Abstract: Background: Polyphenols interact bidirectionally with the gut microbiota and may enhance short‑chain fatty acid (SCFA) production, yet evidence from human randomized controlled trials (RCTs) has not been comprehensively synthesized. Objectives: This systematic review and meta‑analysis evaluated the effects of polyphenol supplementation on gut microbiota composition, microbial diversity, and fecal SCFA concentrations in adults, and examined moderators of these effects. Methods: Five databases were searched through October 2023 for RCTs assessing oral polyphenol supplementation in adults. Eligible studies reported outcomes related to gut microbiota composition or fecal SCFAs. Random‑effects meta‑analyses were conducted for SCFA outcomes, and subgroup analyses examined effects by polyphenol class, dose, duration, health status, and analytical methods. Risk of bias was assessed using the Cochrane RoB 2 tool, and certainty of evidence using GRADE. Results: Fifty RCTs (n = 2,042 participants) were included. Polyphenol supplementation increased total SCFAs in 70.6% of studies and significantly increased butyrate concentrations (pooled SMD = 0.48; 95% CI: 0.32–0.64; I² = 58%). Acetate and propionate increased in 75% and 71.4% of studies, respectively. A consistent shift toward a more butyrogenic fermentation profile was observed. Polyphenols enriched beneficial genera, including Bifidobacterium (81.8%), Akkermansia muciniphila (50%), and Faecalibacterium prausnitzii (45.5%), while reducing potentially pathogenic taxa such as Enterobacteriaceae and Clostridium spp. Improvements in alpha diversity were reported in 66.7% of studies, and beta diversity separation in 87.5%. Effects were stronger in individuals with metabolic disorders and in interventions lasting ≥12 weeks. Conclusions: Polyphenol supplementation consistently enhances beneficial gut bacteria, increases SCFA production, particularly butyrate, and improves microbial diversity in adults. These findings support classifying polyphenols as bioactive prebiotics that meet ISAPP criteria. This term underscores their distinction from traditional prebiotics within our proposed five-phase model: whereas fibers are characterized by their fermentability, polyphenols integrate direct antimicrobial activity against pathogenic species (e.g., Staphylococcus aureus, Enterobacteriaceae) with their role as selective substrates for beneficial microbes. This dual mechanism of action suggests that polyphenols do not merely supplement the microbiota but actively reshape it by pruning harmful taxa while fertilizing beneficial ones. Polyphenol-rich strategies represent promising microbiota-focused approaches; however, while shifts in microbial profiles coincide with better metabolic health, further research is required to bridge the correlation-causation gap and confirm whether these microbial changes directly drive clinical outcomes.

Abstract: Events such as landslides and slope failures happen suddenly and can be catastrophic. To predict the onset of such events, as well as the flow and final deposition of the material, engineers make use of numerical modeling techniques. These events are associated with large deformation and mesh-based methods, such as the finite element method, are not capable of modeling them due to mesh distortion. The material point method (MPM) is a particle-based continuum method capable of modeling large deformation and material flow. In this paper, MPM is used to model the sudden and dynamic flow of material by modeling the collapse and runout of a non-cohesive sand column. The results from two- and three-dimensional models are compared to experiments, showing that MPM accurately predicts the free-surface profile of the material during collapse. Furthermore, the model accurately predicts the runout distance with an error of less than 5%.

Abstract: How life originated in the ancient abiotic world is one of the most fundamental questions in modern bioscience. To address this problem, I propose a scientifically credible, fact-based scenario involving a pre life molecular entity that ultimately gave rise to living organisms. This entity consisted of DNA and RNA, in which double stranded linear DNA replicated in a calm environment with the assistance of RNA and served as a stable repository of information essential for evolution and survival. In the same environment, RNA molecules with catalytic activity replicated exclusively in stem–loop forms and gave rise to ribosomal and transfer RNAs. Under such calm, ribonucleotide rich conditions, the information stored in double stranded linear DNA was transcribed into messenger RNA. The seemingly improbable emergence of the extraordinarily complex translational system is hypothesized to have occurred through extended wobble-based recognition of all messenger RNA triplets by only two prebiotic tRNAs, enabling protein synthesis. Finally, independently evolved rRNA and tRNA are proposed to have been abiotically reverse transcribed and integrated into DNA based entities in a calm, deoxynucleotide rich environment. Thus, DNA and RNA are functionally interdependent: DNA stores genetic information encoding essential RNAs and produces self-beneficial protein products, whereas information stable double stranded DNA relies on RNA for its replication and transcription, particularly in calm prebiotic environments. This mutual dependence establishes a self-sustaining molecular system capable of problem solving, thereby enabling the emergence and evolution of life.

