Search Results (1,427)

Background: Radiation therapy is an important treatment method for non-small-cell lung cancer (NSCLC). However, predicting patient prognosis remains challenging due to considerable interpatient heterogeneity. The TP53 signaling pathway, implicated in tumor radiosensitivity and treatment outcomes, represents a promising predictive biomarker. Accordingly, in this study, we aimed to identify TP53-signaling pathway-related genes and develop a novel prognostic model for risk stratification for NSCLC patients undergoing radiation therapy. Methods: Publicly available NSCLC transcriptomic datasets were obtained from the GEO and TCGA databases. Utilizing bioinformatics approaches, we identified differentially expressed genes (DEGs) associated with the TP53 signaling pathway. Feature selection was performed using LASSO regression, followed by the construction of a multivariate-Cox-regression-based prognostic prediction model. In vitro validation was performed using a cell viability assay, colony formation, cell cycle analysis, apoptosis detection, γH2AX immunofluorescence staining and comet electrophoresis. In vivo validation was performed utilizing a subcutaneous tumor-bearing mouse model, where radiosensitivity was assessed by monitoring tumor volume post-irradiation. Results: We constructed a robust prognostic prediction model based on five TP53-signaling-pathway-related genes (MDM2, THBS1, TP53I3, ATM, and SESN3), achieving a 5-year AUC of 0.828 in the training set and a 3-year AUC of 0.824 in the validation set. The model exhibited a significant ability to stratify patients into distinct high- and low-risk groups, demonstrating good predictive performance. The poor prognosis observed in the high-risk group was associated with lower infiltration of anti-tumor immune cells but higher infiltration of immunosuppressive cells. Both in vitro and in vivo experiments demonstrated that TP53I3 knockdown significantly enhanced the radiosensitivity of NSCLC through increased DNA damage, cell cycle arrest and apoptosis. Conclusions: In this study, a five-gene signature derived from the TP53 signaling pathway was developed, and the model was shown to effectively predict the prognoses of NSCLC patients undergoing radiotherapy. This signature has the potential to be developed into a clinically applicable tool for personalizing radiotherapy regimens for NSCLC. Full article

The rapid growth of Unmanned Aircraft Systems (UASs) and Advanced Air Mobility (AAM) presents significant integration and safety challenges for the National Airspace System (NAS), often relying on disconnected Air Traffic Management (ATM) and Unmanned Aircraft System Traffic Management (UTM) practices that contribute to airspace incidents. This study evaluates Geographic Information Systems (GISs) as a unified, data-driven framework to enhance shared airspace safety and efficiency. A comprehensive, multi-phase methodology was developed using GIS (specifically Esri ArcGIS Pro) to integrate heterogeneous aviation data, including FAA aeronautical data, Automatic Dependent Surveillance–Broadcast (ADS-B) for crewed aircraft, and UAS Flight Records, necessitating detailed spatial–temporal data preprocessing for harmonization. The effectiveness of this GIS-based approach was demonstrated through a case study analyzing a critical interaction between a University UAS (Da-Jiang Innovations (DJI) M300) and a crewed Piper PA-28-181 near Purdue University Airport (KLAF). The resulting two-dimensional (2D) and three-dimensional (3D) models successfully enabled the visualization, quantitative measurement, and analysis of aircraft trajectories, confirming a minimum separation of approximately 459 feet laterally and 339 feet vertically. The findings confirm that a GIS offers a centralized, scalable platform for collating, analyzing, modeling, and visualizing air traffic operations, directly addressing ATM/UTM integration deficiencies. This GIS framework, especially when combined with advancements in sensor technologies and Artificial Intelligence (AI) for anomaly detection, is critical for modernizing NAS oversight, improving situational awareness, and establishing a foundation for real-time risk prediction and dynamic airspace management. Full article

