Search Results (1,893)

Electroencephalography records brain electrical activity arising from synchronized synaptic activity of neurons in the cerebral cortex, as measured at the scalp surface. In this work, neural activity is modeled as an equivalent current dipole with arbitrary orientation located within the innermost conductive layer. To represent the head anatomy, the volume conductor is modeled as a central brain compartment enclosed by concentric spherical shells representing the cerebrospinal fluid (CSF), skull, and scalp, with different conductivity values. The present study incorporates anisotropic conductivity with distinct radial and tangential components within a multilayer spherical head model by extending existing analytical formulations. While analytical solutions for isotropic spherical models are well established, anisotropic formulations are typically addressed using numerical or approximate methods. By applying spherical harmonics to the Poisson equation in layered anisotropic media, analytical expressions are derived for the electric potential generated by dipole sources. The forward model is evaluated using electrode positions (θ, φ) defined according to the EEGLAB layout, for a representative configuration with a head radius of 9.2 cm. Quantitative comparisons are performed using MAG and RDM metrics for homogeneous and inhomogeneous anisotropic conductivity models. The results indicate that conductivity anisotropy significantly influences both the magnitude and spatial distribution of scalp potentials, particularly due to attenuation and spatial smoothing effects introduced by the skull layer. The analytical expressions derived contribute to the theoretical study of EEG forward modeling in anisotropic layered media and may serve as reference solutions for the assessment of numerical formulations. Full article

Foot-and-mouth disease (FMD) is a highly transmissible viral infection of livestock that threatens food security and causes substantial economic losses in endemic regions. Despite its economic impact, the role of environmental viral load and wildlife reservoirs in sustaining FMD transmission remains poorly quantified. The aim of this study is to assess the extent to which community viral load sustains FMD persistence and to identify key transmission drivers in a coupled livestock–wildlife–environment system. A Susceptible–Exposed–Infected (SEI) model with a free-living virus compartment was analyzed via the basic reproduction number ($R_0$) and solved numerically using a Nonstandard Finite Difference Method. Sensitivity analysis identified wild host population size, transmission rates, host recruitment, environmental viral decay, and viral load thresholds as major determinants of $R_0$. Results indicate that higher transmission rates accelerate susceptible depletion and increase exposed and infected classes, with wildlife dominating environmental viral contributions. Community viral load is central to sustaining outbreaks and informs targeted control strategies. Full article

Background/Objectives: Propranolol (PROP) is a non-selective β-blocker widely prescribed for cardiovascular and neurological disorders. Its pharmacokinetics (PK) are highly variable, and co-administration with omeprazole (OME), a CYP2C19 substrate and inhibitor, may alter systemic exposure. Herein, this study aimed to investigate factors influencing PROP PK variability and evaluate the effect of OME coadministration using physiologically based pharmacokinetic (PBPK) modeling and population PK (popPK) analysis. Methods: PBPK models for PROP and OME were developed and validated against published data. DDI simulations were conducted across clinically relevant dosing regimens. A two-period fixed-sequence virtual trial of 125 subjects was simulated with PROP alone and PROP combined with OME. Population PK (popPK) analysis was performed on simulated plasma concentration data to identify covariates affecting PROP disposition and quantify DDI magnitude. Results: PBPK models were successfully developed and validated. PROP disposition was best described by a two-compartment model with linear elimination. Health status was found to influence clearance, and body surface area (BSA) affected the central volume of distribution. Co-administration with OME increased PROP exposure, with larger effects in patients with renal impairment. Simulated plasma concentrations remained below established toxicity thresholds. Conclusions: Virtual clinical trials integrating PBPK and popPK modeling provide a robust approach to identifying key determinants of PK variability and DDI risk. Although these findings were not directly translated to clinical observations, this helps identify sources of PK variability in PROP treatment settings and factors that may intensify its interaction with OME, thereby supporting model-informed precision dosing to enhance safety and efficacy. Full article