Abstract: To alleviate the shortage of natural river sand and promote the utilization of aeolian sand, concrete was prepared by replacing river sand with Taklamakan Desert aeolian sand at different mass ratios. The effects of replacement ratio and curing age on compressive strength and microstructure were investigated using compressive strength tests, SEM, and EDS. A quadratic regression model was established by response surface methodology using replacement ratio, curing age, and Ca/Si ratio as variables. The results showed that compressive strength first increased and then decreased with increasing aeolian sand content, with the 20% replacement group achieving the highest strength. Strength increased with curing age, but the growth rate slowed after 28 days. SEM and EDS results indicated that suitable aeolian sand content promoted hydration product formation and matrix densification, whereas excessive replacement increased pores and interfacial defects. The Ca/Si ratio generally increased with curing age. The model showed good fitting accuracy, with R² = 0.9970, providing a reference for strength prediction and mix design optimization of aeolian sand concrete. Keywords: aeolian sand concrete; compressive strength; microstructure; Ca/Si ratio; response surface methodology

Abstract: Background/Objectives: Endodontic success in maxillary first molars is often complicated by their complex anatomy, increasing the risk of procedural errors in "danger zones" where dentine is thin. While global data on root morphology exists, population-specific information for South Africans is lacking. This study aims to quantify root dentine thickness in a Black South African sample using a novel software program to enhance accuracy for preoperative planning and improved clinical outcomes. Methods: Micro-CT scans of 97 maxillary first molars (57 individuals) were analyzed. Den-tine thickness was measured at 0.1 mm intervals using a novel surface-to-interface software tool, which enabled automated, high-precision quantification of complex curved geometries. Data were standardized into 1 mm segments for analysis. Reliability trials confirmed high precision (within 0.0001 mm). Results: Buccal and lingual surfaces of mesiobuccal and distobuccal roots were consistently thicker than mesial and distal surfaces. All roots showed progressive thinning toward the apical third. Conversely, palatal roots exhibited an opposing pattern with mesial and distal surfaces that were thicker than buccal and lingual aspects. Age correlations were not statistically significant. Conclusions: The study identifies specific anatomical patterns in root dentine thickness within a South African sample. The thinner mesial and distal walls of buccal roots represent critical "danger zones" for clinicians. The novel software proved highly effective for precise morphometric mapping and offers a versatile framework for broader endodontic research. These findings provide essential data for optimizing endodontic treatment strategies and the development of population-specific dental instruments.

Abstract: This paper introduces the Generalized Coordinate System (GCS) as a framework for analyzing and generating rhetorical modes---the conventional patterns of discourse. The GCS is composed of low-dimensional, mediating and high-dimensional axes. The low-dimensional axes are Thing, Feature, Quantitative Attribute, Qualitative Attribute, Formal Attribute axes and form the objects or foundational elements for rhetorical modes. The mediating axes are Basic Expressive-Representational Elements and Rhetorical Mode axes and transform the raw material into communicable languages. The high-dimensional axes include Cognitive Function axis, Epistemic Purpose axis and the Five-Level Expression Staircase axis (Depth axis). The high-dimensional axes determine the cognitive depth and ultimate purpose, and capture the developmental progression of language competence- from raw perception to paradigm-shattering insight. Three types of semantic or modal mapping are defined: low-dimensional mapping (from low-dimensional axes to the mediating axes), high-dimensional mapping (from the mediating axes to high-dimensional axes), and full-dimensional mapping. These mappings form a pyramidal hierarchy, progressing from foundational elements (things, features, and attributes) to higher-order cognitive functions and epistemic purposes. By employing three core logical structures---combinatory, parallel, and embedded---the GCS consolidates infinite expressive possibilities within the finite intersections of its axes. The system's generative capacity, quantifiable by the number of axis intersections (generalized mode number), enables the navigation of nearly infinite expressive variations while steering practical applications toward finite, purpose-driven goals. The GCS transitions rhetorical modes from a static taxonomy to a dynamic analytical system for discourse construction and analysis, offering possibly insights for the development of large language models through the integration of a programmable rhetorical mode system.

