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.

This paper systematically reviews the current status of integrated traditional Chinese and western medicine in the treatment of Helicobacter pylori （Hp） infection， as well as recent progress in clinical and basic research both in China and internationally. It summarizes the advantages of traditional Chinese medicine （TCM） in Hp infection management， including improving Hp eradication rates， enhancing antibiotic sensitivity， reducing antimicrobial resistance， decreasing drug-related adverse effects， and ameliorating gastric mucosal lesions. These advantages are particularly evident in patients who are intolerant to bismuth-containing regimens， those with refractory Hp infection， and individuals with precancerous gastric lesions. An integrated， whole-process management approach and individualized， staged comprehensive treatment strategies combining TCM and western medicine are proposed for Hp infection. Future prevention and control of Hp infection should adopt an integrative Chinese-western medical strategy， emphasizing prevention， strengthening primary care， implementing proactive long-term monitoring， optimizing screening strategies， and advancing the development of novel technologies and mechanistic studies of Chinese herbal interventions. These efforts aim to provide a theoretical basis and practical pathways for the establishment and improvement of Hp infection prevention and control systems.

Objective To investigate the regulatory mechanism of transforming growth factor-β1 (TGF-β1) in different types of mitral valvular disease (MVD) with atrial fibrillation (AF). Methods From August 2011 to August 2012, patients with moderate to severe MVD accompanied by AF who required mitral valve replacement at the Department of Cardiovascular Surgery, West China Hospital, Sichuan University, were included. Based on echocardiographic results, patients were divided into two groups: a mitral regurgitation (MR) with AF (MR-AF) group and a mitral stenosis (MS) with AF (MS-AF) group. Left atrial tissue samples were collected during surgery. Techniques such as enzyme-linked immunosorbent assay, real-time fluorescence quantitative polymerase chain reaction, immunohistochemistry, and Western blotting were used to detect key molecules in the TGF-β1/JNK pathway. Results Sixteen patients were enrolled. There were 8 patients in the MR-AF group, including 5 males and 3 females, with an average age of (41.38±11.19) years; and 8 patients in the MS-AF group, including 6 males and 2 females, with an average age of (43.12±5.30) years. The left atrial volume load was higher in MR-AF patients, while the left atrial pressure load was higher in MS-AF patients. In MS-AF patients, the relative expression levels of MAPK9, JUN, CASP3, BAX, and BCL2 mRNA in left atrial tissues were significantly upregulated. The serum TGF-β1 protein level and the relative expression levels of p-JNK, p-c-Jun, and Caspase-3 proteins in the left atrial tissues of the MR-AF group were higher. Myocardial cell damage was more severe in the MS-AF group, and the protein expression level of Bcl-2 was higher. Conclusion Different MVD have distinct hemodynamic characteristics. The myocardium of the left atrium in MR-AF patients is more prone to apoptosis, possibly through the activation of the TGF-β1/JNK signaling pathway.

OBJECTIVE To investigate the influence of CYP2C19 gene polymorphism on platelet function and inflammatory cytokines in elderly patients with ischemic stroke， and to analyze potential factors associated with poor prognosis. METHODS A retrospective study was conducted on elderly patients with ischemic stroke admitted to our hospital from June 2024 to June 2025， wh o underwent CYP2C19 genotype testing and received antiplatelet therapy with clopidogrel. The levels of platelet function indicators and inflammatory cytokines before and after treatment were compared among patients with different metabolic phenotypes. Based on the prognosis at 6 months post-treatment， patients were divided into poor prognosis group and good prognosis group. Univariate analysis was performed on general data， metabolic phenotype， the levels of platelet function indicators and inflammatory cytokines. Variables with P ＜0.05 and the levels of inflammatory cytokines before treatment were included in a multivariate Logistic regression analysis to identify independent risk factors for poor prognosis. Multiple linear regression was used to further analyze the relationship between metabolic phenotypes and inflammatory cytokines. RESULTS A total of 448 elderly patients with ischemic stroke were included； among them， 162 cases were normal metabolic phenotype， 218 were intermediate metabolic phenotype， and 68 were poor metabolic phenotype. No rapid or ultrarapid metabolic phenotypes were observed. After treatment， platelet aggregation rate， the levels of P-selectin and platelet activated complex-1 （PAC-1）， high-sensitivity C-reactive Protein （hs-CRP）， interleukin-1β （IL-1β）， IL-6 and tumor necrosis factor-α （TNF-α） in the normal metabolic phenotype group， intermediate metabolic phenotype group， and poor metabolic phenotype group （except for platelet aggregation rate， and the levels of P-selectin and PAC-1 in the poor metabolic phenotype group） were significantly lower than those before treatment in the same group. Moreover， the above indicators in the normal metabolic phenotype group were significantly lower than those in the intermediate and poor metabolic phenotype groups at the corresponding time， and the levels of platelet function indicators in the intermediate metabolic phenotype group were significantly lower than those in the poor metabol ic phenotype group at the corresponding time （ P ＜0.05）. Univariate and multivariate Logistic regression analyses showed that combined with hypertension， combined with diabetes mellitus， and intermediate or poor metabolic genotypes were independent risk factors for poor prognosis in elderly patients with ischemic stroke （ P ＜0.05）. Multiple linear regression analysis showed that serum levels of hs-CRP， IL-1β， IL-6 and TNF-α before treatment were significantly higher in patients with intermediate and poor metabolic genotypes compared to those with normal metabolic genotype （ P ＜0.05）， with a greater magnitude of increase in inflammatory cytokines observed in the patients with poor metabolic genotype. CONCLUSIONS The elderly ischemic stroke patients with CYP2C19 intermediate and poor metabolic genotypes have poor inhibition effect on platelet and higher levels of inflammatory cytokines than normal metabolic genotype； CYP2C19 gene polymorphism， and in combination with hypertension and diabetes， can be used as independent predictors of poor prognosis.

