The inflammatory microenvironment is closely associated with the initiation and progression of osteoarthritis （OA）， specifically manifesting as macrophage activation， dysregulation of inflammatory cytokines， and redox imbalance. Following an overview of the pathological characteristics of the OA inflammatory microenvironment， this paper reviews the research progress on the mechanism of traditional Chinese medicine （TCM） intervening in OA by modulating the inflammatory microenvironment. It has been found that TCM monomers/active ingredients （such as total alkaloids from Strychnos nux-vomica ， quercetin， triptolide， etc.）， herb pairs （e.g. Angelica pubescens - Gentiana macrophylla ， Carthami Flos-Lycopodii Herba）， and TCM formulas （such as Zhuanggu jianxi formula， Duhuo jisheng decoction and Rongjin niantong formula， etc.） can inhibit macrophage activation， reduce the release of proinflammatory cytokines and the generation of reactive oxygen species by inhibiting multiple signaling pathways， including nuclear factor-κB， Wnt/ β -catenin， and mitogen-activated protein kinase， thereby alleviating the articular inflammatory microenvironment， restoring local joint homeostasis， and slowing the progression of OA.

Background Neck-related work-related musculoskeletal disorders (WMSDs) are a major type of musculoskeletal disorders with a relatively high proportion. Shanghai has a large number of occupational populations; however, the occurrence of WMSDs at neck among the occupational populations across industries in this city has not been reported, and needs to be addressed. Objective To understand the occurrence of neck-related WMSDs and their influencing factors among occupational populations in 8 industries in Shanghai, and to provide a scientific basis for the prevention and control of WMSDs in this population. Methods From February 2024 to February 2025, a cross-sectional survey employed stratified cluster sampling to select 7829 employed workers from 48 enterprises across 8 industries in Shanghai. The study investigated the occurrence of neck-related WMSDs among the participants over the preceding 12 months. Logistic regression analysis was employed to examine the relationships between WMSDs and various occupational factors. Results A total of 7770 questionnaires were collected, yielding an effective response rate of 99.2%. Overall, the positive rate of neck-related WMSDs among the participants was 11.89% (924/7770). Among different industries, the environmental sanitation industry (19.48%), pharmaceutical manufacturing industry (14.57%), and cigarette manufacturing industry (13.66%) had higher prevalence of neck-related WMSDs. Univariate analysis showed that the risk of neck-related WMSDs was higher in the following groups: those with a job tenure ≥5 years in the current position (OR=1.50–1.70), females (OR=1.77), those with higher education levels (master’s degree or above, OR=2.27), and those with worse self-rated health (very poor health, OR=4.38) (P＜0.05). Multivariate logistic regression analysis identified the following independent risk factors for neck WMSDs: environmental sanitation industry (OR=7.30, 95%CI: 4.72, 11.87), higher educational attainment (master’s degree or above: OR=2.16, 95%CI: 1.36, 3.35), worse self-rated health status (very poor: OR=1.95, 95%CI: 1.31, 2.85), work performed in a single workshop (OR=1.36, 95%CI: 1.13, 1.64), understaffing (OR=1.46, 95%CI: 1.25, 1.70), slight neck forward flexion (OR=1.64, 95%CI: 1.32, 2.06), severe neck forward flexion (OR=2.55, 95%CI: 1.97, 3.30), and maintaining a fixed neck posture for a prolonged period (OR=2.28, 95%CI: 1.93, 2.70). Conversely, work rotation (OR=0.75, 95%CI: 0.65, 0.87), adequate rest (OR=0.70, 95%CI: 0.60, 0.82), and severe back flexion (OR=0.63, 95%CI: 0.46, 0.85) were protective factors against neck-related WMSDs. For the nomogram, the area under the curve (AUC)=0.75 (95%CI: 0.74, 0.77), Hosmer-Lemeshow test P=0.764, and Brier score=0.094, indicating that the model had good discrimination and calibration. Conclusion Among the occupational populations in Shanghai, the environmental sanitation industry, pharmaceutical manufacturing industry, and cigarette manufacturing industry are identified as high-risk industries for neck-related WMSDs. Industry affiliation, educational level, work organization patterns, and awkward neck working postures are confirmed as the core influencing factors for the development of neck-related WMSDs. Targeted and comprehensive intervention measures should be formulated focusing on the aforementioned high-risk industries and key influencing factors. Multi-dimensional collaborative efforts, including ergonomic optimization, improvement of labor management systems, and strengthened health education and promotion, should be implemented to effectively control the risk of neck-related WMSDs in the occupational population, and to provide robust statistical evidence for the advancement of regional occupational health prevention and control strategies.

