In recent years, there has been a growing interest in the research on NOD-like receptor thermal protein domain associated protein 3(NLRP3) inflammasome inhibitors in the treatment of inflammatory diseases. The NLRP3 inflammasome is integral to the innate immune response, and its abnormal activation can lead to the release of pro-inflammatory cytokine, consequently facilitating the progression of various pathological conditions. Therefore, investigating the pharmacological inhibition pathway of the NLRP3 inflammasome represents a promising strategy for the treatment of inflammation-related diseases. Currently, the Food and Drug Administration(FDA) has not approved drugs targeting the NLRP3 inflammasome for clinical use due to concerns regarding liver toxicity and gastrointestinal side effects associated with chemical small molecule inhibitors in clinical trials. Natural small molecule compounds such as polyphenols, flavonoids, and alkaloids are ubiquitously found in animals, plants, and other natural substances exhibiting pharmacological activities. Their abundant sources, intricate and diverse structures, high biocompatibility, minimal adverse reactions, and superior biochemical potency in comparison to synthetic compounds have attracted the attention of extensive scholars. Currently, certain natural small molecule compounds have been demonstrated to impede the activation of the NLRP3 inflammasome via various action mechanisms, so they are viewed as the innovative, feasible, and minimally toxic therapeutic agents for inhibiting NLRP3 inflammasome activation in the treatment of both acute and chronic inflammatory diseases. Hence, this study systematically examined the effects and potential mechanisms of natural small molecule compounds derived from traditional Chinese medicine on the activation of NLRP3 inflammasomes at their initiation, assembly, and activation stages. The objection is to furnish theoretical support and practical guidance for the effective clinical application of these natural small molecule inhibitors.
NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammasomes/metabolism* ; Inflammation/drug therapy* ; Anti-Inflammatory Agents/therapeutic use* ; Humans ; Animals ; Disease Models, Animal ; Biological Products/therapeutic use* ; Drug Discovery ; Medicine, Chinese Traditional/methods*

Alveolar bone reconstruction simulation is an effective means for quantifying orthodontics, but currently, it is not possible to directly obtain human alveolar bone material models for simulation. This study introduces a prediction method for the equivalent shear modulus of three-dimensional random porous materials, integrating the first-order Ogden hyperelastic model to construct a computed tomography (CT) based porous hyperelastic Ogden model (CT-PHO) for human alveolar bone. Model parameters are derived by combining results from micro-CT, nanoindentation experiments, and uniaxial compression tests. Compared to previous predictive models, the CT-PHO model shows a lower root mean square error (RMSE) under all bone density conditions. Simulation results using the CT-PHO model parameters in uniaxial compression experiments demonstrate more accurate prediction of the mechanical behavior of alveolar bone under compression. Further prediction and validation with different individual human alveolar bone samples yield accurate results, confirming the generality of the CT-PHO model. The study suggests that the CT-PHO model proposed in this paper can estimate the material properties of human alveolar bone and may eventually be used for bone reconstruction simulations to guide clinical treatment.
Humans ; Tomography, X-Ray Computed/methods* ; Porosity ; Alveolar Process/physiology* ; Bone Density ; Computer Simulation ; Elasticity ; X-Ray Microtomography ; Stress, Mechanical ; Finite Element Analysis ; Models, Biological

