Thermodynamic landscape of the redox-centres in the electron-confurcating [FeFe]-Hydrogenase (TmHydABC) of Thermotoga maritima.

Attack and defense techniques in large language models: A survey and new perspectives.

The proline-rich domain (PRD) of the tumour suppressor p53 plays a central role in modulating conformational dynamics and molecular interactions, yet its intrinsic structural behaviour remains incompletely understood. Here, we combine extensive all-atom molecular dynamics (MD) simulations with biophysical validation to characterise the conformational ensemble of the p53 PRD. The domain behaves as an intrinsically disordered region (IDR), sampling a highly heterogeneous ensemble with average end-to-end distance and radius of gyration of 52.5 Å and 21.8 Å, respectively. Despite this disorder, transient local structure is prominent: unordered conformations dominate, followed by substantial polyproline II (PPII) content, with β-bends and turns linking conserved PXXP motifs. Circular dichroism and small-angle X-ray scattering (SAXS) experiments corroborate the largely disordered yet partially structured nature of the PRD. Ramachandran and contact analyses reveal that consecutive prolines, particularly Pro71-Pro72, impose steric constraints that stabilize locally extended conformations and restrict backbone collapse. To approximate the PRD within full-length p53, additional simulations were performed with restrained terminal distances, yielding reduced conformational variability and improved agreement with SAXS data while preserving secondary-structure propensities. PPII helices emerge as particularly robust features, acting as stiff spacers linking the transactivation domain to downstream regions. Finally, simulations of clinically relevant variants reveal mutation-specific local perturbations: P72R disrupts consecutive proline rigidity and increases flexibility, whereas P82L abolishes a PXXP motif and its associated PPII helix. Together, these results identify proline-mediated rigidity and transient PPII structure as key determinants of the dynamic conformational landscape of the p53 PRD.

ABSTRACT The Middle Berach Basin, located on the eastern margin of the Thar Desert, preserve several Acheulean sites with cleaver-rich assemblages. The criteria for the typological classification of cleavers remain ambiguous and vary across different studies. Furthermore, factors governing variability within and between these tool types remain debated, resulting in several competing hypotheses. This study measures cleaver typological and technological diversity using 104 specimens from 36 Palaeolithic localities. The results reveal a strong preference for end-struck flakes used as blanks (72%) and predominant reliance on quartzitic sandstone (70.19%). Refinement index values (0.407) indicate intensive secondary flaking and structured edge modification, suggesting standardized blank selection and controlled reduction strategies. These patterns point to technological responses shaped by raw-material constraints and landscape dynamics, while also implying hominin behavioral flexibility. Comparitive analysis with Acheulean assemblages from South Asia, Africa, and Europe situate the basin within broader Pleistocene trends in lithic variability and adaptive strategies.

Pandemics often involve complex transmission dynamics in which epidemiological surveillance is essential but not sufficient for containment, as resurgence may be driven by emerging or imported variants. Rapidly evolving pathogens produce complex disease dynamics driven by emerging variants often differing in their transmissibility, immune escape, and cross-infection. These processes influence individuals' immune life histories, producing highly dynamic immune landscapes that modulate the emergence and dominance of novel variants. We develop an integrated modeling framework that couples multivariant mean-field epidemic modeling with a mechanistic genomic dominance model and a probabilistic surveillance model. This study examines how variant emergence timing, infectiousness advantage, and cross-infection jointly shape epidemic trajectories, immune landscapes, and genomic composition. Our results demonstrate that the dominance dynamics of cocirculating variants correspond to a selective sweep characterized by a system of multilogistic equations driven by population immunity. Moreover, we show that the detection time of newly introduced variants can be accelerated or delayed depending on their emergence conditions and the prevailing variant landscape. Finally, we demonstrate that the effectiveness of response strategies depends critically on the evolving genomic composition of the outbreak, highlighting trade-offs between surveillance sensitivity and intervention timing. We validate our framework by jointly fitting epidemiological and genomic data from the spread of the Ancestral, Alpha, Gamma, and Delta variants in the United States, Denmark, the United Kingdom, and Canada. The results provide a quantitative foundation for linking epidemic dynamics, genomic surveillance, and immune life histories, advancing the development of genomic epidemiology for multivariant outbreaks.

