Abstract: Exposed bone fractures (EBF) represent a critical clinical challenge due to the simulta-neous disruption of bone and surrounding soft tissues, requiring multifunctional bio-materials capable of providing mechanical adaptability, structural stability, and bio-logical support. In this study, we developed a smart, shear-thinning, self-healing hy-drogel composed of guar gum, polyvinyl alcohol, gelatin, collagen, and chi-tosan-stabilized manganese phosphate (MnP) micro/nanoparticles. MnP particles were synthesized via a quitosan/ascorbic acid-assisted route and characterized by SEM, DLS, FTIR, and EDS, confirming spherical morphology and successful phosphate incorpora-tion. The resulting nanostructured hydrogel exhibited high porosity (>85%), controlled swelling, pH responsiveness, and efficient rheological self-recovery (>90% storage modulus restoration under cyclic deformation). The system demonstrated non-Newtonian behavior and effective adhesion to skin without irritation after 10 h of contact. In vitro assays using MC3T3-E1 pre-osteoblasts confirmed cytocompatibility and concentration-dependent modulation of cell migration. The incorporation of MnP micro/nanoparticles contributes potential osteogenic functionality while preserving mechanical integrity and dynamic responsiveness. These findings suggest that the de-veloped nanocomposite hydrogel represents a promising auxiliary platform for the treatment of exposed bone fractures.

Abstract: Parkinson’s disease (PD) is a progressive neurodegenerative disorder character-ized by α-synuclein aggregation and degeneration of nigrostriatal dopaminergic neu-rons. Increasing evidence implicates gut microbiota (GM) dysbiosis as a potential con-tributor to PD pathophysiology through bidirectional gut–brain interactions. This narrative review integrates recent taxonomic, functional, metabolomic, im-munological, and interventional evidence linking GM alterations to basal ganglia dys-function. Across multiple cohorts, PD is consistently associated with reduced abun-dance of short-chain fatty acid (SCFA)-producing taxa (e.g., Faecalibacterium, Roseburia) and enrichment of mucin-degrading and pro-inflammatory organisms (e.g., Akkermansia). Shotgun metagenomic studies further reveal alterations in vitamin biosynthesis pathways, carbohydrate metabolism, and microbial network architecture. Metabolomic and Mendelian randomization analyses implicate SCFAs, branched-chain amino acids, bile acids, and GABA metabolism in modulating intestinal permeability, immune activation, and dopaminergic vulnerability. Experimental mi-crobiota transplantation models support mechanistic links involving intestinal barrier disruption, Toll-like receptor signaling, microglial priming, and potential vagal prop-agation of α-syn pathology. Emerging microbiome-targeted strategies—including dietary modulation, probi-otics, prebiotics, fecal microbiota transplantation, and interventions targeting bacterial levodopa metabolism—demonstrate early translational promise. However, inter-cohort heterogeneity and limited longitudinal data highlight the need for precision microbi-ome stratification and prodromal studies. Overall, current multi-level evidence supports gut dysbiosis as a biologically plausible contributor to PD pathogenesis and a promising target for adjunctive nutri-tional and pharmacomicrobiomic interventions.

Abstract: Rheumatoid arthritis (RA) is increasingly recognized as a mucosa-initiated autoimmune disease rather than a disorder that begins within the joint itself. This review synthesizes epidemiological, mechanistic, and experimental evidence supporting a model in which mucosal dysbiosis, altered microbial metabolites, barrier dysfunction, and antigenic mimicry converge to prime systemic autoimmunity. Across gut, oral, and pulmonary sites, RA and at-risk individuals exhibit reproducible microbial shifts, reduced short-chain fatty acid production, increased succinate and indole signaling, and elevated permeability. These changes skew dendritic cell activation, amplify IL-1β/IL-6/IL-23–dependent Th17 responses, impair Treg stability, and lower systemic immune tolerance thresholds. In parallel, microbial citrullinated epitopes and cross-reactive peptides—particularly from Prevotella and Streptococcus species—provide antigenic substrates that may drive ACPA maturation and epitope spreading. While direct causality remains unresolved, we propose that RA initiation reflects cumulative immune conditioning at mucosal interfaces, with joint inflammation emerging as a secondary, tissue-focused consequence of a systemically primed inflammatory state.

