The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Organoid technology has become a highly promising in vitro model in biomedical research, but its traditional culture relies on animal-derived basement membrane matrices, which suffer from batch-to-batch variability, undefined biochemical composition, and poorly controllable mechanical properties. Recent studies have confirmed that matrix stiffness, viscoelasticity, topography, and temporal mechanical dynamics play regulatory roles equally as critical as biochemical signals in stem cell self-organization, lineage specification, and functional maturation of organoids. This review systematically summarizes the progress in understanding how extracellular matrix (ECM) mechanical properties regulate organoid formation. Focusing on the YAP/TAZ factors and the integrin receptors, which engage in crosstalk with biochemical signals to synergistically determine cell fate. We then elaborate how specific mechanical parameters, such as stiffness, viscoelasticity, and topography, influence each distinct stage of organoid development, from initial aggregation and compaction, through proliferative expansion, to lineage-committed differentiation and terminal functional maturation. Appropriate stiffness facilitates efficient aggregation and symmetry breaking, while excessive rigidity impairs proliferation and accelerates cellular senescence. In hepatic organoid expansion where only stiffness matching liver tissue(~6.2 kPa) supported robust growth. Viscoelastic stress relaxation promotes integrin clustering, enhances focal adhesion maturation, and stimulates endogenous ECM deposition, thereby supporting self-organized crypt-villus architecture and basement membrane assembly. Notably, dynamic softening of hydrogels enables optimal crypt budding, whereas rapid stress relaxation permits nephron segment coiling and drives vascular organoid maturation toward arteriole differentiation, highlighting stress relaxation as a key temporal parameter. Topographical cues provide contact guidance that directs polarized outgrowth, lumen formation, and neuronal orientation, all of which are essential for achieving organotypic architecture. The embedded 3D printing of complex neural networks enables precise control over branching geometries, facilitating studies of morphogenesis under spatial constraints. The engineered mechanical microenvironments have been successfully applied to recapitulate disease phenotypes: stiff matrices induce fibrosis and epithelial-mesenchymal transition in liver organoids, promote chemoresistance in cholangiocarcinoma. Furthermore, we summarize engineering strategies for both natural and synthetic hydrogels aimed at creating mechanically defined culture platforms. Natural biomaterial modifications achieve spatial separation of mechanical constraints from biochemical support, enabling self-limited compressive stimulation within a defined time window. Synthetic polymers allow independent tuning of stiffness, ligand density, and viscoelasticity through adjustable crosslinking and dynamic non-covalent interactions, thus providing orthogonal control over multiple mechanical parameters. Dynamic microenvironments that mimic progressive stiffening as observed in development, tumor evolution, or fibrosis can be constructed using composites that undergo spontaneous structural transitions. In the future, critical challenges include deciphering the synergistic rules governing mechanical-biochemical interplay, developing spatiotemporally programmable hydrogels that enable on-demand modulation of local mechanics, establishing comprehensive databases of tissue-specific mechanical parameter windows, and advancing standardized high-throughput screening platforms to accelerate preclinical validation and clinical translation. Moreover, integrating real-time mechanical sensors and non-invasive imaging techniques would allow dynamic monitoring of intracellular forces and tissue-level stress during culture. Ultimately, this review aims to provide a theoretical foundation for deepening our understanding of mechano-biological coupling mechanisms and for rationally designing high-fidelity, physiologically relevant organoid culture platforms that fully harness the regulatory power of mechanical cues.

Under the influence of long-term space flights and the confined space environment,it is very easy to induce space depression syndrome,mainly manifested as decreased emotional stability,sleep disorders,mental fatigue,etc.,which seriously affect the living conditions and working abilities of astronauts.The current treatment methods mainly focus on psychological support and drug intervention.Acupuncture has a good effect in treating depression.Therefore,starting from the TCM pathogenesis and modern medical pathogenesis of aerospace depression syndrome,we conducted literature retrieval from databases such as the Chinese Medical Classic,China National Knowledge Infrastructure(CNKI),Wanfang,VIP,PubMed,and Web of science.For the included literature,we adopted the stratified evidence scoring method and combined the TCM mechanism and modern medical mechanism of the effect of acupuncture.A prescription for acupuncture points was constructed to provide a basis for selecting acupuncture points for the prevention of aerospace depression syndrome through acupuncture.

