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.

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.

ObjectiveTo explore the regulatory effects and mechanisms of Astragali Radix polysaccharide （APS） on inhibitor of differentiation1 （ID1） and protein kinase B （Akt） in gastric cancer. MethodsImmunohistochemical staining was used to detect the expression of ID1 and Akt in 61 gastric cancer tissue samples and 20 adjacent normal gastric tissue samples. Immunofluorescence was used to detect the localization of ID1 and Akt. The effects of APS at the concentrations of 0.625， 1.25， 2.5， 5， 10， 20 mg·L^-1 on the proliferation of gastric cancer MGC-803 cells were examined by the cell counting kit-8（CCK-8） method and the colony formation assay. The target information of APS was retrieved from the Traditional Chinese Medicine Systems Pharmacology and Analysis Platform and Swiss Target Prediction. Keywords such as gastric cancer， gastric tumor， and stomach cancer were searched against GeneCards， UniProt， DisGeNET， and Online Mendelian Inheritance in Man （OMIM） for the screening of gastric cancer-related targets. The online tool jvenn was used to create the Venn diagram to identify the common targets， and STRING and Cytoscape were used to construct the protein-protein interaction network. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analyses were conducted via R 4.2.2 to predict the potential roles of APS in the development of gastric cancer. The cell scratch assay was employed to assess the effect of APS on the migration of MGC-803 cells. The protein and mRNA levels of ID1 and Akt in the cells treated with APS were determined by Western blot and Real-time PCR， respectively. ResultsCompared with the adjacent normal gastric tissue， the gastric adenocarcinoma tissue showed increased positive expression of ID1 （χ² =81.00， P<0.01）. Immunofluorescence detection showed that ID1 and Akt were mainly located in the cytoplasm of gastric adenocarcinoma cells. Bioinformatics analysis identified 14 common genes shared between APS and gastric cancer. The average degree of protein-protein interaction network nodes was 14.29. GO and KEGG pathway enrichment results showed that ID1 and Akt were significantly enriched in the Rap1 and phosphatidylinositol-3-kinase （PI3K） /Akt signaling pathways. Cell experiments demonstrated that 5-fluorouracil （0.1 mg·L^-1） and APS （10， 20 mg·L^-1） groups showed decreased cell proliferation， migration， and colony formation. Compared with the control group， 10， 20 mg·L^-1 APS inhibited the proliferation of MGC-803 cells （P<0.01）， with 10 mg·L^-1 APS demonstrating stronger inhibitory effect. In addition， APS at 10， 20 mg·L^-1 inhibited the migration （P<0.01） and colony formation （P<0.05， P<0.01） of MGC-803 cells. Compared with the control group， APS at 10， 20 mg·L^-1 down-regulated the protein levels of ID1 （P<0.01） and Akt （P<0.05） and the mRNA levels of ID1 （P<0.05， P<0.01） and Akt （P<0.05， P<0.01） in MGC-803 cells. ConclusionID1 and Akt are highly expressed in the gastric adenocarcinoma tissue， which may be related to the development of gastric cancer. APS can down-regulate the protein and mRNA levels of ID1 and Akt to exert anti-tumor effects， which is expected to provide new therapeutic targets for gastric cancer treatment.