ObjectiveTo explore the effects of Wumeiwan on liver metastasis and lung metastasis of colorectal cancer and its potential mechanism. MethodsFirstly， mice were randomized into control， low-dose （20 g·kg^-1） Wumeiwan， high-dose （40 g·kg^-1） Wumeiwan， and paclitaxel （10 mg·kg^-1） groups. Secondly， liver metastasis and lung metastasis models of colorectal cancer were established in mice. After 4 weeks of intervention， the body weight of each mouse was recorded， and the lung weight， liver weight， and survival time of mice with metastatic colorectal cancer were determined. Hematoxylin-eosin （HE） staining was employed to detect the effects of Wumeiwan on liver metastasis and lung metastasis. Real-time PCR was employed to determine the mRNA levels of M1 and M2 macrophage markers in the liver tissue. Finally， the content of M1 macrophage markers CD80 and CD86 in the liver tissue was measured by flow cytometry. ResultsCompared with the control group， Wumeiwan and paclitaxel reduced the body weight （P<0.01） and liver weight （P<0.01） and prolonged the survival of the mouse model of liver metastasis of colorectal cancer （P<0.01）. In the mouse model of lung metastasis of colorectal cancer， Wumeiwan and paclitaxel also reduced the body weight （P<0.01） and lung weight （P<0.01） and extended the survival time （P<0.01）. Histopathological results showed that compared with the control group， Wumeiwan inhibited the liver and lung metastases of colorectal cancer. Real-time PCR results showed that compared with the control group， Wumeiwan upregulated the mRNA levels of M1 macrophage markers IL-1β， IL-6， tumor necrosis factor-α （TNF-α）， inducible nitric oxide synthase （iNOS）， and prostaglandin-endoperoxide synthase 2 （PTGS2） in the liver and lung tissue of mice with liver metastasis and lung metastasis of colorectal cancer （P<0.01）. Meanwhile， Wumeiwan downregulated the mRNA levels of M2 macrophage markers Arg1， CD163， and CD206 （P<0.01）. Meanwhile， the flow cytometry results showed that compared with the control group， Wumeiwan increased the content of CD86 and CD80 （P<0.01）. In addition， immunohistochemical results showed that Wumeiwan promoted the expression of CD86 and inhibited the expression of CD206 in the liver and lung tissue of mice with liver metastasis and lung metastasis. ConclusionWumeiwan can inhibit the liver metastasis and lung metastasis of colorectal cancer by promoting the M1 polarization of macrophages in the liver and lung of the model mice.

