Search Results (36)

Malignant gliomas are the most common primary tumors of the central nervous system (CNS), originating from glial cells. They account for 30% of all CNS tumors. Among them, glioblastoma (GBM) is the most common, accounting for 45% of all glial tumors, while low-grade gliomas (LGGs) account for 31.8% of all gliomas. The aim of this study was to analyze the protein-expression profile of HTR4 and PDE4D genes in patients with glioma by immunohistochemical (IHC) analysis, to determine whether some interrelationship between them exists, to correlate their expression with clinical and histopathological parameters and therapy, and to determine their impact on patients’ survival. In addition, we analyzed the level of genomic instability (GI) (microsatellite (MIN), chromosomal (CIN) and total GI) by AP-PCR, in order to understand whether it can represent a tool for biological stratification of glioma tumors and risk assessment. Our results revealed that synchronized expression of 5-HTR4 and PDE4D proteins represents a stable modulatory signaling axis of glial-tumor biology, and reflects the activity of cAMP signaling pathway, but cannot independently stratify patients. Moreover, our study confirms that the combination of MIN, CIN and total GI represents a powerful tool for biological tumor stratification, risk assessment and understanding the pathobiological spectrum of the disease. Full article

With the increasing integration of regional energy systems, the dynamic coupling characteristics of cooling, heating, and power flows have become significantly pronounced. However, traditional scheduling models often utilize steady-state assumptions that neglect the thermal transmission delay of the pipeline network, leading to spatiotemporal mismatches between energy supply and load demand. To address this issue, this paper proposes an optimal operation strategy for regional Combined Cooling, Heating, and Power (CCHP) systems that explicitly integrates thermal inertia. First, a Pipeline Fluid Micro-element Discretization Method (PFMDM) is developed based on the Lagrangian specification to accurately characterize the dynamic flow and thermal decay processes without the heavy computational burden of partial differential equations. In addition, the accuracy of PFMDM is directly benchmarked against a high-fidelity transient PDE solver (finite-volume TVD–MUSCL scheme) over a wide range of pipe lengths, flow velocities, and thermal loss coefficients, where the outlet-temperature RMSE remains below 0.2 °C. This model quantitatively reveals the “Virtual Energy Storage” (VES) mechanism of the pipeline network. Second, to overcome the “curse of dimensionality” in dynamic scheduling, a Load-Gradient-Based Adaptive Temporal Discretization (LG-ATD) method is proposed. This method maintains a fine-grained baseline for electrical settlement while dynamically aggregating thermal/cooling steps based on load fluctuations. Simulation results demonstrate that the proposed strategy corrects the significant physical deviations of the traditional steady-state model. The analysis reveals that the steady-state model underestimates the required heating and cooling supply capacities by up to 26.66% and 39.15%, respectively, due to the neglect of transmission losses and delays. By leveraging the VES mechanism, the proposed method enables a fuel-shift in the energy-supply structure, substantially decreasing the electricity purchasing cost (by 75.2% in the tested case). This reduction reflects a reallocation from grid purchases to on-site gas-fired cogeneration to maintain physical feasibility under delay and loss effects, and therefore, it is accompanied by an increase in natural gas consumption and a higher total operating cost. Furthermore, the LG-ATD method significantly alleviates the computational burden by substantially compressing the presolved model size and reducing the overall solving time by more than 80%, thereby effectively mitigating the curse of dimensionality for practical engineering applications. Full article