Objective: To investigate the role and mechanism of the heat-clearing and detoxifying drug Laggerae Herba in regulating the nuclear factor-erythroid 2-related factor-2(Nrf2)/solute carrier family 7 member 11 (SLC7A11)/glutathione peroxidase 4 (GPX4) signaling pathway to inhibit ferroptosis and improve chronic heart failure induced by transverse aortic arch constriction in mice. Methods: Twenty-four male ICR mice were divided into the sham (n=6) and transverse aortic arch constriction groups (n=18) according to the random number table method. The transverse aortic arch constriction group underwent transverse aortic constriction surgery to establish models. After modeling, the transverse aortic arch constriction group was further divided into the model, captopril, and Laggerae Herba groups according to the random number table method, with six mice per group. The captopril (15 mg/kg) and Laggerae Herba groups (1.95 g/kg) received the corresponding drugs by gavage, whereas the sham operation and model groups were administered the same volume of ultrapure water by gavage once a day for four consecutive weeks. After treatment, the cardiac function indexes of mice in each group were detected using ultrasound. The heart mass and tibia length were measured to calculate the ratio of heart weight to tibia length. Hematoxylin and eosin staining were used to observe the pathological changes in myocardial tissue. Masson staining was used to observe the degree of myocardial fibrosis. Wheat germ agglutinin staining was used to observe the degree of myocardial cell hypertrophy. Prussian blue staining was used to observe the iron deposition in myocardial tissue. An enzyme-linked immunosorbent assay was used to detect the amino-terminal pro-brain natriuretic peptide (NT-proBNP) and glutathione (GSH) contents in mice serum. Colorimetry was used to detect the malondialdehyde (MDA) content in mice serum. Western blotting was used to detect the Nrf2, GPX4, SLC7A11, and ferritin heavy chain 1 (FTH1) protein expressions in mice cardiac tissue. Results: Compared with the sham group, in the model group, the ejection fraction (EF) and fractional shortening (FS) of mice decreased, the left ventricular end-systolic volume (LVESV) and left ventricular end-systolic diameter (LVESD) increased, the left ventricular anterior wall end-systolic thickness (LVAWs) and left ventricular posterior wall end-systolic thickness (LVPWs) decreased, the ratio of heart weight to tibia length increased, the myocardial tissue morphology changed, myocardial fibrosis increased, the cross-sectional area of myocardial cells increased, iron deposition appeared in myocardial tissue, the serum NT-proBNP and MDA levels increased, the GSH level decreased, and Nrf2, GPX4, SLC7A11, and FTH1 protein expressions in cardiac tissue decreased (P<0.05). Compared with the model group, in the captopril and Laggerae Herba groups, the EF, FS, and LVAWs increased, the LVESV and LVESD decreased, the ratio of heart weight to tibia length decreased, the myocardial cells were arranged neatly, the degree of myocardial fibrosis decreased, the cross-sectional area of myocardial cells decreased, the serum NT-proBNP level decreased, and the GSH level increased. Compared with the model group, the LVPWs increased, the iron deposition in myocardial tissue decreased, the serum MDA level decreased, and Nrf2, GPX4, SLC7A11, and FTH1 protein expressions in cardiac tissue increased (P<0.05) in the Laggerae Herba group. Conclusion Laggerae Herba improves the cardiac function of mice with chronic heart failure caused by transverse aortic arch constriction, reduces the pathological remodeling of the heart, and reduces fibrosis. Its mechanism may be related to Nrf2/SLC7A11/GPX4 pathway-mediated ferroptosis.

BACKGROUND: The achievement of an optimal return to sport (RTS) has remained a key goal after sports-related injuries, with the ongoing debate on the effectiveness of different surgical approaches for anterior cruciate ligament (ACL) rupture. This study aims to assess clinical outcomes and RTS across various surgical methods, such as anatomical single-bundle reconstruction (ASBR), central-axial single-bundle reconstruction (CASBR), and double-bundle reconstruction (DBR). METHODS: A randomized clinical trial was conducted, comprising 191 patients who underwent ACL rupture. These patients were divided into three groups based on the ACL reconstruction techniques they received (ASBR, CASBR, DBR). Over the 2-year follow-up period, the study assessed RTS through four single-hop tests, isokinetic extension tests, and limb asymmetry indices. Postoperative graft status was determined using the signal-to-noise quotient (SNQ), while knee function was evaluated using the International Knee Documentation Committee 2000 (IKDC-2000) score, Lysholm score, Tegner score, and degree of knee laxity. A binary logistic regression model was developed to forecast the factors influencing ideal RTS. RESULTS: DBR (67.63%) and CASBR (58.00%) exhibited higher RTS passing rates compared to ASBR (30.39%; χ2 = 19.57, P <0.05). Quadriceps strength symmetry in the lower limbs was identified as the key determinant of RTS ( χ2 = 17.08, P <0.05). The RTS rate was influenced by SNQs of the graft's tibial site (odds ratio: 0.544) and quadriceps strength of the reconstructed knee joint at 60°/s (odds ratio: 6.346). Notably, the DBR group showed enhanced knee stability, evidenced by superior results in the Lachman test ( χ2 = 13.49, P <0.01), objective IKDC-2000 ( χ2 = 27.02, P = 0.002), and anterior instability test ( χ2 = 9.46, P <0.01). Furthermore, DBR demonstrated superior clinical outcomes based on the Lysholm score (DBR: 89.57 ± 7.72, CASBR: 83.00 ± 12.71, ASBR: 83.21 ± 11.95; F = 10.452, P <0.01) and IKDC-2000 score (DBR: 90.95 ± 7.00, CASBR: 84.64 ± 12.68, ASBR: 83.63 ± 11.41; F = 11.78, P <0.01). CONCLUSION: For patients with ACL rupture, more ideal RTS rate and clinical outcomes were shown in the DBR group than in the ASBR and CASBR groups. Autograft status and quadriceps strength are postively related to RTS. TRIAL REGISTRATION ClinicalTrials.gov (NCT05400460).
Humans ; Anterior Cruciate Ligament Reconstruction/methods* ; Male ; Female ; Adult ; Anterior Cruciate Ligament Injuries/surgery* ; Young Adult ; Return to Sport ; Adolescent ; Anterior Cruciate Ligament/surgery* ; Treatment Outcome

