Abstract: In agricultural practice, botanical extracts have emerged as promising biostimulants that can modulate key metabolic and redox processes in crops, thereby increasing stress resistance and productivity. This review provides a comprehensive synthesis of current knowledge on how botanical extracts influence plant metabolism and redox homeostasis, with particular emphasis on their role in adaptive cellular responses. Additionally, it examines how agronomic practices, such as nutritional strategies, water availability, light regimes, and preharvest biostimulant applications, can be utilized to increase the bioactive composition and efficacy of these extracts. By integrating recent advances in metabolomics and transcriptomics, this review outlines the biochemical and molecular reprogramming triggered by botanical extracts, identifies knowledge gaps, and outlines future research directions to optimize their use in sustainable agriculture. The sections comprising the review are an introduction that establishes the context and objective of the manuscript. The second section describes the bioactive constituents found in botanical extracts from different species, along with their metabolic and redox effects. The third section describes the plant response to the botanical extracts. The fourth section describes the metabolic and gene expression reprogramming that occurs following the application of a botanical extract. The last section presents the conclusion and future directions envisioned by the authors.

Abstract: Background: Cutaneous melanoma remains a highly lethal malignancy once metastatic. Current prognostic stratification relies primarily on staging and serum lactate dehydrogenase (LDH), which incompletely captures inter-patient biological heterogeneity. Increasing evidence highlights the importance of tumour–immune interactions in melanoma progression and response to therapy. Aim: This narrative review summarises and critically evaluates current evidence on circulating cytokines as prognostic and biologically informative biomarkers in melanoma, with particular emphasis on the immunotherapy era. Main findings: Several circulating cytokines—most consistently interleukin-6 (IL-6) and interleukin-8 (IL-8)—are associated with adverse outcomes in advanced melanoma. However, baseline elevations predominantly reflect tumour burden and systemic inflammation, indicating prognostic rather than treatment-specific predictive value. In contrast, early on-treatment changes, particularly decreases in IL-8, may better capture evolving tumour–immune interactions during immune checkpoint inhibitor therapy. C-reactive protein (CRP), a downstream marker of IL-6 signalling, similarly reflects systemic inflammatory status and carries reproducible prognostic significance. Early circulating tumour DNA (ctDNA) dynamics demonstrate strong associations with response and survival and may provide complementary insight into tumour burden kinetics. Conversely, cytokines central to effective antitumour immunity, such as interferon-γ (IFN-γ), are more reliably characterised at the tumour transcriptional level than by circulating protein measurements. Conclusions: Circulating cytokines represent biologically meaningful but methodologically challenging biomarkers in melanoma. Their most realistic clinical role lies in complementing established prognostic factors within integrated biomarker frameworks rather than functioning as standalone tests. Standardization of pre-analytical handling, assay platforms, and sampling time points, together with prospective validation, is essential before broader clinical implementation.

Abstract: Large language models (LLMs) require a significant redesign in solutions to preserve privacy in data-intensive applications due to their text-generation capabilities. Indeed, LLMs tend to memorize and emit private information when maliciously prompted. In this paper, we introduce Private Association Editing (PAE) as a novel defense approach for private data leakage. PAE is designed to effectively remove Personally Identifiable Information (PII) without retraining the model. Experimental results demonstrate the effectiveness of PAE with respect to alternative baseline methods. We believe PAE will serve as a critical tool in the ongoing effort to protect data privacy in LLMs, encouraging the development of safer models for real-world applications.

Abstract: Unmanned aerial vehicle (UAV) remote sensing has evolved from experimental imaging into an operational diagnostic infrastructure supporting climate-smart agriculture through high-resolution, flexible, and timely crop observation. This review synthesizes advances in UAV platforms, multisensor payloads, artificial intelligence (AI) analytics, and multisource data fusion to evaluate their combined potential for monitoring heterogeneous smallholder systems. A PRISMA-guided analysis of 59 studies (2013–2024) classified sensing architectures, analytical approaches, and application domains across diverse agroecological contexts. Integrated UAV–AI frameworks improve detection of crop stress, yield variability, biomass distribution, and phenological dynamics compared with conventional monitoring, particularly when multimodal sensor data are fused with satellite and ground observations. Predictive performance and diagnostic reliability increase when spectral, thermal, and structural datasets are analyzed jointly using machine-learning or deep-learning models. However, scalability remains constrained by operational, infra-structural, and regulatory factors, especially in resource-limited systems. These findings demonstrate that integrated sensing–analytics systems form a critical foundation for scalable climate-smart agricultural transformation and data-driven decision support across farm, landscape, and institutional scales.

