Search Results (115)

Aortic diseases, including thoracic and abdominal aneurysms as well as aortic dissections, represent life-threatening vascular disorders characterized by progressive wall degeneration and inflammation. Increasing evidence indicates that oxidative stress is a central driver of aortic pathology through the induction of DNA damage in vascular smooth muscle cells and endothelial cells. Oxidative DNA lesions activate the DNA damage response (DDR), a highly coordinated network of damage sensors, signaling kinases, and repair effectors that determines cell fate decisions such as DNA repair, apoptosis, or cellular senescence. In aortic tissue, persistent or dysregulated DDR signaling contributes to chronic inflammation, extracellular matrix degradation, and loss of vascular integrity. Key molecular regulators, including base excision repair enzymes OGG1 and APE1, as well as DDR mediators such as ATM, ATR, p53, PARP, and NOTCH1, integrate oxidative stress signals with pro-inflammatory and pro-degenerative pathways. Aberrant activation of these mechanisms promotes vascular smooth muscle cell VSMC phenotypic switching from contractile to synthetic phenotype, endothelial dysfunction, and senescence-associated secretory responses, thereby accelerating aortic wall weakening and aneurysm progression. This review highlights the mechanistic links between oxidative stress-induced DNA damage, DDR pathway activation, and vascular remodeling in aortopathies. A deeper understanding of these molecular interactions may uncover novel biomarkers and therapeutic targets aimed at limiting inflammation, preserving genomic stability, and preventing catastrophic aortic events. This work represents a narrative review and therefore has inherent limitations in terms of systematic literature search and selection. Full article

The increasing demand for continuous and reliable air traffic surveillance over remote and oceanic regions has prompted the exploration of innovative solutions beyond traditional radar and satellite-based systems. In this context, High-Altitude Pseudo-Satellites (HAPSs) have emerged as a promising technology capable of extending surveillance and communication coverage within the stratosphere at significantly lower cost and greater operational flexibility. This paper presents the results of Research and Development (R&D) efforts focused on the conceptualization and development of a HAPS prototype serving as a proof of concept to enhance Air Traffic Management (ATM) surveillance capabilities. The study quantitatively examines the HAPS operational environment by classifying and evaluating the geometric, physical, environmental, thermal and atmospheric factors influencing prototype performance. The developed prototype establishes a scalable foundation for future multi-platform HAPS networks, and forthcoming research will focus on experimental validation under real-world conditions and performance optimization to enable integration into next-generation ATM systems. Full article

A group of experts of different specialties involved in the care of prostate cancer (PCa) patients participated in the ENFOCA2 project, promoted by the Spanish Oncology Genitourinary Group (SOGUG), with the aim to review, discuss, and summarize current relevant aspects related to screening, diagnosis, imaging, risk-based approach, and molecular characterization of PCa. A multidisciplinary team (MDT) approach is essential to ensure that patients receive evidence-based care, promoting shared decision-making, and tailoring treatment to the patient’s unique values and preferences. Population-based screening based on risk-stratified algorithms is needed to overcome the limitations of opportunistic screening for detecting clinically significant PCa. Next-generation imaging (NGI) methods, such as prostate-specific membrane antigen (PSMA) PET/CT alone or combined with multiparametric MRI (mpMRI), have a promising role in different scenarios of the diagnostic process due to their high sensitivity. The diagnostic yield of mpMRI should be improved, especially for assessing extraprostatic extension. The use of specific molecular probes as imaging markers for MRI could improve the staging of metastatic disease. Protocols for germline testing developed by international societies, such as the European Association of Urology (EAU) and the National Comprehensive Cancer Network (NCCN), should be adapted at local levels, with BRCA1/2, ATM, PALB2, CHEK2, MLH1, MSH2, MSH6, PMS2, EPCAM, and HOXB13 as the genes to be investigated. Genomic classifier tools help identifying aggressiveness of cancers and aid in personalized treatment decision-making. Joint efforts of multidisciplinary physicians are crucial to improve health outcomes for patients with PCa across the spectrum of this disease. Full article

