Abstract: This paper develops a new generalized model that describes the complex dynamical behavior of a financial system through three state variables, namely the interest rate, investment demand and the price index. The developed model extends and improves numerous financial models available in the literature by incorporating two time delays. The first delay accounts for the time lag in price adjustment, whereas the second captures the delayed feedback effect on investment demand. For the first time in the context of financial systems, a novel threshold parameter is introduced to characterize the existence of equilibria. The dynamical properties of the proposed model, including the stability and the occurrence of Hopf bifurcation, are rigorously analyzed. Furthermore, sensitivity analysis and numerical simulations are conducted to investigate the influence of model parameters on the dynamics of the financial system and to illustrate the analytical results.

Abstract: Brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2), which encodes Insulin Receptor Substrate Protein 53 (IRSp53), has emerged as a brain-disease gene. BAIAP2 involvement in pathogenic CNS disorders is due to its roles in molecular architecture, synaptic signaling, circuit computation, and human neurodevelopmental pathology can be examined within a single mechanistic framework. Unlike many synaptic risk genes that are assigned broad scaffolding functions, IRSp53 is distinguished by the convergence of membrane-shaping capacity, actin control, and postsynaptic condensate organization, through which N-methyl-D-aspartate receptor (NMDAR) -dependent signaling is tuned rather than merely supported. Across mouse models, disrupted IRSp53 has been linked to altered postsynaptic density assembly, abnormal glutamatergic physiology, reduced prefrontal population activity, and impaired social behavior. These phenotypes have not only been observed across scales but, in part, have been reversed in adulthood, indicating that pathogenic effects are not fixed once development has ended. In parallel, emerging human studies have extended BAIAP2 beyond idiopathic neuropsychiatric association toward defined neurodevelopmental disorders, including cortical migration defects and developmental epileptic encephalopathy. A multi-scale view is that the BAIAP2 is not considered as a synaptic organizer, but a causal bridge between nanoscale postsynaptic structure, systems-level dysfunction, and disease expression.

Abstract: Huperzine A (HupA) is a natural Lycopodium alkaloid known for its potent neuro-protective properties through the inhibition of acetylcholinesterase. Nevertheless, the limited understanding of its biosynthesis restricts its broader application. This study integrates full-length and second-generation transcriptomes with the quantification of HupA and its precursor, huperzine B, across various tissues of Huperzia serrata, the primary source plant. By employing phylogenetic clustering, expression profiling, and correlation analysis between gene expression and metabolite abundance, we identified 71 candidate genes from seven enzyme families potentially involved in the synthesis of the HupA backbone, including lysine/ornithine decarboxylases, copper amine oxidases (CAOs), chalcone synthases, and cytochrome P450 monooxygenases. Additionally, 28 genes from two families were identified for modification reactions, specifically 2-oxoglutarate/Fe(II)-dependent dioxygenases and caffeoyl shikimate esterases. Comparative analysis between young and mature leaves revealed 3,801 up-regulated genes in young leaves, with 84 showing a high correlation with HupA content across seven families. Protein–protein interaction network analysis indicated interactions with transcription factors from the MYB, NF-YC, GRAS, ERF, BHLH, and SAP families. Functional validation of two candidate CAOs in planta confirmed their catalytic roles in amine/alkaloid metabolism. This study provides a theoretical foundation and a set of candidate genes for elucidating the biosynthetic pathway of HupA and related alkaloids in H. serrata.

Abstract: Phosphate is an essential element for energy metabolism, bone mineralization and chondrocyte function, particularly during growth. Its homeostasis involves complex interactions between dietary intake, renal excretion and hormonal regulation, notably through fibroblast growth factor 23 (FGF23) and growth hormone (GH). The intricate balance of phosphate and its interplay with FGF23 and GH are examined in the context of normal development and disorders such as X-linked hypophosphatemia (XLH) and chronic kidney disease (CKD), which disrupt this balance through mechanisms of hypophosphatemia or hyperphosphatemia. FGF23 emerges as a key regulator, mediating phosphate excretion and vitamin D metabolism, while GH exerts a counter-regulatory effect by promoting phosphate reabsorption and chondrocyte proliferation. This hormonal interaction maintains skeletal integrity but becomes dysregulated in pathological conditions, leading to impaired growth and mineralization. Recent insights into the molecular mechanisms of phosphate transporters and the role of the PHEX gene in FGF23 regulation provide promising avenues for therapeutic interventions. Emerging treatments, including phosphate binders, calcitriol supplementation and anti-FGF23 antibodies such as burosumab, offer potential to address the complications of phosphate dysregulation. However, challenges remain in optimizing therapies for pediatric populations and mitigating adverse effects like vascular calcification. Future research into phosphate homeostasis, transporter dynamics and gene-based approaches holds the promise of advancing clinical outcomes for phosphate-related disorders. This review explores the dual role of phosphate in skeletal growth, highlighting its critical contributions to chondrocyte maturation, apoptosis and hydroxyapatite formation during endochondral ossification.