Background/Objectives: Preclinical models that accurately reflect Ewing sarcoma (ES) will enable the prioritisation of clinically active targeted agents from bench to clinic. To expedite this process, we have established and characterised patient-derived ES cultures (PDES) in vitro. Methods: Fluorescence in situ hybridisation, RT-PCR and western blotting were used to examine expression of the pathognomonic EWSR1 fusions. Activation or repression of EWSR1 fusion downstream targets and proliferation was examined by immunofluorescence and immunohistochemistry. Using next-generation sequencing, the DNA and transcriptomic profiles of PDES and cell lines were compared. The response of PDES and cell lines to standard-of-care chemotherapeutics, ionising radiation and investigational drugs was examined. Results: All PDES contain EWSR1 fusion DNA, consistent with a diagnosis of ES. EWSR1 fusion gene RNA and protein were detected in 70% and 21% of PDES, respectively. Markers of proliferation and expression of EWSR1 fusion target genes were consistent with the tumours from which PDES were derived (R² = 0.74, p < 0.0001) and the paediatric mesenchymal lineage (SBS5 and SBS1, ID1 and ID2). In contrast, the transcriptome of PDES was significantly different from that of cell lines. PDES had a significantly increased doubling time (p < 0.00001), decreased expression of Ki67 (p < 0.0001) and increased migration (p < 0.02) compared to cell lines. Consistent with the longer doubling time, PDES were more resistant to doxorubicin, etoposide and vincristine and ionising radiation (p < 0.0001) than cell lines. PDES were sensitive to mTKIs (cabozantinib, lenvatinib, and regorafenib), and trabectedin. The response of PDES to drugs in vitro reflects the clinical experience of patients. Conclusions: Models incorporating PDES cells may positively contribute to the preclinical pipeline. Full article

Thoracoabdominal aortic aneurysms (TAAAs) are rare and often remain asymptomatic until rupture, leading to high morbidity and mortality. Elastin degradation, largely mediated by matrix metalloproteinases (MMPs), plays a central role in their pathogenesis. This study aimed to evaluate plasma desmosine (pDES), a specific biomarker of elastin breakdown, as a non-invasive tool for TAAA detection and risk stratification. In a prospective single-centre case–control study, 30 patients with TAAA and 30 age- and sex-matched controls were enrolled. Plasma pDES levels were quantified using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Aortic wall samples from 12 patients were analysed for elastic fibre content and MMP expression by histology and western blotting. Statistical analyses included correlation testing, propensity score matching, and receiver operating characteristic (ROC) analysis. TAAA patients exhibited significantly higher pDES levels compared with controls (0.40 ± 0.31 vs. 0.22 ± 0.15 ng/mL; p < 0.001). pDES correlated positively with MMP-2 (ρ = 0.68, p = 0.02), TIMP-1 (ρ = 0.72, p = 0.01), and the proportion of elastic fibres in the aortic media (ρ = 0.61, p = 0.03). ROC analysis showed good diagnostic performance (AUC = 0.82), with a threshold of 0.27 ng/mL yielding 78.6% sensitivity and 76.7% specificity. Elevated pDES levels reflect aortic elastolytic activity and may serve as a promising biomarker for TAAA detection and risk assessment. Full article

Alzheimer’s disease (AD) affects over 55 million individuals worldwide, yet no transformative disease-modifying therapies exist. Mathematical modelling provides a powerful framework to elucidate complex disease mechanisms, predict therapeutic outcomes, and enable precision medicine—capabilities urgently needed where multiscale spatiotemporal processes defy experimental analysis alone. We developed a mechanistic spatiotemporal model coupling four AD hallmarks: β-amyloid (Aβ) accumulation, T-protein (T-p) aggregation, neuroinflammation and electrical conductivity decline. Formulated as non-linear partial differential equations (p.d.es) on a 3-dimensional biological interpretation of non-linear terms (the ellipsoidal brain domain with biologically grounded parameters), the model was solved using eigenfunction expansion, Fourier analysis and numerical methods. Therapeutic interventions were simulated through mechanistically motivated parameter modifications and validated against longitudinal biomarker data from major cohort studies. Simulations reveal Aβ-initiated spatiotemporal cascades originating in the hippocampus and spreading radially at 0.15–0.20 cm/year, with T-pathology emerging after 2–3 years. Conductivity decline accelerates upon T-onset (year 5–7), reflecting the transition to symptomatic disease. Multimodal intervention at early symptomatic stages reduces peak Aβ by 36% and inflammation by 52% and preserves 41% more conductivity than untreated controls. Sensitivity analysis identifies Aβ production and inflammatory regulation as critical therapeutic targets, with dose–response curves demonstrating linear efficacy relationships. This biologically grounded framework explicitly links molecular pathology to functional decline, enabling patient-specific trajectory prediction through parameter calibration. The model establishes a foundation for precision medicine applications including individualized prognosis, optimal treatment timing and virtual clinical trial design, advancing quantitative systems biology of neurodegeneration. Full article