UAV-based object detection faces critical challenges including extreme scale variations (targets occupy 0.1–2% image area), bird’s-eye view complexities, and all-weather operational demands. Single RGB sensors degrade under poor illumination while infrared sensors lack spatial details. We propose ATM-Net, a lightweight multimodal RGB–infrared fusion network for robust UAV vehicle detection. ATM-Net integrates three innovations: (1) Asymmetric Recurrent Fusion Module (ARFM) performs “extraction→fusion→separation” cycles across pyramid levels, balancing cross-modal collaboration and modality independence. (2) Tri-Dimensional Attention (TDA) recalibrates features through orthogonal Channel-Width, Height-Channel, and Height-Width branches, enabling comprehensive multi-dimensional feature enhancement. (3) Multi-scale Adaptive Feature Pyramid Network (MAFPN) constructs enhanced representations via bidirectional flow and multi-path aggregation. Experiments on VEDAI and DroneVehicle datasets demonstrate superior performance—92.4% mAP50 and 64.7% mAP50-95 on VEDAI, 83.7% mAP on DroneVehicle—with only 4.83M parameters. ATM-Net achieves optimal accuracy–efficiency balance for resource-constrained UAV edge platforms. Full article

One of the key functions of Air Traffic Management (ATM) is to balance airspace capacity and demand. Despite measures that are taken during the strategic and pre-tactical phases of flight, demand–capacity imbalances still occur in flight, often manifesting as localised regions of high traffic complexity, known as hotspots. These hotspots emerge dynamically, leaving air traffic controllers with limited anticipation time and increased workload. This paper proposes a Machine Learning (ML) framework for the prediction and resolution of hotspots in congested en-route airspace up to an hour in advance. For hotspot prediction, the proposed framework integrates trajectory prediction, spatial clustering, and complexity assessment. The novelty lies in shifting complexity assessment from a sector-level perspective to the level of individual hotspots, whose complexity is quantified using a set of normalised, sector-relative metrics derived from historical data. For hotspot resolution, a Reinforcement Learning (RL) approach, based on Proximal Policy Optimisation (PPO) and a novel neural network architecture, is employed to act on airborne flights. Three single-clearance type agents—a speed agent, a flight-level agent, and a direct routing agent—and a multi-clearance type agent are trained and evaluated on thousands of historical hotspot scenarios. Results demonstrate the suitability of the proposed framework and show that hotspots are strongly seasonal and mainly occur along traffic routes. Furthermore, it is shown that RL agent performance tends to degrade with hotspot complexity in terms of certain performance metrics but remains the same, or even improves, in terms of others. The multi-clearance type agent solves the highest percentage of hotspots; however, the FL agent achieves the best overall performance. Full article

This study presents a computational tool for analyzing gas mixtures resulting from the integration of biomethane and hydrogen into natural gas networks. It calculates key properties, such as relative density, higher heating value and Wobbe index, based on composition, temperature and pressure, using the van der Waals equation to model real gas behavior. The tool also offers interactive 3D visualizations to explore how these properties vary under different conditions. With prediction errors below 0.5% at 20 atm, it provides a reliable basis for assessing technical feasibility, regulatory compliance and energy efficiency in the integration of alternative gases into existing networks. Full article

The synthesis and electrocatalytic properties of amorphous first- and third-row transition metal sulfides (a-TMS) for green hydrogen generation have been comprehensively reviewed. These electrocatalysts can be prepared by several solution processes, including chemical bath deposition, electrodeposition, sol–gel, hydrothermal reaction and thermolysis. The deposition method strongly influences the electrochemical properties of the synthesized a-TMS electrocatalyst. Based on overpotential at 10 mA/cm², the electrocatalytic activity of mono-metallic a-TMS for hydrogen evolution is ranked as follows: a-NiS_x > a-CuS_x > a-CoS_x > a-WS_x > a-FeS_x. The best performing a-NiS_x prepared by chemical bath deposition has an overpotential at 10 mA/cm² of 53 mV and Tafel slope of 68 mV/dec in 1 M KOH electrolyte. The integration of Ni into the a-TMS network structure is crucial to achieving high activity in multi-metallic a-TMS electrocatalyst, as demonstrated by the bifunctional (NiFe)S_x/NiFe(OH)_y nanocomposite catalyst. The critical role of Ni in a-TMS catalyst design can be attributed to the lower free energy change for hydrogen adsorption on Ni. Finally, the emerging catalyst design strategy of amorphous–crystalline heterostructures with a three-dimensional morphology will be discussed together with the need to identify hydrogen adsorption sites on a-TMS electrocatalysts in future. Full article