Multiple Sclerosis (MS) is a chronic, immune-mediated disorder of the central nervous system characterized by leukocyte infiltration, inflammation, demyelination, and progressive neurodegeneration. Susceptibility to MS is influenced by genetic factors, including variants within the human leukocyte antigen (HLA) region, (notably HLA-DR15), and multiple single nucleotide polymorphisms that modulate T cell function and immune regulation. Clinically, early manifestations such as visual disturbances, sensory deficits, fatigue, and impaired coordination often precede more advanced features, including cognitive decline and bladder or bowel dysfunction. Although experimental and genetic models of neuroinflammation have facilitated the development of therapies that reduce relapse rates and slow disease progression, the underlying pathological mechanisms remain incompletely understood. Emerging evidence points to the importance of cytoskeletal organization and membrane-associated signaling platforms in maintaining neuronal and immune cell function. Disruption of these systems may contribute to demyelination and neuroinflammatory cascades. Within this context, a systems biology perspective is particularly valuable, as it emphasizes the integration of multiple, interdependent pathways rather than isolated mechanisms. Caveolin-1 (Cav-1), an integral membrane protein of caveolae, has gained attention as a potential central regulator due to its role in coordinating signaling processes across diverse cellular compartments. In this review, we examine the potential genetic and functional contributions of Cav-1 to MS pathophysiology, with a focus on its involvement in oxidative stress, inflammation, blood–brain barrier integrity, and autophagy. By framing these processes as components of an interconnected network, we highlight Cav-1 as a context-dependent modulator that may influence both disease progression and severity. However, despite its mechanistic relevance, the translational potential of Cav-1 remains uncertain, and further studies are required to clarify its precise role and evaluate its suitability as a therapeutic target in MS. Full article

Celiac disease (CD) is an autoimmune enteropathy of the small intestine affecting genetically susceptible individuals, characterized by an aberrant immune response to gliadin and sustained IgA-driven inflammation. IgA exists in two main subclasses, IgA1 and IgA2, which differ in distribution and function, but their profile in CD remains poorly characterized. Circulating free light chains (FLCs) are markers of B-cell activation and immune dysregulation, yet their role in CD has not been fully explored. The aim of this study was to characterize IgA subclasses and FLC profiles in newly diagnosed celiac patients. We analyzed sera from 108 CD patients and 29 healthy controls, assessing conventional serological markers (anti-tissue transglutaminase and anti-endomysial antibodies), together with total IgA, IgA1, IgA2, and FLC levels using a turbidimetric method. CD patients exhibited higher total IgA levels and an increased IgA1/IgA2 ratio, alongside a decreased k/λ ratio; these differences remained significant after adjustment for age and sex. When combined in a multivariable logistic model, these biomarkers yielded an AUC of 0.827, suggesting that the parameters identified in the univariate analyses provide complementary, non-redundant information that jointly highlights a reorganization of the humoral immune response. Due to the limited sample size, our results need confirmation in larger cohorts. However, our findings suggest a reorganization of the IgA compartment in CD, with selective expansion of IgA1 and preferential λ light chain usage, highlighting coordinated alterations in the humoral immune response. The integration of such markers, potentially in combination with -omics approaches, may contribute to a more refined and less invasive characterization of celiac disease. Full article

Preclinical multimodal imaging is widely applied in small animal models for longitudinal studies of human diseases. Beyond murine systems, cost-effective and ethically sustainable models such as the chicken embryo and its chorioallantoic membrane are gaining increasing interest in accordance with the 3Rs principles. This study evaluated the feasibility of using both high-frequency ultrasound and magnetic resonance imaging for the non-invasive longitudinal monitoring of chicken embryo development in ovo. Fifty fertilized eggs were incubated under controlled conditions and examined up to embryonic day 14. High-frequency ultrasound (15–71 MHz) enabled real-time imaging and quantitative assessment of superficial structures, including cranial biometry and limb growth, while magnetic resonance imaging (7T) provided high-resolution three-dimensional visualization of internal organs and extraembryonic compartments. Together, these modalities allowed the progressive identification of key anatomical structures from ED5 onward, with HFUS enabling earlier linear measurements and MRI facilitating detailed anatomical and volumetric evaluation. The integration of these techniques allowed the generation of a developmental imaging timeline and quantitative reference dataset of normal embryogenesis. This multimodal approach represents a promising strategy for in vivo developmental studies, offering a robust baseline to characterize structural alterations induced by experimental conditions. Moreover, the use of the chicken embryo model provides significant ethical and economic advantages, supporting its application in preclinical research and imaging-based studies. Full article