Pancreatic cancer (PC) remains a highly lethal malignancy with limited treatment options and poor survival. Targeting DNA damage response (DDR) pathways has emerged as a promising therapeutic strategy, particularly the ATR-CHK1 and ATM-CHK2 axes. Preclinical studies demonstrate that ATR inhibition disrupts replication stress tolerance, impairs homologous recombination, and disables checkpoint control, enhancing cytotoxicity from standard therapies including gemcitabine, FOLFIRINOX, fluoropyrimidines, and radiotherapy. Synergistic effects have also been observed with other DDR-targeted agents, such as PARP and WEE1 inhibitors. Genomic contexts, including ATM deficiency, ARID1A alterations, and oncogene-driven replication stress, refine therapeutic sensitivity, supporting precision patient stratification. Early-phase clinical trials of ATR inhibitors (ART0380, AZD6738, BBI-355) alone or in combination show promising safety, tolerability, and preliminary efficacy. In this review, we summarize current literature on targeting the ATM-CHK2 and ATR-CHK1 pathways in PC, highlighting preclinical evidence, clinical developments, and strategies for biomarker-driven, precision oncology approaches. Full article

The article presents the current state of knowledge on genetic modifiers of ovarian cancer risk in women carrying pathogenic variants (PVs) in the BRCA1 and BRCA2 genes, which are major contributors to hereditary susceptibility to this malignancy. Although PV carriers have high disease penetrance (BRCA1: ~40% and BRCA2: 11–27%), substantial variability in individual risk is observed, suggesting the influence of additional genetic variants. Background: Ovarian cancer is characterized by late detection and high mortality, and a significant portion of risk among BRCA1/2 carriers is shaped by reproductive and environmental factors as well as genetic modifiers. The article emphasizes that carriers of the same BRCA PV can exhibit markedly different risk levels depending on additional variants that modulate key biological processes, such as DNA repair, cell cycle regulation, and apoptosis. Methods: A systematic literature search covering the years 1996–2025 was conducted in the PubMed database. Initially, 734 publications were identified; after removing duplicates, thematically irrelevant articles, non-full-text papers, and studies not meeting the inclusion criteria, 47 articles were included in the review. These studies covered candidate gene analyses, GWAS, and data from the CIMBA consortium, which enables the examination of large cohorts of PV carriers. Results: The review identified numerous variants associated with increased or decreased ovarian cancer risk in BRCA1 carriers, including the following: OGG1, DR4, MDM2, CYP2A7, CASP8, ITGB3, HRAS1, TRIM61, and MTHFR. The reviewed studies also identified both protective and risk-increasing variants among BRCA2 PV carriers: UNG, TDG, and PARP2, and haplotypes in ATM, BRIP1, BARD1, MRE11, RAD51, and 9p22.2. The analysis identified 11 variants affecting both BRCA1 and BRCA2 carriers, most of which increase risk, including the following: IRS1, RSPO1, SYNPO2, BABAM1, MRPL34, PLEKHM1, and TIPARP. Protective variants include BNC2 and LINC00824. The only SNP reaching genome-wide significance (p < 5 × 10⁻⁸) was in BNC2. Conclusions: The article summarizes the growing number of genetic modifiers of ovarian cancer risk among BRCA1/2 carriers and highlights their potential to improve individualized risk assessment, enhance patient stratification, support personalized prevention and surveillance strategies, deepen the understanding of disease biology, and identify potential therapeutic targets. Full article

Human–machine teaming (HMT) in air traffic management (ATM) promises safer, more efficient operations by combining human expertise in decision-making with machine efficiency in data processing, where traffic pair crossing identification is crucial for effective conflict detection and resolution by recognizing aircraft pairs that may lead to conflict. To facilitate this goal, this paper presents a four-phase cognitive framework to enhance HMT for monitoring traffic pairs at crossing points through a human-centered, visual-based approach. The visual cognitive framework integrates three data streams—eye-tracking metrics, mouse-over actions, and issued radar commands—to capture the traffic context from the controller’s perspective. A target pair identification method is designed to generate potential conflict pairs. Controller behavior is then modeled using a sighting timeline, yielding insights to develop the cognitive mechanism. Using air traffic crossing-conflict monitoring in en route airspace as a case study, the framework successfully captures the state of controllers’ monitoring and awareness behavior through tests on five target flight pairs under various crossing conditions. Specifically, aware monitoring activities are characterized by higher fixation count on either flight across a 10 min window, with 53% to 100% of visual input activities occurring between 8 to 7 and 3 to 2 min before crossing, ensuring timely conflict management. Furthermore, the study quantifies the effect of crossing geometry, whereby narrow-angle crossings (21 degrees) require significantly higher monitoring intensity (15 paired sightings) compared to wide or moderate angle crossings. These results indicate that controllers exhibit distinct monitoring and awareness behaviors when identifying and managing conflicts across the different test pairs, demonstrating the effectiveness and applicability of the proposed visual cognitive framework. 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