Glaucoma is the leading cause of irreversible blindness worldwide, with its primary risk factor arising from elevated intraocular pressure (IOP) due to an imbalance between aqueous humor production and outflow. This study aims to establish quantitative correlations among IOP, iris mechanical properties, channel microstructures, and aqueous humor dynamics through three-dimensional modeling and finite element analysis, overcoming the limitations of conventional experimental techniques in studying aqueous flow within the trabecular meshwork (TM) outflow pathway. A three-dimensional fluid-structure interaction (FSI) model incorporating the layered TM structure, Schlemm's canal (SC), iris, and other anterior segment tissues was developed based on human ocular anatomy. FSI simulations were performed to quantify the effects of IOP variations and iris Young's modulus on tissue morphology and aqueous humor dynamics parameters. The computational results demonstrated that axial iris deformation showed significant correlations with IOP and iris Young's modulus. Although elevated IOP exhibited minimal effects on hydrodynamic parameters in the anterior and posterior chambers, it markedly suppressed aqueous flow velocity in the TM region. Additionally, wall shear stress in SC and collector channels displayed high sensitivity to IOP variations. These findings reveal that the tissue mechanics-FSI mechanism modulates outflow resistance by regulating aqueous humor dynamics, offering valuable references for developing clinical therapies targeting IOP reduction in glaucoma management.
Humans ; Trabecular Meshwork/anatomy & histology* ; Finite Element Analysis ; Aqueous Humor/metabolism* ; Intraocular Pressure/physiology* ; Glaucoma/physiopathology* ; Iris/anatomy & histology* ; Computer Simulation ; Models, Biological

In order to characterize the characteristics of pathological tremor of human upper limb, a simulation system of pathological tremor of human arm was provided and its dynamic response was analyzed. Firstly, in this study, a two-degree-of-freedom human arm dynamic model was established and linearized according to the arbitrary initial angle of joints. After solving the analytical solutions of steady-state responses of the joints, the numerical solution was used to verify it. The results of theoretical analysis show that the two natural frequencies of the developed dynamic model are 2.9 Hz and 5.4 Hz, respectively, which meet the characteristic frequency range of pathological tremors. Then, combined with the measured parameters of human arm, a tremor simulation system was built, and the measured results of joint responses are in good agreement with the theoretical and simulation analysis results, which verifies the effectiveness of the theoretical model. The results show that the human arm pathological tremor simulation system designed in this paper can characterize the frequency and response amplitude of the human upper limb pathological tremor. Moreover, the relevant research lays a theoretical foundation and experimental conditions for the subsequent development of wearable tremor suppression devices.
Humans ; Tremor/physiopathology* ; Computer Simulation ; Arm/physiopathology* ; Joints/physiopathology* ; Biomechanical Phenomena ; Upper Extremity/physiopathology* ; Models, Biological

The lumbar intervertebral disc exhibits a complex physiological structure with interactions between various segments, and its components are extremely complex. The material properties of different components in the lumbar intervertebral disc, especially the water content (undergoing dynamic change as influenced by age, degeneration, mechanical loading, and proteoglycan content) - critically determine its mechanical properties. When the lumbar intervertebral disc is under continuous pressure, water seeps out, and after the pressure is removed, water re-infiltrates. This dynamic fluid exchange process directly affects the mechanical properties of the lumbar intervertebral disc, while previous isotropic modeling methods have been unable to accurately reflect such solid-liquid phase behaviors. To explore the load-bearing mechanism of the lumbar intervertebral disc and establish a more realistic mechanical model of the lumbar intervertebral disc, this study developed a solid-liquid biphasic, fiber-reinforced finite element model. This model was used to simulate the four movements of the human lumbar spine in daily life, namely flexion, extension, axial rotation, and lateral bending. The fluid pressure, effective solid stress, and liquid pressure-bearing ratio of the annulus fibrosus and nucleus pulposus of different lumbar intervertebral discs were compared and analyzed under the movements. Under all the movements, the fluid pressure distribution was closer to the nucleus pulposus, while the effective solid stress distribution was more concentrated in the outer annulus fibrosus. In terms of fluid pressure, the maximum fluid pressure of the lumbar intervertebral disc during lateral bending was 1.95 MPa, significantly higher than the maximum fluid pressure under other movements. Meanwhile, the maximum effective solid stress of the lumbar intervertebral disc during flexion was 2.43 MPa, markedly higher than the maximum effective solid stress under other movements. Overall, the liquid pressure-bearing ratio under axial rotation was smaller than that under other movements. Based on the solid-liquid biphasic modeling method, this study more accurately revealed the dominant role of the liquid phase in the daily load-bearing process of the lumbar intervertebral disc and the solid-phase mechanical mechanism of the annulus fibrosus load-bearing, and more effectively predicted the solid-liquid phase co-load-bearing mechanism of the lumbar intervertebral disc in daily life.
Humans ; Finite Element Analysis ; Intervertebral Disc/physiology* ; Lumbar Vertebrae/physiology* ; Weight-Bearing/physiology* ; Biomechanical Phenomena ; Stress, Mechanical ; Computer Simulation ; Models, Biological

