Search Results (4,874)

Background: Targeted therapies directed against oncogenic drivers have substantially improved outcomes for patients with epidermal growth factor receptor (EGFR)-mutant and anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC). Despite high initial response rates, most patients ultimately develop acquired resistance to tyrosine kinase inhibitors (TKIs), reflecting complex biological adaptations under therapeutic pressure. Methods: This narrative review synthesizes experimental, translational, and clinical studies examining how environmental and occupational respiratory exposures may influence resistance mechanisms in EGFR- and ALK-driven NSCLC. The review emphasizes exposure-associated signaling plasticity, inflammatory microenvironmental modulation, metabolic reprogramming, and pharmacokinetic alterations. Results: Recent evidence suggests that respiratory exposures, including cigarette smoke, air pollution, diesel exhaust, and occupational inhalational toxicants, can modulate oncogenic signaling networks relevant to resistance to targeted therapies. These mechanisms include aberrant EGFR activation, bypass signaling through the mesenchymal–epithelial transition receptor (MET) and SRC pathways, epithelial–mesenchymal transition (EMT), adaptive kinome remodeling, and exposure-associated inflammatory signaling, all of which may influence tumor evolution and therapeutic response. Conclusions: This review introduces a novel exposome-driven conceptual framework integrating environmental exposures with signaling plasticity and resistance evolution in oncogene-driven NSCLC. These findings support the concept that the respiratory exposome may represent an underrecognized modifier of targeted therapy response. Incorporating structured exposure assessment into precision oncology approaches may refine risk stratification and inform exposure-aware therapeutic strategies. Full article

This study examines the dynamic interlinkages among energy, food, and metal commodity markets under geopolitical tensions using daily data from January 2022 to July 2025. The empirical framework integrates correlation analysis, Granger causality tests, and a Vector Error Correction Model (VECM) to capture both short- and long-run transmission mechanisms, with robustness assessed through impulse response functions, forecast error variance decomposition, and a Diebold–Yilmaz connectedness analysis across three structurally distinct geopolitical event windows. The results reveal asymmetric and sector-specific transmission patterns in which geopolitical risk significantly influences key commodity prices—particularly WTI crude oil, wheat, copper, and aluminium—confirming its role as a primary external shock driver. WTI emerges as the dominant transmitter of shocks, while industrial metals exhibit strong internal connectedness. Critically, gold’s role proves to be conditional and context-dependent: within an integrated energy–food–metal network under geopolitical stress, it functions primarily as a net receiver and passive absorber of macroeconomic uncertainty rather than as a systemic transmitter, a finding that complements, rather than contradicts, its established safe-haven role in financial asset pricing frameworks. These findings are subject to limitations, including reliance on futures price data and a linear VECM framework that may not fully capture nonlinear or regime-dependent dynamics. Full article

Introduction: Financial support is a key driver of international student mobility. This study examines whether the financial incentives attracting international students to Hungary also translate into meaningful academic and social integration and a sense of belonging, comparing scholarship holders with self-funded students. Methods: A mixed-methods, cross-sectional online survey was conducted among international students enrolled in Hungarian higher education institutions (N = 232). The survey assessed motivations for choosing Hungary, academic and social integration, and willingness to recommend the country as a study destination. Group differences were analysed using independent-samples t-tests, Mann–Whitney U tests and multivariate analyses, while open-ended responses were examined using thematic analysis. Results: Scholarship programmes, academic quality, and Hungary’s relative affordability emerged as dominant motivational factors. While no significant difference was observed in overall academic integration (p = 0.127), scholarship recipients reported stronger inclusion within the Hungarian community (p = 0.032) and were markedly more likely to recommend Hungary (p < 0.001). Nonetheless, language barriers, limited interaction with host-country students, and social isolation persisted across groups, indicating that financial support alone does not ensure holistic engagement. Conclusion: Scholarship schemes yield the greatest impact when paired with institutional and social initiatives that actively foster integration, inclusion, and a sense of belonging. The study offers empirical insights from a non-traditional study destination, highlighting strategies to enhance international student experiences and strengthen Hungary’s competitiveness globally. Full article