Abstract: IoT devices operate as integrated systems spanning hardware, firmware/software layers, and communication layers. In operational settings, many faults and performance degradations are emergent: they arise from cross-layer interactions, workload changes, and telemetry artifacts rather than a single physics-of-failure mechanism. These realities make traditional supervised fault classification difficult because labeled fault data are rarely available during deployment, and the fault surface is unknown a priori. This paper presents a practitioner-oriented, label-free fault detection and diagnosis (FDD) pattern based on Dynamic Time Warping (DTW) for rapid implementation in production IoT telemetry. The method represents a device as a sequence of overlapping episodes and organizes telemetry into interpretable layers (hardware sensors, communication health proxies, and software/firmware-derived KPIs). A reference library of regular episodes is built from an assumed-healthy training window; new episodes are scored using constrained DTW distances against this library, while retaining per-layer and per-channel contributions for attribution. We show that production performance depends strongly on operational parameterization, including episode length, DTW constraints, robust threshold learning, and temporal validation. Within a verified-healthy evaluation window, the tuned configuration achieves an AUROC of 0.97 for the temporally-structured faults DTW is suited to (bias, drift, and interaction faults, with spikes detected at AUROC 0.93), detecting 100% of injected faults at a mean delay under 25 minutes. We further show that constant-value (stuck-at) and missing-data (dropout) faults fall outside DTW's shape-matching scope (AUROC about 0.66) and are better served by complementary variance- and missingness-based detectors, a consequence of DTW's shape-matching scope rather than a parameter choice. This work contributes a system-level methodological framework for deploying DTW as an IoT fault-detection-and-diagnosis capability: an episode-and-layer architecture aligned with hardware, communication, and software/firmware ownership; a label-free reference library requiring only assumed-healthy data; per-layer and per-channel attribution for cross-domain triage; and a reproducible operational tuning procedure. Together these deliver a fast-to-deploy, scalable, and accurate first-line detector for label-scarce IoT systems.

Abstract: Large Language Models (LLMs) are increasingly deployed for editorial and text-processing tasks, yet their application to high-stakes domain editing exposes a class of failures distinct from hallucination. Where hallucination involves a model generating false information, constraint-adherence failure involves a model ignoring or overriding explicit user constraints in favour of its parametrically weighted training data — producing output that is fluent, stylistically polished, and wrong in precisely the ways that matter most. This paper documents the development, iterative testing, and deployment of a dual-pass HITL (Human-in-the-Loop) architecture designed to perform source-critical developmental editing on an 8,000-word academic manuscript analyzing the genealogy of nineteenth-century homeopathic materia medica. Through systematic prompt engineering conducted under a HITL framework, we identified and categorized ten distinct constraint-adherence failure modes, including Parametric Memory Override, Constraint Poisoning, Invented Math Anchors, and Source-Category Collapse. We demonstrate that effective mitigation of these failures requires not elaborated natural-language requests — the conventional understanding of prompt engineering — but the application of rigid, software-like constraints that directly counteract specific neural network behaviors at the token-generation level. Our findings reframe the role of LLMs in scholarly editorial work: not as autonomous “Auto-Editors” capable of independent philological judgment, but as “AI Surgical Assistants” operating under the continuous direction of a human Lead Surgeon whose domain expertise cannot be encoded in any prompt. The Subject Matter Expert Override Protocol documented here provides a replicable model for high-fidelity LLM-assisted editing in any domain where semantic precision is non-negotiable.

Abstract: Electric micromobility may reduce transport emissions, but its system-level benefits depend on which journeys and vehicles it replaces. This study assesses e-bike, e-scooter and e-cargo-bike pathways in an electrifying UK transport system using an expanded Transport Energy Air pollution Model (TEAM-UK). Socio-technical scenarios are modelled annually to 2050, estimating travel activity, energy demand, direct CO₂ and NO_X emissions, life-cycle greenhouse gas emissions and local air pollutants, including non-exhaust sources. Fleet electrification dominates long-run reductions in tailpipe CO₂ and NO_X. However, e-bike-led pathways deliver the largest additional reductions in car-kilometres, energy demand, cumulative life-cycle emissions and non-exhaust PM2.5. E-cargo bike pathways provide more targeted benefits, while e-scooter pathways produce modest system-level gains. Electric micromobility is most effective when embedded in policies that substitute car and van travel with lighter, low-energy modes.

