Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

BACKGROUND:Carboxylesterase 1 and inflammatory factors play a crucial role in regulating lipid metabolism and glucose homeostasis.However,the effects of different exercise intensity interventions on carboxylesterase 1 and inflammatory factors in skeletal muscle of type 2 diabetic rats remain to be revealed. OBJECTIVE:To investigate the effects of different exercise intensity interventions on carboxylesterase 1 and inflammatory factors in skeletal muscle of type 2 diabetic rats. METHODS:Thirty-two 8-week-old male Sprague-Dawley rats were randomly divided into normal control group(n=12)and modeling group(n=20)after 1 week of adaptive feeding.Rat models of type 2 diabetes mellitus were prepared by high-fat diet and single injection of streptozotocin.After successful modeling,the rats were randomly divided into diabetic control group(n=6),moderate-intensity exercise group(n=6)and high-intensity intermittent exercise group(n=6).The latter two groups were subjected to treadmill training at corresponding intensities,once a day,50 minutes each,and 5 days per week.Exercise intervention in each group was carried out for 6 weeks.After the intervention,ELISA was used to detect blood glucose and blood lipids of rats.The morphological changes of skeletal muscle were observed by hematoxylin-eosin staining.The mRNA expression levels of carboxylesterase 1 and inflammatory cytokines were detected by real-time quantitative PCR.The protein expression levels of carboxylesterase 1 and inflammatory cytokines were detected by western blot and immunofluorescence. RESULTS AND CONCLUSION:Compared with the normal control group,fasting blood glucose,triglyceride,low-density lipoprotein cholesterol,insulin resistance index in the diabetic control group were significantly increased(P<0.01),insulin activity was decreased(P<0.05),and the mRNA and protein levels of carboxylesterase 1,never in mitosis gene A related kinase 7(NEK7)and interleukin 18 in skeletal muscle tissue were upregulated(P<0.05).Compared with the diabetic control group,fasting blood glucose,triglyceride,low-density lipoprotein cholesterol,and insulin resistance index in the moderate-intensity exercise group and high-intensity intermittent exercise group were down-regulated(P<0.05),and insulin activity was increased(P<0.05).Moreover,compared with the diabetic control group,the mRNA level of NEK7 and the protein levels of carboxylesterase 1,NEK7 and interleukin 18 in skeletal muscle were decreased in the moderate-intensity exercise group(P<0.05),while the mRNA levels of carboxylesterase 1,NEK7,NOD-like receptor heat protein domain associated protein 3 and interleukin 18 and the protein levels of carboxylesterase 1 and interleukin 18 in skeletal muscle were downregulated in the high-intensity intermittent exercise group(P<0.05).Hematoxylin-eosin staining showed that compared with the diabetic control group,the cavities of myofibers in the moderate-intensity exercise group became smaller,the number of internal cavities was reduced,and the cellular structure tended to be more intact;the myocytes of rats in the high-intensity intermittent exercise group were loosely arranged,with irregular tissue shape and increased cavities in myofibers.To conclude,both moderate-intensity exercise and high-intensity intermittent exercise can reduce blood glucose,lipid,insulin resistance and carboxylesterase 1 levels in type 2 diabetic rats.Moderate-intensity exercise can significantly reduce the expression level of NEK7 protein in skeletal muscle,while high-intensity intermittent exercise can significantly reduce the expression level of interleukin 18 protein in skeletal muscle.In addition,the level of carboxylesterase 1 is closely related to the levels of NEK7 and interleukin 18.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Objective We aimed to evaluate the efficacy and safety of Shengxuebao Mixture in the treatment of cancer-related anemia(CRA)presenting with syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood.Methods A randomized,double-blind,placebo-controlled,multicenter clinical trial was conducted.Eligible patients with malignant tumors meeting the inclusion and exclusion criteria were enrolled from 26 hospitals,including Dongzhimen Hospital,Beijing University of Chinese Medicine,Xiaogan Central Hospital,and Yangzhou Hospital of Traditional Chinese Medicine,from June 1,2022,to September 30,2024.Patients were allocated 1:1 to either the experimental group receiving Shengxuebao Mixture or the control group receiving its simulator(placebo)using a block randomization method under double-blind conditions.Both groups received 15 mL orally three times daily for 28 consecutive days.The primary efficacy indicators included the hemoglobin(Hb)improvement rate(RHb)and the traditional Chinese medicine(TCM)syndrome improvement rate(RTCM)at week 4 of treatment.The secondary efficacy indicators encompassed Hb and red blood cell(RBC)count,Karnofsky Performance Status(KPS)score,TCM syndrome score,individual TCM symptom scores,and changes in each of these indicators compared to the baseline period at weeks 2,4,and 6 of treatment.Safety evaluations were conducted at week 4 of treatment.Results A total of 239 patients were enrolled,with 225 cases included in the Full Analysis Set(FAS)(109 in the experimental group vs.116 control group),163 in the Per Protocol Set(PPS)(77 vs.86),and 225 in the Safety Set(SS)(109 vs.116).Baseline characteristics between groups showed no significant differences.Significant differences were observed between the experimental and control groups in RHb at week 4(FAS:49.51%vs.35.24%,P<0.05;PPS:53.25%vs.36.05%,P<0.05)and RTCM at week 4(FAS:61.54%vs.39.62%,P<0.01;PPS:64.94%vs.40.70%,P<0.01).At weeks 2,4,and 6,the experimental group showed greater improvements in Hb and RBC counts than the control group.Additionally,the TCM syndrome scores were lower in the experimental group than in the control group at these time points.Except for week 2 in PPS,the KPS improvement was better in the experimental group than in the control group(P<0.05).The experimental group also demonstrated a greater reduction in scores for individual TCM symptoms such as spiritlessness and weakness,poor appetite and reduced food intake at weeks 4 and 6 compared to the control group(P<0.05,P<0.01).Furthermore,the reduction in vertigo score was more pronounced in the experimental group at week 6(P<0.01).For the score of pale and lusterless complexion,only in the PPS was the reduction from baseline more significant in the experimental group than in the control group at weeks 4 and 6(P<0.05).No significant differences were observed between the experimental and control groups in the incidence of all adverse events or drug-related adverse reactions.Conclusion Shengxuebao Mixture demonstrates significant efficacy in patients with CRA presenting syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood,effectively increasing Hb levels,ameliorating TCM syndromes,alleviating clinical symptoms,and enhancing functional status,with no significant difference in adverse drug reactions compared to the placebo.

