Search Results (1,511)

Family conflict is a relational process that may shape adolescent aggression through disruptions to emotional security, reinforcement of coercive interactions, and the development of aggressive scripts and beliefs. Because adolescents are also exposed to violence in community and media contexts, these broader ecological experiences may independently contribute to aggression or alter the influence of family conflict. We analyzed two waves of data collected six months apart from 345 U.S. middle school students and examined whether exposure to family conflict was associated with an increase in adolescent aggression, and whether this association was stronger than effects of community and media violence exposure. We also examined interactive effects to test if violence exposure in community and media contexts operates independently or interacts with family conflict to alter its effect on adolescent aggression. Family conflict and community violence exposure independently predicted later aggression after accounting for baseline aggression. Family conflict made the largest relative contribution among the three contextual predictors. A significant interaction between family conflict and media violence exposure indicated that family conflict was associated with later aggression at low, but not high, levels of media violence exposure; no other interactions were significant. These findings position family conflict as a particularly salient relational context for adolescent aggression while showing that its influence may depend on violence exposure in other social contexts. Prevention efforts should prioritize reducing hostile and coercive family interactions while attending to media and other social contexts that may reinforce, normalize, or otherwise alter family conflict effects on adolescent aggression. Full article

Highly aggressive gliomas remain difficult to treat because of their marked invasiveness, frequent recurrence, and association with glioma-related epilepsy. Increasing evidence suggests that ion channels expressed in glioma cells, including voltage-gated Na⁺ channels, large-conductance Ca²⁺-activated K⁺ (BK_Ca) channels, intermediate-conductance Ca²⁺-activated K⁺ (IK_Ca) channels, and inwardly rectifying K⁺ (Kir) channels, contribute to these malignant phenotypes and represent potential therapeutic targets. This perspective summarizes current evidence for eight representative drugs and phytoconstituents—perampanel, valproic acid, cilostazol, berberine, oxaliplatin, temozolomide, arecoline, and triptolide—that modulate these ion channels. Perampanel and valproic acid suppress voltage-gated Na⁺ current in glioma cells and may provide additional benefits in controlling glioma-associated epilepsy. Cilostazol activates BK_Ca channels, whereas berberine, oxaliplatin, and temozolomide inhibit IK_Ca channel activity. Arecoline suppresses IK_Ca and Kir channel activity, while triptolide inhibits Kir channels. These observations suggest that ion channel modulation may influence glioma cell proliferation, migration, invasion, and excitability. To complement the available experimental evidence, we performed molecular docking analyses as a hypothesis-generating approach to explore potential ligand–channel interactions. Because these computational predictions have not been experimentally validated, they should be interpreted cautiously and viewed as a framework for future mechanistic studies rather than definitive evidence of binding. We also discuss important translational considerations, including the limited clinical evidence and the toxicity profiles of several compounds. In particular, arecoline is associated with carcinogenicity and neurotoxicity, triptolide with significant systemic toxicity, berberine with poor oral bioavailability and potential drug interactions, and oxaliplatin with dose-limiting neurotoxicity. Overall, this perspective highlights ion channels as promising therapeutic targets in glioma while emphasizing the need for rigorous experimental validation and careful evaluation of safety before clinical translation. Full article

