Flap transplantation is a critical surgical strategy for the reconstruction of tissue defects caused by trauma, tumor resection, and congenital malformations, and its survival rate directly determines surgical efficacy and patient prognosis. Following transplantation, flaps inevitably undergo ischemia-reperfusion (I/R) injury, during which oxidative stress, inflammatory responses, and metabolic disturbances are intricately intertwined, ultimately leading to cellular injury and tissue necrosis. Recent studies have demonstrated that multiple forms of programmed cell death—including apoptosis, pyroptosis, ferroptosis, necroptosis, and PANoptosis—play central roles in flap I/R injury. The extensive crosstalk and molecular interactions among these pathways form a highly complex cell death network. Specifically, apoptosis is mediated by the imbalance of Bcl-2 family proteins and the activation of cysteine-dependent aspartate-specific protease (caspase) cascades; pyroptosis is driven by the NLRP3-caspase-1-GSDMD axis, resulting in membrane pore formation and the release of pro-inflammatory cytokines; ferroptosis is characterized by iron-dependent lipid peroxidation and dysfunction of glutathione peroxidase 4 (GPX4); necroptosis is triggered by the receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-RIPK3-MLKL signaling complex, leading to membrane rupture; and PANoptosis represents an integrated form of inflammatory cell death that coordinates multiple death pathways. Importantly, these forms of programmed cell death are not independent but are interconnected through extensive signaling crosstalk. Key regulatory molecules, including caspase-8, reactive oxygen species (ROS), nuclear factor-κB (NF-κB), and nuclear factor erythroid 2-related factor 2 (Nrf2), collectively modulate the dynamic balance among these pathways. Therefore, the multidimensional interplay and spatiotemporal dynamics of programmed cell death constitute a fundamental pathological basis of flap I/R injury. This review systematically summarizes the latest advances in the mechanisms and interactions of various programmed cell death pathways in flap I/R injury, aiming to elucidate the underlying regulatory network. These insights may provide novel theoretical foundations for optimizing flap protection strategies, improving flap survival, and promoting tissue repair.

Andrological diseases have become an important public health problem threatening men's health worldwide， which significantly affects the quality of life of patients and brings a heavy disease burden. Western medicine often faces the dilemma of obvious side effects and limited efficacy. Traditional Chinese medicine has unique advantages in the prevention and treatment of andrological diseases and has accumulated rich clinical experience. Epimedii Folium， as a traditional Chinese medicine for strengthening kidney and Yang， exerts a key therapeutic effect on andrology diseases through multi-component synergy， multi-target regulation， and multi-pathway intervention. Recent studies have found that the main active components of Epimedii Folium， such as icariin， icariside， and icaritin， are the key material basis for the treatment of andrological diseases. The active components of Epimedii Folium can play a role in common andrological diseases such as erectile dysfunction， male infertility， and prostate cancer by regulating the activity of the nitric oxide/cyclic guanosine monophosphate （NO/cGMP） pathway， participating in oxidative stress response， regulating the secretion of hypothalamic-pituitary-gonadal axis hormones， improving spermatogenic dysfunction， and inhibiting the proliferation of cancer cells. However， the systematic action network and molecular mechanisms of the active components of Epimedii Folium have not been fully elucidated， thereby limiting its potential for clinical translation and application. In the future， it is necessary to combine cutting-edge technologies such as metabolomics， single-cell sequencing， and targeted nanoscale drug delivery systems， strengthening the research on the compatibility rules of active components and organ-specific delivery， providing a scientific basis for the development of innovative andrology traditional Chinese medicine formulas with international competitiveness， and promoting the innovation and breakthrough of andrology disease treatment modes.

