Abstract: One of the most puzzling and unsolved challenges in molecular biology is understanding how proteins fold. Despite having advanced predictive tools that can accurately estimate the native structures of proteins, we still lack a comprehensive model that explains how amino acid sequences dictate folding pathways and trajectories. This manuscript introduces a novel treatment for the issue by employing the “principle of least action.” This approach enables us to explore an intriguing question: how does a protein achieve its native state at a constant folding rate and within a biologically plausible time frame? A response to this inquiry will help us understand why proteins must fold along specific pathways and identify the boundary conditions that limit their availability. Additionally, the principle of least action—together with the effective trajectory conjecture—enables us to explain why different proteins could exhibit the same folding rate. Finally, it will enable us to provide an in-depth description of the genesis and solution of Levinthal's paradox. Our results are expected to pave the way for a more profound understanding of how proteins fold, shedding light on how the amino acid sequence and its surrounding environment encode the protein's folding pathways and, consequently, the protein's three-dimensional structure.

Abstract: In this work, the light curve of the Seyfert galaxy Mrk 6 constructed from photometric observations in the B, V, and Rc filters over the period from 5 April 2016 to 1 February 2026 is presented and analyzed. Over the entire monitoring interval (2016–2026), the variability amplitude of the light curve reaches ΔB=1.9 mag, ΔV=1.5 mag, and ΔRc=1.4 mag. During 2024–2026, the galaxy exhibits synchronous photometric variability in the B, V, and Rc filters with an amplitude of ∼0.3 mag. The study also uses spectroscopic observations obtained on 15 and 22 November 2025 and 16 February 2026 at the Shamakhy Astrophysical Observatory (Azerbaijan), as well as on 9 January 2026 at the Fesenkov Astrophysical Institute (Kazakhstan). The fluxes of the Hβ emission line were calibrated using the [O III] λ5007 Å line, ensuring consistent relative calibration of the spectral data. The radius of the broad-line region RBLR was taken to be equal to the average time delays (lags), amounting to ≈20 light-days for the Hβ line and ≈28 light-days for the Hα line.

Abstract: The nature of consciousness, specifically the state of "pure consciousness"—often characterized in contemplative traditions as a state of awareness devoid of intentional content—has transitioned from a topic of purely philosophical inquiry to a rigorous subject of neuroscientific study. This review synthesizes current clinical and neurobiological research to propose that oxytocin (OT), a nonapeptide traditionally associated with social bonding and parturition, acts as a critical neuro-modulator of the ego-construct. By facilitating the down-regulation of the amygdala and modulating the Default Mode Network (DMN), oxytocin creates the necessary neuro-chemical substrate for non-dual awareness. We explore the neurobiology of the oxytocinergic system, the intersection of social salience and ego-dissolution, and the empirical evidence for OT-mediated shifts in self-referential processing. Finally, we discuss the ethical implications of using neuro-pharmacology to influence meditative states and propose future clinical pathways for treating psychiatric disorders characterized by rigid, pathological self-narratives.

Abstract: Background: The objective was to identify management strategies of IFI in critically ill patients through a Spanish national survey. Methods: A cross-sectional multicentre survey among ICU specialist, experienced in IFI was performed (22-April-25-July 2024). The survey consisted of 13 questions with four closed answers. Results: Sixty-three experts from 51 hospitals of 16 regions completed the survey. 95% stated that, in high-risk patients with clinical suspicion of Pulmonary Aspergillosis (PA), request galactomannan in BAL to initiate treatment. In the treatment of patients with PA and influenza, 86% declared that isavuconazole and liposomal amphotericin B are recommended treatments and in high suspicion of aspergillus coinfection, 76% recommended empirical treatment waiting for microbiological confirmation. 90% declared that the use of Extracorporeal Membrane Oxygenation (ECMO) and Renal Replacement Therapies (RRT) could be associated with lower azole levels. Regarding intraabdominal candidiasis, 78% that physiopathological changes in critically ill patients, reduce their entry into the peritoneal fluid. Conclusion: The majority of the experts agreed (>80%) on: • In suspicion of PA, Galactomannan in BAL to guide treatment is mandatory • In case of aspergillosis and influenza, isavuconazole and liposomal amphotericin B are the recommended treatments. • The use of ECMO and RRT could be associated with lower azole levels.