LIM and calponin homology domain-containing protein 1 (LIMCH1) has recently gained attention as a functionally perplexing factor in human cancers, with studies attributing both tumor-suppressive and tumor-promoting properties that defy simple categorization. Originally described as an actin-associated cytoskeletal protein that promotes non-muscle myosin-IIA (NM-IIA) activity and thereby curtails cell migration, LIMCH1 has more recently been linked to diverse oncogenic pathways across a range of tumor types. In lung adenocarcinoma and clear-cell renal cell carcinoma, diminished LIMCH1 expression is associated with more aggressive clinical behavior and reduced overall survival, aligning with a tumor-suppressive role. By comparison, in triple-negative and invasive breast cancers and in cervical squamous cell carcinoma, increased LIMCH1 expression correlates with enhanced metastatic spread, immune escape, and unfavorable outcomes, suggesting a pro-oncogenic function. In this review, findings from over 30 published studies are integrated with an original TCGA pan-cancer expression and survival analysis to propose that LIMCH1 is best understood as a context-dependent conditional regulator rather than as a classical tumor suppressor or oncogene. Based on the available evidence, we propose a hypothesis-generating conceptual framework in which its ultimate phenotypic effect is shaped by three interacting contextual determinants: (i) TP53 mutation status (determining whether the HUWE1-p53 axis is intact); (ii) tumor matrix stiffness (modulating actomyosin contractility and migration mode); and (iii) upstream signaling cues (e.g., MAPK/ERK, TGFβ). Of note, other tumor-lineage and microenvironmental factors may also contribute and warrant further investigation. This framework resolves the apparent functional duality of LIMCH1 in a cancer type-specific manner and provides critical guidance for future mechanistic research, standardized detection workflows, and the clinical translation of LIMCH1-based biomarkers. Full article

Neuroblastoma is among the most aggressive pediatric cancers, and resistance to standard therapies highlights the need for alternative strategies targeting lipid metabolism and apoptosis-associated pathways. This study aimed to investigate the cytotoxic and apoptotic effects of fingolimod, ceranib-2, and carmofur, administered individually and in combination, in SH-SY5Y neuroblastoma cells, with particular emphasis on ceramide metabolism. Cytotoxicity was evaluated using the MTT assay, and morphological alterations were assessed by confocal microscopy. Colony-forming ability was examined using a soft agar assay, apoptosis-associated responses were evaluated by Annexin-V staining and caspase 3/7 activation analysis, and intracellular ceramide levels were determined using an ELISA-based method. The results showed that all three compounds reduced cell viability in a concentration-dependent manner and decreased clonogenic survival. The triple combination produced the most pronounced changes in apoptosis-associated parameters and showed marked inhibition of colony formation, although fingolimod alone exhibited the lowest IC₅₀ value and therefore remained the most potent treatment on an IC₅₀ basis. Confocal microscopy revealed prominent apoptosis-associated morphological alterations, including chromatin condensation, nuclear fragmentation, and cytoskeletal disruption, particularly in the triple-combination group. Annexin-V and caspase 3/7 analyses showed increased apoptotic cell populations, with the highest levels observed following triple-combination treatment. Intracellular ceramide levels were also significantly elevated, particularly in cells treated with ceranib-2 and the triple combination. Collectively, these findings indicate that simultaneous modulation of ceramide- and S1P-associated pathways influences apoptosis-associated responses, clonogenic growth, and intracellular ceramide levels in SH-SY5Y cells. However, because the study was conducted in a single neuroblastoma cell line and did not include comprehensive dose-by-time or formal combination-interaction analyses, the findings should be regarded as preliminary in vitro observations. Further validation in genetically distinct neuroblastoma models, together with systematic dose–response and time–response studies, will be required to determine the reproducibility, biological significance, and broader therapeutic relevance of this approach. Full article

Mirror segmentation aims to identify mirror pixels from a single RGB image, yet remains challenging because mirrors provide weak intrinsic texture cues and their appearance is dominated by scene-dependent reflections under varying illumination and viewpoints. While recent models improve performance by leveraging contextual contrast, symmetry priors, frequency/spectral cues, or additional modalities (e.g., depth), many cross-cue or symmetry-aware designs still rely on direct spatial-domain fusion, such as concatenation, addition, or attention. Such fusion can amplify reflection-induced high-frequency variations and lead to leakage, shape distortion, and unstable boundaries. In this paper, we propose a symmetry-aware mirror segmentation framework that stabilizes cross-branch interaction via a frequency-domain cross-conditioned fusion mechanism. We build a dual-path Siamese encoder using the original image and its horizontally flipped counterpart, and introduce Heat Conduction Operator-based Cross Fusion (HCOCF), which performs heat-conduction-inspired spectral attenuation in the DCT domain. Unlike conventional fusion, HCOCF generates a nonnegative cross-conditioned attenuation coefficient map from the opposite branch and applies it to the DCT coefficient grid of the target branch. This produces a DCT-domain attenuation mask that controls the spectral refinement strength of each target feature stream, enabling global context propagation while suppressing unstable reflection-induced high-frequency responses without aggressive direct feature mixing. For multi-scale decoding, we adapt the cross-scale decoder of the baseline symmetry-aware architecture by replacing simple addition with conditional feature aggregation, which refines the HCOCF-enhanced features and improves boundary recovery. Extensive experiments on MSD, PMD, and RGBD-Mirror demonstrate competitive performance against representative supervised mirror segmentation methods. In particular, our RGB-only model achieves 88.47% IoU on MSD and 73.72% IoU on PMD, and remains competitive on RGBD-Mirror without using depth input. Full article