The increasing demand for air travel has intensified the need for more efficient air traffic management (ATM) solutions. One of the key challenges in this domain is the optimal sectorization of airspace to ensure balanced controller workload and operational efficiency. Traditional airspace sectors, typically static and based on historical flow patterns, often fail to adapt to evolving traffic complexity, resulting in imbalanced workload distribution and reduced system performance. This study introduces a novel methodology for optimizing ATC sector geometries based on air traffic complexity indicators, aiming to enhance the balance of operational workload across sectors. The proposed optimization is formulated in the horizontal plane using a two-dimensional cell-based airspace representation. A graph-partitioning optimization model with spatial and operational constraints is applied, along with a refinement step using adjacent-cell pairs to improve geometric coherence. Tested on real data from Madrid North ACC, the model achieved significant complexity balancing while preserving sector shapes in a real-world case study based on a Spanish ACC. This work provides a methodological basis to support static and dynamic airspace design and has the potential to enhance ATC efficiency through data-driven optimization. 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

Background: Optical genome mapping (OGM) detects genome-wide structural variants (SVs), including balanced rearrangements and complex copy-number alterations beyond standard-of-care cytogenomic assays. In chronic lymphocytic leukemia (CLL), cytogenetic and genomic risk stratification is traditionally based on fluorescence in situ hybridization (FISH), karyotyping, targeted next-generation sequencing (NGS), and immunogenetic assessment of immunoglobulin heavy chain variable region (IGHV) somatic hypermutation status, each of which interrogates only a limited aspect of disease biology. Methods: We retrospectively evaluated fifty patients with CLL using OGM and integrated these findings with cytogenomics, targeted NGS, IGHV mutational status, and clinical time-to-first-treatment (TTFT) data. Structural variants were detected using OGM and pathogenic NGS variants were derived from a clinical heme malignancy panel. Clinical outcomes were extracted from the electronic medical record. Results: OGM identified reportable structural variants in 82% (41/50) of cases. The most frequent abnormality was del(13q), observed in 29/50 (58%) and comprising 73% (29/40) of all OGM-detected deletions with pathologic significance. Among these, 12/29 (42%) represented large RB1-spanning deletions, while 17/29 (58%) were focal deletions restricted to the miR15a/miR16-1 minimal region, mapping to the non-coding host gene DLEU2. Co-occurrence of adverse lesions, including deletion 11q/ATM, BIRC3 loss, trisomy 12, and deletion 17p/TP53, were recurrent and strongly associated with shorter TTFT. OGM also uncovered multiple cryptic rearrangements involving chromosomal loci that are not represented in the canonical CLL FISH probe panel, including IGL::CCND1, IGH::BCL2, IGH::BCL11A, IGH::BCL3, and multi-chromosomal copy-number complexity. IGHV data were available in 37/50 (74%) of patients; IGHV-unmutated status frequently co-segregated with OGM-defined high-risk profiles (del(11q), del(17p), trisomy 12 with secondary hits, and complex genomes whereas mutated IGHV predominated in OGM-negative or structurally simple del(13q) cases and aligned with indolent TTFT. Integration of OGM with NGS further improved genomic risk classification, particularly in cases with discordant or inconclusive routine testing. Conclusions: OGM provides a comprehensive, genome-wide view of structural variation in CLL, resolving deletion architecture, identifying cryptic translocations, and defining complex multi-hit genomic profiles that tracked closely with clinical behavior. Combining OGM and NGS analysis refined risk stratification beyond standard FISH panels and supports more precise, individualized management strategies in CLL. Prospective studies are warranted to evaluate the clinical utility of OGM-guided genomic profiling in contemporary treatment paradigms. Full article