In chronic obstructive pulmonary disease (COPD), dysregulated calcium homeostasis, oxidative stress, and mucus hypersecretion converge to suppress ciliary beat frequency (CBF), thereby compromising mucociliary clearance (MCC). These mechanisms are subject to pharmacological modulation. Long-acting muscarinic antagonists (LAMAs) exert direct cilia-stimulatory effects and may counteract pathogen-induced mucin overproduction without impairing clearance. Long-acting β₂-agonists (LABAs) enhance ciliary activity through the cAMP–PKA–dynein (cyclic adenosine monophosphate–protein kinase A–dynein) signalling pathway. Inhaled corticosteroids (ICSs), although largely neutral on CBF, provide indirect protection by suppressing IL-13–driven inflammation. Phosphodiesterase (PDE)-4 inhibitors sustain intracellular cAMP and promote ciliary motility, though their clinical use remains limited by adverse effects. Emerging evidence suggests that dual and triple therapies may provide additive or synergistic benefits for preserving mucociliary function. Clinically, ex vivo CBF interpretation may be influenced by ongoing pharmacotherapy and tissue sampling site. Nasal brush samples may predominantly reflect systemic rather than inhaled therapy. Moreover, differences in PDE isoform expression between nasal and bronchial epithelium further complicate direct extrapolation of results. Rigorous patient stratification by treatment regimen is therefore essential to reconcile inconsistencies reported across studies. Ultimately, preservation of MCC in COPD depends on a delicate balance between oxidative stress and pharmacological modulation of ciliary function. Full article

Bellows compensators are critical components in pipeline systems, designed to absorb thermal expansions, vibrations, and pressure reflections. Ensuring their operational reliability requires accurate prediction of the stress–strain state (SSS) and stability under internal pressure. This study presents a comprehensive mathematical model for analyzing corrugated bellows compensators, formulated as a boundary value problem for a system of partial differential equations (PDEs) within the Kirchhoff–Love shell theory framework. Two numerical approaches are developed and compared: a finite difference method (FDM) applied to a reduced axisymmetric formulation to ordinary differential equations (ODEs) and a finite element method (FEM) for the full variational formulation. The FDM scheme utilizes a second-order implicit symmetric approximation, ensuring stability and efficiency for axisymmetric geometries. The FEM model, implemented in Ansys 2020 R2, provides high fidelity for complex geometries and boundary conditions. Convergence analysis confirms second-order spatial accuracy for both methods. Numerical experiments determine critical pressures based on the von Mises yield criterion and linearized buckling analysis, revealing the influence of geometric parameters (wall thickness, number of convolutions) on failure mechanisms. The results demonstrate that local buckling can occur at lower pressures than that of global buckling for thin-walled bellows with multiple convolutions, which is critical for structural reliability assessment. The proposed combined approach (FDM for rapid preliminary design and FEM for final verification) offers a robust and efficient methodology for bellows design, enhancing reliability and reducing development time. The work highlights the importance of integrating rigorous PDE-based modeling with modern numerical techniques for solving complex engineering problems with a focus on structural integrity and long-term performance. Full article