Abstract: Let R be a commutative ring with nonzero identity, and δ an expansion function of its ideals. In this paper, we introduce and study the concept of cube-difference factor absorbing δ(0)-ideals. A proper ideal I of R is called a cube-difference factor absorbing δ(0)-ideal (cdf-absorbing δ(0)-ideal, for short) if, for all a, b ∈ R, the condition a³ − b³ ∈ I implies that a − b ∈ I or a² + ab + b² ∈ δ(0). We establish various properties and characterizations of such ideals. We also examine the transfer of this property across several ring constructions, including polynomial rings, localizations, trivial ring extensions, and amalgamated algebras along an ideal. In particular, we characterize cdf-absorbing δ₀(0)-ideals of Z: among prime ideals via the third cyclotomic polynomial Φ3(x) = x² + x + 1 and its connection to Eisenstein primes, and among all ideals via a squarefreeness condition. We further extend the prime ideal characterization to arbitrary principal ideal domains.

Abstract: The increasing contamination of aquatic environments by heavy metals, together with the growing ecological impact of invasive aquatic species, highlights the need for sustainable remediation strategies. In this study, shells of the invasive crayfish Faxonius limosus were investigated as a low-cost biosorbent for the removal of Zn(II) and Cd(II) ions from aqueous solutions. The material was characterized using FTIR, SEM, and BET/BJH analyses, which confirmed the presence of amino, hydroxyl, amide, and carbonate functional groups and a predominantly mesoporous structure favorable for adsorption. Batch adsorption experiments showed rapid adsorption kinetics, with equilibrium reached after approximately 60 min. The pseudo-second-order kinetic model provided the best fit for both metal ions, indicating chemisorption as the dominant mechanism. Adsorption isotherms were best described by the Langmuir model, suggesting monolayer adsorption on homogeneous active sites. The maximum adsorption capacities predicted by the Langmuir model were 70.69 mg/g for Zn(II) and 302.12 mg/g for Cd(II). The study also demonstrated the potential reuse of metal-loaded shells as biofillers in natural rubber composites, contributing to sustainable waste valorization and circular economy principles.

Abstract: Brushless DC (BLDC) motors are now the dominant propulsion choice for electric vehicles (EVs) because of their high torque density, efficiency and reliability, but their nonlinear dynamics, electronic commutation and wide load and speed range make fixed-gain control difficult. A single set of proportional–integral–derivative (PID) gains tuned at one operating point degrades when inertia, back-EMF or load torque change. This paper presents a hybrid adaptive PID speed controller for a BLDC EV drive that couples an online PID auto-tuner, which re-estimates the gains from a frequency-response estimate of the plant, with a fast fixed-structure PID that supplies the rapid corrective action the auto-tuner cannot provide during its estimation interval. The novelty of the work is this explicit two-element decomposition operating on a cascaded speed/voltage loop driven by Hall-sensor feedback, which removes the need for an exact analytical feedback model while retaining the transparency of classical PID. A full analytical model of the BLDC machine and the closed-loop transfer functions is derived and implemented in MATLAB/Simulink. Across step references of 1000–1800 rpm and load steps to 10 N·m, and against a conventional fixed-gain PID and a Flower Pollination Algorithm (FPA) tuned PID, the proposed controller holds overshoot below 1% at low-to-mid speed and consistently lower torque ripple, while a 12.4% transient undershoot at 1800 rpm under sudden load identifies the present operating limit and a direction for future work.

Abstract: Urban public parks are vital for recreation, public health, environmental quality, and sustainable urban growth. Nonetheless, access to these parks remains uneven across many cities, disproportionately impacting low-income, marginalised, and spatially segregated communities. This study systematically examines socio-spatial disparities in park access and their effects on spatial justice. Using the PRISMA 2020 framework, 108 peer-reviewed articles published from 2000 to 2025 were analysed through thematic narrative synthesis. The results identify key factors influencing accessibility disparities, including socio-economic status, residential location, race and ethnicity, transport infrastructure, urban form, governance, and demographic vulnerability. Socio-economic status (24%), residential location and spatial distribution (20%), race and ethnicity (18%), and urban form and transport systems (17%) were the most common determinants. Limited park access exacerbates socio-economic inequality, worsens environmental injustice, contributes to health gaps, reinforces spatial segregation, hampers urban sustainability, and marginalises vulnerable populations. The review integrates Spatial Justice Theory, Environmental Justice Theory, and Urban Political Ecology into a comprehensive analytical framework and introduces a conceptual model linking accessibility factors to spatial justice outcomes. These findings underscore the importance of equitable green infrastructure planning, inclusive governance, and better access in underserved urban areas.