The development of functional polymer films on porous paper substrates is inherently constrained by substrate-induced defects that hinder film continuity and barrier performance. In this study, process-controlled amylose–Poly(Vinyl alcohol) (PVA) coatings incorporating ZnO nanoparticles (ZnO NPs) were fabricated via aqueous deposition to investigate the process-structure-property relationship governing oxygen barrier behavior on paper. The moisture resistance of the coating was also evaluated. Single-layer coatings exhibited severe barrier failure due to insufficient film formation and pervasive pinhole defects. In contrast, systematic multi-layer deposition enabled the formation of continuous polymer films. A pronounced non-linear reduction in oxygen transmission rate was observed once the dry coating thickness exceeded approximately 5 µm. Under these conditions, the oxygen transmission rate decreased to approximately 15 cc/m²·day·atm at 20 °C and 65% relative humidity. This transition was correlated with the elimination of substrate-induced defects, as confirmed by morphological analysis. In addition to enhanced barrier performance, ZnO NP-loaded coatings demonstrated strong and broad-spectrum antimicrobial activity against both Escherichia coli and Staphylococcus aureus, indicating their multifunctional potential for active packaging applications. Supporting evaluations further indicated adequate mechanical flexibility and high repulpability, highlighting the suitability of the coating for sustainable paper-based packaging. Overall, this work identifies a quantitative critical film thickness that serves as process-specific design guideline for engineering high-performance functional polymer coatings on porous paper substrates. Full article

DNA double-strand breaks (DSBs) can be induced by cellular byproducts or genotoxic agents. Improper processing of these lesions leads to increased genome instability, which constitutes a hallmark of pathological conditions and fuels carcinogenesis. DSBs are primarily repaired by homologous recombination (HR) and non-homologous end joining (NHEJ) and the proper balance between these two pathways is finely modulated by specific molecular events. Here, we report that the histone chaperone DAXX plays a fundamental role in the response to DSBs. Indeed, in human cells, DSBs induce ATM/ATR-dependent phosphorylation of DAXX on serine 424 and 712 and promote its binding to chromatin and the deposition of the histone variant H3.3 in proximity to DNA breaks. Enrichment of H3.3 at DSBs promotes 53BP1 recruitment to these lesions and the repair of DNA breaks by HR pathways. Moreover, H3.3-specific post translational modifications, particularly K36 tri-methylation, play a key role in these processes. Altogether, these findings indicate that DAXX and H3.3 mutations may contribute to tumorigenesis-enhancing genome instability. Full article

Desmoplastic small round cell tumor (DSRCT) is a rare but aggressive soft tissue sarcoma of the abdomen. With an asymptomatic course and rapid dissemination, DSRCT’s prognosis is poor at diagnosis. This study characterizes the demographic variation and genomic profile of DSRCT to guide studies into diagnosis and treatment. The AACR GENIE database was utilized to identify genetic alterations in DSRCT. Data was queried to identify disease prevalence by different demographic variables. Information was collected on frequency of somatic mutations and copy number alterations, rates of mutation co-occurrence, and mutations seen in primary and metastatic samples. ARID1A, TP53, ATM, TERT, and FGFR4 were the most frequently identified somatic mutations. Copy number alterations seen in DSRCT were commonly homozygous deletions in tumor suppressor genes. Independent of sex, WT1 mutations were most common. Non-White patients saw single occurrences of many mutations but recurrent ones in ANKRD11 and KMT2C. Co-occurrence was found between FGFR4 and EP300. Moreover, primary tumor samples had exclusive mutations in AKAP9, KDM2B, MAGED1, MKI67, PCLO, and TRAF1. Metastatic samples had exclusive mutations in FIP1L1 and NRIP1. Our data highlights mutational variation across demographic cohorts. These patterns are vital to future studies into identifying diagnostic markers or therapeutic targets. Full article

Ammonia (NH₃) is a zero-carbon fuel and an attractive hydrogen (H₂) carrier for gas turbine power generation due to its high energy density, ease of storage, and transportation. This study numerically investigates NH₃/air combustion using a hybrid Well-Stirred Reactor (WSR) and Plug Flow Reactor (PFR) model in Cantera at pressures of 1–20 atm, temperatures of 1850–2150 K, and equivalence ratios (ϕ) of 0.7–1.2. The effects of pressure, equivalence ratio, and temperature on NH₃ conversion and NO formation are examined. Results show that NH₃ exhibits a non-monotonic conversion curve with pressure after the WSR, reaching a minimum near 5 atm, whereas NO formation decreases monotonically from 1 to 20 atm. Equivalence ratio sweeps show that NO decreases steeply as ϕ increases from 0.7 to ~1.1 as nitrogen is redirected toward N₂ and oxidizer availability declines; residual NH₃ increases rapidly for ϕ > 1.0, especially at high pressure. Increasing temperature accelerates NH₃ oxidation and raises NO formation, most strongly at low pressure where thermal and NH/OH pathways are least inhibited. These results indicate that co-tuning pressure and equivalence ratio near rich operation enables low-NO_x ammonia combustion suitable for advanced gas turbine applications. Full article