Polycythemia vera (PV) is a JAK2V617F-driven myeloproliferative neoplasm characterized by erythroid expansion, increased thrombotic risk, and heterogeneous clinical outcomes. Although prior studies have described key transcriptional abnormalities—including Janus kinase–signal transducer and activator of transcription (JAK–STAT) hyperactivation and chronic myeloinflammation—most have examined single hematopoietic compartments. A multi-compartment approach may reveal conserved and lineage-specific disease-associated transcriptional programs. Here, an integrated, multi-compartment transcriptomic analysis of publicly available microarray datasets was performed, spanning bone marrow (BM) CD34+ progenitors, peripheral blood (PB) CD34+ progenitors, and whole blood from PV patients and healthy controls, with independent validation in neutrophils. Differential gene expression, pathway enrichment, and protein–protein interaction network analyses were used to delineate conserved versus compartment-specific transcriptional programs and to evaluate persistence of progenitor-derived signatures into mature myeloid cells. Across compartments, PV demonstrated consistent enrichment of inflammatory, interferon, and JAK–STAT-associated pathways despite limited overlap at the individual gene level, indicating that core disease processes are maintained through lineage- and differentiation-stage-specific transcriptional reprogramming. Network analysis identified highly connected hub genes, which were used to derive a single-sample gene set enrichment (ssGSEA) signature. This signature showed strong diagnostic performance across cohorts; remained enriched in PV neutrophils; and correlated with platelet count, indolent disease status, and reduced levels in post-splenectomy patients. Together, these findings support a model in which PV is driven by stable, progenitor-derived inflammatory programs that persist across myeloid differentiation while incorporating compartment-specific adaptations, and highlight the value of multi-compartment, network-based approaches for translational biomarker development. Full article

Background: Gliomas are characterized by a high degree of molecular heterogeneity, which impairs the reproducibility of predictive biomarkers derived from bulk-based molecular profiling due to immune/stromal contamination of tumors and the high prevalence of the IDH mutation signature. Methods: In this study, we used MOFA+ to derive intrinsic molecular signatures from transcriptional, methylation, and genomic profiles of a cohort of 667 diffuse gliomas in the Cancer Genome Atlas database. Thereafter, factor scores were derived for two separate Chinese Glioma Genome Atlas batches (Batch 1, n = 325; Batch 2, n = 693) without any retraining on the model. The prognostic independence of identified molecular signatures was assessed using multivariable Cox regression adjusted for IDH mutation status and tumor purity; purity-residualized survival analyses; IDH-stratified Cox regression in each cohort; validation by concordance index against established molecular signatures; and survival extreme profiling. To characterize the biological significance of factor signatures, we projected gene set signatures corresponding to each factor signature onto a single-cell RNA-seq dataset of GBM (GSE131928). Results: MOFA+ identified 12 latent factors, of which a vascular–extracellular matrix (ECM) remodeling axis (Factor 1) explained the highest multi-omics variance (24.9%) and was the strongest independent prognostic factor. In multivariable Cox regression adjusting for IDH status and tumor purity, Factor 1 remained independently prognostic (HR = 1.67, 95% CI 1.27–2.20, p = 0.0002); in a fully-adjusted model additionally including age, WHO grade, MGMT methylation, and 1p/19q codeletion (plus radiotherapy and chemotherapy status in the CGGA cohorts), Factor 1 remained prognostic in both CGGA cohorts (CGGA1: HR = 1.50, p = 3.8 × 10⁻⁵; CGGA2: HR = 1.18, p = 0.003) but lost significance in TCGA (HR = 1.04, p = 0.83), consistent with the cohort-dependent magnitude reported in the IDH-stratified and meta-regression analyses below. Purity-residualized survival analysis showed negligible attenuation of the Factor 1 signal (raw HR = 3.57 vs. residualized HR = 3.72; concordance 96.5%). Within IDH-wildtype gliomas, Factor 1 was significant in both external validation cohorts (CGGA1: HR = 1.64, FDR = 4.6 × 10⁻⁶; CGGA2: HR = 1.20, FDR = 0.02), though the TCGA IDH-wildtype subgroup showed a trend that did not survive FDR correction (FDR = 0.060). All validation was performed without model retraining. Within IDH-mutant gliomas, Factor 1 was strongly prognostic in both CGGA cohorts but was not significant in TCGA (HR = 1.17, FDR = 0.33). These findings should therefore be interpreted as consistent in directionality across cohorts but not uniformly replicated at the FDR-adjusted significance threshold in the TCGA discovery dataset. Concordance index benchmarking on a matched subset (n = 503) showed Factor 1 achieved discrimination comparable to the Mesenchymal signature (C = 0.797 vs. 0.801; ΔC = −0.004) while outperforming four other established classifiers. Factor 1 consistently separated patients with extreme survival phenotypes (OS < 6 vs. >15 months) across all three cohorts (all log-rank p < 0.001). Projection onto a single-cell GBM atlas (GSE131928), supported by inferCNV-based malignant-cell classification, localized the Vascular–ECM program to malignant cells and the Immune–ECM axis to myeloid compartments. Conclusions: The Vascular–ECM axis is a consistent, prognostic program robust to purity adjustment for diffuse gliomas that remains relevant across IDH-defined subgroups in three independent datasets comprising 1685 patients. The Vascular–ECM axis is a reproducible, purity-robust prognostic program in diffuse glioma, with directionally consistent adverse effects across TCGA, CGGA Batch 1, and CGGA Batch 2 (pooled n = 1685). Given the strong co-loading of endothelial, ECM, and myeloid genes observed in the single-cell projection, Factor 1 is best interpreted as a vascular/ECM-associated tumor–microenvironment ecosystem program rather than a malignant-cell-autonomous signature. Its FDR-adjusted significance within IDH-stratified subgroups is cohort-dependent and robust in both CGGA cohorts but attenuated in the TCGA IDH-wildtype (FDR = 0.060) and TCGA IDH-mutant (FDR = 0.33) strata. The pooled signal should therefore be interpreted as evidence of a generalizable biological program rather than a uniformly replicated subgroup-specific biomarker. It is possible to calculate factor scores based on RNA sequencing alone using fixed loadings (Z = XWᵀ), which may have implications for future translational applications. All findings are correlative; a causal role for the Vascular–ECM program in glioma progression, invasion, or therapy resistance remains to be established through functional perturbation experiments. Full article