Background: Non-small cell lung cancer (NSCLC) progression is driven by dysregulated competing endogenous RNA (ceRNA) networks, where non-coding RNAs sequester miRNAs to modulate oncogene expression. The tumor-suppressor miR-145 is frequently downregulated in NSCLC, but its lncRNA-mediated regulation remains incompletely characterized. Methods: Integrated transcriptomic analysis of NSCLC datasets (GSE135304: blood RNA from 712 patients; GSE203510: plasma miRNAs) was used to identify dysregulated genes (|log2FC| > 0.1, p < 0.05) and miRNAs (|log2FC| > 1, p < 0.05). Experimentally validated targets from miRTarBase/TarBase were intersected with dysregulated genes, followed by WikiPathways/GO enrichment. ceRNA networks were constructed via co-expression analysis. RT-qPCR validated miR-145-3p expression in A549/MRC-5 cells and NSCLC tissues. GEPIA assessed FN1/CCND1 clinical relevance. Results: We identified 8271 dysregulated genes and 52 miRNAs. miR-145-3p, critical in immune regulation, was significantly downregulated (log2FC = −1.24, p = 0.036). Intersection analysis revealed 27 miR-145-3p targets (e.g., FN1, CCND1, SMAD3) enriched in immune pathways (FDR < 0.05) and TGF-β-mediated EMT within the dysregulated geneset. Six immune-linked hub genes emerged. LncRNAs LOC729919 and LOC100134412 showed strong co-expression with hub genes and competitively bind miR-145-3p, derepressing the expression of the metastasis drivers FN1 (ECM regulator) and CCND1 (cell cycle controller). This ceRNA axis operates within a broader dysregulation of ATM-dependent DNA damage, Hippo signaling, and cell cycle pathways. RT-qPCR confirmed significant miR-145-3p suppression in NSCLC models (p < 0.05). GEPIA revealed a significant FN1-CCND1 co-expression (p = 0.0017). Conclusions: We characterize a novel LOC729919/LOC100134412–miR-145–FN1/CCND1 ceRNA axis in NSCLC pathogenesis. FN1’s prognostic value and functional linkage to CCND1 underscores its potential clinical relevance for therapeutic disruption. Full article

Atmospheric aerosols are known to alter the Earth’s radiative balance and influence climate. However, accurately quantifying the magnitude of aerosol-induced radiative forcing remains challenging. We characterize optical properties of biomass-burning (BB) and non-biomass-burning (NB) aerosols and quantify BB aerosol radiative forcing at two AERONET (AErosol RObotic NETwork) sites in Huancayo (Peru) and La Paz (Bolivia) during 2015–2021. From AERONET data, we derive aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), and asymmetry parameter (ASY). We then employ the SBDART model to calculate aerosol radiative forcing (ARF) on monthly and multiannual timescales. BB aerosols peak in September (AOD: 0.230 at Huancayo; 0.235 at La Paz), while NB aerosols reach maxima in September at Huancayo (0.109) and November at La Paz (0.104). AE values exceeding unity for BB aerosols indicate fine-mode dominance. Huancayo exhibited the highest BB ARF in November: +16.4 W m⁻² at the top of the atmosphere (TOA), –18.6 W m⁻² at the surface (BOA), and +35.1 W m⁻² within the atmospheric column (ATM). This was driven by elevated AOD and high scattering efficiency. At La Paz, where SSA data was only available for September, BBARF values were also significant (+15.16 at TOA, –17.52 at BOA, and +32.73 W m⁻² within the ATM). This result underscores the importance of quantifying the ARF, particularly over South America where data is scarce. Full article

