Search Results (3,493)

Background/Objectives: Triple-negative breast cancer (TNBC) is frequently characterized by notably elevated Ki-67 expression, a hallmark of uncontrolled rapid cell-cycle progression. However, the underlying mechanisms remain unclear, leading to limited therapeutic options. Methods: In this study, hub gene was identified through integrated bioinformatic analysis of public datasets (TCGA-BRCA and METABRIC). Subsequent functional validation was performed both in vitro and in vivo using siRNA-mediated knockdown and small-molecule inhibitors. Phenotypic effects—including cell viability, cell cycle distribution, DNA synthesis, and clonogenic survival—were comprehensively assessed using MTT assays, flow cytometry, EdU, and colony formation assays. Protein-level changes were confirmed by Western blotting and immunohistochemistry (IHC). To dissect the transcriptional regulation of the key hub gene TTK, we first predicted potential upstream transcription factors using the JASPAR database; binding specificity was then validated through in silico motif analysis, luciferase reporter assays, and chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR). Results: The mitotic kinase TTK is significantly overexpressed in TNBC compared with non-TNBC breast cancers. Notably, TTK overexpression exhibited a strong positive correlation with elevated Ki-67 indices and reduced overall survival in TNBC patients. Functional validation demonstrated that pharmacological or genetic inhibition of TTK effectively induced G2/M cell-cycle arrest and potently suppressed TNBC proliferation in both in vitro cell cultures and in vivo xenograft models. Mechanistically, TTK overexpression stems from enhanced transcriptional initiation driven by the transcription factor NFYA binding to the CCAAT box in the TTK promoter—an interaction newly identified here. Concurrently, TTK blockade disrupted spindle assembly checkpoint (SAC) signaling via BUB1B/MAD1L1 downregulation, triggering mitotic arrest and catastrophe. Conclusions: Collectively, these findings establish TTK as a key cell-cycle regulator driving TNBC proliferation. More importantly, targeting mitotic control through TTK inhibition represents an efficient strategy to impede the aberrantly fast cell cycle progression in TNBC. Full article

Transarterial chemoembolization (TACE) is the standard treatment for patients with intermediate-stage hepatocellular carcinoma (HCC), yet nearly half of treated patients fail to achieve durable benefit, and reliable biomarkers enabling early therapeutic stratification are still lacking. Treatment response is typically assessed by imaging one month after TACE and at three-month intervals, potentially delaying timely access to alternative therapies in non-responding patients. Circulating microRNAs (miRNAs) represent promising biomarkers due to their stability in body fluids and ease of detection. Here, we evaluated circulating miR-22 as an early predictor of TACE non-responder status and as a mechanistically relevant therapeutic target. Circulating miR-22 levels were measured by microarray and quantitative RT–PCR in three independent cohorts of early-to-intermediate-stage HCC patients undergoing TACE. Circulating miR-22 increased significantly in non-responders as early as 48 h after treatment, and fold changes consistently predicted treatment failure across two independent validation cohorts. Mechanistically, we identified the G2/M checkpoint kinase WEE1 as a direct functional target of miR-22. Modulation of the miR-22/WEE1 axis affected cell-cycle progression, proliferation, apoptosis, and DNA damage response in HCC cell lines and xenograft models. Under hypoxia-mimicking conditions combined with doxorubicin exposure, pharmacological inhibition of WEE1 induced mitotic catastrophe in highly proliferative miR-22-silenced cells. Collectively, these findings identify early post-TACE elevation of circulating miR-22 as a biomarker of non-response and highlight the miR-22/WEE1 axis as a potential target for precision treatment strategies in HCC. Full article

Uninterrupted traffic flow monitoring is a prerequisite for optimal resource allocation and minimizing vehicular emissions in smart cities. However, centralized traffic management architectures are highly vulnerable to single points of failure. When structural sensor malfunctions occur, the resulting network unobservability paralyzes dynamic signalization, triggering cascading traffic congestion, extended idling times, and severe greenhouse gas emissions. To address this cyber-ecological vulnerability, we propose the Hybrid Multi-Agent State Estimation (H-MASE) protocol, a fully decentralized decision-support framework designed from an applied systems reliability engineering perspective. By deploying PSAs and VLAs directly onto IoT-enabled edge devices at smart intersections, H-MASE leverages a hop-by-hop edge computing topology to collaboratively track macroscopic route flow dynamics. Mathematically, this distributed estimation process is formulated as a network-wide least-squares convex optimization problem, where local projection operators function as exact Distributed Gradient Descent steps to minimize the global residual sum of squares. The distributed consensus mechanism acts as a spatial variance reduction tool, effectively dampening measurement noise and stochastic demand fluctuations. Furthermore, we introduce an autonomous anomaly detection logic that isolates severe structural faults rapidly, which is mathematically structured to prevent false alarms under bounded disturbance conditions. Numerical simulations demonstrate that the protocol yields a highly resilient optimality gap (e.g., a Root Mean Square Error of merely 0.81 vehicles per estimated state) even under catastrophic hardware failures. Ultimately, H-MASE provides a robust, fail-safe data foundation for sustainable urban logistics and green-wave signalization, ensuring that smart cities maintain ecological resilience and optimal resource utilization under severe structural disruptions. Full article