Objective:To explore the structural equation model to explore the levels of work-related musculoskeletal disorders (WMSDs) and various risk factors in the feet and ankle of China's occupational population, providing scientific basis for for preventing WMSDs in feet and ankles.Methods:Data of 73497 national occupational epidemiological cases were selected from June 2018 to December 2023 used the Chinese version of the Electronic Questionnaire on Musculoskeletal Disorders. The adverse ergonomic factors and their source classification standard and confirmatory factor analysis were used to investigate foot and ankle WMSDs and their related risk factors (including individual factors, work organization, work posture, work type, fatigue, etc.) in key occupational groups in China, and structural equation model hypothesis, fitting, verification, and path and intermediary effect analysis were carried out. The model fit evaluation indexes included Chi-square specific degrees of freedom ( χ2/ df), gauge fit index (NFI), Tucker Lewis index (TLI), goodness of Fit index (GFI), adjusted Goodness of Fit index (AGFI) and approximate root mean square error (RMSEA) . Results:A total of 73497 occupational workers were surveyed, with local muscle fatigue and WMSDs incidence rates in the feet and ankles being 17.17% and 12.06%, respectively. The fitting index of the adjusted structural equation model basically meets the standard (GFI=1, AGFI=1, RMESA=0.042, NFI=0.716, TLI=0.663). The top three factors affecting feet and ankle WMSDs are feet and ankle muscle fatigue, work type, and work organization, with standardized path coefficients of 0.221, 0.105, and 0.095, respectively. The top two factors affecting feet and ankle muscle fatigue are work organization and work type, with standardized path coefficients of 0.548 and 0.383, respectively. Feet and ankle muscle fatigue, work type, work organization, and work posture have a direct effect on feet and ankle WMSDs, with effect values of 0.221, 0.105, 0.095, and 0.077, respectively. The organization and type of work can also have indirect effects through feet and ankle muscle fatigue, with effect values of 0.121 and 0.084, respectively.Conclusion:Feet and ankle muscle fatigue has a direct impact on WMSDs, and plays a mediating role between ankle and ankle WMSDs caused by work organization and work type. Feet and ankle muscle fatigue is an important pathway leading to feet and ankle WMSDs. It is recommended that employers and managers detect job fatigue early and take corresponding prevention and intervention measures, which can play a key role in preventing feet and ankle WMSDs.

Extracellular vesicles(EVs)are small vesicles secreted by cells,widely present in various body fluids,and they play important biological roles.In recent years,EVs have garnered significant attention as novel diagnostic and thera-peutic tools in multiple ocular diseases.Glaucoma,as a common cause of irreversible blindness,is primarily caused by optic nerve damage associated with pathologically elevated intraocular pressure.Emerging evidence indicates that EVs hold considerable therapeutic potential in glaucoma management,particularly in modulating aqueous humor circulation and pro-viding retinal neuroprotection.This review summarizes the latest research progress on EVs in the treatment of glaucoma.

[Objective]To investigate the effect of nicotinamide adenine dinucleotide on vascular endothelial injury in hypertension and its molecular mechanism.[Methods]C57BL/6J mice were randomly divided into saline group(Saline)and hypertension group(Ang Ⅱ,which were infused with Ang Ⅱ via subcutaneously implanted osmotic pumps),and supplemented daily with nicotinamide mononucleotide(300 mg/kg),a precursor of NAD+.Blood pressure,endothelial relaxation function and pulse wave velocity were measured after 4 weeks.Wound healing assay and adhesion assay were used to evaluate the function of endothelial cells in vitro.mtROS levels were detected by immunofluorescence staining.RT-PCR was used to detect the mRNA expression of mtDNA,SIRT3 and isocitrate dehydrogenase 2(IDH2).8-hydroxy-2'-deoxyguanosine levels were detected by enzyme-linked immunosorbent assay.The protein expression levels of p-eNOS,eNOS,SIRT3 and IDH2 were detected by Western blot.[Results]NMN supplementation reduced blood pressure(P<0.001)and improved endothelial function and arterial stiffness(P<0.001)in hypertensive mice.In vitro,NMN improved endothelial function in Ang Ⅱ-stimulated endothelial cells(P<0.05)and attenuated mitochondrial oxidative stress levels(P<0.001).Mechanistically,NMN elevated SIRT3 activity(P<0.001),which subsequently enhanced IDH activity(P<0.001)and reduced oxidative stress levels in endothelial cells.Conversely,knockdown of IDH2 would reverse the effect of SIRT3 in improving endothelial function(P<0.001).[Conclusion]NAD+lowers blood pressure and enhances vascular function in hypertension by reducing the level of oxidative stress in endothelial cells through activation of the SIRT3/IDH2 signal pathway.

