Health management is highly complex due to interactions across multiple levels and factors. System dynamics model (SDM) offers a holistic perspective and a dynamic analytical framework for understanding such complex systems. It has been applied across various domains of health management, including psychological interventions, chronic disease management, rehabilitation, optimization of medical services, and health policy development. By identifying key factors and pathways influencing health behaviors, determining critical targets for interventions, conducting cost-benefit analyses and process optimization, and simulating the long-term effects of health policies, SDM provides quantitative support for decision-making from individual-level interventions to macro-level policies. This article reviews the application of SDM in these four major areas within health management, discusses its advantages and limitations, and serves as a reference for researchers and practitioners aiming to utilize SDM in future studies. The goal is to advance health management toward greater personalization and precision, thereby offering stronger support for health interventions and policy development.
Humans ; Health Policy ; Models, Theoretical

Continuous manufacturing, as an innovative pharmaceutical production model, offers advantages such as high production efficiency and ease of control compared to traditional batch production, aligning with the future trend of drug production moving toward greater efficiency and intelligence. However, the development of continuous manufacturing technology in wet granulation has been slow. On one hand, this is closely related to its high technical complexity, substantial equipment investment costs, and stringent process control requirements. On the other hand, the long-term use of the traditional batch production model has created strong path dependence, and the lack of mature standardized processes further increases the difficulty of technological transformation. To promote the deep integration of wet granulation technology with continuous manufacturing, this review systematically outlines the current application of wet granulation in continuous manufacturing. It focuses on the development of key technologies such as online detection, process modeling, and process scale-up, with the aim of providing a reference for process innovation and application in wet granulation.
Drug Compounding/instrumentation* ; Technology, Pharmaceutical/methods* ; Drugs, Chinese Herbal/chemistry* ; Models, Theoretical

The extraction process of traditional Chinese medicine(TCM) is an important part in the production and processing of TCM products. The modeling of this process is of great significance for achieving intelligent production. This paper summarizes the modeling methods for the extraction process of TCM, which mainly include mechanism modeling, empirical formula modeling, data-driven modeling, and mixed modeling. Among them, mechanism modeling and data-driven modeling are widely used. Furthermore, this paper suggests that the future research on the modeling of the extraction process of TCM can be carried out from the following five aspects: in-depth research and development of the extraction process of TCM compound prescriptions, complete description of the whole extraction process of TCM, development of methods for accurate determination of the properties of TCM decoction pieces before extraction, development of adaptive self-optimization technology for models, and construction of models based on a new generation of artificial intelligence methods.
Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/methods* ; Models, Theoretical ; Artificial Intelligence ; Humans

Exercise intervention is an important non-pharmacological intervention for various diseases, and establishing precise exercise load assessment techniques can improve the quality of exercise intervention and the efficiency of disease prevention and control. Based on data collection from wearable devices, this study conducts nonlinear optimization and empirical verification of the original "Fitness-Fatigue Model". By constructing a time-varying attenuation function and specific coefficients, this study develops an optimized mathematical model that reflects the nonlinear characteristics of training responses. Thirteen participants underwent 12 weeks of moderate-intensity continuous cycling, three times per week. For each training session, external load (actual work done) and internal load (heart rate variability index) data were collected for each individual to conduct a performance comparison between the optimized model and the original model. The results show that the optimized model demonstrates a significantly improved overall goodness of fit and superior predictive ability. In summary, the findings of this study can support dynamic adjustments to participants' training programs and aid in the prevention and control of chronic diseases.
Humans ; Wearable Electronic Devices ; Exercise/physiology* ; Models, Theoretical ; Heart Rate/physiology* ; Exercise Therapy