Abstract: Background: The way individuals perceive and interact with the food environment may influence their dietary practices and health outcomes. This study analyzed associations between social and housing conditions, food environment perception, and food security, and their effects on the nutritional status of children and mothers. Methods: A cross-sectional study conducted between 2022 and 2023 with 314 participants in Vitória de Santo Antão, Pernambuco, Brazil. Socioeconomic variables, housing conditions, perceptions of domestic and community food environments, food security, and anthropometric indicators were assessed using generalized structural equation modeling (GSEM, p < 0.05). Results: Better social and housing conditions were associated with more favorable domestic food environment perceptions and lower food insecurity. No significant associations were observed between the domestic food environment and food security, nor between the community food environment and other model variables. No significant indirect effects were identified, indicating absence of mediation through food environment perceptions. Associations were found between food security and maternal BMI, and between maternal and child BMI. Conclusions: Social and housing conditions play a central role in shaping food security and nutritional outcomes, while food environment perception showed limited relevance. These findings reinforce the need for intersectoral public policies addressing social inequalities and promoting healthy eating.

Abstract: Background: Tuberculosis (TB) remains the leading cause of death among persons with advanced HIV disease (AHD) in high HIV-burden settings. Digital chest X-ray (dCXR) with computer-aided detection (CAD) is a promising tool to overcome human resource constraints and improve TB case detection. This study evaluates the real-world im-plementation and performance of dCXR/CAD for TB screening within a specialized AHD clinic in Maputo, Mozambique. Methods: We conducted a retrospective cohort analysis of 487 new AHD patients at Centro de Referência do Alto Maé (CRAM) from October 2023 to September 2024. Of these, 238 underwent dCXR with CAD interpreta-tion. All patients underwent systematic TB screening according to Ministry of Health (MoH) guidelines. Using the recorded diagnosis of TB (bacteriologically confirmed or clinically diagnosed) as the reference standard, we calculated the sensitivity, specifici-ty, positive predictive value (PPV), and negative predictive value (NPV) of the nation-ally adopted CAD threshold (≥0.5). Results: Among 238 AHD patients screened with CAD, 116 (49%) were diagnosed with TB. At the ≥0.5 threshold, sensitivity was 50% (58/116; 95% CI: 41–59), specificity 92% (112/122; 95% CI: 85–96), PPV 85% (58/68; 95% CI: 75–92), and NPV 65.9% (112/170; 95% CI: 58–73). TB diagnosis rates increased sharply with CAD score: 30% (43/143) in normal, 52% (15/27) in abnormal non-suggestive, and 85% (58/68) in suggestive cases. Bacteriological confirmation was low across all groups (19–26%), reflecting reliance on clinical diagnosis. Conclu-sion: Integrating dCXR/CAD into AHD care is feasible and identifies a high TB burden. However, at the adopted threshold of ≥0.5, CAD demonstrated high specificity but low sensitivity (50%) in this population, missing half of all TB cases. These findings suggest that CAD functions better as a confirmatory decision-support tool than a standalone screening test in AHD. Threshold optimization for this specific population warrants prospective evaluation. Implementation challenges — including fragmented systems and lack of dedicated human resources — must be addressed to realize CAD's full po-tential in TB programs.

Abstract: This paper examines how the travel intention of students is correlated with their mental health, in terms of stress reduction and psychological wellbeing. The study employs a combined model that integrates the Theory of Planned Behavior and Stress Recovery Theory to determine the role of travel intention, which is based on the travel self-efficacy, the pressure of social influence, the value of the travel experience, the perception of affordability, and the attitude towards tourism in affecting the mental health outcome of students. The paper examines the mediating capacities of travel involvement and social connectedness, and the moderating capacities of nature connectedness and travel frequency. Semi-structured interviews with 15 university students and survey among 604 students in various universities in Bangladesh were used to collect data. Hypotheses were tested using PLS-SEM. Findings indicate that travel intention enhance psychological wellbeing and reduce stress, and travel involvement and social connectedness are important mediators. These relations are mediated by nature connectedness and frequency of travel, which increases the restorative effect of travel. The results indicate that tourism could be a viable approach to student mental health promotion, which has both practical and theoretical consequences on university policy and future tourism psychological studies.