Objective:To investigate the additional prognostic value of coronary CT angiography (CCTA)-based flow reserve fraction (CT-FFR) over semi-quantitative CCTA risk scores in predicting the occurrence of major adverse cardiovascular events (MACE) in type 2 diabetic patients.Methods:A total of 231 patients with type 2 diabetes mellitus who underwent CCTA at Lanzhou University from May 2020 to April 2021 were retrospectively enrolled. Clinical baseline data were collected, and patients were divided into a MACE-positive group (20 cases) and a MACE-negative group (211 cases) based on follow-up results. The CCTA images of all patients were analyzed by semi-quantitative CCTA risk score, which included coronary artery disease reporting and data system classification, segment involvement score, segmental stenosis score, Leaman score, and Leiden score. CT-FFR measurements of CCTA data of all patients were performed using Coronary Analysis software. t-test, U-test, and χ2 test were used to compare baseline parameters between MACE-positive and MACE-negative groups. The Cox proportional hazards regression model was used to analyze the relationship between semi-quantitative CCTA risk score and CT-FFR with the occurrence of MACE, and the area under the curve (AUC) of the receiver operating characteristic (ROC) was used to calculate the efficacy of the prediction model established by the semi-quantitative CCTA risk score combined with CT-FFR. Results:There was no statistically significant difference in baseline data between patients in the MACE-positive and MACE-negative groups ( P>0.05), and there were significant differences in semi-quantitative CCTA risk scores and CT-FFR ( P<0.05). Multivariate Cox proportional risk regression analysis of CT-FFR≤0.80 ( HR=3.860, 95% CI 1.477-10.087, P=0.006) and Leaman score≥5 ( HR=5.210, 95% CI 1.136-23.908, P=0.029) were the best and independent predictors for the occurrence of MACE events. The combined CT-FFR and Leaman score prediction model (AUC=0.791, 95% CI 0.733-0.842, P<0.001) was a better predictor of MACE than CT-FFR alone (AUC=0.718, 95% CI 0.656-0.775, P<0.001) and Leaman score alone (AUC=0.711, 95% CI 0.648-0.768, P<0.001) both had better predictive efficacy ( Z=2.62, 1.98, P=0.009, 0.047). Conclusion:CT-FFR independently predict the occurrence of MACE in patients with type 2 diabetes mellitus and significantly improve the predictive capacity of semi-quantitative CCTA risk score for MACE.

Objective:To analyze the clinical efficacy and learning curve of robotic-assisted Warshaw procedure using the da Vinci system.Methods:Clinical data of 91 consecutive patients with pancreatic body and tail lesions undergoing robotic-assisted Warshaw procedure at Qingdao University Affiliated Hospital from October 2021 to April 2023 were retrospectively analyzed, including 21 males and 70 females, aged (50.2±14.3) years. Patient characteristics, operative time, and intraoperative blood loss were recorded. The learning curve was constructed using cumulative sum (CUSUM) analysis, with case number on the x-axis and CUSUM values on the y-axis. Linear fitting was performed, and the model with the highest determination coefficient was selected as the optimal fitting model. The learning process was divided into two phases based on the inflection point of the CUSUM learning curve: the learning phase and the proficiency phase. Perioperative outcomes were compared between these two phases.Results:All 91 procedures were successfully completed using the da Vinci robotic system with R0 resection margins. There were no perioperative mortalities or reoperations due to postoperative splenic infarction. The operative time was (227.84±76.68) min. The optimal fitting equation for the CUSUM learning curve was: CUSUM=0.005 640X 3-1.501X 2+ 92.59X-183.1. The CUSUM learning curve showed an inflection point at case 39, dividing the learning process into the learning phase (cases 1-39) and proficiency phase (cases 40-91). Compared to the learning phase, the proficiency phase demonstrated significantly shorter operative time [(203.0±75.6) min vs. (260.9±65.5) min], less intraoperative blood loss [50.0 (20.0, 50.0) ml vs. 100.0 (50.0, 100.0) ml], and reduced postoperative drainage duration [(8.7±2.4) d vs. (10.8±3.2) d] (all P<0.05). Conclusion:The robotic-assisted Warshaw procedure feasible for patients with pancreatic body and tail lesions. Surgeons require approximately 39 cases to complete the learning curve and achieve proficiency in this procedure.