Abstract: Recent research in cancer detection and monitoring is based on the development of multi-agent systems. They are used for multidimensional multimodal health data integration, medical data augmentation, knowledge representation, predictive diagnosis, and personalized treatment schemes. This paper addresses the last two challenges by introducing intelligent agents to build clustering, classification, and treatment-recommendation models, while also improving overall process time through feature selection and the identification of critical malignant cases. In the first stage, the Wrapper Selection Agent based on Random Forests generated an optimized model with a 98.68% accuracy. Then, the Outlier-based Clustering and Critical Malignant Cases Agents detected the critical malignant cases with a 0.84 Silhouette Score. In the next step, Treatment Clustering and Decision Rules Agents built a perfect model that proposes a personalized treatment for the patients identified by the previous agents. The entire process is automated and provides treatment recommendations in 32.85 seconds.

Abstract: Background: The adaptogen concept, first formalized over half a century ago, describes pharmacological agents that increase nonspecific resistance to stress. Despite extensive clinical evidence supporting the efficacy of adaptogenic botanicals, the concept has re-mained largely phenomenological, lacking a mechanistic framework compatible with modern molecular pharmacology. This has limited its acceptance in evidence-based medi-cine. Aims: We propose that hydroponically cultivated red Panax ginseng preparation HRG80, with its chemically reproducible composition and multilevel evidence base, constitutes a case study through which the mechanistic basis of adaptogenic action can be examined across molecular, cellular, neurophysiological, and clinical levels. Methods: We identified all published preclinical and clinical studies conducted on HRG80 through PubMed, Scopus, and manual citation tracking (last search: March 2026). Ten published studies met the inclusion criterion, including three randomized, dou-ble-blind, placebo-controlled clinical trials and two open-label trials, encompassing ap-proximately 440 human subjects. One manuscript in preparation and one unpublished preclinical gut-brain axis dataset were included with appropriate caveats. We integrated transcriptomic, electrophysiological, in vitro, in vivo, and clinical evidence into a pro-posed mechanistic model. Results: The converging evidence supports a three-tier temporal model of adaptogenic ac-tion. The acute tier (minutes to hours) involves modulation of NMDA and Kainate gluta-mate receptors, enhancing hippocampal long-term potentiation. The subacute tier (days to weeks) involves activation of CREB signaling and the slit-robo axonal guidance pathway, producing structural neuroplasticity functionally equivalent to brain-derived neu-rotrophic factor stimulation. The chronic tier (weeks to months), based on in vitro evidence in non-neuronal models, involves DNMT inhibition and epigenetic reprogramming, sug-gesting a potential mechanism for durable changes in cellular stress resilience. Tran-scriptomic analysis identified 1,061 genes uniquely modulated by the whole extract and not by isolated ginsenosides, consistent with the hypothesis that the adaptogenic effect is an emergent property of the phytochemical network. Preliminary preclinical data from a gut-brain axis model suggest that HRG80 protects intestinal barrier integrity and attenu-ates neuroinflammation, providing a plausible systemic pathway from oral intake to cen-tral effects. Conclusion: HRG80 provides convergent multilevel evidence suggesting that adaptogenic nonspecificity may reflect a hierarchically organized multi-specificity operating across distinct temporal scales. If confirmed by independent replication and further mechanistic studies, this framework could offer a template for the systematic investigation of other adaptogenic botanicals.