Traditional surgical decision-making in traumatic brain injury (TBI) has relied on static intracranial pressure (ICP) thresholds and fixed volumetric criteria, an approach that inadequately reflects the dynamic physiological nature of secondary brain injury. These conventional metrics fail to capture the critical determinant of clinical deterioration: the progressive loss of intracranial compliance, the brain’s capacity to buffer additional volume without harmful pressure escalation. This manuscript proposes a practical, compliance-based framework for selecting precise, personalized surgical strategies using real-time physiological, imaging, and neuromonitoring indicators. Based on the Intracranial Compartment Syndrome (ICCS) model, this approach translates the loss of compensatory reserve into actionable operative decisions. Compliance is assessed through multimodal tools, including ICP waveform morphology, cerebral oxygenation, and complementary noninvasive neuromonitoring. ICCS staging delineates three operative contexts: Stage 1, preserved compliance; Stage 2, compliance failure with maintained oxygenation requiring physiology-guided interventions to restore buffering capacity; and Stage 3, global decompensation with lost of compliance plus oxygenation failure requiring immediate, aggressive intervention for partial or total brain tissue survival. By shifting surgical reasoning from fixed anatomical thresholds to a physiology-centered assessment of intracranial compliance, this framework aims to enhance the timing, selection, and overall effectiveness of neurosurgical interventions in TBI. Full article