Large-scale single-cell atlases have revealed many aging- and disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular analyses. To address this, we developed EnrichSci-a scalable, microfluidics-free platform that combines hybridization chain reaction RNA fluorescence in situ hybridization (FISH) with combinatorial indexing to profile single-nucleus transcriptomes of target cell types with full gene-body coverage. Applied to oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.

ABSTRACT Megalithic landscapes in southwestern Iberia have long been reconstructed from heterogeneous regional inventories, often treating megalith spatial density as a proxy for demographic intensity. Here we present a probabilistic, auditable approach to reassessing megalithic densities and landscape dynamics by integrating conventional inventories with high‐resolution airborne laser scanning (ALS) and explicit uncertainty modelling. We compile the Western Iberia Megalithic Dataset (WIMD) ( n = 3069 sepulchres) from Spanish and Portuguese sources, curate a subset through bibliographic and field checks and evaluate inventoried sites against ALS‐derived visualizations to estimate apparent detectability. We then classify ALS‐only anomalies using a repeatable certainty scale and apply a probabilistic estimation framework to infer the total underlying number of megaliths and omissions in both inventories and ALS detection. Two case studies—(1) the transboundary International Tagus region (Portugal, Spain) and (2) the intensively surveyed eastern Andévalo River basin (Huelva, Spain)—show that ALS can increase inferred monument totals by 35%–50% under conservative assumptions in the analysed areas, while 35%–46% of inventoried mounds remain non‐recognizable in ALS products. Finally, ALS also identifies enclosure‐like settlement features that co‐occur with megalithic clusters, strengthening interpretations of densely structured landscapes and providing transferable priorities for targeted ground verification.

Amid the rapid advancement of the digital economy, the widespread adoption of digital technologies such as big data, cloud computing, and artificial intelligence has profoundly transformed the entrepreneurial landscape and development dynamics of small and medium-sized enterprises (SMEs). These technologies provide SMEs with new opportunities to overcome resource constraints and drive innovative business models. This paper examines the core relationship between the digital economy and SME entrepreneurship, elucidates the empowering value of digital technologies for SMEs, and analyzes the operational challenges SMEs face in digital entrepreneurship. By integrating case studies and theoretical frameworks, the paper proposes targeted pathways for business model innovation. The findings aim to offer theoretical insights and practical guidance for SMEs to achieve efficient entrepreneurship and enhance core competitiveness in the digital economy, ultimately facilitating their high-quality entrepreneurial development.

Abstract Depending on what levels of government and actors in a political system one focuses upon, democratic innovations might seem thriving or waning. This emerges clearly when looking at the main trajectories of democratic innovation in Italy. Compared to other liberal democracies, at the national level, Italy is a laggard; yet, a more dynamic landscape of democratic innovations exists at the local level. Some regions have drafted pioneering legislation institutionalising participatory and deliberative practices and numerous councils have adopted participatory innovations, early and consistently over time. Going beyond institutions, social movements have also been very influential with activists developing their own democratic innovation repertoires, which was especially clear in the movement for the commons. Positive and negative trajectories of democratic innovation may coexist across different actors (e.g., governments and civil society.) and levels of government in Italy. However, when these actors enter in contact with each other, state institutions might use democratic innovations against democratic engagement. We reflect on the implications of this situation for future trajectories of democratic innovation in Italy.

ABSTRACT This study examines multisensory communication in urban contexts through an empirical analysis of the Honghai Morning Market in Northeast China. The market demonstrates how communications among people, goods, and space generate a dynamic sensory landscape shaped by auditory, olfactory, and visual experiences. Focusing on applying research methods in studying sensory communication beyond the visual. To capture these dynamics, it integrates soundwalks, smellwalks, and sensory maps, operationalized into seven stages. On this basis, the study develops a dual-route strategy of structured and organic routes, combined with the overlaying of sensory maps. Drawing on cross-modal correspondence theory, auditory and olfactory data were visualized, and three spatial patterns were identified: sensory co-located zones, interlaced zones, and obscured zones. These results advance the analytical focus from static sensory backgrounds to dynamic sensory events, providing a framework for urban sensory analysis. Furthermore, links sensory research with spatial planning by proposing sensory-guided layout principles and management standards – including stall arrangement, noise control, and ventilation optimization – and by offering design guidelines for environmental improvement and historic district preservation. This article contributes to urban sensory studies by integrating data collection, visualization, and planning practice, highlighting the value of sensory perspectives in designing and managing dynamic urban environments.

