BACKGROUND:Spinal cord injury is a neurological disorder caused by traumatic or non-traumatic events,often leading to severe functional impairment below the injured segment.In recent years,neural stem cell transplantation has been considered to have significant therapeutic potential in regulating the inflammatory response after spinal cord injury,inhibiting excessive proliferation of glial scars,and promoting nerve regeneration. OBJECTIVE:To review and discuss the potential mechanism of action of acupuncture and neural stem cell transplantation therapy in inhibiting spinal cord injury-induced secondary injury,and to delve into the scientific basis for its treatment of spinal cord injury. METHODS:PubMed,Elsevier,WanFang,and CNKI databases were searched using"spinal cord injury,acupuncture,neural stem cells,SDF-1α/CXCR4 axis"as Chinese and English search terms.Totally 96 articles were finally included.The research findings of acupuncture combined with neural stem cells in the treatment of spinal cord injury were summarized and analyzed,and the mechanism of this combination therapy in the treatment of secondary injury after spinal cord injury was summarized. RESULTS AND CONCLUSION:(1)The stromal-derived factor 1α(SDF-1α)/chemokine receptor 4(CXCR4)axis plays a crucial role in neural stem cell transplantation for spinal cord injury.This signaling mechanism not only affects neural stem cell migration,proliferation,and differentiation,but is also a key factor in determining the efficiency of stem cell homing to the injury site.Therefore,the regulation of targeting this axis is of great significance in enhancing the therapeutic effect of spinal cord injury.(2)Acupuncture,as a traditional Chinese medicine therapy,shows unique advantages in the regulation of secondary injury in spinal cord injury.It can effectively reduce secondary injury after spinal cord injury by regulating inflammatory response,inhibiting apoptosis,improving microcirculation,reducing glial scar formation,and counteracting oxidative stress.(3)Acupuncture was also able to influence the expression and function of the SDF-1α/CXCR4 axis,thereby enhancing the homing and survival ability of neural stem cells and promoting nerve regeneration and functional recovery.(4)The therapy combining acupuncture and stem cell transplantation is an innovative treatment strategy for spinal cord injury and suitable for repairing neural circuits.It combines the wisdom of traditional Chinese medicine with the advantages of modern biotechnology,providing a new treatment option for spinal cord injury patients.However,this combination therapy is still in the research and exploration stage,and its long-term efficacy and safety need to be further verified.(5)Taken together,acupuncture and neural stem cell transplantation for the treatment of spinal cord injury has great potential for clinical application,but in-depth research and optimization of treatment options are still needed.In the future,we look forward to further revealing the efficacy mechanism and optimal indications of this therapy through more clinical trials and mechanism studies,so as to bring better hope of recovery and more efficient therapeutic effects to spinal cord injury patients.

ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) S_max+1 min (50%-55%) S_max, 3-5 cycles, S_max is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.

ObjectiveThis study aimed to investigate the effects of 4-week high-intensity interval training (HIIT) on synaptic plasticity in the prefrontal cortex (PFC) of rats exposed to chronic unpredictable mild stress (CUMS), and to explore its potential mechanisms. MethodsA total of 48 male Sprague-Dawley rats were randomly divided into 4 groups: control (C), model (M), control plus HIIT (HC), and model plus HIIT (HM). Rats in groups M and HM underwent 8 weeks of CUMS to establish depression-like behaviors, while groups HC and HM received HIIT intervention beginning from the 5th week for 4 consecutive weeks. The HIIT protocol consisted of repeated intervals of 3 min at high speed (85%-90% maximal training speed, S_max) alternated with one minute at low speed (50%-55% S_max), with 3 to 5 sets per session, conducted 5 d per week. Behavioral assessments and tail-vein blood lactate levels were measured at the end of the 4th and 8th weeks. After the intervention, rat PFC tissues were collected for Golgi staining to analyze synaptic morphology. Enzyme-linked immunosorbent assays (ELISA) were employed to detect brain-derived neurotrophic factor (BDNF), monocarboxylate transporter 1 (MCT1), lactate, and glutamate levels in the PFC, as well as serotonin (5-HT) levels in serum. Additionally, Western blot analysis was conducted to quantify the expression of synaptic plasticity-related proteins, including c-Fos, activity-regulated cytoskeleton-associated protein (Arc), and N-methyl-D-aspartate receptor 1 (NMDAR1). ResultsCompared to the control group (C), the CUMS-exposed rats (group M) exhibited significant reductions in sucrose preference rates, number of grid crossings, frequency of upright postures, and entries into and duration spent in open arms of the elevated plus maze, indicating marked depressive-like behaviors. Additionally, the group M showed significantly reduced dendritic spine density in the PFC, along with elevated levels of c-Fos, Arc, NMDAR1 protein expression, and increased concentrations of lactate and glutamate. Conversely, BDNF and MCT1 contents in the PFC and 5-HT levels in serum were significantly decreased. Following HIIT intervention, rats in the group HM displayed considerable improvement in behavioral indicators compared with the group M, accompanied by significant elevations in PFC MCT1 and lactate concentrations. Furthermore, HIIT notably normalized the expression levels of c-Fos, Arc, NMDAR1, as well as glutamate and BDNF contents in the PFC. Synaptic spine density also exhibited significant recovery. ConclusionFour weeks of HIIT intervention may alleviate depressive-like behaviors in CUMS rats by increasing lactate levels and reducing glutamate concentration in the PFC, thereby downregulating the overexpression of NMDAR, attenuating excitotoxicity, and enhancing synaptic plasticity.