Abstract: Red blood cell (RBC) deformability is a key determinant of microcirculatory flow and can be altered in hematological disorders such as chronic lymphocytic leukemia (CLL). This study aimed to evaluate RBC deformability under controlled microfluidic flow conditions and to assess the influence of software platform choice on deformability quantification. RBC suspensions from healthy individuals and untreated CLL patients were analyzed using a microfluidic imaging system across a range of shear rates. A dedicated image-processing algorithm was developed and implemented in two software environments (LabVIEW and Python) to automatically detect deformed cells, measure major and minor cell axes, and calculate the deformability index (DI). Both analytical approaches demonstrated a shear-dependent increase in DI in healthy controls, whereas RBCs from CLL patients exhibited reduced deformability and a blunted response to increasing shear rates, particularly at intermediate shear rates. Although LabVIEW produced consistently higher absolute DI values than Python, both platforms showed strong correlation and preserved the same relative trends and group discrimination. These findings demonstrate that microfluidic image flow analysis provides a robust approach for assessing RBC biomechanics and highlight the importance of standardized image-processing workflows for reliable deformability quantification across software platforms.

Abstract: Objectives: To provide an evidence-based reference for preventing and managing pediatric acute asthma exacerbations by examining epidemiology and long-term trends of hospitalized cases in Beijing over 30 years. Methods: Retrospective analysis of clinical data from children hospitalized for acute asthma exacerbation at Peking University Third Hospital from 1994 to 2023. Data included demographics, onset timing, and hospital stay duration. Participants were categorized into three age groups: toddlerhood (≥1–3 years), preschool age (≥3–7 years), and school age (≥7–15 years) to assess the distribution of pediatric patients across different years, seasons, and months. Results: The study included 1,106 pediatric patients (65.73% male, 34.27% female) with a median age of 4 years. Hospitalizations peaked in 1999 (8.40%) and declined, reaching the lowest point in 2020 (1.45%) during the COVID-19 pandemic. Most admissions occurred in autumn (34.27%), especially in October (13.29%). Preschool and school-age children had higher admissions in autumn, while infants had more admissions in winter and spring. The average hospital stay was 5.35 ± 2.65 days, longest for infants, with no deaths reported. Conclusions: Over 30 years, pediatric hospitalizations for acute asthma exacerbations in Beijing have declined. The majority of patients were male and preschool-age, with peak admissions in autumn. These findings suggest improved asthma management but highlight the need for enhanced prevention and management strategies, especially for male patients, school-age children, and during autumn, to reduce acute exacerbations and hospitalizations. The results suggest that while asthma management for children has improved, further enhancement of prevention and control strategies is still needed. Targeted efforts to reduce acute exacerbations and hospitalizations remain crucial.

Abstract: Aiming at the black hole "singularity" puzzle in general relativity and the dark matter dilemma of the flattening of galaxy rotation curves, traditional theories have core limitations of cross-scale fragmentation and reliance on unobservable entities (such as higher-dimensional space, dark matter particles, etc.). Starting from the universal logarithmic asymptotic behavior of mainstream dark matter halo models, this paper proposes a minimalist gravitational potential framework with a logarithmic correction term (endowed with the core mechanism of "near-repulsion and far-attraction"). Combined with quantum vortices and nested AdS/CFT correspondence, we present a microscopic physical picture, and construct a modified Poisson equation and Schwarzschild metric. This framework makes a parameter-free a priori prediction of the black hole shadows of Sgr A* and M87* at the black hole scale, which is consistent with the Event Horizon Telescope (EHT) observations. The a priori calculation of the periastron velocities of high-velocity stars S4714 and S62 yields errors within a reasonable range. At the galaxy scale, it fits the rotation curves of various types of galaxies including the Milky Way and the Andromeda Galaxy, which is in high agreement with observations, and physically resolves the singularity through the short-range repulsive potential. This paper presents rigid a priori predictions for the shadows of 6 unobserved black holes, among which NGC315 can be used as a crucial experimental source to distinguish this theory from the standard Kerr paradigm. Without invoking dark matter or higher-dimensional hypotheses, this framework, only using the logarithmically corrected gravitational potential, makes it possible to uniformly describe the cross-scale gravitational mechanism with only the mass of ordinary matter. It provides an observable and falsifiable empirical path for quantum gravity research, and makes it possible to pull the research paradigm of pure mathematical modeling of quantum gravity (which requires conditions far from contemporary observations such as the Planck energy scale) back to the empirical research of contemporary physics.