Abstract: Background: We examined whether higher access to parks and greenspace is independently associated with an increase in physical activity and lower rates of obesity when neighbourhood walkability is accounted for, and to examine whether neighbourhood walkability and park access have synergistic effects on these outcomes. Materials and Methods: We used cross-sectional data from the Canadian Community Health Survey between 2007 and 2014 for adults aged 20 to 74 in Ontario, Canada. Neighbourhood-level access to parks exposures included size of parks and number of parks within 800m of residential areas, and neighbourhood walkability was based on a validated index. The main outcomes were physical activity during leisure time (LPA), both leisure and transportation physical activity (LTPA), and obesity. Descriptive and multivariate logistic regression analyses were conducted, stratified by age groups, accounting for sex, income, ethnicity, and season. Results: Among 41,945 respondents, park access was associated with higher LPA and LTPA, with effects modified by neighbourhood walkability (p< 0.001). Physical activity was highest in neighbourhoods with high walkability and park access and lowest in low walkability areas without parks. In highly walkable neighbourhoods, ≥1 small- or medium-sized park was associated with 29% higher odds of LPA (OR:1.29, 95%CI:1.21–1.37) and 48% higher odds of LTPA (OR:1.48, 95%CI:1.38–1.57) than low walkability/no park access. In contrast, associations were modest in low walkability neighbourhoods (4–7%). High walkability was also associated with lower obesity and marked reductions with very high access to large parks (OR:0.72, 95%CI:0.55–0.94). Findings were consistent across age groups. Conclusion: High neighbourhood walkability was the strongest predictor of physical activity and lower obesity risk, with park access providing additional benefits primarily in already walkable environments. These findings suggest that population health interventions targeting urban design need to consider the combined benefits of neighbourhood walkability and park access on health.

Abstract: Japan’s long-term care insurance (LTCI) system has been pivotal in addressing the challenges of a rapidly ageing population by providing comprehensive care and financial relief to older adults and their families since 2000. This review examines the system’s role in enhancing health equity and accessibility while identifying areas requiring policy adjustments. Stakeholder analysis reveals the interplay between the government, healthcare providers, elderly institutions, and family caregivers in implementing LTCI. Despite improvements in care accessibility and reduced income disparities, the system faces issues of financial sustainability and service disparities, particularly affecting low-income groups. Recommendations include enhancing community-based care, preventive measures, and equitable cost-sharing mechanisms to ensure the system’s effectiveness and sustainability.

Abstract: Draft pick value charts are widely used by NFL teams to evaluate trade proposals during the draft. Traditional charts provide point estimates for the relative value of each selection but do not quantify the uncertainty associated with those values. This paper introduces a statistical framework for estimating the uncertainty in draft pick values using historical trade data.Starting from the Rich Hill draft chart as a prior mean valuation, deviations between observed trade outcomes and chart values are analyzed to estimate the variability associated with each pick. Because individual picks have limited observations, a correlation structure between neighboring selections is introduced through a custom kernel function. Kernel regression is then applied to produce smooth estimates of the standard deviation associated with each pick.The resulting model generates probabilistic confidence intervals for draft pick values and allows trades to be evaluated in terms of statistical percentiles. Using historical trade data, the Rich Hill chart is shown to provide a better baseline representation of observed trade behavior than the traditional Jimmy Johnson chart. Model calibration using normalized residuals, log-likelihood, and confidence interval coverage indicates that the proposed framework produces well-calibrated uncertainty estimates while preserving the empirical structure of draft trades.

Abstract: The public sector constitutes a complex psycho-affective management system where leadership and autonomy are crucial for institutional effectiveness. The objective was to evaluate the differential influence of leadership management on autonomy and well-being in six departments of a municipal government in the state of Zacatecas, Mexico. A quantitative, correlational, and cross-sectional design was used with 235 public servants, employing Reference Guide III of NOM-035-STPS-2018 to identify psychosocial risk categories. The results, analyzed using Welch and Games-Howell tests, reveal significant differences (p < .001) according to the operational nature of each unit. Public Safety and Civil Protection present critical risks due to high demand and low control, while the Municipal DIF (System for Integral Family Development) stands out as a protective environment due to its positive leadership. A robust correla-tion was identified between poor leadership and lack of autonomy (rho = .701), in ad-dition to a widespread absence of recognition within the institution (p = .056). It is concluded that workplace well-being is conditioned by the command structure and the function performed, making it imperative to move towards an organizational culture that prioritizes occupational health to guarantee municipal operational sustainability.