Objective: To address the challenges of systematically identifying herb pairs in traditional Chinese medicine (TCM), we proposed HerbGL, a framework for predicting potential herb pairs that integrates network propagation and graph regularization. Methods: Based on the assumption that herbal actions induce subtle perturbations in biological systems, a framework named HerbGL was proposed. Random walk with restart (RWR) was first applied to the protein-protein interaction (PPI) network to reconstruct herb-specific perturbation effects and generate weighted subnetworks. Then, to quantify affinity between herb pairs, two network-proximity metrics, Closeness and PageRank, were computed from the weighted subnetworks to construct herb-pair affinity matrices. Finally, these matrices, together with known herb pairs (derived from co-occurrence analysis of TCM formulas with a threshold determined from the inflection point of the frequency distribution), were incorporated into a graph regularization model to predict potential herb pairs. Model performance was assessed through baseline comparison, ablation and robustness experiment under different ratios of positive and negative samples, using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), accuracy, and precision as evaluation metrics. Furthermore, the predicted herb pairs were validated through both literature evidence and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Results: The weighted subnetworks constructed by RWR provided a refined simulation of herb-specific perturbation effects, which formed the basis for subsequent affinity modeling and prediction. Analysis of herb pair co-occurrence frequencies revealed a marked change around 150, which was selected as the threshold to distinguish herb pairs from non-herb pairs. HerbGL exhibited superior predictive performance compared with baseline models (AUROC = 0.970 5, AUPRC = 0.955 5, accuracy = 0.726 6, precision = 0.970 6). Ablation results showed that removing the Closeness and PageRank metrics substantially degraded performance (AUROC = 0.819 1, AUPRC = 0.876 8), confirming their necessity. Robustness evaluation under an imbalanced positive-to-negative sample ratio of 1 : 5 yielded AUROC = 0.969 6 and AUPRC = 0.840 4, indicating stable predictive ability. Moreover, multiple case studies further validated the rationality of the predicted herb pairs, such as Fangfeng (Saposhnikoviae Radix) and Qingpi (Citri Reticulatae Pericarpium Viride) which are recorded in Liangpeng Huiji (《良朋汇集》, Collection of Excellent Recipes) Vol. 3: Fangfeng Shengma Tang (防风升麻汤). Additionally, pathway enrichment analysis of the Renshen (Ginseng Radix et Rhizoma) and Lianqiao (Forsythiae Fructus) pair further supported the biological plausibility of their compatibility. Conclusion HerbGL offers an effective and biologically informed framework for identifying herb pairs in TCM. Beyond improving herb pair prediction, the framework also provides data support for research on herb compounds and mechanisms, thereby supporting data-driven exploration of TCM compatibility.

Purpose: Due to the preservation of the entire stomach after endoscopic resection, the occurrence of metachronous gastric cancer (MGC) remains a possibility. In this study, we investigated the incidence and risk factors for MGC in patients with early gastric cancer who underwent endoscopic submucosal dissection (ESD) and successfully eradicatedHelicobacter pylori. Materials and Methods: A retrospective analysis was conducted of 1,191 patients who underwent ESD and successfully eradicated H. pylori at the Affiliated Drum Tower Hospital of Nanjing University. Endoscopic surveillance was performed at 3, 6, and 12 months post-resection, and annually thereafter. MGC was defined as the development of a new cancer at a site other than the primary gastric cancer site, at least 1 year after the initial endoscopic resection. Results: A total of 77 patients were diagnosed with MGC during a median follow-up of 41.5 months. Kaplan-Meier analysis showed a 5-year cumulative incidence of MGC of 9.4% after successful H. pylori eradication. Multivariate analysis of the training set using Cox proportional hazards models identified male sex, severe atrophic gastritis, multiple gastric cancers before H. pylori eradication, and smoking history as independent risk factors for MGC.The nomogram exhibited favorable discrimination, with area under the curves of 0.767 and 0.822 in the training set and 0.724 and 0.745 in the testing set at 3 and 5 years, respectively. Conclusions Patients with gastric cancer who undergo endoscopic resection, even after successful H. pylori eradication, should undergo annual and continuous endoscopic surveillance for MGC.