Cyberbullying among Chinese social media users has been described in relation to hostile words, pragmatic meanings, group alignment, identity positioning, and platform-mediated amplification. This scoping review mapped the linguistic and behavioral mechanisms reported in English-language studies indexed in Scopus and Web of Science concerning target-directed harm in Chinese social media contexts. Following the Arksey and O’Malley framework, Levac refinements, and PRISMA-ScR guidance, searches of Scopus and Web of Science identified 592 records. The 2015–2025 publication-date criterion was applied during screening. After deduplication, screening, and full-text eligibility assessment, 19 sources were included. Data were charted and synthesized thematically across lexical and lexico-semantic features, pragmatic strategies, discursive processes, and platform conditions. Four patterns emerged: evaluative labeling and semantic degradation; indirect aggression conveyed through irony, metaphor, insinuation, and culturally situated meanings; participant alignment and identity construction associated with legitimized hostility; and repetition, visibility, and collective participation associated with amplified harmful communication. Within this indexed English-language evidence base, cyberbullying was recurrently represented as a cumulative communicative process in which linguistic actions acquired harmful force through interpretation, social positioning, and social and technological circulation. Effective identification therefore requires attention to contextual meaning, interactional sequences, target relations, and platform dynamics, rather than reliance on isolated offensive terms. The review offers a provisional behavioral–linguistic framework derived from this indexed English-language evidence base while identifying methodological, platform, language, and database gaps for future empirical research. Full article

Understanding the ecological drivers shaping animal foraging and interactions remains a central question in ecology. Among the most studied systems in this field are the ant–plant interactions, although disentangling the complexity of factors acting in different contexts remains a relevant question. This study investigated how habitat structure, liquid food rewards, and interspecific competition interact to modulate the foraging patterns of the abundant ant Camponotus termitarius on the rosette-shaped plant Eryngium chamissonis in the Brazilian Pampa, where ant–plant interactions are still poorly studied. We monitored 115 plants across three sampling events, measuring ant foraging, trophobiont abundance, vegetation density, plant size, and local nest distributions, and analyzed the relationships using Piecewise Structural Equation Modeling (pSEM). The pSEM revealed that surrounding vegetation density negatively affected C. termitarius nest density, nest extensions, and hemipteran trophobionts. Conversely, denser vegetation and larger plants favored the aggressive competitor Camponotus rufipes. While trophobiont presence and proximal nesting infrastructure directly facilitated C. termitarius activity, hostplant inflorescences promoted the construction of nest extensions on plants. We conclude that C. termitarius foraging is regulated by a multidimensional network where microhabitat complexity mediates spatial niche partitioning and competitive dynamics between sympatric ants. Full article