Heme metabolism in the liver has traditionally been described as a linear pathway that supports oxygen utilization, redox balance, and detoxification. Here, we synthesize recent evidence and propose a framework in which heme functions as a system-level regulator, the “queen” of metabolism, whereas its upstream intermediate protoporphyrin IX (PPIX) represents a chemically reactive “dark twin” that emerges when metabolic flux fails to resolve. In this view, metabolic state is defined not only by end products but also by the behavior of pathway intermediates. This system is spatially organized. Hepatocytes dominate heme synthesis and utilization. In contrast, liver stromal compartments, particularly Kupffer cells, play a central role in heme degradation through heme oxygenase-1 (HMOX1), linking heme turnover to iron recycling and stress adaptation. The metabolic state of the liver therefore reflects not only pathway flux but also the degree of coupling between these cellular compartments. We propose a state model of hepatic heme metabolism. In the resolution state, most evident during inflammation, coordinated hepatocyte–macrophage activity maintains flux and limits intermediate accumulation. In contrast, the expansion state, exemplified in cancer, is defined by impaired flux completion, leading to PPIX accumulation, metabolic heterogeneity, and oxidative stress. This framework reframes liver disease through intermediate behavior rather than pathway presence: porphyrias reflect direct overload, metabolic liver diseases partial expansion, and hepatocellular carcinoma a fully developed expansion state. By focusing on the “intermediate space,” this model links biochemistry, spatial organization, and disease pathogenesis, while suggesting new opportunities for diagnosis and therapy based on metabolic state. Full article

The autoantibody reactome refers to the multidimensional repertoire of antibody reactivities against self-antigens across the human proteome or selected antigenic compartments. This offers a scalable systemic layer for precision immunology across spontaneous autoimmunity and treatment-induced immune toxicity. Autoimmune diseases and immune-related adverse events (irAEs) share major features of dysregulated immunity, yet clinically useful tools for risk stratification, early detection, endotyping, and treatment guidance remain limited and slow. A central challenge is that tissue pathology is highly informative but not uniformly accessible across diseases and organ systems, whereas routine serology captures only a narrow fraction of immune heterogeneity. In this perspective, I argue that a global autoantibody reactome can serve as a central unifying framework linking systemic immune history, tissue pathology, and clinical trajectories across autoimmune disorders and irAEs. Rheumatoid arthritis (RA) provides a strong prototype because its serological diversity, major role of post-translationally modified autoantigens, and marked synovial heterogeneity allow reactome features to be interpreted against tissue biology. Immune checkpoint inhibitor-associated inflammatory arthritis serves as an illustrative rheumatic irAE and a model of treatment-induced immune dysregulation with clear opportunities for longitudinal blood-based profiling. Spatial transcriptomics and proteomics are therefore positioned not as stand-alone solutions, but as mechanistic tools that can decode reactome-defined immune states within tissue microenvironments where tissue is accessible. Clinical translation will require integration of autoantibody reactomes with tissue, circulating proteomic, imaging, genetic, and clinical data through transparent multimodal models, as well as a shift from exploratory resources such as AAgAtlas toward analytically validated and clinically interpretable biomarker panels for risk prediction, endotyping, monitoring, and biomarker-guided intervention. This perspective outlines technical and strategic steps toward clinically actionable decision support, including risk stratification before ICI initiation and treatment guidance for patients who develop ICI-induced inflammatory arthritis, through integration of autoantibody reactome profiling, spatial omics and transparent multimodal AI. Full article

We present a modular microfluidic platform for constructing miniaturized, compartmentalized cell culture systems that support monoculture, co-culture, and organ-on-a-chip models of human tissues. The devices provide architecturally defined three-dimensional microenvironments in which heterogeneous cell populations can be cultured in close proximity while maintaining precise spatial organization and independent access to each compartment. In vivo-like perfusion into, from, and between adjacent chambers is achieved via micro-engineered porous barriers that act as perfusion microchannels, enabling controlled convective and diffusive transport and recapitulating paracrine signaling between tissue units. As a proof of concept, we implement an adipose–immune co-culture model that reproduces key features of inflamed, insulin-resistant adipose tissue, including altered cytokine secretion and glucose uptake. Together, these features establish a versatile platform for the biofabrication of customizable single-organ and multi-organ in vitro models that more faithfully recapitulate human tissue structure and function for applications in disease modeling, immunometabolic studies, and preclinical drug testing. Full article