ObjectiveThis study aims to explore the potential mechanism of the Xiezhuo Jiedu formula in regulating pyroptosis for the treatment of ulcerative colitis （UC） using bioinformatics and in vivo animal experiments. MethodsDifferentially expressed genes （DEGs） in colon tissues of UC patients were retrieved from the Gene Expression Omnibus （GEO） database. Pyroptosis-related genes were obtained from the GEO and GeneCards databases. The intersection of these datasets yielded pyroptosis-related DEGs （Pyro-DEGs）. Pyro-DEGs were subjected to Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis using the Metascape database. A protein-protein interaction （PPI） network was constructed using the STRING database. Least absolute shrinkage and selection operator （LASSO） prediction model and receiver operating characteristic （ROC） analysis were conducted to identify core Pyro-DEGs with diagnostic and therapeutic potential. Immune infiltration analysis of the UC datasets was performed using the deconvolution method （CIBERSORT）， along with correlation analysis with core Pyro-DEGs. Sixty male Sprague-Dawley （SD） rats were randomly divided into a control group， a model group， high-， medium-， and low-dose groups of Xiezhuo Jiedu formula （26.64， 13.32， 6.66 g·kg^-1）， and a mesalazine group （0.27 g·kg^-1）， with 10 rats in each group. UC was established by intrarectal administration of 3，5-trinitrobenzenesulfonic acid （TNBS） dissolved in ethanol. The control and model groups were given distilled water by gavage， while the treatment groups were administered the corresponding drugs for 7 consecutive days. Hematoxylin-eosin （HE） staining was used to observe the colon histopathology. Enzyme-linked immunosorbent assay （ELISA） was used to detect the levels of inflammatory factors such as interleukin-1β （IL-1β）， IL-10， IL-18， and transforming growth factor-β （TGF-β）. Immunohistochemistry （IHC） and Western blot were applied to detect the expression of Caspase-1， gap junction alpha-1 protein （GJA1）， peroxisome proliferator-activated receptor gamma （PPARG）， and S100 calcium-binding protein A8 （S100A8）. Real-time quantitative polymerase chain reaction （Real-time PCR） was utilized to measure mRNA expression of Caspase-1， GJA1， PPARG， and S100A8. Western blot was performed to assess protein expression levels of Caspase-1， GJA1， PPARG， and S100A8. ResultsGEO datasets GSE87466 and GSE87473 yielded 64 Pyro-DEGs. KEGG analysis indicated that these genes were enriched in the NOD-like receptor signaling pathway， tumor necrosis factor （TNF） signaling pathway， and hypoxia-inducible factor 1 （HIF-1） signaling pathway. Four core Pyro-DEGs （Caspase-1， GJA1， PPARG， and S100A8） were identified. Immune infiltration analysis showed that expression of these genes was positively correlated with mast cells， neutrophils， M0 macrophages， M1 macrophages， and dendritic cells. Animal experimental results indicated that compared with the control group， the model group had significantly increased levels of IL-1β and IL-18， significantly decreased levels of IL-10 and TGF-β. The model group showed enhanced Caspase-1， GJA1， and S100A8 staining， and significantly increased mRNA and protein expression of Caspase-1， GJA1， and S100A8 （P<0.01）. In contrast， the expression of PPARG was reduced in the model group （P<0.01）. After treatment， all dosage groups showed varying degrees of improvement （P<0.05， P<0.01）， with the high-dose group showing the most significant improvement （P<0.01）. ConclusionCaspase-1， GJA1， PPARG， and S100A8 are core Pyro-DEGs closely associated with the pathogenesis of UC. These genes may collaborate with immune cells such as mast cells， neutrophils， and M0 macrophages to mediate disease development. The Xiezhuo Jiedu formula may regulate the expression of core Pyro-DEGs through the NOD-like receptor， TNF， and HIF-1 core signaling pathways， thereby modulating immune homeostasis in UC rats and effectively alleviating UC.