Abstract: This paper provides a rigorous examination of eight fundamental architectural deficiencies that render the Linux kernel unsuitable for deployment in safety-critical avionics. These deficiencies include inadequate temporal determinism, the absence of physical memory isolation, driver-induced contamination of global kernel state, an excessively large and unbounded Trusted Computing Base (TCB), open and nondeterministic system semantics, insufficient inter rocess fault containment, unstable kernel behavior due to continuous patching, and a highly complex toolchain that imposes prohibitive DO-330 qualification burdens. Through a technical and standards-aligned analysis, this paper demonstrates that Linux cannot satisfy the determinism, verifiability, isolation, and lifecycle stability required for airworthiness certification, making it inherently incompatible with certifiable airborne platforms.

Abstract: Translational virology, characterized as “from bench to bedside”, covers all issues from basic research through clinical evaluation and final registration and drug/vaccine approval. It covers the identification of the cause of disease, screening of potential prophylactic or therapeutic agents, evaluation in animal models, confirmation of activity in human clinical trials, registration and approval. The recent COVID-19 pandemic represents a perfect example of translational virology, which demonstrated an unprecedented cooperation from the identification of the SARS-CoV-2 to the rapid development of potential repurposed and novel drugs and vaccines for both prophylactic and therapeutic applications. After confirmation of therapeutic and prophylactic efficacy in animal models, clinical phase I-III evaluation was carried out in an overlapping strategy, reducing the development time significantly. To maximize the chances of success, vaccines based on whole viruses, protein and peptide subunits, viral vectors and nucleic acids were developed in parallel. Based on good safety profiles and robust immune responses, COVID-19 vaccine candidates were granted emergency use authorization worldwide allowing the start of mass vaccinations. More than 13.6 billion COVID-19 vaccine doses have been administered, and although severe adverse events have been registered millions of lives have been saved. Due to emerging SARS-CoV-2 variants vaccine re-engineering has been required as part of translational virology. Vaccine production, storage, transport and distribution have also been given attention.

Abstract: This paper presents a conceptual framework, the AI-Augmented Interview Framework (AAIF), requiring empirical validation before deployment. No interviews have been conducted; all thresholds, weights, and KPI linkages are conjectures pending empirical testing. The accelerating adoption of AI-powered development tools (GitHub Copilot, ChatGPT, Claude) is transforming software engineering practice. Industry surveys indicate that over 75% of professional developers now use AI coding assistants regularly (noting potential self-selection bias in survey samples), yet fewer than one in four organizations assess AI fluency during technical interviews. AAIF proposes a structured five-stage interview methodology (Stage 0 fundamentals gate plus four AI-augmented stages) for evaluating developer competencies in AI-mediated environments. The framework assesses: (1) toolchain fluency and prompt engineering, (2) AI output evaluation and critical reasoning, (3) system-oriented problem solving with AI integration, and (4) meta-reasoning about AI limitations, ethics, and failure modes. We develop evaluation rubrics with behaviorally anchored rating scales, propose configurable decision thresholds, and provide an integrated risk framework addressing bias, fairness, legal compliance, and ethical dimensions. The novelty lies in the systematic integration of established methods from industrial-organizational psychology, software engineering, and risk management for the specific and underexplored problem of assessing developers who use AI tools. A detailed four-phase empirical validation protocol is proposed as a key contribution.

Abstract: Colorectal cancer is a major healthcare burden, and modern management of non-metastatic disease relies heavily on guideline concordant care with a basis in histopathologic staging and empiric systemic therapy. While multidisciplinary care pathways and standardized guidelines have improved outcomes at a population level, they fall short in addressing the inter-patient and intra-tumoral heterogeneity that drives lack of response, recurrence, and unnecessary toxicity. Using a hypothetical patient journey, our commentary highlights how current practice often fails to align with patient needs despite being “guideline concordant”. We discuss limitations of current treatment paradigms and the shortcomings of even modern tools like genomic profiling, highlighting the continued need for complementary approaches.We hypothesize that functional precision medicine approaches have the potential to complement existing treatment paradigms and may contribute to improved therapeutic stratification. We provide illustrative examples of potential utility drawn from our recent colorectal cancer clinical correlation study where we reported an association between assay outcomes and clinical response in a retrospective cohort, as well as the ability to identify intra-patient heterogeneity in ex-vivo drug response, suggestive of phenotypically distinct subpopulations with differential drug sensitivity. Further investigation leading to integration of these or similar technologies alongside genomic and minimal residual disease assessments could refine therapy selection and improve existing surveillance strategies.Ultimately, we suggest that while guideline concordant care remains necessary, it is not sufficient for all patients, and that with continued research efforts utilizing functional precision medicine technologies, colorectal cancer management can move toward a personalized framework that maximally benefits patient outcomes.