OpenSim is an open source, free motion simulation and gait analysis software, which can be used to dynamically simulate and analyze the complex motion of the human body, and is widely used in human biomechanical research. Since OpenSim can analyze multi-dimensional motion data such as muscle strength, joint torque, and muscle synergistic activation during human movement, it can be used to study the biomechanical mechanism of musculoskeletal imbalance diseases and various treatment methods in TCM orthopedics, and has a broad application prospect in the field of TCM orthopedics. By the analysis of the basic characteristics, elements, analysis process, and application prospects of OpenSim, it is concluded that OpenSim musculoskeletal model has a large application space in the field of traditional Chinese medicine orthopedic, which is helpful to explain the pathogenesis and mechanism of diseases, and promote the precision diagnosis and treatment of orthopedics diseases;the application of OpenSim musculoskeletal model can solve the problem that the previous research paid attention to the bone malalignment and not enough attention to the tendon, and provide a new method for the research of orthopedic diseases. At present, there are still problems in the promotion and application of OpenSim, such as large equipment requirements and high operation threshold. Therefore, multidisciplinary cooperation, clinical research, and data sharing are the basic research strategies in this field.
Humans ; Biomechanical Phenomena ; Orthopedics ; Traumatology ; Software ; Medicine, Chinese Traditional ; Musculoskeletal System ; Models, Biological

Chronic obstructive pulmonary disease (COPD) currently lacks effective treatments to halt disease progression, making the search for preventive and therapeutic drugs a pressing issue. Natural products, with their accessibility, affordability, and low toxicity, offer promising avenues. Investigating the pharmacological effects and related signaling mechanisms of active components from natural products on COPD animal models induced by various triggers has become an important focus. In animal models induced by cigarette smoke, cigarette smoke combined with lipopolysaccharide (LPS), air pollution, elastase, bacterial or viral infections, the active compounds of natural products, such as flavonoids, terpenoids, and phenolics, can exert anti-inflammatory, antioxidant, mucus-regulating, and airway remodeling-inhibiting effects through key signaling pathways including nuclear factor-erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1), nuclear factor-kappa B (NF-κB), and mitogen-activated protein kinase (MAPK). These findings not only provide a theoretical basis for the clinical diagnosis and treatment of COPD but also point to new directions for future scientific research.
Pulmonary Disease, Chronic Obstructive/etiology* ; Animals ; Disease Models, Animal ; Biological Products/pharmacology* ; Humans ; NF-kappa B/metabolism* ; Flavonoids/pharmacology* ; Signal Transduction/drug effects* ; Anti-Inflammatory Agents/pharmacology* ; Heme Oxygenase-1/metabolism* ; Terpenes/pharmacology* ; Antioxidants/pharmacology* ; NF-E2-Related Factor 2/metabolism* ; Smoke/adverse effects* ; Phenols/therapeutic use*