Objective: The cross sectional study aimed to identify predominant co-occurrence patterns among six common mental health issues in college students, so as to provide empirical basis for designing targeted interventions. Methods: From October 2024, a total of 9 837 students from 4 universities in Xiangtan City, Hunan Province, participated in the current study by multistage random cluster sampling method. Participants completed self report measures, including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7 item Scale (GAD-7), Young s Internet Addiction Diagnostic Questionnaire, the Adolescent Insomnia Symptom Self rating Scale, the Ottawa Self injury Inventory, and the Brief Community Assessment of Psychic Experiences Questionnaire. Demographic and co-occurrence characteristics were first compared using Chi square or trend Chi-square tests, followed by application of the Apriori algorithm to mine association rules for primary co-occurrence patterns. Results: The detection rate of co-occuring the common mental health issues was 46.44%. The detection rate was significantly higher in female than in male students (50.42%, 43.61%; χ 2=44.46) and in students from rural versus urban areas (47.22%, 44.60%; χ 2=5.67) (both P <0.05). Significant differences were observed among freshmen, sophomores, juniors, and seniors (46.63%, 48.35%, 45.05% , 43.66%, respectively; χ 2=9.22, P <0.05), although no statistically significant trend was detected ( χ 2 trend =3.75, P = 0.05 ). Association rule mining identified “anxiety + depression” “anxiety + psychotic experiences + depression” and “anxiety + sleep disorder + depression” as the combinations with the highest support. In addition, “anxiety+depression+Internet addiction+psychotic experiences =>sleep disorder (>= refered to the occurrence of the latter item under the condition that the former item occurs)” and “anxiety + depression+Internet addiction=>sleep disorder” were combinations with relatively high confidence. Conclusions Co-occurrence of these mental health issues among college students is high and exhibits diverse patterns. Strategies to address this burden should prioritize integrated interventions that target these specific combinations of factors.

Objective: To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students. Methods: From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model. Results: The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms. Conclusions The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

It has been demonstrated that long-term space flights have a significantly greater impact on the cardiovascular, skeletal, and nervous systems of astronauts. The structural and functional alterations in the skeletal and muscular systems resulting from exposure to weightlessness can lead to the development of low back pain, significantly impairing the ability of astronauts to perform tasks and respond to emergencies. Both space flight and simulated microgravity have been shown to result in low back pain among astronauts, with the following factors identified as primary contributors to this phenomenon. The occurrence of intervertebral disc (IVD) edema results in the stimulation of type IV mechanoreceptors, which subsequently activate nociceptive afferents. The protrusion of an IVD causes compression of the spinal nerve roots. Furthermore, the elongation of the vertebral column and/or the diminished lumbar curvature of the spine exert traction on the dorsal root nerves. Paravertebral muscle degeneration leads to the inhibition of decreased nociceptive activity of the wide-dynamic range neurons of the spinal dorsal horn. Moreover, endogenous pain descending facilitation triggered by conditioning stimulation can be enhanced via the thalamic mediodorsal nuclei, while endogenous pain descending inhibition triggered by conditioning stimulation can be weakened via the thalamic ventromedial nuclei. Psychological factors may contribute to the development of low back pain. The mechanisms governing the generation, maintenance, and alleviation of low back pain in weightlessness differ from those observed in normal gravitational environments. This presents a significant challenge for space medicine research. Therefore, the elucidation of the occurrence and development mechanism of low back pain in weightlessness is important for the prevention and treatment during space flight. To reduce the incidence of low back pain during long-term missions on the space station, astronauts may choose to wear specialized space clothing that can provide axial physiological loads, designed to stimulate both musculature and skeletal structures, mitigating potential increases in vertebral column length, diminished lumbar curvature, and intervertebral disc edema and/or muscular atrophy. Additionally, assuming a “fetal tuck position” described as the knees to chest position may increase lumbar IVD hydrostatic pressure, subsequently reducing disc volume, rectifying diminished lumbar curvature, and alleviating dorsal root nerve tensions. Moreover, this position may reduce type IV mechanoreceptor facilitation and nerve impulse propagation from the sinuvertebral nerves of the annulus fibrosus. Elongated posterior soft tissues (apophyseal joint capsules and ligaments) with spinal flexion may potentially stimulate type I and II mechanoreceptors. It is also recommended to exercise the paraspinal muscles to prevent and alleviate the decrease in their cross-sectional area and maintain their structure and function. Photobiomodulation has been proved to be an effective means of activating the pain descending inhibition pathway of the central nervous system. In addition, astronauts should be encouraged to participate in mission-related activities and strive to avoid psychological problems caused by the long-term confinement in a small space station. The article presents a concise review of potential causes and targeted treatment strategies for low back pain induced by space flight or simulated microgravity in recent years. Its objective is to further elucidate the mechanisms underlying the occurrence and development of low back pain in weightless environments while providing scientific evidence to inform the development of guidelines for preventing, treating, and rehabilitating low back pain during long-term space flights.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.