Abstract: This contribution proposes an ontological interpretation of the "neurophilosophy of awakening" through the lens of enactive inference. Here, awakening is conceptualized not as an elusive, irreversible endgame found in classical Asian traditions, but as a process-oriented recognition of reality's fundamental structure. It marks the spiritual moment when consciousness becomes aware of itself—a transition into meta-awareness. Within the framework of processual perspectivism, the "Witnessing-Space" emerges as the central, metastable configuration of an enactive inference system. We describe awakening as a radical reorganization of this space: a transition from fragmented, affectively dysregulated patterns to an integrated perspective where the system discerns its own generative architecture. The Witnessing-Space thus serves as an operative hinge between process-ontological philosophy, empirical brain dynamics, and the existential dimensions of spiritual self-realization. Ultimately, we argue that the study of awakening provides a heuristic key to resolving the classical mind-body problem by exposing the generative mechanisms of phenomenal appearance.

Abstract: Background: The aim of the study was to verify the effectiveness of a 5-week intensive protocol of multilayer bandaging alone or in combination with diet, applied to the clinical practice of lipedema. Methods: 114 women with lipedema were studied, divided into three groups: 35 women were treated with multilayer bandaging in biweekly sessions for 5 weeks, 48 were treated with the same bandaging protocol combined with an anti-inflammatory diet, and 31 women received no treatment. The effect on anthropometry, lower limb volume, pain caused by the tissue fold, and subjective symptoms were evaluated. Results: Women who completed the 5-week intensive protocol of multilayer bandaging showed a statistically significant reduction in all observed parameters: body weight, waist and hip circumference, lower limb volume, pain, and subjective symptoms. The group of women treated with multilayer bandaging and diet showed a significantly greater reduction in lower limb volume and body weight. The treatments were effec-tive regardless of age, BMI, clinical stage, and the presence of fovea in both groups. The wearing time with the multilayer bandage had a positive correlation in the group treated with bandage in combination with diet. Conclusion: A 5-week intensive protocol of multilayer bandaging of the lower limbs is an effective treatment for reducing the symptoms and clinical signs of lipedema at all stages of the disease, even in the absence of edema. Adding nutritional therapy during the bandaging cycle increases the effectiveness of the treatment on the volume of the affected extremities and body weight.

Abstract: This study investigates the structural and antimicrobial properties of coconut water–derived microcellulose biocomposites incorporated with glycerol, chitosan, and silver nanoparticles. Microcellulose-based films were fabricated as silver nanoparticle–deposited microcellulose (MN), microcellulose–glycerol–silver nanoparticles (MG), microcellulose–chitosan–silver nanoparticles (MChN), and microcellulose–glycerol–chitosan–silver nanoparticles (MGChN). Antimicrobial performance was evaluated against Pseudomonas aeruginosa, Staphylococcus epidermidis, and Candida albicans using inhibition zone assays. The MG and MGChN films exhibited enhanced elasticity compared to MN and MChN, indicating the plasticizing effect of glycerol. Enzymatic hydrolysis using xylanase yielded microcellulose particles with sizes ranging from 1.19 to 2.07 μm and induced a bio-bleaching effect. Among all formulations, MGChN demonstrated the highest antimicrobial activity against P. aeruginosa and S. epidermidis (strong category), as well as moderate antifungal activity against C. albicans. Overall, the synergistic incorporation of glycerol, chitosan, and silver nanoparticles significantly improved the antimicrobial efficacy of coconut water–based microcellulose, underscoring its potential for advanced biomedical polymer applications.

