Multibody dynamics simulation of the musculoskeletal system is an essential tool for analyzing the biomechanical mechanisms underlying human motion.Recent research trends have shifted from traditional physics-based models toward data-driven or data-physics hybrid frameworks.This review presents the latest developments in these areas.Physics-based multibody dynamics simulations have undergone significant progress in terms of simulation fidelity,optimization algorithms,and software tools.However,their practical implementation remains constrained by the need for complex experimental data and the computational expense of solving differential equations.Conversely,data-driven method bolstered by advancements in deep learning have demonstrated remarkable efficiency in predicting joint angles,postures,ground reaction forces,joint torques,and muscle forces,as well as developing control algorithms for exoskeletons.However,despite these advantages,data-driven approaches face challenges such as limited generalizability and potential violation of biomechanical principles.To address these limitations,data-physics hybrid approaches(e.g.,physics-informed neural network,PINN)which integrate physical constraints(e.g.,Newton-Euler equations,muscle constitutive laws)with data-driven architectures have been developed.This synergy enhances prediction accuracy while preserving the biological plausibility of solutions.Nevertheless,critical challenges persist,including the integration of multi-scale physical equations and the modeling of multi-joint coordination dynamics.Future research should prioritize:optimizing hybrid model architectures to balance computational efficiency and mechanistic accuracy,incorporating markerless motion capture techniques to improve real-world applicability,exploiting multi-scale physics and personalized parameter inversion to advance precision rehabilitation and motion analysis.These efforts will foster innovations in intelligent rehabilitation systems,clinical motion assessment,and related translational fields.

OBJECTIVES: To determine the pharmacological impact of hesperidin, the main component of Citri Reticulatae Pericarpium, on depressive behavior and elucidate the mechanism by which hesperidin treats depression, focusing on the gut-brain axis. METHODS: Fifty-four Sprague Dawley male rats were randomly allocated to 6 groups using a random number table, including control, model, hesperidin, probiotics, fluoxetine, and Citri Reticulatae Pericarpium groups. Except for the control group, rats in the remaining 5 groups were challenged with chronic unpredictable mild stress (CUMS) for 21 days and housed in single cages. The sucrose preference test (SPT), immobility time in the forced swim test (FST), and number in the open field test (OFT) were performed to measure the behavioral changes in the rats. Enzyme-linked immunosorbent assay was used to determine the levels of 5-hydroxytryptamine (5-HT) and brain-derived neurotrophic factor (BDNF) in brain tissue, and the histopathology was performed to evaluate the changes of colon tissue, together with sequencing of the V3-V4 regions of 16S rRNA gene on feces to explore the changes of intestinal flora in the rats. RESULTS: Compared to the control group, the rats in the model group showed notable reductions in body weight, SPF, and number in OFT (P<0.01). Hesperidin was found to ameliorate depression induced by CUMS, as seen by improvements in body weight, SPT, immobility time in FST, and number in OFT (P<0.05 or P<0.01). Regarding neurotransmitters, it was found that at a dose of 50 mg/kg hesperidin treatment upregulated the levels of 5-HT and BDNF in depressed rats (P<0.05). Compared to the control group, the colon tissue of the model group exhibited greater inflammatory cell infiltration, with markedly reduced numbers of goblet cells and crypts and were significantly improved following treatment with hesperidin. Simultaneously, the administration of hesperidin demonstrated a positive impact on the gut microbiome of rats treated with CUMS, such as Shannon index increased and Simpson index decreased (P<0.01), while the abundance of Pseudomonadota and Bacteroidota increased in the hesperidin-treated group (P<0.05). CONCLUSION The mechanism responsible for the beneficial effects of hesperidin on depressive behavior in rats may be related to inhibition of the expressions of BDNF and 5-HT and preservation of the gut microbiota.
Animals ; Hesperidin/therapeutic use* ; Rats, Sprague-Dawley ; Depression/drug therapy* ; Male ; Stress, Psychological/drug therapy* ; Brain/metabolism* ; Brain-Derived Neurotrophic Factor/metabolism* ; Serotonin/metabolism* ; Gastrointestinal Microbiome/drug effects* ; Behavior, Animal/drug effects* ; Rats ; Brain-Gut Axis/drug effects* ; Chronic Disease ; Colon/drug effects*

Bombesin receptor subtype-3 (BRS3) is an orphan G protein-coupled receptor (GPCR) that plays critical roles in energy homeostasis, glucose metabolism, and insulin secretion. Recent structural studies have elucidated BRS3 signaling mechanisms using synthetic ligands, including BA1 and MK-5046. However, the molecular basis of BRS3 activation by bioactive natural compounds and their derivatives, particularly those derived from traditional Chinese medicine, remains unclear. Here, we present high-resolution cryogenic electron microscopy (cryo-EM) structures of the human BRS3-G_q complex in both unliganded and active states bound by two herb-derived compounds (DSO-5a and oridonin), at resolutions of 2.9, 2.8, and 2.9 Å, respectively. These structures display distinct ligand recognition patterns between DSO-5a and oridonin. Although both compounds bind to the orthosteric pocket, they differentially engage the interaction network of BRS3, as demonstrated by mutagenesis studies assessing calcium mobilization and inositol phosphate 1 (IP1) accumulation. These findings enhance our understanding of BRS3 activation and provide valuable insights into the development of small-molecule BRS3 modulators with therapeutic potential.