Background and Aims: Triple-negative breast cancer (TNBC) is a clinically aggressive malignancy marked by rapid disease progression, limited therapeutic avenues, and high recurrence risk. Ferroptosis an iron-dependent, lipid peroxidation-driven form of regulated cell death that has emerged as a promising therapeutic vulnerability in oncology. This study delineates the ferroptosis-associated molecular architecture of TNBC to identify key regulatory genes with prognostic and translational significance. Methods: Transcriptomic profiles from the GSE103091 dataset (130 TNBC and 30 normal breast tissue samples) were analyzed to identify ferroptosis-related differentially expressed genes (DEGs) using GEO2R. Protein–protein interaction (PPI) networks were constructed via STRING and GeneMANIA, with functional enrichment performed through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome analyses. Prognostic relevance was evaluated using GEPIA, BC-GenExMiner, and Kaplan–Meier Plotter survival analyses. Results: Six ferroptosis drivers (MAPK1, TLR4, IFNG, ATM, ULK2, and ATF3) and five suppressors (NFS1, GCLC, TP63, CD44, and SRC) were identified alongside HMOX1, a bifunctional regulator with context-dependent pro- and anti-ferroptotic activity. Enrichment analyses revealed significant associations with oxidative stress regulation, autophagy, immune modulation, and tumor progression pathways. Elevated IFNG expression was consistently linked to improve overall, disease-free, and distant metastasis-free survival, underscoring its dual function in antitumor immunity and ferroptosis sensitization. Conclusions: Ferroptosis represents a critical axis in TNBC pathophysiology, with IFNG emerging as both a prognostic biomarker and a viable therapeutic target. These insights provide a mechanistic foundation for integrating ferroptosis-inducing agents with immunotherapeutic modalities to enhance clinical outcomes and overcome therapeutic resistance in TNBC. Full article

Gastric cancer remains a significant global health challenge, with regional and demographic disparities in incidence, mortality, and treatment outcomes. Despite advances in screening and early detection, prognosis remains poor for many patients, particularly those with advanced disease. Recent insights into DNA damage response pathways have uncovered critical molecular vulnerabilities in gastric tumors, including frequent TP53 mutations, ARID1A loss, ATM deficiency, and oncogene-driven replication stress, which render these cancers highly dependent on the ATR–CHK1 axis for survival. This review synthesizes current clinical and preclinical evidence on ATR and CHK1 inhibitors as therapeutic strategies in gastric cancer. Emphasis is placed on synthetic lethality, immune modulation, and the potential for combination regimens with chemotherapy, radiotherapy, or immune checkpoint blockade. Mechanisms of resistance, including transcription-associated replication stress modulation and bypass signaling networks, are discussed, alongside strategies to predict and overcome therapeutic failure. The review also highlights the importance of biomarker-guided patient selection, adaptive dosing to reduce toxicity, and refined pharmacodynamic monitoring to enhance therapeutic precision. Collectively, these insights support the rational integration of ATR–CHK1 inhibitors into clinical protocols for biomarker-defined gastric cancer subsets and underscore their promise Full article

Long noncoding RNAs (lncRNAs), non-protein-coding transcripts exceeding 200 nucleotides, are critical regulators of gene expression through chromatin remodeling, transcriptional modulation, and post-transcriptional modifications. While ionizing radiation (IR) induces cellular damage through direct DNA breaks, reactive oxygen species (ROS)-mediated oxidative stress, and bystander effects, the functional involvement of lncRNAs in the radiation response remains incompletely characterized. Here, through genome-wide CRISPR activation (CRISPRa) screening in non-small cell lung cancer (NSCLC) cells, we identified LOC401312 as a novel radiosensitizing lncRNA, the stable overexpression of which significantly enhanced IR sensitivity. Transcriptomic profiling revealed that LOC401312 transcriptionally upregulates carbamoyl-phosphate synthase 1 (CPS1), a mitochondrial enzyme involved in pyrimidine biosynthesis. Notably, CPS1 overexpression recapitulated the radiosensitization phenotype observed with LOC401312 activation. Mechanistic investigations revealed that CPS1 suppresses the phosphorylation of ATM kinase (Ser1981) protein, which is a key mediator of DNA damage checkpoint activation. This study established the LOC401312–CPS1–ATM axis as a previously unrecognized regulatory network governing radiation sensitivity, highlighting the potential of lncRNA-directed metabolic rewiring to impair DNA repair fidelity. Our findings not only expand the functional landscape of lncRNAs in DNA damage response but also provide a therapeutic rationale for targeting the LOC401312–CPS1 axis to improve radiotherapy efficacy in NSCLC. Full article