The northern rockhopper penguin (Eudyptes moseleyi) is an endangered species undergoing continued population decline, making ex situ conservation and evidence-based breeding management increasingly important. Yet, behavioural data from ex situ populations remain limited. We provide the first systematic assessment of selected breeding-related behaviours in 13 pairs at Vienna Zoo during the 2024 breeding season using focal video observations. We quantified sex-specific investment in incubation, brooding and nest building, recorded agonistic interactions and nest-material competition, and derived composite indices of pair bonding, coordination, conflict exposure, and aggression initiation. Females contributed significantly more to incubation, whereas males invested more time in nest building, initiated more contact aggression and stole nest material more frequently. Males also received more non-contact aggression but fewer contact aggression events. Higher pair coordination was associated with lower conflict exposure, but the behavioural indices did not reliably predict reproductive success. Birth-origin composition (zoo versus wild-born) was associated with breeding outcome, with mixed-origin pairs showing lower breeding success than same-origin pairs. This exploratory association should be interpreted cautiously given the small sample size and possible confounding by demographic or pair-history characteristics. Our findings identify complementary sex-specific roles, nest-material competition and pair-level coordination as components of ex situ breeding behaviour. Full article

Objectives: Nasopharyngeal carcinoma (NPC) arises in an immune-suppressive milieu that frequently undermines treatment efficacy. TPPP3 has been implicated as a negative regulator of NPC aggressiveness, yet its relevance to immune modulation or chaperone networks remains poorly defined. We therefore sought to determine how TPPP3 shapes the NPC immune landscape and to identify its interacting protein partners. Methods: Public single-cell RNA-sequencing datasets from head and neck squamous cell carcinoma and nasopharyngeal carcinoma were analyzed using R. HK-1 and C666-1 cells stably overexpressing TPPP3 were established. These cells were used to construct humanized xenograft tumor models, with intratumoral immune cell infiltration evaluated by immunohistochemistry. In vitro, the same cells and their controls were indirectly co-cultured with peripheral blood mononuclear cells. Cellular lysates from TPPP3-overexpressing cells were subjected to immunoprecipitation–mass spectrometry and immunofluorescence staining, which identified HSPA8 as a TPPP3-interacting protein. Three groups—control, TPPP3-overexpressing, and TPPP3-overexpressing plus the HSPA8 inhibitor VER155008—were then compared in wound healing, colony formation, cell-cycle, and xenograft assays, with immunohistochemical staining for Ki67, TPPP3, and CD3 performed on tumor sections. Results: TPPP3 transcripts were barely detectable across most tumor cell subsets but showed preferential enrichment in NPC epithelial clusters. Enforced TPPP3 expression curtailed xenograft outgrowth while increasing intratumoral abundance of CD3⁺ T cells, CD8⁺ T cells, and CD11c⁺ dendritic cells. Pharmacological blockade of HSPA8 with VER155008 further enhanced TPPP3-driven suppression of migration, clonogenicity, and tumor expansion, and also altered cell-cycle progression while boosting CD3⁺ T-cell accumulation within grafts. Conclusions: These findings suggest a functional association between TPPP3 and HSPA8 that may contribute to tumor growth suppression and immune microenvironment remodeling in NPC. Pharmacological disruption of HSPA8-dependent proteostasis enhanced TPPP3-associated antitumor activity in both in vitro and in vivo models, indicating that this chaperone pathway represents a candidate mechanism worthy of further mechanistic investigation and therapeutic exploration. Full article