Objective:To establish a method to detect IDH2 gene mutations in the cell-free DNA (cfDNA) sample of angioimmunoblastic T-cell lymphoma (AITL) based on the digital droplet PCR (ddPCR) method. The performance of this method was evaluated.Methods:Specific primers and probes were designed for IDH2 p. R172K, IDH2 p. R172M, and IDH2 p. R172W mutations, and primer combinations were optimized to establish the optimal ddPCR reaction system. In addition, the accuracy, precision, specificity, and detection limit of the method were evaluated using clinical cfDNA samples obtained from 40 patients with AITL at the First Affiliated Hospital of Nanjing Medical University.Results:The IDH2 R172K/M/W F2/R2 primer combination was selected to establish the ddPCR detection method for IDH2 R172K/M/W mutations. Specific standard samples showed no false-positive results. The accuracy test revealed that the relative deviation of the standard sample measurements was within ±10%. The detection limit test indicated that the method could detect 1 ng/μl with a 0.2% mutation rate for IDH2 R172K/M/W mutations. The precision measurements (inter-experimenter, inter-run, and inter-laboratory) all had a coefficient of variation of <5%. ddPCR was applied to 40 clinical samples with IDH2 R172K/M/W mutations, and the results were fully consistent with gene sequencing.Conclusion:ddPCR can detect IDH2 gene mutations in cfDNA from AITL with high sensitivity, specificity, and absolute quantification. This method offers a simple, rapid, and reliable approach for diagnosing and monitoring.

Objective To establish a method for predicting the risk of endometrial cancer(EC)and endometrial atypical hyperplasia(AH)in women with postmenopausal bleeding(PMB)by collecting clinical data on routine medical history.Methods The clinical data of a total of 408 PMB patients admitted to Fuxing Hospital,Capital Medical University were consecutively collected in this retrospective study from December 2013 to December 2023.According to the results of endometrial pathology,patients were divided into case group and control group.EC and AH were included in the malignant group(case group)and the other endometrial pathologies were included in the non-malignant group(control group).Clinical data,including clinical history,high risk factors,and common gynecological ultrasound measurement indicators,were collected and studied by univariate and multivariate Logistic regression analysis.Results The mean age of 408 patients was(60.4±7.8)years.A total of 74 cases(18.1％)were in case group and 334 cases(81.9％)were in control group.Based on Logistic regression analysis,the best predictors of endometrial malignant lesions were selected to create a"LRDNT"(light bleeding,recurrent bleeding,diabetes,non-uniform echogenicity & thickness)model.LRDNT scores range from 0 to 22.The score of LRDNT ≥15 has the largest Yoden index,and the sensitivity to predict endometrial malignant lesions is 79.73％,the specificity is 80.84％,and the prediction accuracy is 80.64％.Conclusions The risk prediction model LRDNT,which combines clinical information and common gynecological ultrasound measurement indicators of PMB patients,can help clinicians classify patients at high and low risk of endometrial malignant lesions,and optimize the strategy of diagnosis and treatment.

Spinal cord injury(SCI)is a structural and functional disruption of the spinal cord caused by various factors,leading to neurological dysfunction.As a common central nervous system disorder in clinical practice,SCI poses significant risks to human life and health.Its pathological mechanism is exceedingly complex,involving multiple pathological processes.Given the irreversibility of primary injury,targeting secondary injury has gradually become the main direction for the clinical treatment of SCI in recent years.Recent studies have highlighted the crucial role of blood-spinal cord barrier damage and microvascular dysfunction in the progression of secondary injury following SCI.Therefore,investigating the pathological mechanisms of microcirculation and exploring targeted therapies could provide valuable insights for clinical SCI treatment.This paper aims to provide an objective review of the role of microcirculation in SCI,identify the critical regulators of microvascular function,and summarize strategies for treating SCI by targeting microcirculation.The findings of this study may offer novel references for the clinical management of SCI.