Interannual climate changes and increasing atmospheric CO₂ (AtmCO₂) have significantly altered sea surface partial pressure of CO₂ (pCO₂) in the Beaufort Sea (BS). Yet, their decadal variability and underlying mechanisms remain inadequately understood. Using observational data and the Regional Arctic System Model (RASM), a decreasing trend transition of the BS summer surface pCO₂ was identified at around 2010–2012. Sensitivity cases reveal that the decadal trend transition in surface pCO₂ (early: 4.12 ± 0.80 μatm/yr, p < 0.05 and late: 1.23 ± 2.22 μatm/yr, p > 0.05) is driven by interannual climate changes. While the long-term increase in AtmCO₂ does not directly drive surface pCO₂ trend transition, it reduces its magnitude. The sensitivity experiment with no interannual AtmCO₂ changes from 1990 reveals that the statistically significant contributor of the decadal trend transition in surface pCO₂ is the concurrent transition in sea ice concentration (SIC, early: −0.0120 ± 0.0037/yr, p < 0.05 and late: 0.0101 ± 0.0063/yr, p > 0.05). The decadal trend transitions in the subsurface and deep layer pCO₂ are negligible compared to that in the sea surface pCO₂ due to the insignificant influence of interannual climate changes on subsurface and deep layer pCO₂. The surface pCO₂ decadal trend transition is significantly correlated with a trend transition of CO₂ sink. On seasonal timescales, the effects of SIC on the decadal trend transition of pCO₂ occur primarily within the duration of open-water (DOW), and align with the decadal trend transitions in the open-water start day, end day, and DOW. The magnitude of sea surface pCO₂ trend transition increases as the magnitude of the DOW trend transition increases. Full article

Background: In nuclear medicine, numerous cancer types are treated via internal irradiation with radiopharmaceuticals, including low-LET (linear energy transfer) beta-emitting radionuclides like Lu-177. In most cases, such treatments lead to low-dose exposure of organ systems with β-irradiation, which induces only few isolated DSBs (double-strand breaks) in the nuclei of hit cells, the most threatening DNA damage type. That damaging effect contrasts with the clustering of DNA damage and DSBs in nuclei traversed by high-LET particles (α particles, ions, etc.). Methods: After in-solution β-irradiation for 1 h with Lu-177 leading to an absorbed dose of about 100 mGy, we investigated the spatial nano-organization of chromatin at DSB damage sites, of repair proteins and of heterochromatin marks via single-molecule localization microscopy (SMLM) in PBMCs. For evaluation, mathematical approaches were used (Ripley distance frequency statistics, DBScan clustering, persistent homology and similarity measurements). Results: We analyzed, at the nanoscale, the distribution of the DNA damage response (DDR) proteins γH2AX, 53BP1, MRE11 and pATM in the chromatin regions surrounding a DSB. Furthermore, local changes in spatial H3K9me3 heterochromatin organization were analyzed relative to γH2AX distribution. SMLM measurements of the different fluorescent molecule tags revealed characteristic clustering of the DDR markers around one or two damage foci per PBMC cell nucleus. Ripley distance histograms suggested the concentration of MRE11 molecules inside γH2AX-clusters, while 53BP1 was present throughout the entire γH2AX clusters. Persistent homology comparisons for 53BP1, MRE11 and γH2AX by Jaccard index calculation revealed significant topological similarities for each of these markers. Since the heterochromatin organization of cell nuclei determines the identity of cell nuclei and correlates to genome activity, it also influences DNA repair. Therefore, the histone H3 tri methyl mark H3K9me3 was analyzed for its topology. In contrast to typical results obtained through photon irradiation, where γH2AX and H3K9me3 markers were well separated, the results obtained here also showed a close spatial proximity (“co-localization”) in many cases (minimum distance of markers = marker size), even with the strictest co-localization distance threshold (20 nm) for γH2AX and H3K9me3. The data support the results from the literature where only one DSB induced by low-dose low LET irradiation (<100 mGy) can remain without heterochromatin relaxation for subsequent repair. Full article