Background/Objectives: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited targeted therapeutic options. Although the anticancer and pro-apoptotic properties of boswellic acids have previously been reported, the interaction profile of chemically defined β-boswellic acid (BA) with doxorubicin (DOX) remains insufficiently characterised in the murine 4T1 TNBC-like model. This study quantitatively evaluated BA–DOX drug interactions using different reference models and characterised the cytotoxic and apoptosis-associated cellular phenotype accompanying combined exposure. Methods: Cytotoxicity was assessed using the MTT assay and BA–DOX interactions were evaluated using the Chou–Talalay combination index (CI), highest single-agent (HSA) and Bliss independence models. Apoptosis and cell-cycle distribution were analysed by flow cytometry and mitochondrial membrane potential was assessed by JC-1 staining. Caspase-3/7 activity, RT-qPCR, live/dead Calcein-AM/PI staining, 4′,6-Diamidino-2-phenylindole (DAPI) nuclear staining, and cytokine measurements were also performed. Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG), and STRING-based protein–protein interaction (PPI) analyses were used to explore putative molecular pathways associated with experimental findings. Results: The 48 h selectivity index of BA was 1.28, indicating only modest differential cytotoxicity between 4T1 cells and HaCaT keratinocytes under the experimental conditions rather than definitive cancer-cell selectivity. Drug-interaction analyses revealed concentration- and model-dependent effects, with the Chou–Talalay analysis indicating synergism in selected intermediate and higher concentration pairs. Under the selected phenotypic-characterisation condition, BA + DOX produced a greater apoptotic response than either single treatment, accompanied by increased G2/M and Sub-G1 fractions, mitochondrial membrane depolarisation, and increased caspase-3/7 activity. This treatment condition was not included in the drug-interaction analysis and was therefore not interpreted as a pharmacologically validated synergistic combination. RT-qPCR demonstrated increased mRNA expression of Bax, Casp3, and Casp9, decreased mRNA expression of Bcl2, and a marked increase in the Bax/Bcl2 mRNA ratio. Calcein-AM/PI and DAPI analyses further demonstrated increased cell death and apoptotic nuclear alterations. The measured concentrations of TNF-α and IL-6 in culture supernatants were lower after BA + DOX treatment, whereas IL-10 remained unchanged; however, these cytokine measurements were not normalised to viable cell number and therefore require cautious interpretation. Exploratory bioinformatic analyses identified predicted associations with apoptosis-, mitochondrial-, and cell-cycle-related processes and pathways; however, these database-derived findings were considered hypothesis-generating and not evidence of BA-dependent target engagement or pathway activation. Conclusions: Combined BA and DOX exposure produced greater cytotoxic and apoptosis-associated responses than either single treatment in 4T1 cells, whereas formal drug-interaction classifications varied according to concentration and analytical model. The accompanying changes in mitochondrial membrane potential, caspase-3/7 activity, and apoptosis-related gene expression describe a treatment-associated cellular phenotype but do not identify a direct molecular target of BA or establish a causal molecular mechanism. The findings also do not demonstrate TNBC-specific selectivity. Further studies using additional breast cancer and tissue-matched non-malignant models, together with direct target-engagement and functional pathway-validation approaches, are required. Full article

Pancreatic cancer (PC) remains one of the most aggressive malignancies, largely due to late diagnosis, rapid metastatic progression, and the limited efficacy of current therapeutics. Piperlongumine, a bioactive alkaloid isolated from Piper longum, has attracted attention for its selective cytotoxicity toward cancer cells and its ability to modulate multiple oncogenic pathways. However, its molecular mechanisms in PC remain insufficiently understood. In this computational systems pharmacology study, a network pharmacology strategy combined with molecular docking was used to investigate the molecular targets and pathways associated with piperlongumine anticancer activity. Targets of piperlongumine and PC-related genes were retrieved from public databases and intersected to identify shared targets. Overlapping targets were used to construct a protein–protein interaction network using the STRING (v.12.0) platform. Hub genes were identified using the CytoHubba plugin using six topological algorithms. Functional enrichment analyses (Gene ontology and KEGG pathway) were performed using the ShinyGO 0.85.1 platform. Prognostic relevance of the hub targets was evaluated using Kaplan–Meier Plotter platform, while immune cell infiltration patterns were explored using the TIMER-2 database. Molecular docking was conducted using AutoDock Vina (1.5.7) to validate ligand-target interactions. A total of 237 intersecting genes were identified. Network analysis revealed several central hub genes, including TP53, Akt-1, STAT-3, CTNNB-1, IL-6, TNF-α, and Bcl-2. KEGG pathway analysis highlighted PC as the most enriched pathway, together with chronic myeloid leukemia, the AGE-RAGE signaling pathway in diabetic complications, prostate cancer, and C-type lectin receptor signaling. Survival analysis revealed significant prognostic associations for several hub genes, while TIMER analysis suggested correlations with tumor-associated immune cell infiltration. Molecular docking confirmed favorable binding affinities of piperlongumine toward key oncogenic targets, particularly Bcl-2 (−7.2 kcal/mol), TP53 (−6.2 kcal/mol), CTNNB-1 (−6.2 kcal/mol), and Akt-1 (−5.8 kcal/mol). Collectively, this study uncovers piperlongumine anticancer potential in PC, mediated through coordinated regulation of apoptosis, inflammatory, and immune pathways, highlighting its promise for future experimental and translational investigations. Full article