Avian influenza (AI) remains a serious threat to poultry and public health worldwide due to its zoonotic nature and pandemic potential. This paper develops and analyzes a coupled system of nonlinear ordinary differential equations and an SEIR-SEIR model that describes the transmission dynamics of avian influenza in both human and bird populations. The model incorporates multiple transmission routes (bird-to-bird, bird-to-human, human-to-human), exposed/latent compartments in both hosts, disease-induced mortality, and demographic processes. From a mathematical perspective, we present a rigorous analysis of this eight-dimensional dynamical system. We prove positivity and boundedness of solutions in ${\mathbb{R}}_{+}^8$, characterize the equilibrium points, and derive the basic reproduction numbers $R_0^b$ and $R_0^h$ using the next-generation matrix method. Local asymptotic stability of the disease-free equilibrium is established via the Routh–Hurwitz criterion. A composite Lyapunov function is constructed to prove global asymptotic stability when both reproduction numbers are less than unity—a result that exploits the cascade structure of the system and provides a template for analyzing similar multi-host models. Sensitivity analysis using normalized forward sensitivity indices identifies critical parameters. In addition, we use neural network models to validate both models and provide error analysis. These results emphasize the crucial role of controlling cross-species transmission and improving recovery efforts, which have significant implications for the design of effective intervention and surveillance programs in the context of the One Health framework. Full article

A within-host HIV dynamics model incorporating latent reservoirs, distributed time delays, and a B-cell-mediated humoral immune response is developed and analyzed mathematically. The model includes five compartments: uninfected CD4⁺ T cells, latently infected cells, actively infected cells, free virions, and B cells. Four distinct distributed delays are introduced to account for the periods between viral entry and the emergence of latently or actively infected cells, reactivation of latently infected cells, and intracellular virion production. For the non-delayed system, the basic reproduction number ${\mathcal{R}}_0$ is derived using the next-generation matrix method. Using Lyapunov functions and LaSalle’s Invariance Principle, a sharp threshold dynamic is proven: the infection-free equilibrium is globally asymptotically stable (GAS) when ${\mathcal{R}}_0\le 1$, whereas a unique endemic equilibrium is GAS when ${\mathcal{R}}_0>1$. For the full distributed-delay system, a delay-dependent reproduction number ${\mathcal{R}}_0^d$ is defined. The global asymptotic stability of the infection-free equilibrium is established for ${\mathcal{R}}_0^d\le 1$, and the global asymptotic stability of the endemic equilibrium is established for ${\mathcal{R}}_0^d>1$, using suitably constructed Lyapunov functionals that account for the delay history. Numerical simulations validate the analytical threshold behavior. A sensitivity analysis of ${\mathcal{R}}_0^d$ identifies the most influential parameters for potential intervention. A treatment-dependent reproduction number is derived, and the critical drug efficacy required for viral eradication is determined. The intracellular production delay is shown to act as a critical threshold for infection clearance. Full article

Objective: Developing foundational biomaterial platforms for cultured meat research requires 3D co-culture systems capable of supporting multiple relevant cell types in a spatially organized manner. This study aimed to establish a compartmentalized tri-culture hydrogel disc incorporating a lipid-containing barrier phase as a proof-of-concept in vitro model. Methods: Beeswax/alginate (Bw/Algi) hydrogels were fabricated and evaluated for morphology and cytocompatibility as a lipid-containing scaffold component. Fucoidan/alginate (Fu/Algi) hydrogels were prepared at varying fucoidan concentrations and screened to identify conditions compatible with C2C12 viability and early-stage differentiation. A composite beeswax/fucoidan/alginate disc (Bw/Fu/Algi) was then assembled by casting cell-laden Fu/Algi regions (myoblasts, fibroblasts, and endothelial cells), separated by Bw/Algi barrier layers and ionically crosslinked with CaCl₂. Scaffold performance was assessed using standard assays for morphology, cytocompatibility, myogenic marker expression, protein production, and thermal stability. Results: Bw/Algi supported cytocompatible C2C12 attachment and growth, while Fu/Algi exhibited concentration-dependent effects on myogenic marker expression, enabling selection of an optimized fucoidan concentration for 3D assembly. The final Bw/Fu/Algi disc maintained viable compartmentalized tri-culture and supported indirect co-culture through spatial separation by the Bw barrier. Myogenic regions exhibited myogenic marker expression with measurable protein production, and differential scanning calorimetry confirmed structural stability under heating. Conclusion: This work establishes a Bw/Fu/Algi tri-culture disc integrating a lipid-containing barrier component with hydrogel-based myogenic compartments, providing a preliminary platform for multicellular in vitro modeling and scaffold design relevant to cultured meat research. Full article