Search Results (18,477)

Colorectal cancer (CRC) is a major global health burden and a leading cause of cancer-related mortality, with metastasis representing the primary cause of death. Angiogenesis plays a critical role in this process, and macrophages within the tumor microenvironment (TME) are its key regulators. Among these, Tie2-expressing macrophages (TEMs) constitute a distinct pro-angiogenic subset that localizes to perivascular regions and responds to angiopoietin2 (Ang2) signaling. Moreover, TEMs contribute to vessel destabilization and the formation of permissive niches for cancer cell intravasation, linking them to both angiogenic and non-angiogenic modes of malignant tumor progression. The significance of TEMs in CRC remains controversial. This controversy, as we noticed, stems from a confluence of methodological challenges, lack of standardized markers, small-scale studies, inconsistent findings across studies, and the inherent complexity of both CRC biology and macrophage biology. Evidence from preclinical models and patient samples highlights the correlation between Ang2/Tie2 activity, TEM infiltration, and poor prognosis in CRC. This review summarizes current knowledge on the role of TEMs and the Ang/Tie2 axis in CRC angiogenesis, metastasis, and resistance to anti-angiogenic therapies. Advancing our understanding of TEMs may enable novel macrophage-focused strategies to inhibit CRC progression and improve patient outcomes. Full article

Context and Objective: Food quality and shelf life are strongly influenced by the interaction between packaging properties and mass transport processes. This study explored how hurdle technology can be applied to food preservation, focusing on olive oil as a practical case due to its high sensitivity to oxidation and light. Methodology: An analogy was developed between transport phenomena in packaging and the fundamental laws of electricity, providing a simple physical basis for understanding preservation mechanisms. This was supported by parametric simulations and mathematical modeling, which were used to predict how different packaging materials and conditions influence product stability. Main Results: The application to olive oil showed that packaging properties such as resistance to oxygen and light permeation have a direct effect on preservation effectiveness. Model predictions highlighted clear differences in stability depending on the choice of packaging, demonstrating the critical role of material selection. Conclusions: The study presents an integrated framework that links packaging characteristics with food preservation outcomes. By combining physical analogies with modeling tools, it offers a practical basis for designing packaging solutions that extend shelf life and protect sensitive foods such as olive oil. Full article

This study analyzed the intersection between Afrodescendant ethnoeducation and the school-to-work transition in three marginalized communities of the Colombian Caribbean: La Boquilla, Tierra Bomba, and Libertad-Sucre. Using a qualitative methodology, the research reconstructed, on the one hand, the institutional framework of Afro-Colombian ethnoeducation since the 1991 Constitution, highlighting public policies implemented and their impacts. On the other hand, it examined the educational dynamics in these localities and their link (or lack thereof) to local labor markets, identifying innovations, limitations, and structural barriers affecting young people’s transition from school to work. The findings show that the Colombian ethnoeducational model has introduced curricular and participatory innovations aimed at enhancing cultural relevance and preparing students for productive life. However, its implementation faces persistent barriers including inadequate infrastructure, the legacies of internal armed conflict, structural racism, limited employment opportunities, and chronic public disinvestment. Despite valuable local initiatives—such as technical training in collaboration with the SENA (National Learning Service, Colombia’s public technical education system) in sectors like fishing and tourism—Afrodescendant youth continue to experience limited labor market integration. Finally, the article offers policy and practical recommendations from a decolonial ethnoeducational perspective, inspired by the pedagogy for liberation, to strengthen the school-to-work transition in contexts of vulnerability. Full article

Time-lapse microscopy of mesenchymal stem cell (MSC) cultures allows for the quantitative observation of their self-renewal, proliferation, and differentiation. However, the rigorous comparison of two conditions, baseline (A) versus perturbation (B) (the addition of molecular factors, environmental shifts, genetic modification, etc.), remains difficult because morphology, division timing, and migratory behavior are highly heterogeneous at the single-cell scale. MSCs can be used as an in vitro model to study cell morphology and kinetics in order to assess the effect of, for example, gene therapy and prime editing in the near future. By combining static, frame-wise morphology with dynamic descriptors, we can obtain weight profiles that highlight which morphological and behavioral dimensions drive divergence. In this study, we present A/B Cells Policy: a modular, open-source Python package implementing a robust cell tracking pipeline. It integrates a YOLO-based architecture as a two-stage assignment framework with fallback and recovery passes, re-identification of lost tracks, and lineage reconstruction. The framework links descriptive statistics to a transferable system, opening up avenues for regenerative medicine, pharmacology, and early translational pipelines. It does this by providing an interpretable, measurement-based bridge between in vitro imaging and in silico intervention strategy planning. Full article