To evaluate the immunogenicity and immunoprotective effects of a tRNA thiouridylase TgMnmA deletion strain of Toxoplasma gondii(T.gondii)on ICR mice,we constructed a mouse model immunized with RH△MnmA.Mice were immunized with 10 RH△MnmA tachyzoites by in-traperitoneal injection.After 30 d,indirect ELISA was used to detect the specific IgG antibody and its subtypes of immunized mice.Spleen lymphocyte suspension was prepared,and the splenic lym-phocyte subsets were analyzed by flow cytometry.Moreover,the relative expression level of cyto-kine mRNA was detected by real-time fluorescence quantitative PCR.After 30 d of immunization,mice were intraperitoneally inoculated with RH△ku80 tachyzoites.At 5 d post infection,the para-site load in the ascites,heart,liver and brain of mice was measured,and the survival of mice within 30 d after infection was observed and recorded.The results showed that compared with the control PBS group,RH△MnmA immunized group produced higher level of IgG and IgG2a antibodies,higher mRNA relative expression level of cytokines IL-2,IL-4,IL-6,IL-10,IL-12 and IFN-γ,and the number of CD4+and CD8a+in spleen lymphocytes also increased significantly.Mean-while,for the attack of RH△ku80 strain,the immune group can effectively reduce the parasite load in the ascites and some tissues,inhibit the reproduction of parasites In vivo,and significantly improve the survival rate of mice.The results of this study showed that the TgMnmA deletion strain of T.gondii can induce strong humoral and cellular immune responses in mice,and provide good immune protection against the infection of RHΔku80 strain,which has the potential to be-come a potentially promising live attenuated vaccine candidate against T.gondii.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Based on the α7 nicotinic acetylcholine receptor(α7nAChR), this study examined how tetrahydropalmatine(THP) affected BV2 microglia exposed to lipopolysaccharide(LPS), aiming to clarify the possible mechanism underlying the anti-depression effect of THP from the perspectives of preventing inflammation and regulating polarization. First, after molecular docking and determination of the content of Corydalis saxicola Bunting total alkaloids, THP was initially identified as a possible anti-depression component. The BV2 microglia model of inflammation was established with LPS. BV2 microglia were allocated into a normal group, a model group, low-and high-dose(20 and 40 μmol·L~(-1), respectively) THP groups, and a THP(20 μmol·L~(-1))+α7nAChR-specific antagonist MLA(1 μmol·L~(-1)) group. The CCK-8 assay was used to screen the safe concentration of THP. A light microscope was used to examine the morphology of the cells. Western blot and immunofluorescence were used to determine the expression of α7nAChR. qRT-PCR was performed to determine the mRNA levels of inducible nitric oxide synthase(iNOS), cluster of differentiation 86(CD86), suppressor of cytokine signaling 3(SOCS3), arginase-1(Arg-1), cluster of differentiation 206(CD206), tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β. Enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of TNF-α, IL-6, and IL-1β in the cell supernatant. The experimental results showed that THP at concentrations of 40 μmol·L~(-1) and below had no effect on BV2 microglia. THP improved the morphology of BV2 microglia, significantly up-regulated the protein level of α7nAChR, significantly down-regulated the mRNA levels of iNOS, CD86, SOCS3, TNF-α, IL-6, and IL-1β, significantly up-regulated the mRNA levels of Arg-1 and CD206, and dramatically lowered the levels of TNF-α, IL-6, and IL-1β in the cell supernatant. However, the antagonist MLA abolished the above-mentioned ameliorative effects of THP on LPS-treated BV2 microglia. As demonstrated by the aforementioned findings, THP protected LPS-treated BV2 microglia by regulating the M1/M2 polarization and preventing inflammation, which might be connected to the regulation of α7nAChR on BV2 microglia.
Berberine Alkaloids/chemistry* ; alpha7 Nicotinic Acetylcholine Receptor/chemistry* ; Microglia/metabolism* ; Mice ; Animals ; Cell Line ; Corydalis/chemistry* ; Humans ; Molecular Docking Simulation ; Inflammation/drug therapy* ; Nitric Oxide Synthase Type II/immunology* ; Tumor Necrosis Factor-alpha/immunology*

Objective To analyze challenges in translating exercise management evidence for patients with metabolism-associated fatty liver disease(MAFLD),develop actionable strategies,and evaluate the application of best evidence.Methods Utilizing the evidence translation model,the best evidence was implemented for MAFLD patients in 4 phases:evidence acquisition,baseline practice review,intervention,and outcome evaluation.We compared the knowledge of exercise management evidence,implementation rates of review indicators,completion of exercise programs,BMI,liver stiffness measurement,controlled attenuation parameters,and patient satisfaction among medical staff at a tertiary hospital in Fujian Province during baseline(March-May 2023),mid-practice(June-August 2023),and late-practice(September-November 2023)phases.Results A total of 88 patients were included at baseline review,95 during mid-practice,and 107 in late-practice.Significant improvements were observed in the implementation rates of 21 review indicators,nurses'knowledge,completion rate,BMI,and controlled attenuation parameters compared to the data at baseline(P＜0.05).Conclusion The application of best evidence in exercise management for MAFLD patients enhances nurses'knowledge,standardizes nursing practices,and reduces patients'BMI and controlled attenuation parameters.