Abstract: Research into auxetic foams and their impact on ground reaction forces (GRFs) across diverse neuropathic etiologies is limited. Auxetic foams—closed-cell materials with a negative Poisson’s ratio—conform to irregular foot structures, offering significant rehabilitative potential to mitigate symptoms by optimizing GRF reduction and enhancing gait. Currently, there is a lack of versatile orthoses capable of addressing the heterogeneous subtypes of foot neuropathy. Conducted in collaboration with the National Aeronautics Space Administration/Marshall Space Flight Center (NASA/MSFC), this feasibility study evaluates the efficacy of auxetic foam insoles in reducing vertical GRFs and improving gait across various neuropathic conditions, comparing performance against standard over-the-counter (OTC) insoles. Six participants (five with varying neuropathic etiologies and one healthy control) performed walking trials across force plates (NUL225, NEULOG) under three conditions: barefoot (with socks), OTC insoles, and fabricated auxetic foam insoles. A 3 × 5 Kruskal-Wallis test analyzed the impact of insole type and neuropathic condition on vertical GRFs (?=0.05). Results indicated a significant interaction between insole type and neuropathy. Auxetic foam insoles effectively reduced GRFs in participants with diabetic, neuropathic arthritis, and personal injury-related neuropathy. Qualitative assessments further demonstrated that auxetic foam significantly improved coordination and gait compared to OTC alternatives.

Abstract: The increasing penetration of photovoltaic (PV) systems in distribution networks has introduced new challenges in voltage regulation and energy loss mitigation, particularly under time-varying loading conditions. This paper presents a constrained multi-objective mathematical optimization framework for the optimal allocation and sizing of PV-STATCOM devices in radial distribution systems. The problem is formulated as a nonlinear optimization model that simultaneously minimizes daily energy losses and voltage deviation indices over a 24-hour operating horizon while satisfying network operational constraints, inverter capacity limits, and renewable penetration restrictions. To efficiently solve the resulting non-convex optimization problem, a metaheuristic algorithm based on the Weighted Mean of Vectors (WMV) is employed. The WMV method integrates wavelet-based weighting mechanisms, mean-driven update rules, vector combination strategies, and a local refinement operator to balance global exploration and local exploitation within the feasible search domain. Constraint violations are handled through a penalty-based mathematical transformation of the objective function. The proposed framework is validated on the IEEE 33-bus and IEEE 69-bus distribution systems under realistic daily load variations. Numerical results demonstrate significant reductions in daily energy losses and voltage profile deviations compared to differential evolution, particle swarm optimization, artificial rabbits optimization, and golden search optimization algorithms. Furthermore, convergence analysis confirms the robustness and computational efficiency of the WMV approach in solving large-scale constrained power system optimization problems.

Abstract: Background: Leukaemia is a hematopoietic defect, and the development of this condition has a correlation with the hematopoietic receptor c-MPL. The function of c-MPL is mostly regulated by the crosstalk and stoichiometry of the different isoforms of c-MPL. Although expression of c-MPL in hematological disorders has been studied, the regulation of the isoforms, their balance, and the mechanism of action in conditions like acute and chronic leukaemias and myeloproliferative neoplasms need to be revealed to develop c-MPL as a therapeutic target for leukaemia cases. Methods: The association of c-MPL isoforms with increased tumorigenesis in leukaemia cells was examined using various molecular and cell biology techniques. The significance of the work depends on the statistical analysis of the experimental and technical triplicates. Results: The severity of the leukemic condition directly depends on the increased expression ratio of MPL-FL/MPL-TR. Furthermore, we have observed that with an increase in the MPL-FL/MPL-TR ratio, STAT5 activation increases to promote the transition of HSC from the G0 state to the HSC proliferative state, leading to an increase in the severity. Conclusion: Through this work, we have observed increased c-MPL expression in cells with hematopoietic disorders, but the severity of the condition is independent of the total MPL expression. Our study also provides compelling evidence for the regulatory role of c-MPL isoforms, particularly MPL-FL, in increasing disease severity in blood cancers. This finding is a significant step towards developing c-MPL as a therapeutic target for leukemic conditions like acute and chronic leukaemias and myeloproliferative neoplasms, but it needs a large-scale validation using AML patient samples.