Aqueous redox flow batteries (ARFBs) are a promising solution for large-scale energy storage; however, the development of organic posolytes that combine high redox potential with long-term stability remains a significant hurdle. This study introduces sodium 3-(10H-phenoxazin-10-yl)propane-1-sulfonate (POZS), a novel sulfonate-functionalized phenoxazine derivative designed to overcome these limitations. By incorporating hydrophilic anionic sulfonic groups, this molecular engineering strategy enhances the structural stability of redox-active phenoxazine materials. Although POZS shows limited solubility in pure water, its solubility increases to 0.98 M (equivalent to a charge capacity of 26.3 Ah L⁻¹) upon the addition of 1.5 M tetraethylammonium chloride (TEAC). This enhancement suggests that the supporting electrolyte optimizes the ionic environment and mitigates intermolecular aggregation, thereby facilitating higher active species concentration. Electrochemical characterization of POZS reveals a highly positive redox potential of 1.51 V (vs. Zn/Zn²⁺) and rapid electron transfer kinetics (2.02 × 10⁻² cm s⁻¹). When tested in a zinc-based hybrid flow cell, the POZS posolyte demonstrates excellent rate capability (up to 50 mA cm⁻²) and a temporal capacity fade rate of 0.335% per hour over 500 cycles—a nearly five-fold improvement over previously reported quaternized phenoxazines. Post-cycling analyses indicate that while the phenoxazine core remains susceptible to nucleophilic ring substitution, the pendant sulfonate groups ensure that any resulting byproducts remain soluble, preventing the catastrophic depletion typically caused by the precipitation of degraded active species. These findings establish a robust molecular framework for the design of high-potential, durable organic posolytes for sustainable energy storage systems. Full article

The earthquake of 23 June 2001, Mw 8.4, caused catastrophic damage in the city of Moquegua (Peru), especially in reinforced-concrete educational buildings. In this research, advanced procedures have been used and compared to assess the seismic performance of a new educational building designed under the current Peruvian construction regulations. Two nonlinear static procedures, the capacity spectrum method and an improved procedure based on the equivalent linearization method, have been applied and compared. Damage probabilities for a 475-year-return-period earthquake for the city of Moquegua evidence that the improved procedure based on the equivalent linearization method turns out to be slightly more conservative than the capacity spectrum method. Incremental dynamic analyses, based on 15 seismic events selected according to specific criteria, are taken as reference and complete the building damage assessment. Probabilistic damage matrices are proposed to assess damage using a probabilistic approach, which makes it possible to determine the levels of risk to be assumed in likely post-seismic scenarios and to carry out probabilistic estimates of the impacted population, the expected damage to structures, and the ranges of economic (social and material) costs. These tools assist stakeholders, civil protection and fire departments and the administrations involved in risk management and contingency planning in developing prevention strategies and improving preparedness for natural disasters such as earthquakes. Full article

Background and Clinical Significance: Mechanical complications and intracavitary thrombus are both recognized causes of clinical deterioration following acute myocardial infarction, yet they require fundamentally different therapeutic approaches. Distinguishing between these entities is critical, as misdiagnosis may lead to unnecessary surgical intervention or delayed anticoagulation with serious consequences. Left ventricular (LV) thrombus typically appears as a well-defined mass; however, atypical and highly mobile morphologies may closely mimic catastrophic post-infarction mechanical complications, creating significant diagnostic uncertainty. This case highlights the pivotal role of contrast-enhanced echocardiography in resolving such ambiguity and guiding appropriate management in a high-stakes clinical setting. Case Presentation: A 60-year-old man presented with acute dyspnea and pulmonary edema ten days after an anterior myocardial infarction treated with percutaneous coronary intervention, complicated by ischemic stroke. Transthoracic echocardiography demonstrated severe LV systolic dysfunction with moderate-to-severe mitral regurgitation and an unexpected, highly mobile, irregular mass protruding into the LV apex. The mass exhibited a shredded, tissue-like appearance, raising urgent concern for post-infarction mechanical complications, including papillary muscle rupture or apical myocardial disruption, and prompting immediate consideration of surgical intervention. Contrast-enhanced echocardiography was performed and revealed a mobile LV apical thrombus. Surgical management was avoided, and systemic anticoagulation was initiated, followed by transition to rivaroxaban in combination with ongoing dual antiplatelet therapy. The patient demonstrated rapid clinical improvement with optimized heart failure treatment and was discharged after four days, with planned follow-up imaging to assess thrombus resolution. Conclusions: Left ventricular thrombus may present with atypical, misleading morphologies that closely resemble life-threatening mechanical complications after myocardial infarction. Full article