Background: Neoadjuvant chemotherapy (NAC) is a standard preoperative intervention for early-stage breast cancer (BC). Dynamic contrast-enhanced magnetic resonance imaging (CE-MRI) has emerged as a critical tool for evaluating treatment response and pathological complete response (pCR) following NAC. Computational modeling offers a robust framework to simulate tumor growth dynamics and therapy response, leveraging patient-specific data to enhance predictive accuracy. Despite this potential, integrating imaging data with computational models for personalized treatment prediction remains underexplored. This case study presents a proof-of-concept prognostic tool that bridges oncology, radiology, and computational modeling by simulating BC behavior and predicting individualized NAC outcomes. Methods: CE-MRI scans, clinical assessments, and blood samples from three retrospective NAC patients were analyzed. Tumor growth was modeled using a system of partial differential equations (PDEs) within a reaction–diffusion mass transfer framework, incorporating patient-specific CE-MRI data. Tumor volumes measured pre- and post-treatment were compared with model predictions. A 20% error margin was applied to assess computational accuracy. Results: All cases were classified as true positive (TP), demonstrating the model’s capacity to predict tumor volume changes within the defined threshold, achieving 100% precision and sensitivity. Absolute differences between predicted and observed tumor volumes ranged from 0.07 to 0.33 cm³. Virtual biomarkers were employed to quantify novel metrics: the biological conversion coefficient ranged from 4 × 10⁻⁷ to 6 × 10⁻⁶ s⁻¹, while the pharmacodynamic efficiency coefficient ranged from 1 × 10⁻⁷ to 4 × 10⁻⁴ s⁻¹, reflecting intrinsic tumor biology and treatment effects, respectively. Conclusions: This approach demonstrates the feasibility of integrating CE-MRI and computational modeling to generate patient-specific treatment predictions. Preliminary model training on retrospective cohorts with matched BC subtypes and therapy regimens enabled accurate prediction of NAC outcomes. Future work will focus on model refinement, cohort expansion, and enhanced statistical validation to support broader clinical translation. Full article

Highly selective inhibitors of the members of the cAMP-selective cyclic nucleotide phosphodiesterases, or PDE4 family, have shown clinically meaningful activity in two different classes of lung disease: roflumilast in obstructive lung disease, specifically chronic obstructive pulmonary disease (COPD), and nerandomilast in restrictive lung diseases characterized by inflammation/fibrosis of the alveolar interstitium, including idiopathic pulmonary fibrosis (IPF) and progressive pulmonary fibrosis (PPF). The beneficial therapeutic benefit of these agents in both of these disorders suggests that they share a common mechanism that underlies their effects on different pulmonary cells and tissues. This review outlines the biochemical, pharmacologic and cellular effects of PDE4-selective inhibitors, emphasizing their role in signal transduction pathways common to many pulmonary cell types. It then compares and contrasts the myriad cellular effects of these agents and their effects in pre-clinical animal models of these disorders. The emerging data are compatible with PDE4-selective inhibitors having targets of action in a large number of pulmonary cell types, only a subset of which is dysregulated in either COPD or IPF. This suggests that differences between the benefits observed with these individual agents in their various clinical indications reflect differences in disease pathogenesis, rather than proven differences in the enzyme-inhibitory effects of the various PDE4 inhibitors that have been studied to date. Full article

South African cattle comprise diverse breeds with distinct evolutionary histories, potentially reflecting differences in recombination landscapes. This study assessed genome-wide recombination rates and hotspots in Bonsmara (n = 190) and Nguni (n = 119) cattle using three-generation half-sib pedigrees genotyped with the Illumina Bovine SNP50 BeadChip. Phasing across 29 autosomes was conducted using SHAPEIT v2, and crossover events were inferred using the DuoHMM algorithm. The total number of crossover events detected was higher in Nguni (n = 8982) than in Bonsmara (n = 7462); however, the average recombination rate per 1 Mb window was significantly higher in Bonsmara (0.31) compared to Nguni (0.18) (p < 0.01). This apparent discrepancy reflects differences in genomic distribution and crossover clustering across breeds, rather than overall recombination frequency. A critical limitation of the study is the reliance on half-sib families with small family sizes, which may underestimate recombination rates due to limited meiotic sampling and increased variance in crossover detection. We identified 407 recombination hotspots in Bonsmara and 179 in Nguni, defined as intervals exceeding 2.5 standard deviations above the mean recombination rate. Genes such as PDE1B and FP which are associated with productions traits were located within hotspot-enriched regions. However, functional causality between these genes and local recombination activity remains unverified. Our results provide statistically supported evidence for breed-specific recombination patterns and hotspot distributions, underscoring the importance of incorporating recombination architecture into genetic improvement strategies for South African cattle. Full article