The extensive production and use of per- and polyfluoroalkyl substances (PFAS) over recent decades have resulted in their pervasive distribution in environmental compartments worldwide. PFAS concentrations in soil and biota near fluorochemical manufacturing facilities tend to be typically higher near hotspots, which suggests that the consumption of home-produced foods near such hotspots most likely results in higher human exposure. One prominent European hotspot is located near the 3M fluorochemical production facility in Zwijndrecht (Belgium), where the relative contributions of different exposure pathways remain insufficiently characterised. This study therefore aimed to assess the PFAS concentrations and compositional profiles in serum, dwellings and gardens of teenagers residing near this hotspot. Serum samples from teenagers, along with multiple environmental matrices (i.e., soil, compost, vegetables/fruits/nuts, chicken eggs, rainwater and indoor house dust) were analysed for 21 selected PFAS. Additionally, potential determinants of PFAS occurrence and distribution across matrices were investigated using detailed questionnaire data. We found perfluorooctane sulfonic acid (PFOS) to be the predominant compound in both soil and serum, while perfluorobutanoic acid (PFBA) was most dominant in rainwater, compost, house dust and pods. Perfluorobutane sulfonic acid (PFBS) was most abundant in fruits and chicken eggs, while perfluorododecanoic acid (PFDoDA) was predominant in rooting vegetables and nuts. N-methylperfluorooctane sulfonamidoacetic acid (MePFOSAA) was the dominant compound in fruiting, stem, and leafy vegetables. These results indicate differences in accumulation pathways among the different media and/or differences in affinities of different PFAS in the matrices. Additionally, several environmental and behavioural factors were identified as determinants for PFAS in soil, compost, tree fruits, fruiting vegetables, chicken eggs and house dust, providing insight into potential drivers of exposure variability. The most important factors were related to the soil characteristics, the composting of grass and weeds, the chicken feed (i.e., bread, commercial feed), the type and frequency of ventilation and the frequency of cleaning. Full article

Background: Ponatinib (PON), an effective tyrosine kinase inhibitor for leukemias harboring the T315I mutation, is limited by severe cardiotoxicity, including myocardial infarction and heart failure. Here, we investigated the therapeutic potential of Bone Morphogenetic Protein-7 (BMP-7), an anti-inflammatory growth factor, in a murine model of PON-induced cardiotoxicity. Methods: C57BL/6J mice were distributed into experimental groups receiving PON (25 mg/kg cumulative dose) either alone or with BMP-7 (600 μg/kg cumulative dose), along with a corresponding control group. Cardiac analyses included molecular and histological assessments. Results: PON administration induced a marked increase in monocyte infiltration and M1 macrophage polarization. These inflammatory events led to the upregulation of the pyroptotic cascade, leading to activation of the TGF-β1/SMAD2/3 signaling axis. In contrast, BMP-7 significantly attenuated these pathological responses by suppressing inflammation-induced pyroptosis and the TGF-β1/SMAD2/3 signaling axis. Conclusions: These findings identify inflammation-induced pyroptosis as a central driver of the pathological changes in PON-induced cardiotoxicity. Notably, our work highlights BMP-7’s capacity to inhibit these disease-related alterations. Collectively, these results expand on the current knowledge of the mechanistic framework of PON-induced cardiotoxicity, while also emphasizing BMP-7 as a promising therapeutic candidate with potential translational relevance. Full article

The escalating global challenge of waste management, combined with the urgent need to reduce greenhouse gas emissions, has intensified interest in waste-to-energy (WtE) technologies as integrated solutions for sustainable energy recovery. This review critically examines advanced WtE technologies through three interconnected dimensions: the strength of the evidence base supporting performance and environmental claims, the challenges associated with scalability and system integration, and the implications of these technologies for net-zero energy transitions. The analysis covers thermochemical, biochemical, and hybrid conversion pathways, including pyrolysis, gasification, hydrothermal liquefaction, and anaerobic digestion, with particular emphasis on identifying inconsistencies in the literature and clarifying key uncertainties. A persistent gap between laboratory-scale performance and commercial-scale operation is identified and characterised across conversion pathways. Its principal drivers of feedstock heterogeneity, heat transfer limitations, and operational complexity are examined. Environmental assessments are shown to be highly sensitive to system boundary definitions and carbon accounting methodologies, with lifecycle results varying substantially depending on energy substitution assumptions and biogenic carbon treatment. The integration of WtE within circular economy frameworks demonstrates that energy recovery is most effective when positioned as a complement to material recycling rather than a substitute. The roles of combined heat and power configurations, district heating, carbon capture and storage, and emerging reactor technologies in advancing net-zero contributions are assessed. Significant data gaps are identified in long-term operational performance, modelling transparency, and reporting standardisation. The review concludes that WtE technologies represent valuable components of integrated waste and energy management systems, but their long-term contribution to decarbonisation requires careful system design, sound operational strategies, and harmonised performance evaluation frameworks. Full article