Abstract: This paper presents a generative AI frameworkfor producing structured symbolic sequences with fine-grainedexpressive control. The approach introduces a compact tokenrepresentation combined with phrase-aware latent alignment tosupport coherent generation across variable-length segments. Byintegrating sequence-level regularization directly into attention,the model balances structural consistency and diversity withoutrelying on explicit post-processing constraints. Empirical analysisshows that the method maintains stable distributional behavioracross expressive dimensions, highlighting its suitability forcontrollable symbolic generation tasks.

Abstract: CEMP-rs stars are often interpreted as signatures of intermediate (i-) process nucleosynthesis during early AGB evolution, yet no observed pattern has been shown to favor the i-process over a simple r+s combination. We present a new analysis of TYC 6044-714-1 based on high-resolution UVES spectra and state-of-the-art 1D and 3D non-LTE modelling, deriving precise atmospheric parameters, elemental abundances, and barium isotopic ratios. Modelling of the Ba II 4934 Å line indicates that 86% of barium originates from the s-process, while the derived [Ba/Eu] = 0.25 dex further supports s-process dominance.

Abstract: This paper propose a formal framework for AIagents that unifies semantic reasoning with resource-aware con-trol. Agents act via sparse policies over structured semantic fields,bounded by entropy and sparsity budgets. We define a typedoperational semantics, prove soundness and stability, and derivea sparse free-energy objective with phase transitions. The calculusis categorically structured, maps to unistochastic dynamics, andcompiles to executable policies with verified runtime bounds.This yields a foundation for interpretable, thermodynamically-plausible agent design.

Abstract: Foremost, the structural-, functional- and behavioural traits of birds relate directly or indirectly to powered flight, an elite mode of locomotion which has importantly made them what they are - ‘specialist and extreme animals’. Placing them at the pinnacle of the evolutionary hierarchy, birds possess exceptional biological specialisations which have conferred profound survival advantages. The adaptive novelties of birds are particularly exhibited by the exemplary morphological and physiological refinements of their respiratory system, the lung-air sac system. To contribute to the ongoing discussions and debates on the impacts of the existing extreme environmental conditions (ECs) on the biology of birds, here, a perspective is posed that the adaptive specialisations which birds acquired ostensibly under different ECs may have undermined their capacity of efficiently adjusting to different ones. To explain the viewpoint, the following aspects are considered: the specialist- and extreme biology of birds; the prevailing harsh ECs which are brutally impacting on birds and; the consequences from their enduring the harsh conditions which include among others global warming and habitat devastation. It is contended that under the existential threats, the adaptive capacities of birds appear to have declined, rendering them more vulnerable to external stressors. It is urged that urgent conservation measures, especially of the most threatened species of birds, are necessary.

Abstract: In this study we explore various non-destructive methods for the determination of density of 27 non-porous natural stones. Among the methods investigated the most accurate method was found to be the mass-based suspension method that uses Archimedes principle, with costs of equipment less than 20$. We have used this density measurement method to measure densities of natural stones and copper reference cube in the range of 1.07 – 8.93 g×cm-3, for stones that have volumes less than 16.4 cm3. The measurement are in excellent agreement with more precise methods that use a 4 decimal place analytical balance. The measurement uncertainty of the method was assessed with a Cu density reference cube and was found to be of the order of 0.1% in measuring the volume of stones with arbitrary shape. Finally, we provide details of the design features of a new liquid-based pycnometer that can measure the density of irregular shape natural stones without the need to form a powder. This pycnometer can also be used to measure density changes in liquids as a function of temperature and solute concentration.