Abstract: Organizations are increasingly investing in Process Innovation with Analytics, i.e., the usage of analytics to innovate operational processes. Process innovation with analytics is a challenging and complex endeavor encompassing 1) redesign of processes, 2) development of digital infrastructure, and 3) analytics development. As a result, organizations need guidance on how to approach this complex challenge. While research on IT-enabled process innovation and analytics each offer valuable insights, process innovation with analytics necessitates contextualization of these knowledge bases due to its distinct characteristics. This paper aims to inspire further research into process innovation with analytics by 1) reconceptualizing analytics in the context of process innovation, and 2) proposing a research agenda, consisting of three research directions and five research challenges. The reconceptualization and research agenda are based on the authors’ experience from an Action Design Research study at a large global manufacturer and retailer focused on process innovation with analytics. Bridging analytics, process innovation, and infrastructure perspectives, the paper offers a foundation for future scholarly endeavors and calls for further research into 1) digital infrastructures for process innovation with analytics, 2) the relationship between process change and analytics development, and 3) governance of process innovation with analytics.

Abstract: Quorum sensing (QS) governs microbial virulence, symbiosis, and critical ecosystem processes, such as rhizosphere nitrogen mineralization, positioning QS as both an attractive agricultural target and a potential point of ecological trade-off. This review synthesizes current evidence on coumarins, plant-derived secondary metabolites, that have evolved from being viewed as classical phytoalexins to being recognized as regulators of QS-mediated interaction in the plant-soil system. We synthesize current evidence on the multifaceted mechanisms of coumarin action, from direct antimicrobial effects to selective interference with bacterial QS systems and virulence. Key studies demonstrate that coumarins can suppress phytopathogens while sparing beneficial bacteria, thereby actively editing rhizosphere community composition. However, coumarin effects are profoundly context-dependent, with outcomes ranging from selective microbiome modulation to broad suppression or unintended pathogen enrichment - depending on concentration, plant host and native community structure. Beyond community assembly, coumarin-mediated QS disruption may have functional consequences for QS controlled ecosystem processes such as nutrient cycling. Revealing a potential ecological trade-off between pathogen defense and resource acquisition, this warrants further investigation. Coumarins are versatile compounds that plants use for sensing, communicating with, and actively shaping their microbial environments. Developing the ability to use them precisely and in an environmentally friendly manner represents a promising avenue for sustainable agriculture.

Abstract: Flash floods represent one of the most lethal natural hazards globally, requiring rapid, accurate, and geographically precise warning systems to protect vulnerable populations. The Common Alerting Protocol (CAP), standardized by OASIS and endorsed by the International Telecommunication Union (ITU) as Recommendation X.1303, provides a machine-readable, channel-agnostic framework for emergency alerting. This paper presents a comprehensive review of CAP implementations for flash flood early warning systems worldwide, synthesizing evidence from 30 peer-reviewed publications, technical standards, and operational case studies. We systematically analyze area delimitation methodologies (geocodes, polygons, hybrid approaches), document operational implementations across 10 countries spanning Asia, North America, Europe, and Africa, and evaluate technical architectures, dissemination channels, and performance characteristics. Key findings reveal that successful implementations employ diverse area delimitation strategies tailored to local geographic information infrastructure, with geocode-based administrative targeting (FIPS, HASC, NUTS, SALB) and polygon-based coordinate delimitation representing the dominant approaches. Operational systems demonstrate multi-channel dissemination capabilities (SMS, cell broadcast, satellite radio, web platforms, broadcasting) and sophisticated automation enabling sub-minute warning latency. However, significant challenges persist, including geocoding standardization gaps, message optimization for bandwidth-constrained channels, institutional coordination complexity, and limited evidence from resource-constrained contexts. This review identifies critical research priorities including flash flood-specific performance evaluation, low-resource context adaptations, geocoding harmonization, and long-term sustainability assessment. The findings provide evidence-based guidance for policymakers, emergency managers, and researchers considering CAP adoption for flash flood warning applications.