Background/Objectives: Healthcare facilities are among the most energy-intensive public buildings, yet hospital decision-support models rarely integrate energy-related performance indicators alongside operational metrics. This study aims to address this gap by developing a discrete-event simulation framework capable of jointly evaluating clinical efficiency and energy consumption in elective orthopedic surgical pathways. Methods: A comprehensive discrete-event simulation model was developed to represent the diagnostic imaging and orthopedic surgical process. The model was parameterized using a hybrid data-collection approach that combined clinical activity data, scientific literature, and expert judgment. Energy consumption was modeled by differentiating fixed loads, such as heating, ventilation, and air-conditioning systems and lighting, from activity-dependent loads associated with diagnostic and surgical equipment. Baseline performance was assessed and compared with alternative scenarios for organizational and technological improvements. Results: The analysis showed that fixed infrastructural loads, particularly HVAC systems, were the main drivers of per-patient energy consumption, with inefficient space utilization and prolonged idle times. Scenario analysis demonstrated that organizational interventions, such as increasing operating room throughput and optimizing MRI scheduling, can substantially reduce energy intensity by diluting fixed loads and decreasing idle consumption. Technological interventions, such as replacing conventional surgical lamps with LED systems, produced smaller but still beneficial reductions. The combined implementation of organizational and technological strategies yielded the greatest overall improvement. Conclusions: Integrating energy metrics into discrete-event simulation provides effective support for hospital decision-making by revealing the interaction between workflow design, resource utilization, and environmental performance. The findings indicate that organizational redesign, particularly when combined with technological upgrades, can significantly improve both operational efficiency and sustainability in hospital settings. This study highlights discrete-event simulation as a promising tool for energy-aware healthcare planning. Full article

Background: Aberrant protein O-fucosylation mediated by protein O-fucosyltransferase 1 (POFUT1), has emerged as a hallmark of tumorigenesis that regulates key signaling pathways, including Notch, which is frequently dysregulated in cancers. Protein O-fucosylation, catalyzed by POFUT1, regulates Notch signaling and has been implicated in individual cancers, but its pan-cancer expression patterns, clinical significance, and relationship to tumor immunity remain incompletely characterized. Methodology: We conducted a multi-omics bioinformatics analysis using TCGA and other public datasets to evaluate POFUT1 expression across 33 cancer types (n > 10,000). Differential expressions, tumor stage correlations, and survival outcomes were assessed. Immune cell infiltration was estimated using SangerBox and TIMER algorithms, while promoter methylation patterns were analyzed through UALCAN. Functional enrichment and protein–protein interaction networks were constructed to elucidate functional mechanism. Western blot validation in prostate and ovarian cancer cell lines confirmed our computational analysis. Results: POFUT1 showed significant overexpression in 16 of 33 cancer types (FDR-adjusted p < 0.05), with the highest elevation in BRCA (breast invasive carcinoma; log2FC = 2.31) and LUAD (lung adenocarcinoma; log2FC = 2.1). A high POFUT1 expression correlated with poor overall survival in eight cancer types (HR range: 1.8–3.2, p < 0.01) and disease-free survival in seven cancers. POFUT1 levels positively correlated with myeloid-derived suppressor cells (MDSCs) infiltrating in 15 cancer types, while inversely correlated with natural killer T (NKT) cells presence in 15 cancers (mean R = −0.34, p < 0.05), indicating an association with immunosuppressive microenvironments. Promoter hypomethylation in tumors suggested epigenetic dysregulation as a potential driver of its overexpression. Western blot analysis confirmed POFUT1 protein upregulations in prostate and ovarian cancer cell lines (1.7–2.1-fold. p < 0.01), corroborating transcriptomic findings. Conclusion: This pan-cancer study establishes POFUT1 as a critical oncogenic factor linked to aggressive disease, immune evasion, and poor prognosis. Its consistent overexpression and functional impact highlight its potential as a biomarker and target for anticancer therapy. While these computational findings require experimental validation, POFUT1 emerges as a candidate biomarker warranting functional studies and potential therapeutic targeting. Full article

Many business schools have set strategic objectives to integrate sustainability in their curricula; however, there is limited evidence of effective curriculum change initiatives, including organizational change approaches that could inform effective strategy design and implementation. This paper examines how a business school sought to embed sustainability content in undergraduate business education, and how it navigated contested understandings of sustainability and multiple orientations to teaching sustainability, including ESG, Corporate Social Responsibility (CSR), Sustainable Development Goals (SDGs), Social-ecological Systems, and Social Innovation. Using qualitative documentary curriculum data, a curriculum mapping methodology is presented to quantitatively assess year-on-year changes in sustainability content at curriculum, discipline, and orientation levels. Findings show that sustainability integration increased over the period studied, albeit unevenly across the curriculum, with integration driven by educators of various instructor types and sustainability orientations. The discussion highlights factors that likely supported progress, including the School’s approach to change and the strategy’s explicit recognition of multiple sustainability orientations. The study presents a practical methodology that senior managers seeking to integrate sustainability in higher education can use to track curriculum change progress, drivers, and orientations. It also offers guidance on how to advance sustainability integration in organizational contexts characterized by different sustainability orientations. Full article