This study investigates the impact of employee well-being, work flexibility, and innovative work behavior on job performance among full-time and gig workers in digital businesses. A comparative analysis was conducted to examine potential differences between the two groups. A structured questionnaire was administered to 201 full-time employees in digital business system development and 199 gig workers from the IT Support Thailand group on Facebook using convenience sampling. The data were analyzed using multiple group structural equation modeling (MG-SEM) via partial least squares (PLS). The findings reveal that work flexibility boosts innovative work behavior, with gig workers showing greater adaptability than full-time employees. Innovative work behavior is positively linked to job performance, underscoring creativity’s role in organizational success. However, employee well-being and work flexibility did not demonstrate a significant direct effect on job performance. This study employed a sample of full-time and gig workers in Thai digital businesses, which may limit the generalizability of our findings to other industries or sectors. To enhance external validity, future research is recommended, including comparative studies across diverse employment forms and industries. Moreover, the adoption of a mixed-methods approach is encouraged to provide a more comprehensive understanding and broaden the scope of inquiry across multiple national contexts. Our findings underscore the need for policies that promote flexibility, well-being, and innovation to boost job performance. Digital business managers should foster adaptability, creativity, and support for both full-time and gig workers. An inclusive, balanced work environment can enhance performance, innovation, and satisfaction, helping organizations stay competitive in fast-changing markets. This study contributes to digital business research by examining the interplay between employee well-being, work flexibility, and innovative work behavior in determining job performance across different employment types. Full article

Environmental noise exposure is omnipresent, but the type of noise source and its appraisal may differ in varying contexts. For instance, studies have found significant differences in annoyance ratings between urbanisation levels. In this article, a re-analysis of existing survey data is presented, assessing noise annoyance and sleep disturbance from road traffic and railway noise in a random sample stratified by rural, suburban, and inner-city areas. Noise exposure was estimated using modelled L_den and L_night levels. Exposure–response curves showed greater annoyance at lower road traffic noise levels compared to the WHO guidelines (10% highly annoyed at 35 dB L_den vs. WHO 53 dB L_den). Railway noise annoyance aligned with the WHO estimates; however, sleep disturbance was lower at comparable exposure levels (3% highly sleep-disturbed at 53 dB L_night vs. WHO 44 dB). This re-analysis provides robust exposure–response relationships. The findings indicate higher levels for road traffic noise annoyance in Germany compared to international standards. A resulting policy implication is to link regular population surveys to noise action planning as a form of public participation. This approach enables the development of measures tailored to local conditions and supports the estimation of potential impacts, such as the number of people who may benefit from reduced noise exposure. Full article

This study investigates the transformations of the Hungarian Catholic clergy during the 20th century in its social relations, self-perception, and attitudes, with a particular focus on the Diocese of Pécs. It concentrates on events that caused collective shock, such as the advance of the front and the Soviet occupation during World War II; the confiscation of church property; the enforced migration processes; and the impact of the Communist regime’s ecclesiastical and social policies. The analysis emphasizes the role- and context-dependent patterns discernible in the documents produced by the clergy concerning these events, particularly in the parish Historia Domus. The study models the impact of these violent reconfigurations on clergy dispositions within the framework of Bourdieu’s concept of habitus, specifically the notions of “cleft” and “plural habitus”, highlighting the significance of behavior patterns in praxis transmitted through generations of clergy. It interprets the discrepancy between the altered context of action and the long-established, “interiorized” habitus, considering the phenomenon of asynchronicity, and identifies general and context-specific characteristics through a method of historical comparison. Overall, the study offers a perspective that perceives the historically evolved specificities of the norm as intrinsically linked to the local context. Full article