Anaplastic thyroid carcinoma (ATC) is an aggressive malignancy with poor response to standard therapies. While Dabrafenib plus Trametinib (DT) combination therapy has improved the survival of patients with BRAF-mutant ATC, resistance remains a challenge. Given the association of macrophages with poor prognosis, and that SPRY4 has emerged as a mediator in ATC–macrophage interactions, we investigated their role in DT resistance and evaluated the therapeutic potential of macrophage targeting. Transwell co-cultures of BRAF-mutant ATC cell lines (T235 and T238) with THP-1-derived macrophages were established, and viability, invasion, and macrophage phenotype were assessed. Macrophages were also characterised in tumour samples from eleven ATC patients treated with DT. In vitro, DT significantly reduced ATC cell viability and invasion. However, macrophage co-culture significantly restored these effects, also promoting cytoskeletal remodelling and increased vimentin expression, despite DT treatment. DT significantly downregulated SPRY4 and suppressed MAPK signalling and PD-L1. These effects were also significantly reversed by macrophages. Under DT, macrophages showed an increase in M2-like polarisation in co-culture. Patients’ tumour samples were highly infiltrated with macrophages. In vitro targeting of macrophages with Edicotinib, in combination with DT, significantly enhanced the anti-tumour effects of DT and decreased the M2-like polarisation, bypassing the macrophage-mediated DT resistance. Overall, the in vitro findings suggest that macrophages modulate ATC response to DT by enhancing viability, invasion, MAPK signalling and PD-L1, supporting a pro-tumoural phenotype. Targeting macrophages overcomes this resistance, highlighting the CSF1/CSF1R signalling pathway within the ATC–macrophage axis as a promising therapeutic target to improve DT efficacy. Full article

Contemporary mural paintings contribute a significant part of urban cultural heritage, yet their conservation remains challenging due to the complex materials used and the aggressive conditions of the urban environment. Among the main deterioration factors, vandalic graffiti is particularly problematic, as its removal must be carried out without damaging the original paint layer, which often has a similar chemical composition. In this context, laser cleaning is a promising alternative to conventional mechanical and chemical methods. This study evaluates the effectiveness and selectivity of a nanosecond Nd:YAG laser (1064 nm) for the removal of a blue alkyd graffiti spray paint applied over mock-ups prepared with alkyd and polyvinyl acetate (PVA) paints on concrete substrates. The cleaning results were evaluated by stereomicroscopy, colour spectrophotometry, measurement of static contact angle, profilometry, near-infrared (NIR) hyperspectral imaging, Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) to assess physical and chemical changes after laser treatment. The results show that the effectiveness and selectivity of the process depend strongly on the chemical composition of both the vandalism layer and the original paint system, highlighting the importance of preliminary material characterisation prior to laser cleaning interventions. Although laser cleaning enabled the partial or substantial removal of the blue alkyd graffiti in all cases, alkyd-based paints exhibited greater resistance to laser irradiation and allowed more effective graffiti removal with fewer surface alterations than PVA-based paints. Among them, the green alkyd paint achieved the highest cleaning efficiency. These results indicate that the interaction between laser radiation and the materials was governed not only by the binder type, but also by the pigment composition and the optical properties of the paint layers. Full article

