leukocyte count added little incremental value. Even a single documented MMR dose was associated with the complete absence of ICU transfers, underscoring the urgent need for catch-up immunisation campaigns. Integrating IL-6-guided triage with intensified vaccination outreach could substantially reduce measles-related morbidity and health-system strain in low-coverage EU settings. Full article

Background: Peripherally inserted central catheters (PICCs) are becoming an increasingly utilised alternative to traditional central venous access devices. Their uptake, particularly among oncology patients, is due to their growing ease of access, suitability for medium-term use and perceived safety profile. However, PICCs can be a source of severe and life-threatening complications such as central line-associated bloodstream infection (CLABSI), deep vein thrombosis (DVT), pulmonary embolism (PE), malpositioning, dislodgement, and occlusion. Methods: This narrative was constructed from a literature review of the PubMed database, utilising MESH terms for peripherally inserted central catheters, percutaneous central catheters, PICC, and complications. Randomised controlled trials, systematic reviews, and meta-analyses published between 2015 and 2025 were included. Additional articles were obtained through targeted PubMed searches or from references within previous articles. Results: Major periprocedural complications were seen in 1.1% of PICC insertions, CLABSI in 1.4–1.9%, venous thrombosis embolism (including PE) in 2.3–5.9%, and malpositioning in 7.87%. The overall PICC complication incidence was 9.5–38.6%, which is greater than that of centrally inserted central venous access. A higher BMI, diabetes mellitus, chronic renal failure, and malignancy were the most significant predictive factors for PICC-associated complications. Conclusions: PICC complications are common, occurring more frequently than other forms of central venous access, and may lead to significant morbidity and mortality. Appropriate assessment of patient risk factors and optimisation strategies may reduce complication rates. Full article

Smart contracts have become integral to decentralized applications, yet their programmability introduces critical security risks, exemplified by high-profile exploits such as the DAO and Parity Wallet incidents. Existing vulnerability detection methods, including static and dynamic analysis, as well as machine learning-based approaches, often struggle with emerging threats and rely heavily on large, labeled datasets. This study investigates the effectiveness of open-source, lightweight large language models (LLMs) fine-tuned using parameter-efficient techniques, including Quantized Low-Rank Adaptation (QLoRA), for smart contract vulnerability detection. We introduce the EVuLLM dataset to address the scarcity of diverse evaluation resources and demonstrate that our fine-tuned models achieve up to 94.78% accuracy, surpassing the performance of larger proprietary models, while significantly reducing computational requirements. Moreover, we emphasize the advantages of lightweight models deployable on local hardware, such as enhanced data privacy, reduced reliance on internet connectivity, lower infrastructure costs, and improved control over model behavior, factors that are especially critical in security-sensitive blockchain applications. We also explore Retrieval-Augmented Generation (RAG) as a complementary strategy, achieving competitive results with minimal training. Our findings highlight the practicality of using locally hosted LLMs for secure, efficient, and reproducible smart contract analysis, paving the way for broader adoption of AI-driven security in blockchain ecosystems. Full article

Introduction: Tacrolimus is a cornerstone immunosuppressant in kidney transplantation (KT), but its narrow therapeutic index necessitates precise monitoring. Early post-transplant tacrolimus trough concentrations (C0) are critical, as suboptimal levels can increase rejection and infection risks. This study evaluated the impact of C0 levels at discharge on early post-transplant outcomes in a large Korean cohort. Materials and Methods: This retrospective analysis included 5293 KT recipients from the Korean Organ Transplant Registry (KOTRY) who received a kidney transplant between 2014 and 2019. Recipients were categorized into three groups based on C0 levels at discharge: <5.9 ng/mL, 5.9–9.5 ng/mL, and >9.5 ng/mL. Clinical outcomes, including serum creatinine (sCr), biopsy-proven acute rejection (BPAR), and infections requiring hospitalization, were analyzed using the Kruskal–Wallis test and chi-squared test. Results: The BPAR rates were 22.5%, 20.9%, and 21.5% for the low, middle, and high C0 groups, respectively (p = 0.221). However, the incidence of infections requiring hospitalization was significantly higher in the high C0 group (28.1%) compared to the middle (23.9%) and low (21.7%) groups at 1-year follow-up (p < 0.001). In high-risk recipients, lower C0 levels correlated with increased BPAR rates (33.9% vs. 29.1% and 26.4%, p = 0.030). Higher intrapatient variability (IPV) between discharge and 6 months was linked to higher infection risk in all recipients and increased BPAR and infection risk in high-risk patients. Conclusions: Optimal C0 levels at discharge are essential to balance rejection and infection risks in KT. Lower C0 levels and higher IPV increase the risk of adverse outcomes, especially in high-risk sensitized recipients, underscoring the need for careful monitoring and personalized management. Full article

mRNA-LNP-based COVID-19 vaccines, namely Pfizer-BioNTech’s Comirnaty and Moderna’s Spikevax, were successfully deployed to help control the SARS-CoV-2 pandemic, and their updated formulations continue to be recommended, albeit only for high-risk populations. One widely discussed aspect of these vaccines is their uniquely broad spectrum and increased incidence of adverse events (AEs), collectively referred to as post-vaccination syndrome (PVS). Although the reported PVS rate is low, the high number of administered doses among healthy individuals has resulted in a substantial number of reported vaccine-related injuries. A prominent manifestation of PVS is multisystem inflammation, hypothesized to result from the systemic transfection of organ cells with genetic instructions for a toxin, the spike protein, delivered with lipid nanoparticles (LNPs). In this narrative review, we focus on endothelial cells in the microcirculatory networks of various organs as primary sites of transfection with mRNA-LNP and consequent PVS. We outline the anatomical variations in the microcirculation contributing to the individual variability of symptoms and examine the molecular and cellular responses to vaccine nanoparticle exposure at the endothelial cell level with a focus on the pathways of a sustained cascade of toxic and autoimmune processes. A deeper understanding of the mechanisms underlying mRNA-LNP-induced AEs and PVS at the organ and cellular levels is critical for improving the safety of future vaccines and other therapeutic applications of this groundbreaking technology. Full article

Tuberculosis remains a serious infectious disease that causes over 1.3 million deaths annually. Following the COVID-19 pandemic, the global incidence of tuberculosis has increased to 10.8 million cases. Pregnant women represent a particularly vulnerable population requiring tailored approaches to the prevention, diagnosis, and treatment of tuberculosis. SARS-CoV-2 infection may have impacted existing clinical protocols. Implementing updated methods of tuberculosis prevention, diagnosis, and treatment in pregnant women could help reduce adverse maternal and fetal outcomes. The aim of this review was to explore potential modifications in tuberculosis management among pregnant women in the post-COVID-19 era, including co-infection with SARS-CoV-2. Methods: A review was conducted, incorporating a systematic literature search across major international databases, including Medline, PubMed, Web of Science, Scopus, and Google Scholar. The search covered publications released between December 2019 and September 2024 and used targeted keywords such as “COVID-19” OR “SARS-CoV-2”, “tuberculosis” OR “TB” OR “latent tuberculosis infection” OR “pulmonary tuberculosis”, and “pregnancy” OR “pregnant women”. Results: Pregnant women living with HIV are at increased risk of developing tuberculosis, which can negatively affect both maternal and perinatal outcomes. Screening for tuberculosis is recommended for all HIV-positive pregnant women, even in the absence of clinical symptoms. Notably, immunological testing before and during pregnancy facilitates the timely and safe detection of tuberculosis infection, enabling preventive and therapeutic interventions during any stage of gestation and the early postpartum period, for the benefit of both mother and child. Drug–drug interactions play a significant role in tuberculosis management, both among anti-tuberculosis agents and with medications for comorbid conditions. Current knowledge of the pharmacokinetics and pharmacodynamics of antituberculosis agents, coupled with therapeutic drug monitoring, supports the development of individualized and effective treatment regimens, which are particularly critical for pregnant patients. Recommendations for managing tuberculosis in pregnant women after COVID-19 infection include measuring D-dimer levels, performing echocardiography, and consulting cardiologists to prevent treatment-related complications. Conclusions: Pregnant women represent a distinct subgroup of tuberculosis patients requiring individualized management. Changes observed in tuberculosis progression and treatment responses in pregnant women before and after SARS-CoV-2 infection should inform therapeutic choices, especially in cases of drug-resistant tuberculosis treated with bedaquiline. COVID-19 has been associated with increased cardiovascular risk, which may heighten the likelihood of adverse drug reactions in this population, especially given the limited therapeutic options. Further research is required to assess the long-term outcomes of latent tuberculosis infection in pregnant women and to evaluate the safety and efficacy of novel regimens for drug-resistant TB during pregnancy. Full article

This study addresses gas drainage challenges in the Pingdingshan NO.10 mine JI_15-16 coal seam through coupled COMSOL-FLAC^3D numerical simulations. The research evaluates the effectiveness of a cross-measure borehole drainage system. It analyzes the failure mechanisms of the surrounding rock in both the machine roadway and floor roadway of the 24130 working face under the influence of boreholes. The results demonstrate that extended drainage duration progressively reduces both gas content and pressure within the borehole-affected zone of the coal seam while enhancing the effective permeability of the JI_15-16 coal stratum. The operational system extracted 1,527,357 m³ of methane, achieving a pre-drainage efficiency of 59.18% through cross-measure boreholes. The measured gas content aligns with simulated predictions, though field-recorded gas pressure registered slightly higher than modeled values. This validated drainage design complies with the Pingmei Group’s regulations for coal and gas outburst prevention. Critically, cross-measure boreholes alter stress distribution around both coal and floor roadways, promoting plastic zone expansion. Consequently, during the development of the 24130 working face’s machine roadway, intensified ground pressure monitoring is essential near borehole locations in the roof, floor, and rib strata. Supplementary support reinforcement should be implemented when required to prevent rib spalling and roof collapse incidents. Full article

The capability to discriminate among nuclear fuel properties is essential for a successful nuclear safeguard and security program. Accurate nuclear material identification is hindered due to challenges such as differing levels of enrichments, weak radiation signals in the case of fresh nuclear fuel, and complex self-shielding effects. This study explores the application of supervised machine learning algorithms to digitized radiation detector data for classifying signatures of special nuclear materials. Three scintillation detectors, an EJ-309 liquid scintillator, a CLYC crystal scintillator, and an EJ-276 plastic scintillator, were used to measure gamma-ray and neutron data from special nuclear material at the National Criticality Experiments Research Center (NCERC) at the National Nuclear Security Site (NNSS), at Nevada, USA. Radiation detector pulse data was extracted from the collected digitized data and applied to three separate supervised learning models: Random Forest, XGBoost, and a feedforward Deep Neural Network, chosen for their wide-spread use and distinct data ingest and processing analytics. Through model refinement, such as adding an additional parameter feature, an accuracy of greater than 95% was achieved. Analysis on model parameter feature importance revealed Countrate, which is the overall gamma-ray and neutron incidents for each detector, was the most influential parameter and essential to include for improved classification. Initial model versions not including the Countrate parameter feature failed to classify. Supervised learning models allow for measured gamma-ray and neutron pulse data to be used to develop effective identification and discrimination between material compositions of different fuel assemblies. The study demonstrated that traditional pulse shape parameters alone were insufficient for discriminating between special nuclear materials; the addition of Countrate markedly improved model accuracy but all models were heavily dependent on this specific feature, thus illustrating the need for alternative, more distinct parameter features. The machine learning development framework captured in this study will be beneficial for future applications in discriminating between different fuel enrichments and additives such as burnable poisons. Full article

Streptococcus pyogenes (Group A Streptococcus, GAS) is a major human pathogen capable of causing infections ranging from mild pharyngitis and impetigo to severe invasive diseases such as bacteremia, necrotizing fasciitis, and streptococcal toxic shock syndrome (STSS). Historically, the incidence of GAS infections declined during the early antibiotic era but began rising again from the early 2000s, driven partly by the emergence of hyper-virulent strains such as emm1 and emm12. From 2005 onward, significant increases in GAS infections were reported globally, accompanied by rising antibiotic resistance, particularly to macrolides and tetracyclines. During the COVID-19 pandemic, widespread public health measures led to a sharp decline in GAS infections, including invasive cases, but this trend reversed dramatically in late 2022 and 2023, with surges exceeding pre-pandemic levels, notably in children. Recent data implicate factors such as “immunity debt,” viral co-infections, and the spread of virulent clones like M1UK. Looking forward, continued surveillance of GAS epidemiology, virulence factors, and resistance patterns is critical. Moreover, the emergence of GAS isolates with reduced susceptibility to beta-lactams underscores the need for vigilance despite the absence of fully resistant strains. The development of an effective vaccine remains an urgent priority to reduce GAS disease burden and prevent severe outcomes. Future research should focus on vaccine development, molecular mechanisms of virulence, and strategies to curb antimicrobial resistance. Full article