A model for the flow and thermal explosion of a micropolar gas is investigated, assuming the equation of state for a real gas. This model describes the dynamics of a gas mixture (fuel and oxidant) undergoing a one-step irreversible chemical reaction. The real gas model is particularly suitable in this context because it more accurately reflects reality under extreme conditions, such as high temperatures and high pressures. Micropolarity introduces local rotational dynamic effects of particles dispersed within the gas mixture. In this paper, we first derive the initial-boundary value system of partial differential equations (PDEs) under the assumption of spherical symmetry and homogeneous boundary conditions. We explain the underlying physical relationships and then construct a corresponding approximate system of ordinary differential equations (ODEs) using the Faedo–Galerkin projection. The existence of solutions for the full PDE model is established by analyzing the limit of the solutions of the ODE system using a priori estimates and compactness theory. Additionally, we propose a numerical scheme for the problem based on the same approximate system. Finally, numerical simulations are performed and discussed in both physical and mathematical contexts. Full article

A Cournot triopoly is a type of oligopoly market involving three firms that produce and sell homogeneous or similar products without cooperating with one another. In Cournot models, firms’ decisions about production levels play a crucial role in determining overall market output. Compared to duopoly models, oligopolies with more than two firms have received relatively less attention in the literature. Nevertheless, triopoly models are more reflective of real-world market conditions, even though analyzing their dynamics remains a complex challenge. A reaction–diffusion system of PDEs generalizing a nonlinear triopoly model describing a master–slave Cournot game is introduced. The effect of diffusion on the stability of Nash equilibrium is investigated. Self-diffusion alone cannot induce Turing pattern formation. In fact, linear stability analysis shows that cross-diffusion is the key mechanism for the formation of spatial patterns. The conditions for the onset of cross-diffusion-driven instability are obtained via linear stability analysis, and the formation of several Turing patterns is investigated through numerical simulations. Full article

PDE11A is a little-studied phosphodiesterase sub-family that breaks down cAMP/cGMP, with the PDE11A4 isoform enriched in the memory-related hippocampal formation. Age-related increases in PDE11A expression occur in human and rodent hippocampus and cause age-related cognitive decline of social memories. Interestingly, age-related increases in PDE11A4 protein ectopically accumulate in spherical clusters that group together in the brain to form linear filamentous patterns termed “PDE11A4 ghost axons”. The biophysical/physiochemical mechanisms underlying this age-related clustering are not known. Here, we determine if age-related clustering of PDE11A4 reflects liquid–liquid phase separation (LLPS; biomolecular condensation), and if PDE11A inhibitors can reverse this LLPS. We show human and mouse PDE11A4 exhibit several LLPS-promoting sequence features, including intrinsically disordered regions, non-covalent pi–pi interactions, and prion-like domains that were particularly enriched in the N-terminal regulatory region. Further, multiple bioinformatic tools predict PDE11A4 undergoes LLPS. Consistent with these predictions, aging-like PDE11A4 clusters in HT22 hippocampal neuronal cells were membraneless spherical droplets that progressively fuse over time in a concentration-dependent manner. Deletion of the N-terminal intrinsically disordered region prevented PDE11A4 LLPS despite equal protein expression between WT and mutant constructs. 1,6-hexanediol, along with tadalafil and BC11-38 that inhibit PDE11A4, reversed PDE11A4 LLPS in HT22 hippocampal neuronal cells. Interestingly, PDE11A4 inhibitors reverse PDE11A4 LLPS independently of increasing cAMP/cGMP levels via catalytic inhibition. Importantly, orally dosed tadalafil reduced PDE11A4 ghost axons in old mouse ventral hippocampus by 50%. Thus, PDE11A4 exhibits the four defining criteria of LLPS, and PDE11A inhibitors reverse this age-related phenotype both in vitro and in vivo. Full article