Medical robotic arm often encounters multi-source and nonlinear errors during the calibration process, making it difficult for traditional mathematical modeling methods to fully characterize system error features, thereby limiting further improvement in calibration accuracy. In this study, a robotic arm parameter error identification model is established, and a calibration method based on an adaptive long short-term memory (ALSTM) neural network is proposed. The method incorporates a particle swarm optimization (PSO) algorithm to optimize the weights of each layer of the LSTM neural network, enabling more effective fitting of robotic arm kinematic errors and ultimately yielding more accurate Denavit-Hartenberg (D-H) parameters. To validate the proposed approach, 110 sets of experimental data are collected using the HSR-JR680 robotic arm calibration system. Experimental results demonstrate that the ALSTM model reduces the root mean square error (RMSE) by 23.07%-80.39% compared to traditional calibration methods, and shortens the convergence time by 32.44% compared to a standard LSTM model. The optimized D-H parameters obtained meet the high-precision calibration requirements of medical robotic arm, confirming the effectiveness of the proposed method.
Calibration ; Neural Networks, Computer ; Algorithms ; Robotics ; Robotic Surgical Procedures ; Models, Theoretical

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*

OBJECTIVE: To analyze Chinese medicine (CM) prescriptions for gastroesophageal reflux disease (GERD), we model topics on GERD-related classical CM literature, providing insights into the potential treatment. METHODS: Clinical guidelines were used to identify symptom terms for GERD, and CM literature from the database "Imedbooks" was retrieved for related prescriptions and their corresponding sources, indications, and other information. BERTopic was applied to identify the main topics and visualize the data. RESULTS: A total of 36,207 entries are queried and 1,938 valid entries were acquired after manually filtering. Eight topics were identified by BERTopic, including digestion function abate, stomach flu, respiratory-related symptoms, gastric dysfunction, regurgitation and gastrointestinal dysfunction in pediatric patients, vomiting, stroke and alcohol accumulation are associated with the risk of GERD, vomiting and its causes, regurgitation, epigastric pain, and symptoms of heartburn. CONCLUSIONS Topic modeling provides an unbiased analysis of classical CM literature on GERD in a time-efficient and scale-efficient manner. Based on this analysis, we present a range of treatment options for relieving symptoms, including herbal remedies and non-pharmacological interventions such as acupuncture and dietary therapy.
Humans ; Gastroesophageal Reflux/drug therapy* ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/therapeutic use* ; Models, Theoretical

There are a large number of natural microbial communities in nature. Different populations inside the consortia expand the performance boundary of a single microbial population through communication and division of labor, reducing the overall metabolic burden and increasing the environmental adaptability. Based on engineering principles, synthetic biology designs or modifies basic functional components, gene circuits, and chassis cells to purposefully reprogram the operational processes of the living cells, achieving rich and controllable biological functions. Introducing this engineering design principle to obtain structurally well-defined synthetic microbial communities can provide ideas for theoretical studies and shed light on versatile applications. This review discussed recent progresses on synthetic microbial consortia with regard to design principles, construction methods and applications, and prospected future perspectives.
Microbial Consortia/genetics* ; Synthetic Biology ; Microbiota ; Models, Theoretical

The ethanol precipitation process of Nauclea officinalis extract was optimized based on the concept of quality by design(QbD). Single factor tests were carried out to determine the levels of test factors. The ethanol volume fraction, pre-ethanol precipitation drug concentration, and ethanol precipitation time were taken as critical process parameters(CPPs). With the comprehensive scores of strictosamide transfer rate and solid removal rate as the critical quality attributes(CQAs), Box-Behnken design was employed to establish the mathematical models and space design between CPPs and CQAs, and the obtained optimal operating space was validated. The optimal operating space included ethanol volume fraction of 65%-70%, pre-ethanol precipitation drug concentration of 22-27 mg·mL~(-1), and ethanol precipitation time of 12 h. Based on the concept of QbD, this study adopted the design space to optimize the ethanol precipitation process of N. officinalis extract, which provided a reliable theoretical basis for the quality control in the production process of N. officinalis preparations. Moroever, this study provided a reference value for guiding the research and industrial production of traditional Chinese medicines.
Drugs, Chinese Herbal ; Ethanol ; Medicine, Chinese Traditional ; Quality Control ; Models, Theoretical

Aortic Dissection ; Aortic Aneurysm, Thoracic ; Humans ; Models, Theoretical