[摘 要] 目的：分析胃癌骨转移患者的临床病理特征及影响预后的因素，探讨不同治疗方案对同时与异时骨转移患者生存的影响。方法：纳入2015年至2023年间南京大学医学院附属鼓楼医院胃癌骨转移患者120例，其中同时骨转移36例，异时骨转移84例。采用χ2检验比较胃癌同时与异时骨转移患者临床病理特征，采用Cox比例风险回归模型分析影响胃癌骨转移患者骨转移后总生存期（OS-BM）的风险因素，使用Kaplan-Meier法分析不同治疗方式对同时与异时骨转移OS-BM的影响。结果：120例胃癌骨转移患者中，有104例（86.6%）合并全身其他器官转移灶。在同时与异时骨转移患者的病理特征比较中，同时骨转移患者血C-反应蛋白（CRP）升高、血浆白蛋白减少；而异时骨转移患者外周血白细胞以及中性粒细胞低于正常值（均P < 0.05）。异时骨转移[HR = 2.35, 95% CI（1.47, 3.74），P < 0.01]、血清CA125 ≥ 30.2U/mL [HR = 1.6，95% CI（1.03, 2.48），P = 0.036]、血白细胞 ≥ 9.5 × 109/L [HR = 2.15，95% CI（1.17, 3.92），P = 0.013]，以及未接受免疫治疗[HR = 2.26，95% CI（1.5, 3.39），P < 0.01]是影响患者预后的独立危险因素。免疫治疗的联合使用相较于未使用免疫治疗，可明显延长胃癌骨转移患者的OS-BM（9.63 vs 4.53个月，P = 0.002）。异时骨转移患者比同时骨转移患者对免疫治疗响应更佳（中位OS-BM：10.8 vs 7.3个月，P = 0.004）。结论：免疫治疗是胃癌骨转移患者生存的独立保护因素，建议此类患者在化疗基础上尽早采用以免疫治疗为主的联合治疗，以延长患者的生存期。

Objective: To evaluate the clinical efficacy of digitally guided precision crown lengthening in secondary aesthetic rehabilitation cases, and to provide a clinical reference for digitally guided crown lengthening procedures and secondary aesthetic restorations. Methods: We present a case of a patient with tetracycline-stained teeth, partial detachment of anterior resin veneers, and gingival margin discrepancies. The patient underwent digitally guided precision crown lengthening followed by secondary aesthetic rehabilitation. Multimodal data, including intraoral, facial, and CBCT scans, were integrated to construct a four-dimensional virtual patient model (incorporating teeth, face, bone, and occlusion) for surgical planning and 3D-printed guide fabrication. Secondary aesthetic restoration was performed after achieving stable post-surgical outcomes. Based on this case, we conducted a detailed analysis and reviewed relevant literature on crown lengthening in secondary aesthetic rehabilitation. Results: The gingival contour of the anterior teeth exhibited significant improvement, with enhanced symmetry and stable gingival margin positioning that closely matched the preoperative design. The crown lengthening procedure demonstrated high precision, and the final outcome was aesthetic and functional. Literature review indicated that secondary restorations frequently present challenges such as gingival contour discrepancies and inflammation. Aesthetic crown lengthening in the anterior region should optimize both soft and hard tissue morphology to meet aesthetic standards, with digital technology improving procedural accuracy. Conclusion Precision crown lengthening effectively addresses gingival margin discrepancies in secondary aesthetic rehabilitation, ensuring stable gingival positioning and superior aesthetic outcomes. This approach is particularly suitable for cases with high aesthetic demands.