In industrial environments, robust Temporal Action Localization (TAL) is essential; however, frequent occlusions often compromise the reliability of skeletal data, leading to negative transfer in multimodal fusion. To address this challenge, we propose a Gated Skeleton Refinement Module (Gated SRM), a universal front-end preprocessing module that explicitly incorporates OpenPose confidence scores into the network architecture. By applying these scores as a logarithmic bias within a self-attention mechanism, our method achieves soft suppression—dynamically attenuating the attention weights assigned to unreliable joints—before adaptively fusing the refined skeletal features with RGB representations through a learnable gating network. Extensive experiments on the heavily occluded IKEA ASM dataset demonstrate that our approach effectively prevents the catastrophic accuracy degradation typical of naive and established multimodal fusion strategies, improving the mean Average Precision (mAP) to 21.77%, maintaining parity with the RGB-only baseline while demonstrating superior robustness. Furthermore, the system maintains a practical end-to-end inference speed of approximately 9.2 frames per second (FPS), which is sufficient for monitoring macro-level industrial workflows. By prioritizing confidence-based data selection over data restoration, this sensor-metadata-driven architecture offers a robust and principled approach acting as a critical fail-safe and safety-net for real-world action recognition under occlusion. Full article

Monitoring oil pipelines is crucial for effective infrastructure management and maintenance, as it helps prevent threats such as vandalism and leaks that can lead to catastrophic events. Pipeline leaks pose significant environmental and economic risks; however, existing detection methods are often expensive, slow, or unreliable, limiting their effectiveness for real-time applications. This study proposes a lightweight thermal-imaging-based intelligent leak detection system that integrates Convolutional Neural Networks (CNN), Autoencoder (AE), and Knowledge Distillation (KD), suitable for deployment on edge devices. The proposed system addresses challenges associated with existing pipeline detection techniques, including large model sizes, high transmission latency, and excessive energy consumption. Thermal images of pipelines are captured and compressed using an autoencoder before being processed by a CNN model optimized through knowledge distillation. The model was trained and tested on a locally collected thermal image dataset and designed for deployment on edge devices such as Raspberry Pi to simulate edge computing scenarios. Experimental results demonstrate that the proposed CNN + KD + AE model achieved 98% accuracy, 98% precision, 98% recall, and an F1-score of 98%, outperforming baseline models such as MobileNetV2 (91%), InceptionV3 (84%), EfficientNet-Lite (81%), and ResNet (74%). Furthermore, the number of trainable parameters was significantly reduced to 1.18 million, with a compact model size of 4.51 MB. These findings confirm the system’s suitability for real-time leak detection in remote and resource-constrained environments, contributing to the development of cost-effective, scalable, and energy-efficient solutions for intelligent pipeline monitoring. Full article

This article examines how ancient Greek tragedy mobilizes landscape to reflect on the limits of civic order and the conditions of human dwelling. Rather than treating mountains, groves, meadows, and borderlands as neutral settings or as simple “nature/culture” oppositions, it argues that tragic landscapes are ethically charged spaces where human norms meet forces that exceed political regulation—divine presence, necessity, vulnerability, and finitude. Written for the polis yet unsettled by what lies beyond it, tragedy repeatedly turns to extra-civic spaces to test civic stability. Three case studies develop the argument. In Hippolytus, woodland and meadow sustain an ideal of purity grounded in withdrawal, an orientation incompatible with social life and culminating in catastrophic isolation. In Bacchae, Pentheus’ project of spatial control collapses as Dionysian forces traverse walls and institutions with ease, exposing the limits of civic rationality. In Oedipus Tyrannus and Oedipus at Colonus, the tragic trajectory moves from Mount Cithaeron, a site of abandonment and opaque necessity, to the sacred grove at Colonus, where prolonged suffering enables a transformed relation to place, law, and divine power. Taken together, these plays suggest that the polis is never fully self-sufficient: civic order endures only through engagement with what it cannot master or expel, and spatial orientation is inseparable from ethical choice. Full article