Objective:To analyze the dynamic changes of serum exosome miR-552 and miR-653 levels in pa-tients with gastric cancer before and after chemotherapy and their relationship with clinical benefit.Methods:IA total of 128 patients with gastric cancer received chemotherapy from January 2022 to January 2024.According to the chemo-therapy effect,the two groups were divided into disease progression group and disease remission group.The levels of serum exosome miR-552 and miR-653 before and after chemotherapy were detected in the two groups,the risk fac-tors affecting the chemotherapy effect of gastric cancer patients were screened,the risk nomogram model was con-structed,and the efficacy was evaluated.Results:The proportion of TNM stage(Ⅲ+Ⅳ),lymph node metastasis,dis-tant metastasis,tumor size(>5 cm),invasion depth(T3/T4)and tumor growth pattern(invasive type)in disease progres-sion group was higher than that in disease remission group(P<0.05).The levels of serum exosomes miR-552 and miR-653 in disease progression group were higher than those in remission group before and after chemotherapy(P<0.05).Compared with before chemotherapy,miR-552 and miR-653 levels in both groups decreased(P<0.05).Logistic regres-sion analysis showed that TNM stage,lymph node metastasis,distant metastasis,tumor size,invasion depth,miR-552 and miR-653 were all risk factors affecting the chemotherapy efficacy of gastric cancer(P<0.05).ROC curve results showed that the AUC,95%CI,sensitivity and specificity of risk nomogram model to predict chemotherapy efficacy of gastric cancer were 0.867,0.672～0.991,92.80%and 80.40%,respectively(P<0.001).Calibration curve results showed that both predicted and actual predicted values were near the ideal curve,and the Hosmer-Lemeshow goodness of fit curve test χ2=1.869,P=0.782.Conclusion:The levels of serum exosomes miR-552 and miR-653 are closely related to the chemotherapy efficacy of gastric cancer,and dynamic monitoring of the above indexes is helpful for the evaluation of the disease and prognosis of gastric cancer.In this study,the risk nomogram model constructed based on the above indexes and other risk factors has high predictive value and clinical practicability for chemotherapy efficacy in patients with gastric cancer.

Tuberculosis(TB),a chronic infectious disease caused by infection with the Mycobacterium tuberculosis complex(MTBC),has re-emerged as the leading cause of death from a single infectious agent worldwide.Because of widespread use and mis-use of anti-tuberculosis drugs,the emergence of multidrug-resistant TB(MDR-TB)and extensively drug-resistant TB(XDR-TB)is increasing,thus posing a serious threat to global health.The current problem of drug resistance is a major prevention and treatment challenge;therefore,the search for new drug targets is urgently needed.In recent years,substantial progress has been made in re-search on anti-tuberculosis drug targets and novel therapeutic strategies.Herein,we summarize recent research progress in anti-tuberculosis drug targets,primarily cell wall synthesis,nucleic acid replication and transcription,and energy metabolism.We also provide an overview of research progress regarding two novel therapeutic strategies,to provide a theoretical basis and research ideas for the development of new clinical drugs.

Medical therapy and surgical intervention are the two primary approaches for treating myocardial bridge.However,there remains controversy regarding the use of coronary artery bypass grafting(CABG)and myocardial bridge unroofing.Here,we report a case of myocardial infarction following CABG in a patient with a myocardial bridge.The patient was admitted to Lanzhou First Peopie's Hospital with persistent chest pain,chest tightness,and shortness of breath lasting 2 hours.Physical examination revealed no significant abnormalities.Electrocardiography(ECG)indicated extensive anterior wall myocardial infarction.Laboratory findings showed myoglobin levels of 140.1 ng/ml and troponin Ⅰ levels of 2.59 ng/ml,with no other significant abnormalities.The initial diagnosis was acute extensive anterior wall myocardial infarction.Emergency coronary angiography revealed a myocardial bridge in the mid-segment of the left anterior descending artery(LAD).Emergency CABG using the left internal mammary artery to the LAD was performed,leading to symptomatic improvement,and the patient was discharged in stable condition.However,the patient experienced a recurrent myocardial infarction seven years post-surgery and received secondary preventive medical therapy.The patient is currently under ongoing follow-up care.CABG is an effective treatment for myocardial bridge.However,based on the case reported in this study,we recommend careful evaluation of whether a patient may benefit from CABG.