Abstract: Background and Objectives: Chronic diabetic foot ulcers (DFUs) and venous leg ulcers (VLUs) remain a major source of morbidity, healthcare utilization, and limb loss, despite adherence to established standards of care protocols and the widespread availability of advanced wound technologies. Many advanced modalities only target isolated aspects of wound healing and fail to address the complex, interdependent pathophysiology of chronic wounds, particularly tissue hypoxia, edema, impaired microcirculation, and persistent inflammation. Cyclical Pressurized Topical Wound Oxygen (TWO2) therapy is a home‑based, multimodal intervention that combines humidified topical oxygen delivery with cyclical non‑contact compression to address these core drivers simultaneously. Materials and Methods: This review synthesizes mechanistic rationale and evidence from randomized controlled trials, long-term venous ulcer studies, and real-world comparative effectiveness analyses. Emphasis is placed on the large cohort study by Yellin et al., which directly compared TWO2 with other advanced modalities including negative pressure wound therapy (NPWT), skin substitutes, and growth factor therapies. Results: Across these studies, TWO2 therapy is consistently associated with improved healing durability, reduced recurrence, and substantial reductions in hospitalization and amputation rates compared with both standard care and advanced wound therapies. Conclusions: The convergence of randomized and real‑world evidence supports TWO2 therapy as a clinically meaningful and mechanism‑driven adjunctive treatment option for patients with chronic, high‑risk lower‑extremity wounds.

Abstract:

Background: Highly educated migrants in Norway often experience prolonged delays before accessing employment that matches their qualifications. During this period, many participate in compulsory education, language training, or work in jobs unrelated to their professions. This study explores how the introductory program for migrants and work outside one’s professional field shape health, identity, and the broader integration process. Methods: We conducted semi‑structured interviews with eight highly educated migrants enrolled in the introductory program in Kristiansand municipality in Norway. Interviews focused on experiences with the program and employment unrelated to the participants’ professional backgrounds. All interviews were transcribed verbatim and analyzed using reflexive thematic analysis and informed by Social Identity Theory. Findings: Participants described employment, and particularly their former professions, as central to their self-esteem, sense of meaning, and social belonging. Prolonged credential recognition processes and limited opportunities for meaningful social contact due to employment status loss, contributed to feelings of stagnation, exclusion, and weakened professional identity. Many participants emphasized a strong desire to contribute to society and regain their professional status. While the introductory program offered valuable peer support and facilitated language learning, it was not experienced as a direct pathway to inclusion in Norwegian society and professional work life. The findings indicate that early access to work-based integration opportunities, such as internships or relevant job placements, may enhance well‑being, foster language acquisition, and strengthen social inclusion for highly educated migrants. Conclusion: The study findings suggest that policymakers and practitioners should prioritize measures that streamline credential recognition and expand early, relevant work-based integration opportunities. Such approaches can improve language development, support identity reconstruction, strengthen social belonging, and ultimately promote better health and integration outcomes for highly educated migrants.

Abstract: The Minimum Dominating Set problem is NP-hard, and the best known polynomial-time approximation factor is O(ln n), which is provably tight unless P = NP. We present a polynomial-time algorithm that reduces an arbitrary input graph to a planar kernel through forced-vertex extraction, pendant elimination, and greedy planarisation, and then applies Baker’s PTAS to that kernel. The algorithm runs in O(mn + m log m) time — in particular O(n log n) on sparse graphs — and is provably within twice the optimum whenever the reduction is tight. We give a structural witness mapping that injects the post-pruning forced-boundary set into the rest of the planar kernel, narrowing the unresolved gap in the analysis to a single inequality, |F| ≥ 2|F_R^pruned|. Should that inequality hold universally, a 2-approximation would follow and would imply P = NP. We complement the theory with an experimental study on thirteen DIMACS benchmark graphs: in every case the algorithm finishes in well under five minutes and returns a dominating set whose size is at most 1.80× the ILP optimum, with an average ratio of 1.42. An open-source implementation is provided as the Furones package (v0.2.6).