Background: An aortic disease diagnosis can be perceived by patients as a stressful and often life-altering event. In addition, an acute event, such as aortic rupture or dissection—and the surgical intervention that will be required to address it—can be viewed as potentially life-threatening and traumatic. Serious health conditions, including stroke and acute coronary syndromes, have been described in the literature to correlate with trauma-like symptoms. Post-traumatic stress disorder (PTSD) is well described in connection with external traumatic events, such as war, assault and similarly catastrophic events. A key element of this type of PTSD is that its occurrence arises secondary to an external traumatizer. However, recent work has suggested that internal events—such as a catastrophic medical event (e.g., acute cardiovascular event and/or surgery)—can trigger PTSD symptoms. An important question is whether medical event-initiated PTSD can (or should) be treated similarly to traditionally defined PTSD, when the triggering threat may persist rather than having been confined to a past event. This systematic review will summarize the literature on the occurrence of PTSD as a consequence of an acute cardiovascular event and attempt to identify effective treatments using meta-analysis, if the literature quantity and quality support it. Methods: The search strategy will include publicly available electronic databases, including MEDLINE via PubMed and OVID, EMBASE via Elsevier, Cumulative Index for Nursing and Allied Health Literature (CINAHL) via EBSCOhost, SCOPUS, PsychInfo, and the Cochrane Library, to identify publications that report the development and/or treatment of PTSD as a consequence of an acute cardiovascular event, which include cardiac arrest, acute coronary syndromes, and acute aortic syndromes. Identification of publications, article classification, methodological review/quality assessment, and data extraction will be performed by two trained experts in cardiovascular epidemiology, with the resolution of disagreements carried out by a third independent reviewer. The review conduct and meta-analysis will follow PRISMA and MOOSE guidelines. Data will be aggregated using random effects models when quantitative data are reliable and heterogeneity is reasonable. If a quantitative synthesis is not possible due to data quality, a narrative synthesis will be conducted. Statistical heterogeneity will be assessed by I² statistics. The quality of evidence will be assessed using the GRADE criteria. Ethics and Dissemination: This study did not require an institutional review board or human subjects protection committee approval given the nature of the study design. The results will be published in a peer-reviewed journal, along with recommendations for future research. Full article

Automated pavement distress classification using high-resolution Unmanned Aerial Vehicle (UAV) imagery is pivotal for intelligent transportation systems. However, long-term UAV monitoring faces a continuous stream of evolving distress types and changing remote sensing background textures, necessitating Class-Incremental Learning (CIL) capabilities. Existing methods struggle to balance stability and plasticity, especially under the severe storage limitations typical of local edge stations in air–ground collaborative systems. This data scarcity leads to catastrophic forgetting and confusion among fine-grained distress categories. To address these challenges, we propose a data-efficient approach named Analytic Geometric Alignment (AGA). Our framework mainly consists of three key components. First, to overcome the optimization gap between the feature extractor and the fixed geometric target, we introduce a Subspace-Aware Analytic Initialization (SAI) that computes a closed-form projection to instantly align the feature subspace with the ETF manifold before each task training. Second, on this aligned basis, a Decoupled Geometric Adapter (DGA) is incorporated to facilitate continuous non-linear adaptation to complex aerial textures. Finally, for stable incremental training, we design a Memory-Prioritized Regression (MPR) loss to enforce tighter geometric constraints on replay samples, significantly enhancing model stability. Extensive experiments on the UAV-PDD2023 dataset demonstrate that AGA significantly outperforms state-of-the-art methods, showcasing excellent robustness and data efficiency. Full article