Abstract: The hierarchy problem, the anomalous weakness of gravity relative to other fundamental forces, remains one of the most persistent challenges in theoretical physics. Here we introduce the Information Lattice Model (ILM), a framework that reinterprets gravity not merely as spacetime curvature but as the macroscopic manifestation of directed informational flow across a permeable, multi-layered lattice spanning our observable 4-dimensional brane and a higher-dimensional bulk. In the ILM, mass-energy density modulates the bandwidth of inter-node links, naturally accounting for gravitational weakness via trans-layer dilution and resolving the black hole information paradox through lattice-mediated data transfer. The model aligns with recent developments in braneworld scenarios, Causal Dynamical Triangulations, and holographic principles, while generating two falsifiable predictions: anomalous attenuation in high-frequency gravitational wave spectra detectable by LIGO/LISA, and non-linear deviations in quantum decoherence rates near lattice saturation. Beyond its physical core, the ILM offers a speculative but theoretically grounded framework for technosignature detection, proposing that advanced intelligences may be identified by their degree of lattice sovereignty, and for Unidentified Anomalous Phenomena (UAP), reinterpreted here as bulk-brane perturbation events. We also identify consciousness as a participatory interface within the lattice architecture, whose neural complexity functions as a biological transducer of bulk-brane informational coupling. This structural continuity between mind and lattice suggests that UAP encounters may constitute bilateral informational exchange events sharing common substrate in the higher-dimensional bulk.

Abstract: The ZNF469 transcription factor and collagen-homologous matrix contributor, first related to recessively inherited brittle cornea syndrome, was found variant in 8 patients with Ehlers-Danlos syndrome and an additional 14 from the literature with related connective tissue findings. Systematic documentation of skin, skeletal, cardiovascular, and neuro-autonomic findings in the 8 patients supported the diagnosis of Ehlers-Danlos hypermobile type, component diagnoses of aneurysms-dissections or blue sclerae-skeletal change predominating in 9 patients having cardiovascular screening or 5 carriers among many in brittle cornea syndrome families. Locations of these 22 patient variants along with 60 related to EDS and 68 to brittle cornea syndrome from the ClinVar database were spread throughout the 3953 amino acid ZNF469 coding sequence. Heterozygous variants except for 3 in a zinc finger region were associated with diagnoses of Ehlers-Danlos syndrome or its component findings, all documented or inferred biallelic ZNF469 variations except for one associated with brittle cornea syndrome. Limitations of this study point to the need for matching of systematically evaluated patients with the multiple DNA variants inherent in complex disease, network action exemplified by the fibrillar participation and regulatory feedback of ZNF469.

Abstract: Regenerative agriculture (RA) is expanding across the Western Canadian Prairies, but its microbial foundations under climatic constraints remain insufficiently integrated. This review synthesizes evidence from long-term prairie field experiments, regional datasets, and global meta-analyses to evaluate how regenerative management reshapes soil biological processes and system performance. Across studies, RA is consistently associated with increases in microbial biomass, enzymatic activity, arbuscular mycorrhizal connectivity, and nitrogen-use efficiency, alongside gains in soil organic carbon, aggregation, and water-holding capacity. These biological enhancements correspond with lower soilborne disease pressure, moderated weed dynamics, reduced dependence on synthetic nitrogen and pesticides, and progressively stabilized yields under semi-arid, short-season conditions. Prairie findings broadly align with global regenerative trends, although short-term and site-specific responses range from negative to positive, underscoring the importance of temporal scale. In regions characterized by high interannual climate variability, conserved microbial mechanisms appear central to resilience, while the rate at which agronomic benefits emerge depends on climatic and edaphic constraints. Overall, the synthesis identifies microbial restoration as the central pathway linking regenerative management to soil health, pest suppression, and sustainable productivity. Continued long-term, system-level research is needed to refine regionally adapted regenerative transitions and to clarify how microbial processes mediate resilience under future climate uncertainty.

Abstract: Oxidative stress accelerates skin aging by causing damage to DNA, lipids and proteins in skin cells. Exacerbated by environmental factors such as UV rays, pollution and smoking, it leads to loss of elasticity, the appearance of wrinkles, cutaneous dryness, pigmentation spots and a general weakening of the skin's natural defenses. These changes, accumulated over time, are responsible for premature or accelerated aging. Against this backdrop, PAOTScan is an innovative, non-invasive technology for assessing the oxidative state of the skin in real time. The device is based on a patch equipped with microelectrodes and an electrochemical gel. It provides two essential scores: the PAOTScore, which measures the skin's Total Antioxidant Power to neutralize free radicals, and the POTScore (Total Oxidant Power), which quantifies the level of oxidants. These data provide a detailed analysis of the skin's redox balance, enabling early detection of imbalances responsible for premature aging. The PAOTScan not only measures the speed of skin ageing, but also enables prevention and treatment strategies to be adapted. It is therefore an invaluable tool in dermatology and dermato-cosmetics, making it easier to monitor the effectiveness of anti-aging interventions and helping to preserve the skin's health and youthfulness.