Abstract: We derive, from a well-defined action principle, a redshift-dependent perturbation \( \alpha(z) \) to the dark energy density that arises when a canonical scalar field \( \phi \) couples to a spontaneously confining hidden \( SU(N) \) gauge sector through a chiral anomaly portal. The ultraviolet cutoff of the effective theory is fixed, without adjustment, at Λ_UV = 13.6 TeV, consistent with the null results of the Large Hadron Collider (LHC). The confinement scale of the hidden sector is set equal to that of Quantum Chromodynamics, Λ_QCD = 300 MeV, providing the infrared anchor of the construction. A perturbative expansion around the ΛCDM background yields a closed-form ordinary differential equation (ODE) for \( \alpha(z) \), whose solution reproduces the expected transition behaviour at \( z_c \approx 0.7 \) and leaves a cosmologically small but non-zero residue at \( z=0 \) from the TeV anomaly. The resulting effective equation-of-state parameter \( w_{eff}(z) \) departs from -1 by at most \( 2\% \) at low redshift, yet generates a \( 6\% \) suppression in the matter fluctuation amplitude \( \sigma_8 \) relative to ΛCDM, in the direction required to reduce the present \( 2-3\sigma \) discrepancy with weak-lensing measurements. All parameters are either fixed by known physics or by numerical convergence criteria; none is tuned to reproduce a pre-specified output. A dedicated section on falsifiability examines experimental signatures at LHC, ALPS~II, neutron electric-dipole moment (nEDM) experiments, and the Eöt-Wash torsion balance. The scope and domain of validity of the construction are stated explicitly in a limitations section.

Abstract: This paper introduces the dual process machine learning paradigm, which builds upon the unified machine learning and physics field framework. By integrating machine learning architectures and physics models into a single field-theoretical entity and constructing hidden layers and learning weights based on physical systems, complex machine learning is interpreted as a set of physical interactions. The super dual process machine learning leverages duality relations inherent in physical systems, enabling a simplified "dual" process to replicate the statistical behavior of the original complex "primary" process. We demonstrate that the super dual process opens a new pathway for AI engineering, wherein algebraic structures from underlying physical principles guide model design and computation. We present both the theoretical foundations and practical implementations of super dual machine learning, achieving improved scalability and efficiency compared to traditional methods.

Abstract: One of the most common dynamic phenomena occurring in surface waters is the transport of soluble and insoluble contaminants from various sources (e.g., industry, agriculture). A key concern associated with this transport is the rate at which contaminants migrate downstream to a point of interest, as well as their overall impact. To characterize contaminant transport in a surface water body (in this case, a river), this study applied a one-dimensional advection-dispersion model incorporating transient storage effects. This allowed for the characterization of nutrient transport, considering varying flow velocities along the river’s course. This work adopts a more comprehensive, or systemic, approach to enable a more holistic environmental application, facilitating parameterization of a considerably larger river than previous case studies. The novelty of the model lies in the use of conventional pollutants as potential tracers that allow characterizing the mixing conditions and pollutant transport in surface water streams, as well as in its dynamic nature, which provides a reasonable approximation of the real system’s behavior over time. Finally, for management purposes, the proposed model is replicable without the need for extensive changes, which may be required in its fundamental structure.

Abstract: Background: Chronological age remains deeply embedded in perioperative risk assessment because it is readily available and intuitively linked to adverse outcomes. In clinical practice, however, patients of similar age frequently experience markedly different postoperative trajectories. This observation may suggest that physiological reserve, rather than years lived, more accurately reflects vulnerability to surgical stress. We therefore examined whether age-based stratification misclassifies perioperative risk when compared with functional phenotyping using frailty status and baseline handgrip strength. Methods: We conducted a prospective, multicenter observational cohort study including 223 adults undergoing elective abdominal surgery between January 2023 and June 2025. Chronological age was evaluated both continuously and using a conventional threshold (<70 vs ≥70 years). Physiological reserve was characterized using a phenotype-based frailty model (fit, pre-frail, frail) and baseline handgrip strength measured at hospital admission. Prolonged hospitalization, defined a priori as a length of stay exceeding 10 days, was used as an external benchmark to examine classification performance. Analyses were primarily descriptive and classificatory, focusing on discordance, overlap, and risk re-ranking across age and functional strata rather than outcome prediction. Results: Substantial discordance was observed between chronological age and frailty phenotype. Among patients younger than 70 years, 7.7% met criteria for frailty, whereas 58.0% of patients aged 70 years or older were classified as fit or pre-frail. Prolonged hospitalization occurred in 48 patients (21.5%) and varied markedly by frailty status within each age group. Frail individuals consistently exhibited the highest hospitalization burden regardless of age, while fit and pre-frail older patients often demonstrated outcomes comparable to, or better than, younger fit patients. Baseline handgrip strength showed wide dispersion and extensive overlap between age groups, indicating substantial inter-individual variability in physiological reserve that chronological age alone did not capture. Conclusions: Chronological age appears to provide limited discriminatory resolution for perioperative risk stratification. Functional phenotyping using frailty status and baseline handgrip strength may better reflect underlying physiological reserve and support more individualized, function-centered perioperative decision-making.