Objective: To observe the distribution characteristics of sex differences in physical growth among children and adolescents aged 6-15 years in Taiwan, China from 2007 to 2024, so as to provide clues for improving growth assessment standards and promoting the health of children and adolescents. Methods: Using publicly available height and weight data for children and adolescents aged 6-15 years in Taiwan, China from 2007 to 2024 released by the statistics agency of the Taiwan education authorities, sex difference indices were analyzed. Growth curve charts and Pearson correlation were used to analyze the correlation between height/weight and year, as well as trends of change with age and year. These were compared with data from the 8th National Survey on Students Constitution and Health in 2019, covering Han and ethnic minority groups aged 6-15 years in mainland China. Results: The sex difference index for height among children and adolescents in Taiwan, China ranged from -1.20% to 6.67%, showed a trend of decreasing first and then increasing with age. The sex difference index for weight ranged from 3.76% to 19.15%, exhibited an age related trend of a slight initial increase, followed by a decrease, and then an increase. The sex difference indices for height in the 12-15 age groups and for weight in the 15-year-old group were positively correlated with the year ( r =0.74, 0.66, 0.61, 0.92 ; 0.63), while the sex difference indices for weight in the 6-8 age groups were negatively correlated with the year ( r =-0.71, -0.77, -0.53) (all P <0.05). In 2024, the height of children and adolescents in Taiwan, China increased gradually with age, but the growth rate for girls slowed down after age 12. A "two crossover" was observed in height between boys and girls, with boys being taller than girls in the 6-9 age range and after age 12. Weight for both sexes gradually increases with age, but boys have greater weight than girls at all ages. In 2019, the sexual differences in body size among children and adolescents in the Taiwan region, China (the sex difference indices for height:-0.96% to 6.49%；the sex difference indices for weight:4.69%-17.89%) fell within the variation ranges of counterparts in mainland China (the sex difference indices for height:-5.43% to 7.69%；the sex difference indices for weight:-10.12% to 21.56%). Conclusion The sex differences in physical growth among children and adolescents in Taiwan, China are dynamically changing with age and over the long term.

Objective: To investigate the association between screening detected myopia in primary school students and mixed exposure to air pollutants, so as to provide a scientific basis for the prevention and control of myopia in children and adolescents. Methods: From May to July 2023, a cluster random sampling method was used to select 15 102 primary school students in grades 3 through 6 from Hefei, Zhongshan, Shenyang, and Nanchang citys. Data were collected through questionnaires, distance vision screening, and computerized refraction. Monthly average concentration data for particulate matter (PM 10 ), fine particulate matter (PM 2. 5), NO 2 and SO 2 were used to calculate the annual average pollutant concentrations for primary school students. Quantile g computation model was employed to analyze the association between mixed exposure to air pollutants and screening detected myopia. Results: The differences in concentrations of the four pollutants among cities were statistically significant ( H =12 886.0, 13 285.0, 8 559.0, 13 181.0, all P <0.01). In the overall sample, there was no statistically significant association between combined exposure to air pollutants and the risk of myopia ( β=0.033, 95%CI=-0.004-0.072, P =0.08). Stratified analysis by outdoor activity time showed that among primary school students with outdoor activity time ≤1 h/d, mixed exposure to air pollutants was positively associated with the risk of myopia ( β=0.050, 95%CI=0.002-0.099, P =0.04); after stratification by city, combined exposure to air pollutants was significantly associated with the risk of myopia among primary school students in Nanchang and Shenyang [ β (95% CI )= 0.232(0.175-0.289), 0.080(0.006-0.155), both P <0.05], whereas no statistically significant association was observed among primary school students in Hefei and Zhongshan [ β (95% CI )=-0.010(-0.071-0.051), -0.032(-0.167-0.102), both P ＞ 0.05 ]. Conclusions Exposure to multiple air pollutants may increase the risk of myopia in primary school students, with the risk influenced by time spent outdoors and geographical location. It is recommended that outdoor activity management for children be strengthened in areas with higher air pollution levels, and that environmental factors be incorporated into comprehensive myopia prevention and control strategies.

ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

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.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

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.