Background/Objectives: Drug discovery is a lengthy and expensive process, taking an average of 10 years and more than USD 2 billion from target discovery to drug approval. It is even more challenging in complex diseases due to disease heterogeneity and limited knowledge about the underlying mechanisms. We present a novel computational framework that integrates network analysis, statistical mediation, and deep learning to identify causal target genes and repurposable small-molecule candidates. Methods: We applied weighted gene co-expression network analysis (WGCNA) and bidirectional mediation analysis (causal WGCNA) to transcriptomic data from idiopathic pulmonary fibrosis (IPF) patients to identify genes causally linked to the disease phenotype. These genes were used as a phenotypic signature for deep learning-based compound screening using the DeepCE model. Results: Using RNA-seq data from 103 IPF patients and 103 controls, we identified seven significantly correlated modules and 145 causal genes. Five of these genes (ITM2C, PRTFDC1, CRABP2, CPNE7, and NMNAT2) were predictive of disease severity in IPF. Our compound screening identified several promising candidates, such as Telaglenastat (GLS1 inhibitor), Merestinib (MET kinase inhibitor), and Cilostazol (PDE3 inhibitor), with significant inverse correlation with the IPF-specific gene signature. Conclusions: This study demonstrates the utility of combining causal inference and deep learning for drug discovery. Our framework identified novel gene targets and therapeutic candidates for IPF, offering a scalable strategy for phenotype-driven drug discovery and repurposing. Full article

Modern scientific knowledge management systems increasingly demand methods capable of flexible modeling and dynamic analytics. This paper presents an approach to modeling for the needs of research knowledge base systems. The presented method integrates extensible XML-based data modeling with advanced analytical tools. The approach enables the structured definition of domain models characterized by hierarchical nesting, historical tracking, and semantic versioning. The presented analytical engine, based on this approach, uses XPath navigation to support dynamic pivot-table aggregations over complex, nested data. The underlying modeling is particularly useful for handling temporal data. It is suitable for broader contexts, resulting in flexible data structures, multi-version record management, interoperability with Linked Open Data (LOD) standards, and FAIR-compliant workflows. The results demonstrate that combining model-centric extensibility, semantic interoperability, and user-driven analytics provides a scalable and adaptable foundation for building information management systems across diverse institutional and organizational settings. A use case for a university knowledge database is presented, and acceptance of the system by users is discussed. Full article

To integrate rapidly growing environmental, social, and governance (ESG) investments into agribusiness, it is essential to understand the decision-making mechanisms behind sustainable practices in small- and medium-sized farms. This study examines the role of corporate governance in promoting sustainable practices using structural equation modeling on survey data from 1111 Japanese farms. The results reveal that internal social sustainability practices, such as improving the work environment and employee well-being, are positively associated with corporate governance and, in turn, significantly enhance sales growth, cash flow, and succession prospects. In contrast, external social sustainability practices show a negative correlation with governance, reflecting the influence of socioemotional wealth and reputation-driven decision-making. Environmental sustainability practices correlate only with sustainable corporate governance, suggesting a lack of strategic integration. These findings underscore the importance of corporate governance as a factor in linking sustainable initiatives to economic outcome. Strengthening internal social sustainability through robust corporate governance is therefore critical for farmers aiming to improve performance through sustainability. Moreover, given that family management preferences shape sustainability choices, policymakers must consider both governance and socioemotional factors to effectively support agricultural sustainability. Full article

This study examines the link between deep approaches to learning (DAL) and undergraduate senior students’ employability skills and perceived satisfaction in STEM fields in the United States. DAL, comprising higher-order (HO) and reflective/integrated (RI) learning constructs, enhances the understanding of real-world applications and promotes reflective thinking about individual ideas in broader contexts. HO activities focus on analyzing, synthesizing, and applying new information in practical scenarios such as internships, classroom discussions, and presentations. RI activities involve integrating existing knowledge with new ideas. The efficacy of DAL in improving student outcomes including employability and satisfaction skills was investigated using Structural Equation Modeling (SEM), which included a Confirmatory Factor Analysis (CFA) to measure observed variables associated with the four latent factors (HO, RI, student satisfaction, and employability skills), followed by structural analysis to explore the relationship between these latent factors. Data from 14,292 senior students surveyed by the National Study of Student Engagement (NSSE) in 2018 were analyzed. The results indicated a significant positive effect of DAL on students’ satisfaction and perceived employability skills, underscoring its importance in higher education for STEM students. These findings can guide higher education institutions (HEIs) in focusing on DAL activities for meaningful learning outcomes and enhanced critical thinking. Full article