Abstract: Cephalonomia stephanoderis (Hymenoptera: Bethylidae) is a solitary ectoparasitoid of Coffee Berry Borer (CBB) that is established in the field in Puerto Rico but poorly studied. Five coffee farms in Maricao, Lares, Utuado, Adjuntas, and Jayuya were surveyed monthly from February 2022 to January 2023 for evidence of C. stephanoderis. On each collection date, fifty dry and fifty mature ripe coffee berries were collected from the tree and held for emergence of CBB adults and parasitoids. From January to April 2023, we collected 50 dry berries (“raisins”) from the same sites but placed each berry in a separate tube to count the number of C. stephanoderis and the number of unparasitized CBB adults which emerged so that we could estimate percent parasitism. In 2022, results showed that dry berries produced significantly more parasi-toids than mature berries. Infested coffee berries from Adjuntas contained the most C. stephanoderis and coffee berries from Jayuya had the fewest. Temperature negatively affects the parasitoid population, while relative humidity and alti-tude effects were not significant. In 2023, the parasitoid population was highest in February and decreased steadily until the end of sampling in April. The percentage parasitism ranged from 2.79% to 4.97% across collection sites. The potential for augmentation biological control for C. stephanoderis and classical biological control via the introduction of other CBB parasitoids are discussed.

Abstract: The high viscosity of biodiesel fuel, caused by the presence of saturated fatty acid esters, limits its application, particularly at low temperatures. Supercritical fluid extraction (SFE) using carbon dioxide represents a promising method for selective fractionation, enabling the removal of high-viscosity saturated components and the enrichment of the fuel with less viscous unsaturated esters. However, the rational design of such processes requires a deep understanding of the interrelationship between flow hydrodynamics, thermodynamic conditions, and mass transfer in a supercritical medium. In this work, a comprehensive computational fluid dynamics (CFD) modeling study of the fractionation process was performed for a model ethyl oleate/ethyl palmitate mixture (25.28:74.72 wt.%) in supercritical CO2 at pressures of 11 and 14 MPa and a temperature of 40 °C. A three-dimensional model of a laboratory-scale extractor was developed using the ANSYS Fluent software environment. Since the target esters are absent from the standard material database, a custom property library and compiled User-Defined Function (UDF) routines were developed. These describe the temperature dependence of density, viscosity, heat capacity, and thermal conductivity for both the individual components and their mixture using established mixing rules. The calculations employed an Eulerian multiphase model, the realizable k–ε turbulence model, and species transport equations. The modeling revealed pronounced selectivity: under the chosen thermodynamic conditions, ethyl palmitate is extracted preferentially over ethyl oleate, with this difference becoming more pronounced as pressure increases. The developed and verified CFD model deepens the fundamental understanding of hydrodynamics and mass transfer during supercritical fractionation and serves as a basis for optimizing process parameters to produce biodiesel with reduced viscosity. The regime at P=14 MPa and t=40 °C provides the most favorable thermodynamic and hydrodynamic conditions for the selective removal of saturated esters.

Abstract: Background/Objectives: Kawasaki’s disease (KD) is a leading cause of heart disease in children. The multisystem inflammatory syndrome (MIS) associated with the SARS-CoV-2 virus is similar to KD. The etiologies of KD and MIS are unknown. Both diseases are associated with pathogens and immunizations. Methods: The Vaccine Adverse Event Reporting System (VAERS) was retrospectively examined for etiology insights into both KD and MIS. Results: Immediate-onset KD-associated safety signals were detected for specific vaccines and coadministered combinations of these vaccines for young infants; a subset of these associations have a male sex bias, whereas others appear to be sex neutral. These specific vaccines may contain manufacturing contaminants (e.g., endotoxins) that are activating mast cells via Toll-like receptors. MIS-V cases were enriched in children of all ages. Conclusions: Both KD and MIS appear to involve two activation pathways. The first pathway involves high titers of immune complexes that activate Fc receptors on mast cells, platelets, and other immune cells. Immune complex titers higher than primary immune response levels are predicted to be required to activate low-affinity IgG FcgR2α receptors on immune cells and platelets. IVIG treatment is predicted to directly compete with immune complex binding to FcgR2α receptors. The second pathway appears to directly activate mast cells and other immune cells without involving immune complexes or Fc receptors. Cardiac adverse events, coronary artery aneurysms (CAAs), myocarditis, transient left ventricular dysfunction, and acquired heart disease are predicted to result from pressure induced lesions indirectly caused by cardiac capillary vasoconstrictions. Second, mast cell activation (e.g., endotoxin contaminants) or persistent infections are likely causes of IVIG nonresponders for KD and MIS. MIS appears to be KD associated with the SARS-CoV-2 virus or the COVID-19 spike protein (MIS-V).