OBJECTIVES: To explore the key role of myeloid-derived suppressive cells (MDSCs) in pre-metastatic niche (PMN) and analyze their interrelationships with the main components in the microenvironment using a mathematical model. METHODS: Mathematical descriptions were used to systematically analyze the functions of MDSCs in tumor metastasis and elucidate their association with the major components (vascular endothelial cells, mesenchymal stromal cells, and cancer-associated macrophages) contributing to the formation of the pre-metastatic microenvironment. Based on the formation principle of the pre-metastatic microenvironment of tumors, the key biological processes were assumed to construct a coupled partial differential diffusion equation model. The existence and uniqueness of the model solutions were investigated using approximation methods, the qualitative theory of partial differential equations and Banach's immovable point theorem, and numerical simulations were carried out by differential numerical methods to verify the reliability and accuracy of the model. RESULTS: The existence and uniqueness of the local and overall solutions of the model were proved using the approximation method, the qualitative theory of partial differential equations and Banach's immovable point theorem in combination with the regularity estimation of the local solutions and the embedding inequality. Numerical simulation results further validated the reliability of the model and demonstrated the important role of MDSCs in the pre-metastatic microenvironment of tumors, especially in angiogenesis and immunosuppression. CONCLUSIONS This study reveals the important functions of MDSCs in the pre-metastatic microenvironment of tumors through mathematical modeling and numerical simulation, which provides an important theoretical basis for understanding the mechanism of tumor metastasis and devising cancer treatment strategies.
Tumor Microenvironment ; Myeloid-Derived Suppressor Cells ; Neoplasm Metastasis ; Humans ; Models, Biological ; Models, Theoretical ; Neoplasms/pathology*

Biomanufacturing harnesses engineered cells for the large-scale production of biochemicals, biopharmaceuticals, biofuels, and biomaterials, playing a vital role in mitigating global environmental crises, achieving carbon peaking and neutrality, and driving the green transformation of the economy and society. The effective design and construction of these engineered cells require precise and comprehensive computational models. Recent technological breakthroughs including high-throughput sequencing, mass spectrometry, spectroscopy, and microfluidic devices, coupled with advances in data science, artificial intelligence, and automation, have enabled the rapid acquisition of large-scale biological datasets, thereby facilitating a deeper understanding of cellular dynamics and the construction of mechanism-based models with enhanced accuracy. This review systematically summarises the mathematical frameworks employed in cellular modelling. It begins by evaluating prevalent mathematical paradigms, such as network topology analyses, stochastic processes, and kinetic equations, critically assessing their applicability across various contexts. The discussion then categorises modelling strategies for specific cellular processes, including cellular growth and division, morphogenesis, DNA replication, transcriptional regulation, metabolism, signal transduction, and quorum sensing. We also examine the recent progress in developing whole-cell models through the integration of diverse cellular processes. The review concludes by addressing key challenges such as data scarcity, unknown mechanisms, multi-dimensional data integration, and exponentially escalating computational complexity. Overall, this work consolidates the mathematical models for the precise simulation of cellular processes, thereby enhancing our understanding of the molecular mechanisms governing cellular functions and contributing to the future design and optimisation of engineered organisms.
Models, Biological ; Cell Physiological Phenomena ; Cell Engineering/methods* ; Humans

The metabolic reactions in cells, whether spontaneous or enzyme-catalyzed, form a highly complex metabolic network closely related to cellular physiological metabolic activities. The reconstruction of cellular physiological metabolic network models aids in systematically elucidating the relationship between genotype and growth phenotype, providing important computational biology tools for precisely characterizing cellular physiological metabolic activities and green biomanufacturing. This paper systematically introduces the latest research progress in different types of cellular physiological metabolic network models, including genome-scale metabolic models (GEMs), kinetic models, and enzyme-constrained genome-scale metabolic models (ecGEMs). Additionally, our paper discusses the advancements in the automated construction of GEMs and strategies for condition-specific GEM modeling. Considering artificial intelligence offers new opportunities for the high-precision construction of cellular physiological metabolic network models, our paper summarizes the applications of artificial intelligence in the development of kinetic models and enzyme-constrained models. In summary, the high-quality reconstruction of the aforementioned cellular physiological metabolic network models will provide robust computational support for future research in quantitative synthetic biology and systems biology.
Metabolic Networks and Pathways/physiology* ; Models, Biological ; Artificial Intelligence ; Systems Biology ; Kinetics ; Cell Physiological Phenomena ; Computational Biology ; Synthetic Biology ; Humans