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.

Diabetic retinopathy(DR)remains the leading cause of vision loss in patients with diabetes. Current anti-vascular endothelial growth factor(VEGF)therapies are limited by inadequate response in some patients and the necessity for repeated intravitreal injections, underscoring the urgent need for novel therapeutic targets. Angiopoietin-like protein 4(ANGPTL4), a multifunctional secreted protein, has emerged as a critical regulator in the pathogenesis and progression of DR, positioning it as a promising interventional target. This review systematically elaborates the biological characteristics of ANGPTL4, with a focus on its expression dynamics, molecular mechanisms, and regulatory networks rolesin the development of DR. Furthermore, the prospects of ANGPTL4-targeted therapeutic strategies are discussed, aiming to offer new insights and directions for understanding DR pathogenesis, advancing multi-target drug development, and improving clinical management.

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.

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.

Objective: To evaluate the long-term effectiveness of an intelligent blood transfusion system in intraoperative blood management by comparing its performance with clinicians' decisions. Methods: A retrospective analysis of 26 760 surgical cases (2017-2024) was conducted, comparing pre- and post-implementation (2017-2019 vs 2020-2024) metrics, including transfusion prediction accuracy, rationality of blood use, and clinical outcomes. The system, powered by XGBoost, integrated patient demographics, laboratory results, and surgical data to predict red blood cell transfusion needs. Results: The intelligent blood transfusion systems achieved an accuracy of 80.62% in predicting transfusion necessity, significantly outperforming clinicians (24.83%, P<0.001). Its blood-use rationality rate was 83.92% vs 18.02% for clinicians (P<0.001). Post-implementation, major surgeries (grades Ⅲ-Ⅳ) increased while the requested blood units decreased. High physician compliance (>75%) correlated with 88.18% rationality. Conclusion: The intelligent blood transfusion system significantly improves the accuracy of transfusion decision-making, reduces excessive red blood cell use, optimizes perioperative transfusion management, and enhances the utilization of blood medical resources.

Occupational noise-induced hearing loss (NIHL) is an irreversible sensorineural hearing loss that severely endangers workers’ health, making early screening crucial. This article reviewed the research progress on early screening methods for occupational NIHL, introduced the testing mechanisms of three core screening methods—tympanometry, otoacoustic emissions, and extended high-frequency audiometry —and summarized their clinical application advantages and limitations. It is proposed that multimodal combined detection (e.g., the combination of tympanometry, otoacoustic emissions, and extended high-frequency audiometry) can significantly improve the accuracy and comprehensiveness of early screening. Meanwhile, future studies with prospective cohort design are encouraged to verify the long-term monitoring value of each method and to strengthen the joint development of screening technologies with cutting-edge approaches such as machine learning, in order to further improve screening efficiency and provide stronger protection for workers’ hearing health.

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers