Search Results (378)

Background/Objectives: Acute coronary syndromes (ACS) encompass a spectrum of clinical entities from unstable angina to non–ST-segment elevation myocardial infarction (NSTEMI) and ST-segment elevation myocardial infarction (STEMI), all associated with significant morbidity and mortality. Inflammation plays a central role in the pathophysiology of ACS, contributing to atherosclerotic plaque destabilization, myocardial injury, and adverse clinical outcomes. Inflammatory biomarkers, together with N-terminal pro–B-type natriuretic peptide (NT-proBNP), are increasingly used for risk stratification, yet their prognostic value across different ACS presentations remains unclear. This study aimed to assess the prognostic value of inflammatory status in patients with acute coronary syndromes in a single-center cohort. Methods: This prospective observational study included 100 consecutive patients with ACS and elevated inflammatory biomarkers, enrolled in 2024–2025 at a tertiary cardiovascular center. Inflammatory status was assessed by using C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII); NT-proBNP was also measured. The primary endpoint was in-hospital MACE, defined as cardiovascular death, recurrent myocardial infarction, stroke, urgent coronary revascularization, or acute heart failure requiring escalation of therapy. Multivariable logistic regression and ROC analyses were performed. Results: Among the 100 ACS patients, half experienced in-hospital MACE. Compared with those without events, patients with MACE were older (p = 0.003) and had higher inflammatory biomarkers—CRP (p < 0.001; strongest association), NLR (p = 0.030), and SII (p = 0.042)—as well as higher NT-proBNP (p = 0.002). Patients with MACE also showed reduced renal function (p < 0.001) and lower left ventricular systolic function, reflected by reduced LVEF (p = 0.001), indicating concomitant renal impairment and ventricular dysfunction. Hypertension was more prevalent in the MACE group (p = 0.028), and new-onset atrial fibrillation was significantly more common among these patients (p < 0.001). In multivariable analysis, LVEF emerged as an independent predictor of short-term outcomes (OR 0.934 per 1% increase; p = 0.047). Conclusions: Inflammatory activation appears closely linked to the occurrence of in-hospital adverse events in patients with acute coronary syndromes. While left ventricular ejection fraction remained an independent determinant of short-term outcomes, inflammatory biomarkers may provide complementary insight into the inflammatory burden accompanying ACS. Full article

To address the issues of corn harvester field operations relying on driver visual guidance for row alignment, high labor intensity, and unstable operation accuracy, this study innovatively proposes a “vision-dominant, gateway-enhanced” dual-mode collaborative row-alignment assistance architecture, and independently develops the R²DC-Mask R-CNN instance segmentation network and MCC-KF robust filtering algorithm to form a deeply coupled hardware–software-assisted driving system. The R²DC-Mask R-CNN network is autonomously designed for corn row-detection scenarios, achieving accurate perception in complex field environments; the MCC-KF algorithm innovatively solves the state estimation divergence problem during transient vision failures through a multi-criteria constraint mechanism, ensuring continuous navigation capability; the intelligent gateway and vision system form a confidence-driven master–slave switching mechanism that adaptively enhances system robustness when vision is restricted. Field experiments demonstrate that within the speed range of 0.5–5.0 km/h, the average lateral deviation in the row alignment assisted by the system is 3.82–5.30 cm, the proportion of deviations less than 10 cm exceeds 96%, and all sample deviations remain within 20 cm; at a speed of 3.5 km/h, the system reduces the average grain loss rate from 3.76% under manual operation to 2.65%, a decrease of 29.5%. This system effectively improves row alignment accuracy and harvest quality, providing a practical human–machine collaborative solution for intelligent harvester operations. Full article

Intracranial atherosclerosis (ICAS) is a distinct, inflammation-dominant vasculopathy and a leading cause of global stroke morbidity. Unlike extracranial atherosclerosis (ECAS), which often utilizes compensatory positive remodeling to maintain patency, ICAS is characterized by a unique architecture and a localized antioxidant gap that favor maladaptive negative remodeling. We critically analyze the molecular cascade initiated by the breakdown of the Piezo-type mechanosensitive ion channel component 1 (PIEZO1) and the Krüppel-like factor 2/4 (KLF2/4) mechanotransduction axis, which triggers endothelial nitric oxide synthase (eNOS) uncoupling and establishes a state of chronic inflammation. This environment facilitates the subendothelial lipid retention of oxidized low-density lipoprotein (oxLDL), a process exacerbated by the intracranial deficiency of Apolipoprotein A-I (ApoA-I) and impaired glymphatic clearance. Crucially, we evaluate how these metabolic and mechanical insults drive vascular smooth muscle cell (VSMC) phenotypic switching; the transdifferentiation of contractile VSMCs into macrophage-like foam cells accounts for up to 60% of the plaque’s lipid-laden pool and destabilizes the fibrous cap. This vascular failure directly compromises the neurovascular unit (NVU), leading to pericyte dropout and blood–brain barrier breakdown. Beyond environmental stressors, we highlight the ring finger protein 213 (RNF213) variant as a critical genetic determinant of this susceptibility. Shifting the clinical paradigm from simple luminal narrowing toward the identification of the vulnerable plaque, we discuss how High-Resolution Vessel Wall Imaging (HR-VWI) and microRNA biomarkers can identify unstable lesions. By integrating these molecular and imaging signatures, we propose a precision medicine framework centered on the NLR family pyrin domain containing 3 (NLRP3) inflammasome and the NVU to effectively mitigate the high residual recurrence risk that persists under conventional therapy. Full article

The Tuzla Submarine Landslide represents one of the most significant mass-wasting features associated with the active North Anatolian Fault Zone (NAFZ). The failure surface geometry and sediment stratigraphy indicate the presence of a mechanically weak, saturated layer that may become unstable under strong seismic loading. This study presents a comprehensive geotechnical evaluation of the Tuzla Submarine Landslide. Based on regional sediment properties, the landslide was characterized and modeled with an estimated volume of 0.015 km³ and an average slope angle of 14°. The submarine landslide potential was investigated through re-analysis of seismic, geotechnical, and bathymetric datasets. Finite Element Method (FEM) simulations were conducted to model the seismic slope failure. Based on these analyses, the seismic slope displacements, stress distributions, and equivalent plastic strains were identified. The estimated landslide displacements under varying seismic acceleration scenarios corresponding to three major earthquakes ranged between 2.38 m and 4.12 m, depending on the triggering ground motion and slope stability conditions. These findings highlight that reactivation of the Tuzla submarine landslide, potentially triggered by a future large earthquake along the NAFZ, could pose a moderate landslide hazard to the coastal settlements bordering the Marmara Sea. Full article

Background: Syndesmotic screw breakage is a well-recognized mechanical complication following ankle fracture fixation. Although several studies have investigated patient-related and technical factors associated with screw breakage, the temporal pattern of screw failure and implant survival remains less clearly defined. Therefore, this study aimed to evaluate one-year syndesmotic screw survival using time-to-event analysis and to identify factors associated with screw breakage. Materials and Methods: A total of 132 patients with unstable AO-Weber 44-B/C ankle fractures treated with syndesmotic screw fixation were retrospectively analyzed. Patients were followed for a minimum of 12 months or until screw breakage occurred. Screw survival was evaluated using Kaplan–Meier analysis and Cox proportional hazards regression was performed to identify factors associated with screw breakage. Demographic variables, fracture type, and screw-related parameters were analyzed. Receiver operating characteristic (ROC) analysis was used to assess the discriminative ability of age. Results: Screw breakage occurred in 31 patients (23.5%) during follow-up. Kaplan–Meier analysis demonstrated significantly lower screw survival in Weber C fractures compared with Weber B fractures (log-rank p < 0.001). Cox regression analysis identified younger age (HR: 0.965, 95% CI: 0.937–0.993, p = 0.016) and Weber C fracture type (HR: 1.811, 95% CI: 1.260–2.602, p = 0.001) as independent predictors of screw breakage. ROC analysis showed that age had moderate discriminative ability (AUC: 0.719, 95% CI: 0.612–0.816), with a cut-off value of 35.5 years. Conclusions: Younger age and Weber C fracture type are associated with an increased risk of syndesmotic screw breakage and Weber C fractures also demonstrating reduced screw survival. These findings may assist in patient counseling; however, the clinical implications of screw breakage remain uncertain. Full article

Background and Aims: Severe alcohol-associated hepatitis (SAH) can trigger unstable decompensations in cirrhosis patients. They experience high rates of emergency department visits and hospitalization. We evaluated real-world clinical outcomes following palliative-faecal microbiota transplantation (pFMT) compared to best supportive care (BSC) in this critically ill population. Patients and Methods: From July 2021 to April 2024, 28 patients on pFMT were compared with 37 on BSC. Patients on pFMT received nasoduodenal healthy donor stool infusion daily for 5-days. Patients were followed up for portal hypertension-related events, infections, hospitalizations, extrahepatic organ failure and 6- and 12-months survival. 16S rRNA sequencing on stool samples collected at baseline and on follow up were analysed for changes in relative abundance (RA) of bacterial communities. Results: Patients were matched for age, type of decompensation and liver disease severity at enrolment. Twelve-month survival was 64.3% in pFMT versus 51.4% in BSC groups. pFMT dramatically reduced hospital readmissions (mean 0.76 ± 0.76 vs. 2.29 ± 1.27, p < 0.001). Unstable decompensations beyond 3 months occurred in 14.3% of pFMT versus 64.9% of BSC (p < 0.001). Organ failures were lesser with pFMT: acute kidney injury 7.7% versus 93.8% (p < 0.001), hepatic encephalopathy 7.1% versus 68.2% (p < 0.001). Infection burden was significantly lower (53.6% vs. 83.8%, p = 0.008), particularly infections requiring admission (17.4% vs. 66.7%, p < 0.001) with pFMT. Microbiome analysis revealed progressive expansion of Gram-negative genera in BSC, and beneficial Actinobacteria in pFMT-treated patients at 3, 6, and 12 months. Conclusions: Palliative FMT represents a unique disease-modifying intervention in end-stage alcohol-related cirrhosis, preventing organ failure progression, reducing healthcare utilization, and improving survival trajectories. Full article

Background and Objectives: To provide a systematic narrative review of published literature on atypical hangman’s fractures focusing on pathophysiology, treatment options and clinical outcomes. Materials and Methods: A systematic review was performed according to PRISMA guidelines. MEDLINE (PubMed), EMBASE, Scopus, and Cochrane Library were searched until March 2025. Studies reporting outcomes of atypical hangman’s fractures treated conservatively or surgically were included. Data on demographics, mechanism of injury, treatment modality, outcomes, and complications were extracted and analyzed. Results: Thirteen studies with a total of 275 patients were included. The average age was 54.36 years. High-energy trauma was the predominant mechanism of injury. Conservative treatment was performed in 210 patients, with 204 (97.14%) achieving fusion and 6 (2.86%) converted to surgical treatment. Surgical fixation was performed in 71 patients, most commonly via a posterior approach. Failure of surgical treatment occurred in 5 patients, all treated with isolated anterior fusion. Neurologic injury was reported in 21 patients (7.63%), with full recovery in 14 (66%). Conclusions: Atypical hangman’s fractures represent a distinct subgroup of C2 fractures with diverse morphology and stability. Most fractures are stable and may be managed conservatively. Surgical fixation should be reserved for unstable patterns. If surgery is pursued, posterior fixation is recommended. Outcomes are generally favorable for both conservative and surgical treatment. Full article

Generative AI systems increasingly mediate how students retrieve literature and generate citations, shifting methodological rigor toward the maintenance of an auditable evidence trail. This study audits the search stage of AI-assisted literature review work, focusing on retrieval performance and citation traceability rather than downstream screening or synthesis. Four widely accessible tools were compared across two retrieval postures, and Boolean queries were executed against Scopus and evaluated against a DOI-verified librarian baseline built from Scopus, Web of Science, and Google Scholar. Using a canonical prompt and a bounded top-k capture rule (k = 20), each bibliographic record was evaluated for DOI traceability, DOI resolution integrity, metadata accuracy, and run-to-run drift. Records were screened through staged title/abstract and full-text eligibility review, and the final set included 37 studies after quality appraisal was 37 studies. Across sixteen audit runs, natural-language prompting frequently produced under-target yields, recurrent integrity failures, and low overlap with the librarian benchmark. Boolean translation improved run completion and increased the proportion of auditable records, but reproducibility remained unstable across repeated runs. These findings show that correctness at the record level does not ensure stability at the evidence-set level. Limitations include the bounded tool set, the search-stage focus, and the absence of downstream screening or synthesis evaluation. Retrieval posture, therefore, emerges as a practical governance lever for AI-assisted literature review workflows and supports the use of a student-facing verification checklist anchored in DOI verification and transparent protocol capture. This research received no external funding. OSF registration: Open Science Framework, 10.17605/OSF.IO/U8NHT. The manuscript reports the final included set as n = 37, states no external funding, and lists the OSF registration DOI. Full article

Classic machine learning and regime identification methods applied to financial time series lack theoretical guarantees and exhibit systematic failure modes: heavy-tails invalidate moment-based geometry, rendering distances and centroids dominated by extremes or unstable; jumps violate smoothness, destabilizing local regressions, kernel methods, and gradient-based learning; and non-stationarity disrupts neighborhood relations, so distances in classical feature spaces no longer reflect meaningful proximity. To address these challenges, we propose a topology-based machine-learning framework grounded on probabilistic reconstruction of state-space geometry, which replaces moment- and smoothness-dependent representations with deformation-stable summaries of state-space geometry, preserving neighborhoods, adjacency, and topology. The finite-sample validity of homeomorphic state-space reconstruction, required for topology-based machine learning, is assessed through numerical studies on synthetic data with heavy tails, jumps, and known ground-truth regimes. Further diagnostics of local invertibility and bounded geometric distortion quantify when embedding windows are consistent with local diffeomorphic behavior, enabling metric-sensitive, geometry-aware learning. Clustering of Hilbert-space summaries accurately recovers underlying market tail-risk regimes with robust results across selected filtrations. Temporal, feature-space, and cluster-label null tests confirm that topology-based clustering captures genuine topological structure rather than noise or artifacts, and encodes temporal dependencies at local, mesoscopic, and network levels associated with market regimes. Full article

Maritime UAV perception must reliably detect and track tiny vessels under harsh specular glare. In practice, detection failures are dominated by two coupled factors: (i) vessels often occupy only a few pixels, causing small-object recall collapse and (ii) sun glint and sea-surface reflections generate over-exposed regions that trigger false positives and unstable associations. This paper presents Resi-YOLO, a system-level pipeline that improves tiny-vessel sensitivity while preserving embedded throughput on a Jetson Orin Nano. At the model level, Resi-YOLO combines a P2-enhanced feature path with CBAM-based glare suppression to strengthen high-resolution semantics and suppress glare-induced artifacts; optional SAHI-style slicing is supported for ultra-high-resolution scenes. At the system level, we adopt a heterogeneous dual-brain deployment, where the Orin Nano performs primary inference and an MCU-based safety-island tracker mitigates delay/jitter via time-stamped measurement replay and IMM-UKF updates. We further define a Glare Severity Score (GSS) to stratify robustness by illumination intensity. Experiments show that Resi-YOLO improves AP_small by 13.1 percentage points over YOLOv8n (18.4% to 31.5%), raises high-glare mAP@0.5 from 41.2% to 53.7%, and runs at 12.8 FPS end-to-end (~100 ms latency) on Jetson Orin Nano, while TensorRT inference-only throughput exceeds 30 FPS. Full article

Electrochemical biosensors integrated into wearable devices have revolutionized the technology in terms of health monitoring and diagnostic systems. However, when it comes to moving the devices from the laboratory to real-world environments, a critical problem emerges with the interface. The problem, in essence, is that biorecognition elements tend to lose their activity, delaminate, and drift when exposed to various environmental stresses. The traditional methods for the immobilization of the biorecognition elements result in receptors with random orientations, hydrolytically unstable bonds, and batch-to-batch variability, regardless of the method, including physisorption or non-selective covalent attachment, like using EDC/NHS. This review is organized around a comparative question: which limitations of classical immobilization strategies (physisorption, self-assembled monolayers used as passive anchoring platforms, and EDC/NHS coupling) can be resolved by click chemistry, which can be resolved by mechanistic features? Accordingly, CuAAC, SPAAC, IEDDA, and thiol-ene/yne photoclick reactions are discussed, not as an isolated catalog of ligations, but as complementary solutions to specific interfacial failure modes, including random bioreceptor orientation, hydrolytically vulnerable attachment, poor batch reproducibility, catalyst sensitivity, and the difficulty of functionalizing soft polymeric or textile substrates. In this framework, click chemistry is treated as a deterministic interface-engineering strategy that enables defined covalent fixation, programmable probe density, and improved mechanical and electrochemical robustness under wearable operating conditions. Full article

To address the challenges faced by heterogeneous Unmanned Aerial Vehicle (UAV) systems in complex task allocation, including over-reliance on centralized scheduling, training deadlock, inadequate capture of temporal collaboration, and unstable training under sparse reward conditions, this paper proposes a distributed task allocation algorithm based on reinforcement learning. The algorithm adopts a decentralized decision-making architecture, which enables the autonomous formation of UAV collaborative groups without the need for a global scheduling center. A cascaded submission timeout mechanism is introduced to prevent training deadlock; the combination of Long Short-Term Memory (LSTM) and attention mechanism is employed to accurately model temporal correlations and collaborative dependencies; and the Proximal Policy Optimization (PPO) algorithm is leveraged to optimize the training stability under sparse reward conditions. Experimental results demonstrate that the proposed algorithm achieves a 100% task success rate in scenarios of different scales, and its key metrics, including makespan, time cost and waiting time, are significantly superior to those of mainstream baseline methods such as the Genetic Algorithm (GA) and the Hungarian Algorithm (HA). Moreover, the algorithm still maintains excellent robustness under the conditions of UAV failures, parameter variations, and dynamic task perturbations. This method supports zero-shot generalization for any number of UAVs and tasks and provides an efficient and reliable solution for the real-time collaborative scheduling of heterogeneous UAV systems. Full article

Climate hazards increasingly disrupt schooling, revealing the limits of preparedness models that treat teachers only as implementers. This study reframes teacher empowerment as a climate-resilience capability and examines how governance arrangements enable (or constrain) hazard-ready education systems. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR), searches of Web of Science, Scopus, and Google Scholar (2000–2025) identified 53 eligible studies. Across diverse hazards and settings, the evidence converges on a governance-to-capability pathway: empowerment becomes resilient performance only when the delegated decision space is matched with financed capacity (time, training, contingency resources), timely risk information and functional communication/digital infrastructure, institutionalized cross-sector coordination (education–DRR–health–protection–local government), and learning-oriented accountability (after-action review and adaptive revision rather than punitive compliance). Reported outcomes include higher preparedness quality, earlier protective action, improved learning continuity and safeguarding, and more sustainable teacher well-being/retention. Predictable failure modes include mandate–resource mismatch, accountability overload, unstable centralization–autonomy dynamics, and inequitable empowerment distribution affecting rural schools, women, and contract teachers, and disability inclusion. The evidence gaps remain pronounced for chronic hazards (especially heat and wildfire smoke), high-vulnerability contexts (fragile/conflict settings and informal settlements), and standardized measures of equity, burden distribution, governance performance, and cost-effectiveness. Policies should prioritize integrated governance packages with explicit protection and equity safeguards. Full article

For the failure issue of the weak part of the safety end of the nuclear power pressure vessel connection, the J-integral method was used to test the fracture toughness of the weak part at the bottom of the dissimilar metal welded joints (DMWJs) of SA508-III and 316L in the temperature range of 25 °C to 320 °C, and the mechanism of temperature-induced crack instability and propagation was studied. The research results indicate that at all test temperatures, the position of the weld near the 316L steel is the failure site of the welded joint. The fracture toughness of the joint decreases with increasing temperature, with a maximum decrease of 42.0%. Analysis shows that as the temperature increases, the dislocation density decreases, the tensile strength decreases, and the yield strength ratio decreases, making it easier for secondary cracks to initiate near the crack tip, thereby accelerating the unstable propagation of cracks. At the same time, as the temperature increases, the number of twin crystals that can promote crack turning and prolong the crack propagation path decreases, the energy absorbed before fracture decreases, and the fracture toughness value decreases accordingly, further accelerating the unstable propagation of cracks. Full article