ABSTRACT In Hong Kong’s higher education landscape, where traditional academic pathways prevail, recent reforms seek to address skills gaps and align vocational education with industry demands through the establishment of Universities of Applied Sciences (UASs). However, the adaptation of international UAS models to Hong Kong’s unique socio-economic context remains underexplored. While policy borrowing is widely discussed in the literature, there is a notable lack of systematic approaches for selecting and adapting role models in vocational higher education, especially for regions like Hong Kong. This study addresses these gaps by proposing a theoretically grounded framework for role model identification in higher education reform. The framework integrates Busemeyer and Trampusch’s Vocational Training Systems Typology with Steiner-Khamsi’s policy borrowing model. A comparative analysis of 13 countries, with a focus on South Korea and Finland, highlights the suitability of Statist Skill Formation Systems – characterized by strong state leadership and selective industry collaboration – for Hong Kong. The findings contribute to international policy borrowing discourse and provide actionable insights for overcoming societal stigma associated with vocational education. This research emphasizes the importance of context-sensitive solutions and outlines a pathway for developing Hong Kong’s UAS system in alignment with its dynamic socio-economic landscape.

The tumour microenvironment (TME) is a complex dynamic ecosystem where cancer cells, immune responses, and the extracellular matrix (ECM) engage in a delicate battle for dominance. Capturing this interesting interplay within a mathematically tractable yet biologically meaningful framework remains a key challenge. In this work, we construct and analyse a novel three-dimensional ODE model that describes the interaction between cancer cells, immune response, and ECM and reveals an interestingly rich dynamical landscape characterized by multiple bifurcation phenomena, deterministic chaos, and stochastic transitions. Through rigorous bifurcation analysis, we uncover transcritical, saddle-node, cusp, and Bogdanov–Takens bifurcations, each portraying critical transitions between distinct tumour states. The system further shows deterministic chaos, illustrating how intrinsic nonlinear interaction can induce unpredictable tumour behaviour even in the absence of external perturbations. Afterward we investigate how random environmental effects modulate tumour persistence or extinction through stochastic sensitivity by incorporating random fluctuations into biologically relevant parameters. Our findings demonstrate that ECM degradation, coupled with immune suppression, orchestrates a key mechanism driving tumour persistence and escape. Theoretically and biologically, our study provides a unified framework that links deterministic and stochastic processes to better understand and control cancer progression.

ABSTRACT This research emphasizes the increasing role of auditors in a dynamic business landscape, primarily due to stricter disclosure requirements under International Financial Reporting Standards (IFRS). It will explore how these standards influence auditors’ responsibilities in ensuring accurate and transparent financial reporting. The study will assess various factors, such as auditor tenure, firm size, and industry specialization, and their impact on the accuracy of financial statements. Additionally, it will underscore the importance of auditor independence and competence in upholding the integrity of the report in a complex regulatory environment. The primary goal is to offer insights into how auditors support the production of accurate financial statements in today’s economic and governance context. The research will also investigate how these variables affect the quality of financial reporting, especially given stakeholders’ growing demands for transparency and accountability. By reviewing the current literature, this study will synthesize key findings on factors that influence audit quality and their relationship to enhanced IFRS disclosure standards. Ultimately, it aims to improve understanding of how audit practices are adapting to preserve the credibility of financial information in a highly regulated environment.

ABSTRACT This study aimed to investigate the interaction potential of sponge metabolites towards signal transducer and activator of transcription 4 (STAT4), one of the potential targets related with rheumatic heart disease (RHD). Out of 100 sponge molecules screened, Halenaquinone demonstrated as potential inhibitor of STAT4 by modelling. Molecular docking revealed that Halenaquinone exhibited strong binding affinity with STAT4 (−10.2 kcal/mol) and favourable interactions, surpassing the binding of the reference drug Prednisolone-NR3C1complex. The interaction between STAT4 and Halenaquinone stabilized through hydrogen bonding and hydrophobic contacts involving several key residues, supporting its possible inhibitory mechanism. Molecular dynamics simulation studies indicated the stability of the STAT4-Halenaquinone complex, with some flexibility observed in the loop and terminal regions. Free energy decomposition revealed that van der Waals and electrostatic interaction were the main contributors to binding. Furthermore, principal component analysis, dynamic cross correlation and free energy landscape analyses suggested that Halenaquinone binding enhances the conformational adaptability of STAT4, consistent with its role as a potential mediator. The present study provides a computational model of STAT4 as a promising target in RHD and suggests Halenaquinone is a potential marine-sponge–derived compound with therapeutic potential.