Abstract: Background: Mitragynine pseudoindoxyl (MP) is a semi-synthetic kratom metabolite increasingly sold online and over-the-counter, marketed misleadingly as "kratom" or "7-OH," despite lacking FDA approval and safety data in humans. Methods: This case report describes a 44-year-old male with polysubstance use history who developed opioid withdrawal after regular MP use (400 mg daily for pain management following neck injury). Vital signs, alcohol and opioid withdrawal scores and clinical outcomes were recorded. Results: The patient presented exhibiting symptoms of moderate opioid withdrawal. A buprenorphine macro-induction protocol was initiated. Following pre-treatment using chlorpromazine as an anti-emetic and diazepam to treat concomitant alcohol withdrawal, 32 mg buprenorphine were provided (16 mg x 2) on day one, with subsequent maintenance dosing and adjunctive medications. The patient demonstrated significant symptomatic improvement with decreased COWS scores and expressed interest in long-acting injectable buprenorphine maintenance therapy. Discussion: This represents the first documented case of MP withdrawal successfully managed with buprenorphine macro-induction, demonstrating the potential efficacy of this approach for novel semi-synthetic kratom metabolites when standard withdrawal management protocols are insufficient. Further studies should evaluate long term outcomes and validate findings.

Abstract: To elucidate the evolution of metabolites and fungal communities during storage of fragrant japonica rice (Liaoxiangjing 1396), and to investigate the biosynthetic mechanisms of key compounds and their association with quality deterioration, this study examined rice samples stored under simulated conditions for 16 months. Samples were collected at 4-month intervals (designated R20, R14, R13, R12, and R11). Metabolites were identified using GC-MS non-targeted metabolomics, while fungal community structure was analyzed through metagenomics. Core mechanisms were further elucidated via PLS-DA, KEGG pathway enrichment, and multi-omics association analysis. Results demonstrated that the fatty acid content of rice increased initially and then stabilized (from 12.24 mg/g in R20 to 17.63 mg/g in R12). A total of 263 metabolites were identified, with oxygenated organic compounds (38 species) and lipids/lepidid molecules (24 species) as the predominant categories. Twelve key differential metabolites were screened from R20 and R12 groups, involving five major metabolic pathways including amino acid metabolism and lipid metabolism. In the fungal community, Pseudomonas (60.2%) and Pantoea (38.19%) were dominant taxa, with a specific Pantoea species (Pantoea sp.) identified as a core biomarker. Multi-omics association analysis revealed that Klebsiella dominated the ndhB energy metabolism pathway, while multiple bacteria cooperatively regulated the mcp chemotaxis pathway, interacting with monosaccharide and amino acid accumulation. This study reveals that the storage quality deterioration of fragrant japonica rice is driven by the "metabolite-microbe-pathway" chain regulation, and the dynamic changes of key metabolites and fungal communities can serve as quality early warning targets.