Abstract: The classification of banana ripeness remains an important task in the food industry, as it directly affects the quality of the product and its shelf life. This paper presents an automated ripeness assessment system implemented using a comparative analysis of machine learning and deep learning algorithms. We tested the effectiveness of Random Forest, a custom CNN model, as well as the pre-trained ResNet50, EfficientNetB0, and VGG16 models, based on a dataset of 9960 images categorized into 3 ripeness stages (overripe, ripe, unripe). The results show the superiority of deep neural networks over classical methods: the ResNet50 architecture demonstrated 98% accuracy with a macro-averaged F1-score of 96%. The implementation of the proposed solution in the retail sector can automate ripeness monitoring and significantly reduce food waste.

Abstract: This study aimed to evaluate whether the Synerjet system can maximize the trans-dermal delivery and skin rejuvenation of nano-NMN. In a 4-week split-face trial (n=21), this combination demonstrated marked clinical superiority over topical nano-NMN alone (p < 0.001), yielding enhanced improvements in wrinkles (170.56% in periorbital and 154.45% in nasolabial, respectively), pore volume (176.62%), and deep hydration (188.02%). Regarding dermal integrity, the test group showed a 111.56% superior increment in skin elasticity and a 149.75% more effective optimization of melanin intensity. Notably, deep-tissue hydration at a 2.5 mm depth demonstrated a 188.02% higher gain, suggesting that the modality significantly fortifies the skin’s physiological moisture reservoir. The test group exhibited a marked improvement over the control across all cutaneous parameters (p < 0.001). Our findings demonstrate that a new combinatorial approach using EP-assisted microjet of Synerjet system after cold plasma pretreatment and a nano-NMN 10% ampoule resulted in significantly greater improvements in wrinkles, pores, elasticity, pigmentation, and deep skin hydration compared to topical application alone. Consequently, these results demonstrated that Synerjet system effectively overcome the inherent lim-itations of nano-delivery technologies, offering a promising modality for advanced cutaneous rejuvenation and a robust framework for future professional dermatological treatments.

Abstract: Background: The late-time fate of black holes and the operational limits of General Rel ativity (GR) in the far future remain open problems in thermodynamic cosmology, and are central to the causal gap discussed in Penrose’s conformal framework. Objective: We determine, within Gibbs Energy Redistribution Theory (GERT), the lower density boundary of GR validity and the thermodynamic fate of supermassive black holes in the Hyperdilute Regime. Methods: Using the asymptotic gas-dominated GERT term, we derive the critical crossing λ_CMB(a) = H−1(a), compute acrit and ρGR,min analytically, and evaluate black-hole thermody namic states (including ∆G and inversion scales) across mass ranges, with no additional premises beyond the base framework. Results: We obtain acrit = 10^12.88±0.12 and log₁₀(ρGR,min) = −65.2 ± 0.4 kg/m³, closing the Layer 3 validity domain from Planck density to a symmetric lower operational threshold (161.9 density decades). At acrit, all black holes with M > M^∗ ≈ 1.7 × 10⁵M⊙ are in thermody namic absorption, with strongly non-spontaneous redistribution (e.g., ∆G ≈ +5800Mc² for 10⁹ M⊙). Thermal inversion occurs later in the Quasi-Vacuum, where cosmological cooling out paces Hawking thermal change by ∼ 10¹⁰⁶; at a_inv(M), supermassive-black-hole Schwarzschild radii exceed the Hubble radius by factors of 4 to 10¹⁰. Conclusions: In this regime, Hawking evaporation is not the operative end-channel for high mass black holes. GERT instead identifies a Gibbs-driven macroscopic phase transition (∆G < 0 in the Quasi-Vacuum) and establishes a symmetric but dynamically inverted boundary struc ture for Layer 3: Inward-dominated at emergence (dH/da < 0) and Outward-dominated at dissolution (dH/da > 0). This provides a quantitative thermodynamic completion scenario and a causal contribution to the CCC end-state problem.