Industrial predictive maintenance programs often rely on SCADA historian signals characterized by low-frequency sampling and asynchronous reporting intervals. These data constraints, specifically non-uniform scan rates and inter-tag time misalignment, limit the applicability of high-resolution or sensor-intensive prognostic models. This study proposes a lightweight, physics-informed health proxy, the temperature-weighted work (TWW) index, designed to monitor motor stator-winding degradation within these industrial limitations. The TWW index accumulates mechanical work derived from torque and speed measurements, weighted by an adaptive exponential temperature-emphasis function that penalizes operation at elevated temperatures. The formulation is inspired by practical thermal-aging heuristics such as Montsinger’s rule in the qualitative sense that higher temperatures are treated as disproportionately more damaging, but it is not intended as a direct implementation of a fixed absolute-temperature life law. Instead, it is designed as a lightweight adaptive index suitable for online SCADA-based implementation. To address SCADA-specific irregularities, the framework incorporates data synchronization and resampling techniques to align heterogeneous tags, alongside power-thresholding to isolate degradation-relevant load periods. The resulting cumulative index is mapped to a normalized health/RUL proxy using failure-referenced thresholds identified from historical events. Validation using field data from industrial three-phase motors demonstrates that the TWW index provides a monotonic degradation profile that is consistent with documented winding-related failures and proactive removals. Case studies confirm that the model enabled proactive maintenance interventions by signaling the terminal phase of insulation life before catastrophic breakdown, offering a hardware-free and scalable solution for real-time asset management. Full article

Remote sensing enables the analysis of landscape dynamics; however, catastrophic disturbances create new surface conditions that are not adequately captured by retrospectively defined land-cover classes. This study addresses the challenge of temporally matching unsupervised classifications to monitor post-catastrophic floodplain dynamics on Khortytsia Island following the destruction of the Kakhovka Reservoir. Multi-temporal Sentinel-2 Level-2A data from 2022 to 2025 were processed using spectral indices, standardised within a common predictor space, and classified through unsupervised clustering. Cluster solutions from individual dates were then matched based on spectral similarity and spatial continuity, with their temporal interpretation guided by concepts of landscape memory and landscape perception. Higher-order spatiotemporal units were subsequently derived through contextual superclustering. The analysis identified 16 clusters across the study period, with 4 to 12 clusters represented on individual dates. Their temporal coordination enabled the distinction of higher-order units exhibiting contrasting dynamics, including directional trend, seasonal, and mixed types. The proposed framework facilitates the identification of newly formed surface states, their temporal coordination, and their integration into a hierarchical spatiotemporal model of post-catastrophic landscape change. Full article

Oil spills along the northeast coast of Brazil have the potential to cause catastrophic contamination of coastal environments and their associated biota. Beyond the direct contamination processes occurring on beaches, oil can also be transported inland by tides through estuaries. In addition, wind-driven transport of oil was observed in nearly all sections studied along the coast. Therefore, this study evaluated the potential of wind to transport oil fragments inland using both direct and indirect methods, including field observations and GIS-based mapping tools. The results identified and quantified oil fragmentation processes and wind-driven transport over relatively large distances (hundreds of meters). The presence of exhumed beachrock, combined with the absence or low elevation of foredunes and the high potential for wind transport, plays a crucial role in trapping oil on the beach surface. These factors further facilitate the fragmentation and inland dispersal of oil particles, allowing them to penetrate deeper into the coastal environment. The findings underscore the importance of assessing the contamination risks posed by oil fragments as they become incorporated into aeolian and other interconnected inland systems. Full article

Background and Objectives: Visceral artery aneurysms (VAAs) are rare but potentially catastrophic vascular abnormalities, particularly in pregnant patients or women of childbearing age. Rupture is often fatal for both mother and fetus, with mortality rates exceeding 70% in some series. While most VAAs are found incidentally, a subset may present acutely with nonspecific abdominal or flank pain, making early recognition and appropriate referral essential. This review article aims to provide General Practitioners (GPs) and emergency department (ED) clinicians with a practical approach to the recognition, investigation, initial management, and escalation pathways for VAAs. Results: Physiological and hormonal adaptations in pregnancy heighten aneurysm rupture risk. Despite this, imaging is frequently delayed. Computed tomography angiography (CTA) remains the gold standard for diagnosis and is safe in pregnancy when clinically justified, with fetal radiation exposure well below teratogenic thresholds. Guidelines from major vascular societies uniformly recommend repairing VAAs in pregnancy or women planning pregnancy irrespective of aneurysm size, and treating pseudoaneurysms urgently in all patients. Endovascular intervention is first-line where anatomy permits, while open or hybrid approaches remain essential in unstable presentations. The manuscript outlines practical steps for ED and GP settings, including haemodynamic stabilization, early obstetric involvement, transfer considerations for rural environments, reproductive counselling, and post-repair surveillance. Conclusions: With an increasing number of abdominal scans being performed in primary and tertiary settings, there is an associated increased volume of incidental findings that require work-up. This article outlines a practical investigation and management strategy for clinicians presented with VAAs, including in high-risk cohorts, emphasizing early imaging, inter-specialty coordination, and guideline-supported thresholds for intervention. Full article