Abstract: Background: An accurate D’Amico risk stratification is mandatory for prostate cancer (PCa) management. The purpose of this proof-of-concept study was to establish a methodological framework of integrating validated clinical nomograms with strict data-quality governance in order to generate reliable artificial neural networks (ANN), even when the sample is small. Methods: We performed a retrospective analysis of a curated cohort of 49 patients from one center. A multilayer perceptron (MLP) was trained using 11 variables, including the ISUP biopsy grade and Briganti nomogram. Model development was guided by a proactive data-quality protocol based on FAIR principles, with stringent checks for accuracy, consistency and validity to ensure data were “AI-ready”. A sensitivity analysis was conducted on three data partitioning scenarios (20/80, 34/66 and 39/61). Results: From a starting pool of 76 patients, the FAIR-based data governance architecture was applied to create a highly selected cohort of 49 patients. A multilayer perceptron (MLP) trained on this “AI-ready” dataset achieved a mathematically perfect but clinically uninterpretable discrimination (AUC 1.000) for High vs. Intermediate risk groups on a small internal test set (N=9 for the 20/80 split). However, this complete accuracy is a best-case scenario reflecting the high data quality, not proof of generalizable clinical utility, as the large confidence interval (66.4-100%) and the requirement to exclude instances with unusual attributes for model validation (as described in the methods) highlight. Conclusions: The main contribution of this proof-of-concept study is the effective illustration of a strict, repeatable data governance approach for producing “AI-ready” urological datasets. Although the MLP demonstrated a robust internal signal for risk discrimination, its flawless accuracy is an ideal, non-generalizable situation. The most important deliverable that needs external validation is the framework, not the model’s performance metrics.

Abstract: We demonstrate that dopant inhomogeneity strongly suppresses thermal conductivity in Cd/Eu co-doped, non-polar a-oriented ZnO films grown on r-plane sapphire (Al₂O₃) by plasma-assisted molecular beam epitaxy. Structural characterization by θ-2θ XRD confirms a-oriented ZnO without detectable secondary phases. Cross-sectional SEM shows continuous films with well-defined interfaces, and SIMS depth profiling verifies Cd/Eu incorporation through the film thickness and a sharp Zn/O drop at the substrate interface. Optical transmittance and Tauc analysis reveal composition-dependent shifts of the absorption edge and band gap. Cross-plane thermal transport was measured at room temperature using frequency-domain photothermal infrared radiometry (PTR) and analyzed by fitting the complex PTR amplitude and phase with a multilayer heat-diffusion model. The extracted thermal conductivity spans ~3.7 - 6.3 Wm-1K-1. The lowest k values correlate with increased defect non-uniformity, consistent with enhanced phonon scattering and reduced effective cross-plane heat transport.

Abstract: Universal health coverage (UHC) requires simultaneous gains in service coverage and financial protection, yet these dimensions are often analysed separately. We conducted a secondary ecological panel study using two public indicator files (UHC-SCI and UHC-FH40). Records were first harmonized through a document-oriented non-relational workflow that preserved irregular subgroup structures before flattening to a country-year panel. The analytic sample comprised 981 observations from 159 countries/economies between 2000 and 2023. We estimated pooled trends, correlations, country and two-way fixed-effects models with clustered standard errors, a random-intercept model, a generalized estimating equation, domain-specific models, wealth- and urbanization-based inequality metrics, beta-convergence models, and country typologies. Mean service coverage rose from 58.9 to 74.1, whereas mean financial hardship fell from 24.0% to 17.3%. Each 1-point increase in the service coverage index was associated with a 0.441 percentage-point reduction in hardship (95% CI: -0.707 to -0.175; p = 0.001). The mean poorest-richest and rural-urban hardship gaps were 53.7 and 12.5 percentage points. Low-income settings showed the steepest inequities and the strongest negative slope. UHC progress therefore remains incomplete unless service expansion, financial protection, and inequality monitoring are interpreted together.