Abstract: Extracellular lipid-containing particles are usually interpreted as extracellular vesicles, lipoproteins, soluble lipid mediators, or carriers of molecular cargo. This article proposes the lipid-state exchange hypothesis (LSE), a falsifiable framework in which cellular or tissue lipid states can be externalized, partially retained, remodeled by biological fluids, and sampled by target cells or clearance systems as functional state inputs. LSE reframes lipid state as a causal variable in extracellular particle biology, linking lipid composition, interfacial organization, carrier presentation, and fluid-phase identity to biological function.LSE is developed in weak, intermediate, and strong forms. Weak LSE places lipid-state function within known extracellular vesicle and lipoprotein biology. Intermediate LSE emphasizes that carrier form, interfacial presentation, and fluid-phase identity can reshape lipid function. Strong LSE predicts a lipid-state-dependent functional layer beyond established extracellular particle classes and cargo-centered mechanisms.The key empirical prediction of strong LSE is the existence of non-classical lipid-state exchange particles (non-classical LSEPs). Operationally, these candidates are expected to appear as extracellular lipid-dominant particle-like or complex-like components with low canonical extracellular-vesicle and classical apolipoprotein markers. Functionally, they are defined by source-state association, lipid-state-dependent activity, and positive causal residuality when conventional particle-, cargo-, and artifact-based frameworks cannot sufficiently explain their effects. Thus, non-classical LSEPs are not proposed as a marker-defined particle class, but as a lipid-state-dominant functional entity.At a broader level, LSE shifts extracellular lipid biology from particle identity and cargo attribution to state causality. It opens a conceptual space in which membrane-derived lipid organization itself may act as a transferable, fluid-edited, and biologically sampleable state-bearing interface for homeostatic regulation, injury interpretation, and disease-relevant extracellular communication.

Abstract: The European crafts ecosystem faces critical structural threats, declining practitioner numbers, weakening intergenerational transmission, limited digital literacy, and competition from industrial imitation. Existing online craft communities are narrowly material-specific and structurally illsuited to the cross-disciplinary dialogue required for systemic sector transformation. This paper presents the design, iterative development, and pilot evaluation of the Craeft Community, a multi-stakeholder Virtual Community of Prac-tice (VCoP) developed within the Horizon Europe CRAEFT project. Three research questions guided the study: how a multi-stakeholder VCoP should be structured to overcome disciplinary fragmentation; to what extent a stewarded digital forum can operationalize Situated Learning and Communities of Practice theory and what factors facilitate or inhib-it engagement and post-funding sustainability. Using design-based research, the platform evolved through four iterative phases, culminating in restructuring from a material-based architecture into five transversal thematic pillars, driven by survey evidence from 151 European craft professionals and systematic stakeholder feedback. The pilot phase yielded 86 registered members, 31 posts, and 27 interactions, with Transmission & Training as the most engaged pillar. Qualitative analysis reveals substantive cross-disciplinary discourse alongside a structural Effort-Engagement Gap, a persistent tension between forum partic-ipation demands and the gravitational pull of mainstream social media. The study demonstrates that a thematically organized, stewarded VCoP can meaningfully opera-tionalize apprenticeship-based learning in digital settings, advancing craft heritage preservation, economic resilience, and hybrid professional identity formation at the inter-section of craft and technology.