Pancreatic ductal adenocarcinoma (PDAC) is associated with high mortality owing to late diagnosis, aggressive tumor biology, and limited clinically useful early diagnostic and prognostic biomarkers. This study provides an exploratory evaluation of the expression profile, survival associations, co-expressed genes, functional association networks, and regulatory relationships of MEAK7 (KIAA1609/TLDC1) in pancreatic cancer using multi-platform bioinformatic approaches. We conducted a comprehensive multi-platform bioinformatic analysis using multiple publicly available datasets and platforms, including TCGA/GTEx, GEO, GEPIA3, HPA, CPTAC/UALCAN, TNMplot, Kaplan–Meier Plotter, DoSurvive, TIMER 3.0, STRING, TargetScan, miRDB, ENCORI and lncRNADisease. Gene expression patterns, survival associations, immune cell infiltration and regulatory non-coding RNA networks were systematically investigated. A STRING-derived protein functional association network was evaluated. MEAK7 expression patterns were additionally assessed in external GEO datasets, including GSE62165, GSE71729, and GSE183795. In summary, MEAK7 expression was elevated in pancreatic cancer compared with normal pancreatic tissues, was detectably expressed across multiple pancreatic cancer cell lines, and was increased in patient-derived PDAC samples. ROC analysis showed that MEAK7 expression discriminated PDAC tumor tissues from adjacent non-tumor pancreatic tissues, with an AUC of 0.795 (95% CI: 0.719–0.871) indicating exploratory transcriptomic discrimination rather than clinical diagnostic performance. Exploratory survival analyses showed that elevated MEAK7 expression was associated with unfavorable overall survival and disease-free outcomes, while multivariable Cox analyses showed that this association persisted after adjustment for the covariates available within the analyzed dataset. GEO-based analyses supported increased MEAK7 expression in early-stage pancreatic cancer samples, although metastatic expression patterns varied across datasets. Correlation and interaction analyses revealed positive associations between MEAK7 and PDAC-related genes, including CTTN, CDCP1, SMARCA4, SFN, and PALB2, as well as high-confidence STRING functional associations with V-ATPase components and RNASEK. Furthermore, MEAK7 was positively correlated with lncRNA UCA1 and negatively correlated with miR-582-5p. Collectively, these findings identify reproducible expression and survival-associated patterns involving MEAK7 across the analyzed datasets and provide a hypothesis-generating framework for further investigation of its potential biological role in PDAC. Experimental studies and prospectively characterized patient cohorts are required before any clinical, prognostic, diagnostic, or therapeutic implications can be established. Full article

Most existing driver behavior classification technologies have focused on highways and other primary road infrastructures, despite secondary roads accounting for a disproportionately large number of traffic fatalities worldwide. Compared with highways, secondary roads present greater variability in road geometry, infrastructure quality, and traffic interactions, making driver behavior recognition considerably more challenging. This paper investigates the classification of driver behavior on secondary roads using machine learning techniques. Naturalistic driving data obtained from the publicly available UAH-DriveSet dataset were analyzed using two complementary feature groups describing lane detection and traffic status. Four supervised machine learning algorithms, namely, Logistic Regression (LR), gradient boosting (GB), Random Forest (RF), and Artificial Neural Networks (ANNs), were evaluated to classify driving behavior into three categories: Normal, Aggressive, and Drowsy. The extracted features were first analyzed through statistical profiling and exploratory feature analysis before training and evaluating the classification models. The experimental results show that gradient boosting consistently achieved the highest performance for both feature groups, attaining an overall classification accuracy of approximately 67% while providing balanced precision, recall, and F1-scores across all behavioral classes. Logistic regression and random forest produced competitive but lower performance, whereas the Artificial Neural Network yielded the lowest classification accuracy. The obtained results demonstrate the effectiveness of ensemble learning methods for driver behavior recognition under secondary-road conditions and highlight their potential for integration into intelligent driver monitoring and Advanced Driver Assistance Systems (ADASs). By enabling earlier identification of aggressive and drowsy driving behaviors on secondary roads, the proposed approach could support timely driver warnings and safety interventions, potentially reducing accident risk. Furthermore, the findings provide a benchmark for future machine learning models designed for real-world secondary-road environments, where driving conditions are more variable and challenging than on highways. Full article