High-precision assembly plays a central role in aerospace, defense, and precision instrumentation, where errors in bolt preload or tightening sequences can directly degrade product reliability and lead to costly rework. Traditional finite element analysis (FEA) offers accuracy but is too computationally expensive for iterative or real-time optimization. Surrogate models are a promising alternative, yet conventional machine learning methods often neglect the sequential and constraint-aware nature of multi-bolt assembly. To overcome these limitations, this paper introduces an integrated framework that combines an Attention-based Bidirectional Long Short-Term Memory (AB-BiLSTM) surrogate with a stratified version of the Harris Hawks Optimizer (SEG-HHO). The AB-BiLSTM captures temporal dependencies in preload evolution while providing interpretability through attention–weight visualization, linking model focus to physical assembly dynamics. SEG-HHO employs an encoding–decoding mechanism to embed engineering constraints, enabling efficient search in complex and constrained design spaces. Validation on a gyroscope assembly task demonstrates that the framework achieves high predictive accuracy (Mean Absolute Error of 3.59 × 10⁻⁵), reduces optimization cost by orders of magnitude compared with FEA, and reveals physically meaningful patterns in bolt interactions. These results indicate a scalable and interpretable solution for precision assembly optimization. Full article

This study investigates how perceptual and emotional factors—perceived naturalness, aesthetic pleasure, environmental concern, and disgust—shape consumer acceptance of a human-hair-derived bio-fabricated textile product (a unisex cardholder). In a scenario-based online survey, participants viewed an AI-generated image accompanied by a short vignette. A purposive sample of young adults in Istanbul with prior experience purchasing sustainable textile products was recruited and screened. All constructs were measured with standard Likert-type scales and translated into Turkish using a two-way back-translation procedure. Data were analyzed with PLS-SEM. Model fit was acceptable, and the model accounted for a substantial share of the variance in adoption intention. Aesthetic pleasure showed a clear positive influence on adoption intention, whereas perceived naturalness did not display a direct effect. Environmental concern modestly strengthened the link between naturalness and adoption. Disgust emerged as the dominant moderator, fully conditioning the naturalness pathway and reducing—but not eliminating—the effect of aesthetic pleasure. Together, these findings indicate that perceived naturalness, aesthetic pleasure, environmental concern, and disgust jointly shape adoption intention and that practical emphasis should be placed on reducing feelings of disgust while enhancing aesthetic appeal. Full article

This article investigates the mechanism of self-organized DNA criticality with open states, which plays a key role in the regulation of gene expression and consequently in cell fate determination. Based on a mechanobiological model developed using methods of statistical physics and thermodynamics, we demonstrate that the collective behavior of DNA open-state ensembles governs transitions between bistable, metastable, and critical genomic states. These states correspond to different gene expression scenarios involved in cell fate determination. Through simulation results, we introduce the concept of a criticality cascade, linking the dynamics of the DNA molecule structural parameter χ with global changes in cellular processes. The findings align with experimental data and offer new perspectives for studying genome regulation mechanisms, including pathological conditions such as cancer. Full article

Background: Adolescence is a particularly vulnerable period for experiencing loneliness. According to the latest statistics, there are worldwide increases in adolescents’ social isolation caused by different psychosocial challenges. A number of different studies have linked a strong belief in being successful at doing something to lower levels of feeling lonely. Objectives: Because we know less about the potential mediators of this relationship, the aim of the current study was to assess: (1) the association between self-efficacy and loneliness; (2) the mediatory role of peer communication. Methods: A total of 191 primary and high school students (M_age = 16.22; SD = 1.44) completed the General Self-Efficacy Scale, the De Jong Gierveld Loneliness Scale, and the Scale of Communication of Adolescents with Peers. Results: The results of the correlation analyses revealed that self-efficacy was negatively associated with loneliness and difficulty in adolescents’ communication with peers. Conversely, self-efficacy was positively associated with openness in adolescents’ communication with peers. Moreover, the outcomes of the PROCESS macro for SPSS (model number 4; Hayes, 2013) showed that openness in adolescents’ communication with peers and difficulty in this communication were mediators in this relationship. Conclusions: Young people who strongly believe in their abilities to achieve success may be more willing to share ideas and personal experiences with others and have less difficulty in communicating with peers, which may lead to a reduced sense of loneliness. Full article