At the international level, heritage is widely recognised as a critical component of sustainable development. However, in South Asian countries such as Pakistan, India, and Bangladesh, historic cities continue to struggle to preserve and integrate built heritage amid rapid urbanisation, socio-economic transformation, and evolving contemporary urban demands. Heritage places in these contexts are shaped by complex interrelations between collective memory, the built environment, and socio-cultural identity. Yet, conservation practices have been mainly implemented through fragmented, building-by-building approaches that neglect urban-scale coherence and intangible cultural dimensions. This article addresses this gap by examining adaptive reuse as a value-based conservation strategy in historic urban quarters, where heritage serves as both a repository of cultural memory and a catalyst for sustainable, experience-based tourism. Drawing on qualitative fieldwork, heritage value assessment matrices, and doctoral research, this study uses the Saddar Bazaar Quarter in Karachi, Pakistan, as a case study to explore how tangible and intangible heritage values can be systematically integrated into conservation and regeneration processes. The findings demonstrate that heritage-led adaptive reuse, when embedded within a comprehensive urban-scale conservation framework, can sustain everyday socio-cultural practices, reinforce local identity, and enhance the legibility of historic urban environments. Rather than positioning tourism as a primary driver, the study shows that culturally sensitive and community-oriented tourism emerges as an outcome of successful heritage integration, grounded in lived urban experience rather than commodified representation. Based on these insights, the article proposes a value-based integration framework that aligns heritage conservation, adaptive reuse, and sustainable tourism within historic urban quarters. The framework offers transferable methodological guidance for revitalising heritage places and collective memories, while providing policy-relevant insights for heritage governance that support sustainability objectives, community resilience, and inclusive urban regeneration in post-colonial contexts. Full article

Environmental factors play a crucial role in shaping human development. This study explores an extension of the United Nations Planetary pressure-adjusted Human Development Index ($PHDI$) by incorporating three methodological refinements: (i) a disaggregated analysis of material footprint data; (ii) the inclusion of a local adjustment factor related to fine particulate matter (PM${}_{2.5}$) exposure; and (iii) a variation to the planetary pressure aggregation method for obtaining the $PHD{I}^{*}$ index. The geographical scope encompasses 137 countries across the five permanently inhabited continents (Africa, America, Asia, Europe, and Oceania). The analysis first evaluates how these additional parameters deviate from the standard UN framework, followed by a continental assessment of national performances and their underlying drivers. A revised global ranking is presented, with countries categorised into four development levels based on Jenks Natural Breaks-derived cut-off values. Comparative cartographic visualisations highlight the shifts among the standard indexes and the proposed $PHD{I}^{*}$, illustrating that while some high-development countries—primarily in Europe—maintain their status, the inclusion of environmental aspects change the categories of important countries. These results suggest that accounting for localised environmental stressors and a more detailed material footprint analysis provides a more granular representation of the constraints on human development. Full article

Urban residents require space-efficient interventions to mitigate chronic stress. While indoor digital nature shows promise, the precise impact of interactive design parameters remains unclear. This study investigated how interactive feedback intensity (none, slow, fast) and color hue (neutral, warm, cool) influence psychological and physiological restoration. Following negative emotion induction, healthy participants engaged in within-subject conditions evaluated via multimodal assessments, including EEG, HRV, and subjective scales (PANAS, PRS, SAM/PAD). Results identified interactive feedback intensity as the primary driver of restoration. Specifically, fast feedback improved positive affect by up to 20.4% and reduced negative affect by 20.8% compared to passive self-restoration. Neurologically, interactive engagement was associated with elevated EEG alpha-band activity by up to 97.8% relative to standing controls, a pattern consistent with cortical relaxation. Furthermore, while physical interaction was uniformly associated with physiological indices broadly consistent with recovery, color hue significantly moderated subjective outcomes. Neutral and warm hues generated significantly higher overall perceived restorativeness (M = 73.18 and M = 70.14, respectively) than the self-restoration control (M = 61.26). Notably, neutral tones were uniquely associated with modest changes in HRV time-domain indices suggestive of parasympathetic autonomic modulation. These findings provide actionable, empirically validated guidelines for deploying responsive digital interventions to support mental well-being in dense urban interiors. Full article