Abstract: Background: Permanent pacemaker (PM) implantation is a well-recognized complication of transcatheter aortic valve implantation (TAVI), but its long-term prognostic impact remains uncertain. Objective: To evaluate the association between PM implantation and all-cause mortality in TAVI recipients.Methods: We performed a post-hoc analysis of a prospective single-center TAVI registry (2016–2020). The primary endpoint was all-cause mortality at 1 and 5 years. Cox regression and Kaplan–Meier analyses were applied. Validation using the nationwide AUTHEARTVISIT claims database was performed.Results: Among 1114 consecutive TAVI patients (mean age 81 ± 5.8 years; 49.8% female), 120 (10.8%) had a pre-existing PM (Pre-PM), and 153 (13.7%) received a new PM within 30 days post-TAVI (Post-PM). Post-PM patients were older (p=0.006), more often male (p<0.001), had higher Troponin T levels (p=0.002), more pre-existing right bundle branch block (p<0.001) and longer QRS duration (p<0.001) compared to patients without PM. On multivariate analysis, one-year mortality was associated with Troponin T (p=0.002) and NT-proBNP (p=0.002) serum levels. Pre-and Post-PM status was not associated with 1-year mortality (p=0.455, p=975). However, Pre-PM was independently associated with 5-year mortality (HR 1.4, 95% CI: 1.0–1.9, p=0.03), whereas Post-PM was not (HR 1.2, 95% CI: 0.8–1.6, p=0.22). Findings were confirmed in the nationwide AUTHEARTVISIT cohort. Conclusion: In this large, real-world TAVI cohort with national validation, Post-PM status was not associated with mortality at 1 or 5 years. In contrast, Pre-PM identified patients at higher long-term risk, possibly reflecting underlying cardiac disease.

Abstract: Zeolitic imidazolate framework-8 (ZIF-8) is one of the most extensively studied metal–organic frameworks due to its high surface area, tunable porosity, chemical stability, and intrinsic antimicrobial activity. Recent research has focused on engineering ZIF-8 through metal doping and surface functionalization to enhance its physicochemical performance and expand its applications in food safety and environmental systems. Metal-doped ZIF-8 incorporating Cu2+, Fe2+/Fe3+, Ag+, or Mn2+ improves reactive oxygen species generation, enables controlled metal-ion release, and promotes synergistic bactericidal mechanisms against both Gram-positive and Gram-negative pathogens. In parallel, surface modification using biopolymers such as hyaluronic acid, chitosan, alginate, and polyethylene glycol enhances colloidal stability, reduces cytotoxicity, modulates surface charge, and improves adhesion to food-contact surfaces. These combined strategies enable the development of multifunctional nanoplatforms with sustained antimicrobial activity, improved aqueous dispersibility, and compatibility with food packaging, sanitizers, and water treatment systems. This review summarizes recent advances in synthesis strategies, structure–property relationships, antimicrobial and antibiofilm mechanisms, and environmental safety considerations. Key challenges, including scalability, regulatory acceptance, stability, and long-term ecotoxicological impact, are discussed, along with perspectives on stimuli-responsive systems, essential oil encapsulation, and smart antimicrobial coatings.

Abstract: The increasing share of wind power generation has intensified the occurrence of curtailment events in power systems worldwide, mainly driven by transmission constraints, operational limitations, and imbalances between generation and demand. In the Brazilian context, this phenomenon has become more pronounced since 2023, highlighting structural challenges of the Brazilian Interconnected Power System and the need for reliable methodologies to estimate curtailed wind generation. This study presents a methodology to estimate wind power potential during curtailment events, aiming to support forecasting models and the economic compensation of affected generating agents. The proposed approach integrates measured power generation data, technical information of wind farms, and anemometric measurements from SCADA systems, combining data filtering and consistency procedures, gap-filling based on spatial correlation among wind farms, and regression models supported by statistical and computational techniques for wind-to-power conversion. The methodology was applied to more than 1,000 wind farms connected to the Brazilian transmission grid and achieved accuracy levels above 95% on a semi-hourly basis and exceeding 99% for annual aggregations.