Abstract: Background: Tumor necrosis factor-alpha (TNF-α) inhibitors have transformed the management of chronic inflammatory diseases, yet they impose a substantially elevated risk of tuberculosis (TB) reactivation—up to 25-fold depending on the agent used. This risk is principally driven by disruption of granuloma architecture and suppression of interferon-gamma (IFN-γ)–dependent macrophage bactericidal activity. Current prophylactic strategies rely predominantly on isoniazid chemoprophylaxis, which carries hepatotoxicity risks and compliance challenges. There remains an unmet need for adjunctive immunomodulatory approaches that can selectively bolster anti-mycobacterial immunity without exacerbating the underlying autoimmune condition. Hypothesis: We propose that low-dose hydroxychloroquine (HCQ), administered concomitantly with TNF-α inhibitor therapy, can serve as a targeted immunomodulatory prophylactic strategy against TB reactivation. This hypothesis is grounded in recent single-cell transcriptomic evidence demonstrating that HCQ selectively upregulates IFNG expression and cytotoxicity-associated gene programs (GZMA, GZMB, PRF1, NKG7) in effector CD8+ T cells while simultaneously reducing the dysfunctional CD38+ CD8+ T cell subset. We posit that this CD8+ T cell–mediated IFN-γ augmentation can partially compensate for the TNF-α inhibitor–induced deficit in the IL-12/IFN-γ axis, thereby preserving granuloma integrity and macrophage mycobactericidal function. Evidence Synthesis: We integrate mechanistic data from immunology, pharmacology, and TB pathogenesis to construct a multi-layered rationale. We examine the dose-dependent immunomodulatory effects of HCQ, the differential impact of TNF-α inhibitors on mycobacterial immunity, and the critical role of IFN-γ in phagosome maturation and granuloma maintenance.Conclusion: This hypothesis establishes a mechanistically grounded framework for repurposing HCQ as adjunctive TB prophylaxis in the anti-TNF setting. We propose a phased translational research program to evaluate this novel immunomodulatory strategy.

Abstract: Echinometra lucunter (Linnaeus, 1758) is a sea urchin widely distributed throughout the Caribbean, recognised for its pivotal ecological role as a bioindica-tor. Its niche is characterised by herbivory within coral reef frameworks and shal-low rocky substrates, where it significantly contributes to nutrient cycling and net primary productivity across Caribbean marine ecosystems. However, anthropo-genic climate change poses a substantial threat to its populations, specifically through perturbations in marine hydrochemistry. This study aims to estimate and analyse the habitat suitability of E. lucunter in the Southwestern Caribbean under current conditions and future climate risk scenarios. To achieve this, we employed ecological niche modelling (ENM) using an ensem-ble forecasting approach that integrates multiple algorithms, including Maximum Entropy (MaxEnt), Generalized Linear Models (GLM), and Random Forest (RF). Models were calibrated using physical and chemical oceanographic variables and projected onto two contrasting climate pathways (SSP1-1.9 and SSP5-8.5) for the 2040–2050 horizon. Our results indicate that while the contemporary distribution of the species is strongly dictated by physiographic factors such as bathymetry and coastal proximity biogeochemical variables, including pH fluctuations, sea surface temperature (SST), and chlorophyll-a net productivity, are the primary drivers of habitat suitability shifts. Both future scenarios project a marked niche contraction, characterized by severe loss of core habitat and a high risk of local extirpation. Con-versely, specific insular and coastal regions in Colombia may serve as climate re-fugia, suggesting a potential buffering effect against regional declines. In conclu-sion, E. lucunter emerges as a species highly vulnerable to climate-driven stress-ors, underscoring the urgent requirement for spatially explicit conservation strate-gies within the Caribbean basin.

Abstract: Neural computation is not performed by static circuits processing signals corrupted by noise, but by actively moving biological structures that use motion itself to sample, encode, and predict the world. Neurons are often modelled as filters that transmit information through chemical and electrical signals constrained by noise and bandwidth. However, this static view contrasts with biological reality, in which dynamical processes operate across scales, from whole-animal movements to motion at the subneural level. Here, we combine recent experimental observations with biophysically realistic modelling to show that neural information processing, beyond electrochemical signalling, is dynamically shaped by motion across biological scales, from morphodynamic ultrastructural changes to whole-body movements. In this framework, ultrafast mechanical adjustments in cellular and synaptic structures interact with retinal, eye, head, and body motions to accelerate encoding and enhance precision. Adaptive variability in self-motion-coupled morphodynamic sampling arises from changes in response waveforms, latencies, refractoriness, and ultrastructural dynamics. This variability improves signal fidelity and extends spatiotemporal resolution, enabling neurons to generate reliable, high-speed representations with minimal delay. Thus, through active sensing, animals continuously enhance the speed and reliability of sensory representations. This perspective, in which self-generated sampling motion across multiple scales enhances encoding and perception, offers new insight into how the brain achieves efficient, predictive, and noise-resistant computation while providing a foundation for future experimental tests and biologically inspired AI designs. We first explain how motion-coupled encoding improves neural performance, focusing on edge-coding in early sensory systems. We then extend these ideas more speculatively, proposing how motion-coupled sampling may have influenced the evolution of neural architectures at multiple levels, potentially contributing to efficient predictive cognition.