This study reconceptualises marginality in China’s inter-provincial border regions as a dynamic, scale-sensitive spatial relationship rather than a static condition of underdevelopment. Using the Hubei–Henan–Anhui border area as a case study, we quantitatively assess marginality across three dimensions—production, livelihood, and ecology—based on panel data from 61 counties for 2000, 2010, and 2021. The entropy-weighted TOPSIS method is used to calculate comprehensive development indices, and geographic detector models identify key driving factors. The results show that production marginality is persistently shaped by economic level and industrial structure. Livelihood marginality exhibits a clear temporal shift: dominant drivers move from healthcare security to cultural amenities and finally to transport accessibility. Ecological marginality remains primarily determined by natural endowments such as habitat quality and ecosystem services. Theoretically, the study advances marginality analysis by integrating spatial, temporal and dimensional perspectives. Practically, it offers a diagnostic framework to support differentiated, cross-administrative governance strategies that can transform peripheral border regions into cooperative hubs. Full article

Seaweed cultivation is a primary economic driver in Tawi-Tawi, Philippines, yet the industry faces significant challenges regarding the physiological integrity of propagules during inter-island transit. This study evaluated the effects of varying transportation durations (0, 12, 24, 36, and 48 h) on the specific growth rate (SGR), occurrence of ice-ice disease, and dry biomass yield of Kappaphycus striatus over a 30-day cultivation period using a modified fixed-off-bottom method. The results demonstrated that transportation duration significantly influenced SGR at Day 10 and Day 30 (p < 0.05), whereas no significant differences were observed at Day 20. The control group (0 h transport) exhibited the highest growth performance (4.61 ± 0.18% day⁻¹ at Day 10), whereas the lowest growth was recorded in the 48 h treatment group at Day 30 (0.93 ± 0.49% day⁻¹). Pathological assessment indicated that ice-ice disease occurrence was highly significant during the initial recovery phase (Days 1–7) and at Day 20 (p < 0.05). Specifically, propagules subjected to 48 h transport reached 100% disease incidence within the first four days post-transplant, while the 36 h group reached 96.67%, highlighting acute transport-induced stress. Although the 48 h group exhibited significantly higher initial ice-ice spot counts (p < 0.05), statistical differences diminished between Day 10 and Day 30, suggesting a degree of physiological resilience and recovery capacity. Ultimately, prolonged transportation exceeding 24 h induced severe dehydration stress, resulting in a 62.7% reduction in SGR by Day 30 compared to the control. These findings suggest that seedling transport should be optimized within a 24 h window to preserve thallus vigor and maximize sustainable yields. Future research should investigate post-transport recovery protocols to mitigate the effects of unavoidable shipping delays. Full article

Financial distress prediction remains a central topic in corporate finance and risk management, with extensive research devoted to improving classification accuracy through increasingly sophisticated statistical and machine learning techniques. Nevertheless, the influence of data preparation on predictive performance has received comparatively less systematic attention. This study examines how an economically grounded data-preparation process affects the predictive performance of selected statistical and machine-learning models dedicated to predicting corporate financial distress. Using the chosen financial ratios, generally accepted indicators of corporate financial stability and economic performance, financial distress models are estimated on both raw, unprocessed input data and pre-processed data involving the exclusion of economically implausible accounting values, treatment of missing observations, and class balancing. In light of the above, the study adopts a structured methodological approach to assess the predictive performance of selected classification models, namely decision tree algorithms (CART, CHAID, and C5.0), artificial neural networks (ANNs), logistic regression (LR), and linear discriminant analysis (DA), using confusion-matrix–based evaluation and a comprehensive set of evaluation measures. The results suggest that the process of input data preparation is a critical factor, significantly improving the predictive performance of financial distress prediction models across most modelling techniques employed. The most pronounced gains are observed in decision tree models. ANNs also demonstrate marked improvement after input data preparation, whereas LR benefits more moderately, and linear DA remains limited despite preprocessing. The average gain in accuracy across all six modelling techniques, calculated as the difference between pre-processed and raw performance for each method and averaged across methods, was approximately 15.6 percentage points, with specificity improving by approximately 26.9 percentage points on average, amounting to roughly half the performance variation attributable to algorithm choice, which underscores that data preparation is a primary determinant of model reliability alongside algorithm selection. A step-level detailed analysis further shows that missing value imputation is the dominant driver of improvement for tree-based models, while class balancing contributes most for ANNs and logistic regression. The findings highlight that reliable financial distress prediction depends not only on technique selection but also on the consistency and economic plausibility of the input data, underscoring the central role of structured data preparation in developing robust early-warning models. Full article