Objective To analyze the differences in distribution of traditional Chinese medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without, and to explore the potential correlation between the distribution of TCM syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of TCM syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between TCM syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary TCM syndrome elements related to disease location were the lung and liver, and the primary TCM syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary TCM syndrome elements related to disease location were the lung and spleen, and the primary TCM syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of TCM syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there was significant difference in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, the results showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of TCM syndrome elements and the species abundance and composition of salivary microbiota between the patients with pulmonary nodules and the healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

ObjectiveTo observe the clinical efficacy of the stasis-dispelling and detoxifying therapy in endometriosis （EMs） patients with the syndrome of kidney deficiency and blood stasis and the effects of this therapy on the expression levels of proteins related to the c-Jun N-terminal kinase （JNK） signaling pathway. MethodsA total of 72 patients with EMs due to kidney deficiency and blood stasis who met the criteria at the Integrated Traditional Chinese and Western Medicine Center for Reproduction and Genetics of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine from March 2024 to February 2025 were selected and randomized into a treatment group and a control group， with 36 patients in each group. Another 36 patients undergoing in vitro fertilization-embryo transfer （IVF-ET） due to male factors alone were selected as the blank group. The treatment group took the Zishen Quyu Jiedu formula orally， while the control group and the blank group took placebos. The treatment course encompassed the cycle before ovarian stimulation and the oocyte retrieval cycle. The TCM syndrome score of kidney deficiency and blood stasis， as well as the serum level of cancer antigen 125 （CA125）， were evaluated at the time of enrollment （before treatment） and on the trigger day （after treatment）. Serum levels of sex hormones were measured on day 2 of the menstrual cycle. On the trigger day， the duration and dosage of gonadotropin （Gn） administration and the serum levels of hormones on the day of human chorionic gonadotropin （HCG） injection were assessed. Embryo outcomes were evaluated 3 days after oocyte retrieval， and clinical pregnancy rates were assessed 28 days after embryo transfer. The baseline data of three groups were observed. The TCM syndrome scores and serum CA125 levels before and after treatment were compared between the treatment and control groups. The baseline endocrine levels， Gn days， Gn dosage， hormone levels on the day of HCG administration， number of oocytes retrieved， number of 2 pronucleus （2PN） fertilizations， number of available embryos， high-quality embryo rate， and clinical pregnancy rate were also assessed in all three groups. Six patients from each group were selected for determination of the protein levels of JNK， c-Jun， and nuclear receptor subfamily 4 group A member 2 （NR4A2） in ovarian granulosa cells （GCs） on the day of oocyte retrieval by Western blot. Results（1） There were no statistically significant differences in the baseline data among three groups， indicating comparability. （2） Compared with the baseline within the same group， the treatment group showed a decrease in the syndrome score of kidney deficiency and blood stasis after treatment. After treatment， serum CA125 levels decreased in both groups （P<0.05）， with a more substantial reduction in the treatment group， resulting in a difference between the two groups （P<0.05）. （3） There were no significant differences among three groups in terms of baseline serum levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， estradiol （E₂）， and progesterone （P）， as well as the duration and dosage of Gn administration and the serum levels of LH， E₂， and P on the day of HCG administration. （4） For embryo outcomes， the number of oocytes retrieved， 2PN fertilizations， available embryos， and high-quality embryo rates in the treatment group and the blank group were higher than those in the control group （P<0.05）， and the treatment group and the blank group had similar 2PN fertilizations. （5） There were differences in clinical pregnancy rate among three groups （P<0.05）， and the treatment group had higher pregnancy rate than the control and blank groups. （6） The protein levels of JNK， c-Jun， and NR4A2 in the GCs of the treatment group were lower than those in the control group （P<0.01） and close to those in the blank group （P<0.01）. （7） No obvious adverse reactions were observed in any of the subjects during the clinical observation process. ConclusionZishen Quyu Jiedu formula can ameliorate the clinical symptoms of patients with EMs due to kidney deficiency and blood stasis， reduce the serum CA125 level， increase the number of oocytes retrieved， 2PN fertilizations， available embryos， and high-quality embryo rate， and improve pregnancy outcomes. The mechanism may involve downregulating the levels of JNK， c-Jun， and NR4A2 to reduce the apoptosis of ovarian GCs and improve the ovarian function in the patients.