Pulse detonation engines (PDEs) have become a transformative technology in the field of aerospace propulsion due to the high thermal efficiency of detonation combustion. However, initiating detonation waves within a limited space and time is key to their engineering application. Direct initiation, though theoretically feasible, requires very high critical energy, making it almost impossible to achieve in engineering applications. Therefore, indirect initiation methods are more practical for triggering detonation waves that produce a deflagration wave through a low-energy ignition source and realizing deflagration to detonation transition (DDT) through flame acceleration and the interaction between flames and shock waves. This review systematically summarizes recent advancements in DDT methods in pulse detonation engines, focusing on the basic principles, influencing factors, technical bottlenecks, and optimization paths of the following: hot jet ignition initiation, obstacle-induced detonation, shock wave focusing initiation, and plasma ignition initiation. The results indicate that hot jet ignition enhances turbulent mixing and energy deposition by injecting energy through high-energy jets using high temperature and high pressure; this can reduce the DDT distance of hydrocarbon fuels by 30–50%. However, this approach faces challenges such as significant jet energy dissipation, flow field instability, and the complexity of the energy supply system. Solid obstacle-induced detonation passively generates turbulence and shock wave reflection through geometric structures to accelerate flame propagation, which has the advantages of having a simple structure and high reliability. However, the problem of large pressure loss and thermal fatigue restricts its long-term application. Fluidic obstacle-induced detonation enhances mixing uniformity through dynamic disturbance to reduce pressure loss. However, its engineering application is constrained by high energy consumption requirements and jet–mainstream coupling instability. Shock wave focusing utilizes concave cavities or annular structures to concentrate shock wave energy, which directly triggers detonation under high ignition efficiency and controllability. However, it is extremely sensitive to geometric parameters and incident shock wave conditions, and the structural thermal load issue is prominent. Plasma ignition generates active particles and instantaneous high temperatures through high-energy discharge, which chemically activates fuel and precisely controls the initiation sequence, especially for low-reactivity fuels. However, critical challenges, such as high energy consumption, electrode ablation, and decreased discharge efficiency under high-pressure environments, need to be addressed urgently. In order to overcome the bottlenecks in energy efficiency, thermal management, and dynamic stability, future research should focus on multi-modal synergistic initiation strategies, the development of high-temperature-resistant materials, and intelligent dynamic control technologies. Additionally, establishing a standardized testing system to quantify DDT distance, energy thresholds, and dynamic stability indicators is essential to promote its transition to engineering applications. Furthermore, exploring the DDT mechanisms of low-carbon fuels is imperative to advance carbon neutrality goals. By summarizing the existing DDT methods and technical bottlenecks, this paper provides theoretical support for the engineering design and application of PDEs, contributing to breakthroughs in the fields of hypersonic propulsion, airspace shuttle systems, and other fields. Full article

Porcine latissimus dorsi muscle (LDM) is a crucial source of pork products. Meat quality indicators, such as the proportion of muscle fibers and intramuscular fat (IMF) deposition, vary during the growth and development of pigs. Numerous studies have highlighted the heterogeneous nature of skeletal muscle, with phenotypic differences reflecting variations in cellular composition and transcriptional profiles. This study investigates the cellular-level transcriptional characteristics of LDM in large white pigs at two growth stages (170 days vs. 245 days) using single-nucleus RNA sequencing (snRNA-seq). We identified 56,072 cells across 12 clusters, including myofibers, fibro/adipogenic progenitor (FAP) cells, muscle satellite cells (MUSCs), and other resident cell types. The same cell types were present in the LDM at both growth stages, but their proportions and states differed. A higher proportion of FAPs was observed in the skeletal muscle of 245-day-old pigs. Additionally, these cells exhibited more active communication with other cell types compared to 170-day-old pigs. For instance, more interactions were found between FAPs and pericytes or endothelial cells in 245-day-old pigs, including collagen and integrin family signaling. Three subclasses of FAPs was identified, comprising FAPs_COL3A1⁺, FAPs_PDE4D⁺, and FAPs_EBF1⁺, while adipocytes were categorized into Ad_PDE4D⁺ and Ad_DGAT2⁺ subclasses. The proportions of these subclasses differed between the two age groups. We also constructed differentiation trajectories for FAPs and adipocytes, revealing that FAPs in 245-day-old pigs differentiated more toward fibrosis, a characteristic reminiscent of the high prevalence of skeletal muscle fibrosis in aging humans. Furthermore, the Ad_PDE4D⁺ adipocyte subclass, predominant in 245-day-old pigs, originated from FAPs_PDE4D⁺ expressing the same gene, while the Ad_DGAT2⁺ subclass stemmed from FAPs_EBF1⁺. In conclusion, our study elucidates transcriptional differences in skeletal muscle between two growth stages of pigs and provides insights into mechanisms relevant to pork meat quality and skeletal muscle diseases. Full article