Abstract: This study examined the potential of AI-assisted tools to improve English language learning for neurodiverse students (with ADHD, dyslexia, or autism) in low-resource settings in Iran, considering student and teacher perspectives and students’ lan-guage-learning outcomes. The study used a convergent mixed-methods design, and 142 neurodiverse learners and 97 teachers participated through surveys, a 4-week ex-perimental study involving 30 learners (15 AI intervention, 15 controls), and semi-structured interviews with 15 learners, 10 teachers, and five parents. The out-comes were positive: learners stated that they enjoy adaptive features such as multi-modal input and gamification (M=4.2/5) and are motivated by them, and teachers found inclusivity to be important but perceived low confidence (M=2.7/5) because of the training gaps. The AI group showed substantial improvements in vocabulary (+16.3, d=1.21), reading comprehension (+13.3, d=1.05), and oral fluency (+9.2 wpm, d=0.89) compared to controls. Qualitative themes emphasized personalization as em-powerment, as well as obstacles such as infrastructural constraints, exam-based cur-ricula, and cultural cynicism. Recommendations were provided on the transformative power of AI in promoting equity and the need to train teachers and make changes in low-resource schools.

Abstract: Psoriatic disease is an autoinflammatory, autoimmune systemic disease characterized by the presence of psoriasis which may be accompanied by psoriatic arthritis (PsA). The disease is characterized by the presence of metabolic syndrome. Obesity, arterial hypertension, diabetes mellitus type 2, hyperlipidemia and fatty liver disease may be observed in patients with psoriatic disease. The pathophysiology of metabolic syndrome in patients with psoriatic disease has not been completely elucidated. However, hyperinsulinemia may be observed and may be implicated in the pathogenesis of systemic inflammation observed in psoriatic disease. All components of the metabolic syndrome in patients with psoriatic disease need treatment. Arterial hypertension should be managed, diabetes mellitus should be managed, and hyperlipidemia should be specifically therapeutically tar-geted. The presence of obesity may necessitate specific adaptation of the management of PsA such as ad-justment of the dose of biologic agents applied for the management of the disease. Weight loss induced either by diet or surgically or via an incretin-based approach improves psoriasis. Weight loss may prevent progression of psoriasis to PsA. Weight loss may improve disease activity in PsA. Modern treatment modalities in the man-agement of obesity hold a great promise in the treatment of psoriatic disease as they appear to have both metabolic as well as immune modulating effects. In this review the pathophysiology, management and thera-peutic implications of metabolic syndrome in patients with psoriatic disease will be discussed.

Abstract: Agent-based computational economics (ACE) relies on hand-coded heuristics or stylized utility maximization to model firm behavior. We propose using large language models (LLMs) as economic agents---firms that reason in natural language about investment decisions under realistic market conditions. We design a simulation framework in which GPT-based agents, representing heterogeneous manufacturing firms, decide whether to adopt CNN-based visual inspection technology across five rounds with declining costs. We test whether emergent aggregate behavior aligns with propositions from production theory regarding scale economies in adoption, declining adoption thresholds, and capital-labor substitution. Across 150 firm-round decisions (30 firms \( \times \) 5 rounds), decision-level logistic regressions show that time strongly predicts adoption (\( \hat{\beta}_{\text{round}} = 0.88 \), \( p < 0.001 \); marginal effect: \( +13 \) percentage points per round), while firm size has no statistically significant effect (\( \hat{\beta}_{\log q} = -0.11 \), \( p = 0.55 \)). Among adopters, larger firms exhibit greater proportional QA labor displacement (\( \hat{\beta}_{\log q} = -0.05 \), \( p = 0.007 \)), consistent with scale-dependent substitution elasticity. Robustness experiments across three prompt personas and six temperature settings reveal dramatic persona sensitivity---rational optimizers reach 100\% adoption by Round~4 while risk-averse owners never adopt---interpretable as distinct behavioral types (risk neutrality, moderate risk aversion, high loss aversion). We identify behavioral phenomena not predicted by standard theory---status quo bias, production disruption anxiety, and reasoning heterogeneity (97 distinct decision factors)---suggesting LLM agents capture bounded rationality absent from stylized models. Our open-source framework provides a tool for hypothesis generation and behavioral prior elicitation for agent-based computational economics.