Abstract: Irregular migration across the Mediterranean Sea causes thousands of deaths annually, mostly due to shipwrecks involving structurally inadequate vessels navigating under severe meteo-marine conditions. The forensic investigation of human remains recovered in such contexts is particularly challenging due to advanced decomposition and the absence of documentary evidence linking victims to a specific departure event. In the present study, a methodology is developed and validated for reconstructing the most probable departure location of human remains recovered at sea, through the integration of backward Lagrangian drift simulations with large-scale oceanographic and atmospheric datasets provided by the Copernicus Marine Service (CMEMS). The methodology was applied to five bodies recovered in the Aeolian Islands area (Sicily, Italy) between March and June 2024. Simulations were performed using the OpenDrift Leeway model, with an ensemble of several drifters released across five temporal offsets per recovery site. Results were synthesised through a drift probability metric Pd and a newly proposed Hydrodynamic Connectivity Index (HCI), cross-referenced with documented shipwreck incidents and complemented by a wave climate analysis. The methodology successfully identified the port of Bizerte (Tunisia) and the shipwreck event of 5-6 February 2024 as the most probable origin, in full agreement with independent forensic findings, demonstrating the reliability of the proposed approach for forensic reconstruction of shipwreck events in the central Mediterranean and the possibility of being used as aid in recovering further remains.

Abstract: Hong Kong's architectural culture is characterized by the systematic reproduction of Western visual languages, despite the availability of other spatial traditions. This article argues that this condition represents "aesthetic internalisation" — a process wherein colonial hierarchies of taste become structurally embedded in professional formation and the semi-conscious perceptual field of architects. Drawing on Bourdieu's habitus, Bhabha's colonial mimicry, Quijano's coloniality of power, and Fanon's account of subjectivity, the study posits that the dominance of Western architectural forms in postcolonial Hong Kong is structural rather than preferential. To counter this, the article proposes the Spatial Cipher methodology, integrating the Neo-Confucian concept of Li (理, inherent organising principles). This methodology extracts deep organisational logics rather than superficial visual forms from suppressed spatial traditions, translating them into contemporary material decisions. The argument is developed through case analysis of 46FLT, a mixed-use building in Kowloon City (2014–2017) designed by the author. The project operationalises Spatial Cipher by engaging with the spatial memory of the former Kowloon Walled City. Furthermore, drawing on situated epistemology, the article reflects on the diasporic architect's position as a productive vantage point from which colonial aesthetic inheritance can be observed and contested. The study demonstrates that decolonial architectural practice is viable within standard commercial and regulatory constraints, offering an actionable framework beyond theoretical discourse.

Abstract: A programmable Cas12a-based biosensing system is developed for sensitive and se-lective detection of Pectobacterium polaris, a newly emerging pathogen affecting a wide range of agriculturally important plants. The system relies on asymmetric PCR (aPCR) and PAM-independent recognition of single-stranded DNA by a Cas12a/gRNA complex and allowed to determine P. polaris with limit of detection of 10 copies of bacterial genome per reaction. The overall assay time is about 2 h. The detection is achieved by using PCR primers specific for Pectobacterium species and gRNA selectively recognizing sequence unique for P. polaris. With no PAM requirement, the system selectivity was fine-turned by properly positioning gRNA spacer on single-stranded amplicons. The designed aPCR/Cas12a biosensing system is compatible with the introduction of uracil into ampli-cons to prevent carryover contamination and with visual detection. In a broad context, the findings suggest that PCR tests for pathogen detection can be easily adapted to a format of aPCR/Cas12a programmable biosensing by converting PCR into aPCR and by coupling aPCR to PAM-independent Cas12a analysis of single-stranded amplicons. This may pave the way to modify current laboratory-based PCR tests into on-site tests conducted on con-ventional inexpensive thermocyclers with subsequent visual detection for on-site screen-ing or initial decision-making.

Abstract: Synthetic mRNA produced by in vitro transcription is the active pharmaceutical ingredient of approved vaccines and of many drugs under development. It typically contains a 3’ poly-A tail required for optimal stabilization and translation of the mRNA. The average length of the poly-A tail in the produced mRNA cannot be precisely predicted and consequently must be measured using complicated technologies such as reverse transcription and sequencing or cleavage of the poly-A tail and analysis by capillary electrophoresis or mass spectrometry. We report an accelerated method to evaluate the average poly-A tail length in synthetic mRNA, which benefits from the fact that thiazole orange is fluorescent only when in close proximity of nucleic acid. A poly-dT(12) oligonucleotide having thiazole orange at its extremities emits a fluorescence signal proportional to the amount of poly-A sequence available. Using a titration curve made with known amounts of poly-A RNA oligonucleotide, the thiazole orange oligo dT probe can instantly indicate the average length of the poly-A tail in an mRNA sample. This fast and easy method can be used in any laboratory to determine the size of the poly-A tail in in vitro transcribed mRNA produced for research, pre-clinical studies and clinical trials.

Abstract: Contemporary radiobiology explains tissue response to ionizing radiation through the linear-quadratic model and the four Rs of fractionation—tools that falter on FLASH sparing, the non-local responses of spatially fractionated radiotherapy (SFRT), the supra-linear control of stereotactic body radiotherapy (SBRT), and reversible non-genetic resistance, each currently explained by its own single-timescale literature. We propose that these are perturbations of one multi-scale adaptive state, organized by the timescale of adaptation into four coupled layers: fast redox chemistry (ms–s), collective organization (s–days), persistent epigenetic memory (days–weeks), and clonal evolution (weeks–months). The framework's claim is not these bands but their dynamical coupling through shared substrates, so that a perturbation entering one propagates to another—made concrete by the recent identification of an Activator Protein-1 (AP-1) –mediated write converting transient signals into heritable states. We formalize this as a coupled, spatially-resolved dynamical system in which every mechanism enters cell kill through a single modulation factor, recovering the linear-quadratic model as its frozen-state limit. Simulations reproduce the defining behaviors of spatially fractionated delivery and adaptive therapy, and show that closing the cross-band loop yields a bistable, hysteretic persistent state, a memory-writing geometry distinct from the dose-optimal one, and history-dependence at fixed dose. The framework generates falsifiable, cross-modality predictions absent from conventional radiobiology—notably that modality interactions are selective, additive when two modalities perturb the same state variable and non-additive when they perturb different coupled ones—and reframes treatment planning as a game against a largely latent, adapting state, played through multiple handles of which dose is only one. Because that state is only partially observable and its parameters are not generally identifiable from clinical data, the planner must act against a posterior rather than a known opponent, making the clinical problem one of Bayesian, latent-state adaptive control rather than fixed calibration.

Abstract: Introduction: Intraductal papillary mucinous neoplasms (IPMNs) are precursor lesions of pancreatic cancer. This study investigated the association between MRI-derived pancreatic fat fraction and IPMN.. Material Methods: This retrospective case-control study included 60 patients with IPMN and 120 controls evaluated between 2018 and 2025. All participants underwent pancreatic MRI with proton density fat fraction (PDFF) imaging. Pancreatic fat fraction was measured in the pancreatic head, body, and tail on PDFF maps, and mean pancreatic fat fraction was calculated. Group comparisons, receiver operating characteristic analysis, and logistic regression analyses were performed to evaluate the association between pancreatic fat fraction and IPMN. Results: A total of 180 participants were included in the study, comprising 60 patients with IPMN and 120 controls without IPMN. Patients with IPMN were significantly older than controls (72.5 vs. 57.0 years, p=0.001). The IPMN group demonstrated higher glucose and LDH levels and lower HDL cholesterol, hemoglobin, hematocrit, and platelet counts compared with controls (all p<0.05). Pancreatic fat fraction measurements were significantly increased in patients with IPMN across all pancreatic regions. Head, body, tail, and mean pancreatic fat fractions were markedly higher in the IPMN group than in controls (all p=0.001). In multivariable logistic regression analyses, age and pancreatic fat fraction remained independently associated with IPMN presence. ROC analysis demonstrated excellent diagnostic performance, with mean pancreatic fat fraction showing the highest discriminative ability (AUC=0.968), followed by head (AUC=0.934), body (AUC=0.922), and tail fat fraction (AUC=0.876). Conclusion: Pancreatic fat fraction was significantly higher in patients with IPMN and remained independently associated with IPMN presence after multivariable adjustment. Mean pancreatic fat fraction demonstrated excellent diagnostic performance for distinguishing IPMN from non-IPMN individuals. Quantitative MRI-based assessment of pancreatic fat may represent a useful imaging biomarker for IPMN detection.