Synaptic plasticity is believed to underlie a range of cognitive functions, including learning and memory. Numerous studies have shown that memory formation not only modifies the strength of existing synapses but also alters the dynamics of synaptic turnover. The dynamics of the synaptic landscape reflect brain-wide genetic changes and the activation of molecular mechanisms that mediate pre- and postsynaptic structural plasticity. The activity-dependent nature of these mechanisms leads to an intriguing possibility that synapses between engram neurons across multiple brain regions, or "engram synapses," may act as a hub for such synaptic changes. This review aimed to highlight the close relationship between the dynamics of synapse turnover and memory storage and summarize the underlying molecular mechanisms involved. The analysis highlights the need for more systematic investigation into how engram-specific synapses form and are eliminated across different brain regions.

Due to climate change and intense land use, soils are highly dynamic in Mediterranean regions. Soil redistribution rates (erosion/accumulation) are assumed to be the main factor changing soil evolutional trajectories, weathering and organic carbon dynamics in these landscapes, but their interactions remain poorly understood. Therefore, we investigated soil redistribution rates, weathering state, soil organic carbon dynamics and its chemistry in a Mediterranean area, Corleone, Sicily. Although the soils showed clear signs of degradation and erosion of up to 39 t ha −1 yr −1 , as determined by 239+240 Pu tracing, soil erosion measurement and modelling were made challenging by the vertic characteristics of some soils. With decreasing erosion rates, the soils had a higher amount of oxalate-extractable Fe stocks, more crystalline Fe, a lower (Ca + K)/Ti ratio (as a weathering indicator) or a higher CIA value. The organic C stocks ranged from 7 to 25 kg m −2 (average of 14 kg m −2 ). A major part of organic carbon was stored in the large aggregate fraction (≥63 μm). Soil organic carbon dynamics and quality were strongly linked to the soil redistribution rates. Erosion removed the strongly weathered part of the soil and left behind a younger and fresher soil matrix with a low org. C content, but an organic carbon fraction that was enriched in aliphatic chains and lignin-like compounds having a less mature status. The investigated soils had in general an optimal composition for stabilising and sequestering organic matter, even highly eroded and shallow soils still contained a considerable amount of org. C, which is untypical for Mediterranean areas. • In the planned Geopark of Corleone, soil erosion rates are high with up to 39 t ha −1 yr −1 . • Despite high erosion rates, organic carbon stocks remained astonishingly high with 7–25 kg m −2 . • Most of the organic carbon was stored in the fraction >63 μm. • More mature soil organic matter was accumulated in soils having a lower erosion rates. • A clear correlation exists between soil organic C stocks and erosion rates.

Monitoring environmental changes over time requires images with extensive historical depth. However, high spatial resolution images often lack such depth. This study investigates the impact of spatial resolution on image classification. Thus, Landsat 8 and Sentinel-2 images acquired between October and December 2020 were processed and classified using Random Forest regression on Google Earth Engine (GEE). This method allows for continuous land cover maps, required for robust assessment of land cover dynamics in patchy landscapes. A total of 1719 training samples were collected from the Collect Earth Online (CEO) platform to train the model. In addition to the spectral bands, vegetation indices were considered to optimize classification results. The study revealed statistical differences in land cover areas estimated by the two sensors. These differences are statistically significant at p < 0.001, although they are small. Validation results showed that the RMSE from Sentinel-2 is slightly lower than that from Landsat 8, with this difference significant at p < 0.05. Therefore, spatial resolution influences the accuracy of image classification. Nevertheless, given the observed differences between the two sensors, which ranged from 0.03% to 3.94% across land covers, Landsat imagery remains suitable for producing reliable land cover maps in heterogeneous landscapes.

Perceived Needs of Families of Critically Ill Patients.

Tectono-climatic controls on episodic paleosurface development in the Cauvery Basin, Southern India: Implications for basin-scale landscape dynamics

Trend-based satellite monitoring of urban landscape dynamics and modeling cooling-connectivity networks in Tehran metropolis