The impact of alternative distribution channels, such as bank Automated Teller Machines (ATMs), on the financial industry is growing due to technological advancements. Investing in ideal locations is critical for new ATM companies. Due to the many factors to be evaluated, this study addresses the problem of determining the best location for ATMs to be deployed in Istanbul districts by utilizing the multi-criteria decision-making framework. Furthermore, the advantages of fuzzy logic are used to convert expert opinions into mathematical expressions and incorporate them into decision-making processes. For the first time in the literature, a model has been proposed for ATM location selection, integrating clustering and the interval-valued Fermatean fuzzy analytic hierarchy process (IVFF-AHP). With the proposed methodology, the districts of Istanbul are first clustered to find the risky ones. Then, the most suitable alternative location in this district is determined using IVFF-AHP. After deciding the ATM locations with IVFF-AHP, in the last step, a Double Deep Q-Network Reinforcement Learning model is used to optimize the Cash in Transit (CIT) vehicle route. The study results reveal that the proposed approach provides stable, efficient, and adaptive routing for real-world CIT operations. Full article

Eliciting DNA damage in tumor cells continues to be one of the most successful strategies against cancer. This is the case for classical chemotherapy drugs and radiotherapy. In the modern era of personalized medicine, this strategy tries to identify specific vulnerabilities found in each patient’s tumor, to inflict DNA damage in certain cell contexts that end up in massive cancer cell death. Cells rely on multiple DNA repair pathways to fix DNA damage, but cancer cells frequently exhibit defects in these pathways, many times being tolerant to the damage. Key vulnerabilities, such as BRCA1/BRCA2 mutations, have been exploited with PARP inhibitors, leveraging synthetic lethality to selectively kill tumor cells and improving patients’ survival. In the DNA damage response (DDR) network, kinases ATM, ATR, Chk1, and Chk2 coordinate DNA repair, cell cycle arrest, and apoptosis. Inhibiting these proteins enhances tumor sensitivity to DNA-damaging therapies, especially in DDR-deficient cancers. Several small-molecule inhibitors targeting ATM/Chk2 or ATR/Chk1 are currently being tested in preclinical and/or clinical settings, showing promise in cancer models and patients. Additionally, pharmacological blockade of ATM/Chk2 and ATR/Chk1 axes enhances the effects of immunotherapy by increasing tumor immunogenicity, promoting T-cell infiltration and activating immune responses. Combining ATM/Chk2- or ATR/Chk1-targeting drugs with conventional chemotherapy, radiotherapy or immune checkpoint inhibitors offers a compelling strategy to improve treatment efficacy, overcome resistance, and enhance patients’ survival in modern oncology. Full article

Background/Objectives: DNA damage response (DDR) is a highly conserved and complex signal transduction network required for preserving genome integrity. DNA repair pathways downstream of DDR include the tyrosyl-DNA phosphodiesterase1 (TDP1) enzyme that hydrolyses the phosphodiester bond between the tyrosine residue of topoisomerase I (TopI) and 3′-phosphate end of DNA. A small TDP1 subfamily, composed of TDP1α and TDP1β, is present in plants. The aim of this work was to investigate the role of the two TDP1 genes in the DDR context. Methods: A series of Arabidopsis thaliana DDR single and double mutants defective in the sog1, e2fb, pol2A, atm, and atr genes, treated with the genotoxic agents camptothecin (CPT, inhibitor of TopI) and NSC120686 (NSC, inhibitor of TDP1), were used. These compounds were specifically used due to their known impact on the TDP1 function. The effect of the treatments was assessed via phenotypic analyses that included germination percentage, speed, and seedling growth. Subsequently, the expression of the TDP1α and TDP1β genes was monitored through qRT-PCR. Results: Overall, the gathered data indicate that the atm mutant was highly sensitive to NSC120686, both phenotypically and concerning the TDP1α gene expression profiles. Alternatively, the upregulation of TDP1β in e2fb, pol2a, and atr supports its implication in the replication stress response. Conclusions: The current study demonstrates that genotoxic stress induced by CPT and NSC has a genotype-dependent effect reflected by a differential expression of TDP1 genes and early phenotypic development. Full article