Abstract: This study investigates the dynamic interplay between financial inclusion, inequality, and systemic risk across European economies from 2000 to 2035 using a stochastic diffusion framework. By integrating drift–diffusion modeling, Monte Carlo simulations, network transmission analysis, and scenario-based forecasting, we examine how financial, labor, and technological factors shape both the level and volatility of inequality. Empirical results indicate that higher financial inclusion consistently reduces mean inequality, dampens volatility, and enhances crisis resilience, while network centrality amplifies the propagation of shocks in high-volatility regions. Forecast scenarios highlight the asymmetric risk structure, showing that proactive digital finance and labor inclusion policies significantly mitigate extreme inequality outcomes. The study provides actionable policy insights for European financial integration, emphasizing that multi-pronged strategies combining digital finance, labor upskilling, and redistribution can stabilize inequality, enhance welfare, and reduce systemic risk.

Abstract: High-throughput plant phenotyping is increasingly constrained by the mismatch between the demand for field-relevant, fine-grained phenotypic data and the limited capability of conventional observation platforms under complex agricultural conditions. In this context, mobile phenotyping systems, particularly ground robots, are emerging as a key technological pathway for bridging macro-scale monitoring and organ-level trait analysis. This review examines the development of mobile phenotyping platforms for high-throughput plant phenotyping, with emphasis on the evolving role of ground robots in field-based sensing, decision-making, and active interaction. We first compare the functional characteristics of unmanned aerial vehicles and unmanned ground vehicles and discuss their complementarity in multiscale phenotypic data acquisition. We then summarize recent advances in the core technical framework of mobile phenotyping robots, including multimodal perception, localization and mapping, motion planning, deep-learning-based phenotypic analysis, active observation, robotic intervention, and edge deployment. Major challenges are further discussed, particularly those related to environmental generalization, data annotation, standardization, reproducibility, and long-term field reliability. Finally, future directions are outlined from the perspectives of air–ground collaboration, multi-robot systems, foundation models, and embodied intelligence. This review highlights ground robots as a central carrier for advancing mobile phenotyping toward autonomous, fine-grained, and field-deployable systems.

Abstract: Current efforts in improving photodynamic therapy focus on nanomaterials that integrate deep-tissue imaging with efficient reactive oxygen species generation. Gold nanoclusters (Au NCs) are promising alternatives to conventional photosensitizers due to their effective ROS production and enhanced biocompatibility when stabilized by protein corona. However, both photosensitizers and Au NCs are typically activated by ultraviolet or visible light, which cannot penetrate deeper into tissues and is limited to superficial applications. Here, we report a near-infrared (NIR)-activated photodynamic nanoplatform based on core-shell upconverting nanoparticles (UCNPs; NaGdF₄:Yb³⁺,Er³⁺@NaGdF₄:Yb³⁺,Nd³⁺), functionalized with a protein corona containing bovine serum albumin-stabilized Au NCs (BSA-Au NCs) and photosensitizer chlorin e6 (Ce6). Spectroscopic data confirmed the formation of the UCNP-BSA-Au-Ce6 nanoplatform and demonstrated 32% energy transfer efficiency from UCNPs to Ce6, resulting in efficient reactive oxygen species generation under 808 nm irradiation. Cellular experiments confirmed effective internalization and optimal biocompatibility of the nanoplatform in human breast cancer and healthy cells. Upon 808 nm irradiation, the nanoplatform significantly reduced viability of MDA-MB-231 cancer cells. These findings indicate that the UCNP-BSA-Au-Ce6 nanoplatform couples NIR activation with enhanced singlet oxygen production, providing a multifunctional platform for deep-tissue imaging and NIR-activated photodynamic therapy.