Objective To investigate the detection rate of non-alcoholic fatty liver disease (NAFLD) and influencing factors in the elderly population undergoing physical examination in Nanjing. Methods People who participated in the elderly physical examination in Nanjing from 2018 to 2023 were selected as the study subjects according to the inclusion and exclusion criteria. Basic information and physical examination results were collected. The t-test and Chi-square test were used to compare the detection status of NAFLD in different characteristic populations, and multivariate logistic regression model was used to analyze influencing factors of NAFLD. Results A total of 41 066 people were included in the study, with a detection rate of 39.55%. The detection rate in males (24.12%) was significantly lower than that in females (49.75%) (χ² = 2702.442, P<0.001). Trend χ² test results showed that the detection rate of NAFLD increased gradually with BMI (χ²_trend = 4084.414, P_trend < 0.001). Multivariate logistic regression analysis showed that female (OR = 3.055, 95% CI : 2.911-3.206), primary school or below (OR = 1.075, 95% CI : 1.009-1.146), unmarried (OR = 1.107, 95% CI : 1.039-1.179), BMI (18.5kg/m²-23.9 kg/m²: OR = 4.876, 95% CI :3.340-7.119; 24.0 kg/m²-27.9 kg/m²: OR = 15.324, 95% CI : 10.503-22.358; ≥28.0 kg/m²: OR = 37.433, 95% CI : 25.591-54.753), hypertension (OR = 1.095, 95% CI : 1.040-1.153), diabetes mellitus (OR = 1.317, 95% CI :1.250-1.387), and dyslipidemia (OR = 1.574, 95% CI : 1.501-1.652) were risk factors for NAFLD (all P<0.05). Conclusion The detection rate of NAFLD in the elderly population undergoing physical examinations in Nanjing is relatively high. Women, unmarried people, people with low education, overweight and obesity, and people with hypertension, diabetes, and dyslipidemia are the high-risk groups.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

Objective: To conduct screening for rare blood types within important blood group systems for the Chinese population, such as Rh, Duffy, Kidd, P1Pk, Diego, and MNS, in the Guangzhou region, and to establish a corresponding rare blood type database and physical repository. Methods: The saline medium microplate method was used to screen blood donors with the ccDEE phenotype combined with either Jk(a-) or Jk(b-). The polybrene microplate method was employed to screen for donors with Fy(a-), s(-), Lu(b-), Di(b-), k(-), and p phenotypes. The urea lysis microplate method was applied to screen for the Jk(a-b-) phenotype. A high-resolution melting (HRM) curve method was established for screening some donors with the Di(b-) phenotype. Subsequently, expanded phenotyping of antigens in the Rh, Kidd, MNS, Duffy, P1Pk, Lewis, Kell, and Lutheran blood group systems was performed on identified rare blood type donors using monoclonal antibodies. The test results are entered into the Rare Blood Type Bank Management System of the Guangzhou Blood Center, enabling functions such as confirmation reminders and cryopreservation storage when the donor donates again. Red blood cells of rare blood types are processed into frozen red blood cells for long-term storage. Results: Among voluntary blood donors, 16 cases of the ccDEE combined with Jk(a-) phenotype were identified (0.221 7%, 16/7 216); 10 cases of the ccDEE combined with Jk(b-) phenotype (0.138 6%, 10/7 216); 78 cases of the Fy(a-) phenotype (0.169 5%, 78/46 012); 39 cases of the Lu(b-) phenotype (0.138 2%, 39/28 214); 31 cases of the s(-) phenotype (0.081 8%, 31/37 913); 22 cases of the Di(b-) phenotype (0.029 9%, 22/73 691); 30 cases of the Jk(a-b-) phenotype (0.010 1%, 30/298 250); and 1 case of the k(-) phenotype (0.001 3%, 1/77 382), which was further identified as KELnull phenotype (K0). No p phenotype donors were identified (0/88 528). A total of 228 units of frozen red blood cells were prepared. The screening results were compared and analyzed with rare blood type data from other regions. Conclusion: This study, through a combination of different screening methods, significantly improved the efficiency of rare blood type screening while remaining cost-effective. By conducting large-scale screening and performing data informatization processing, a database and physical repository of rare blood types in the Guangzhou region were successfully established. This provides a strong guarantee for the timely supply of blood to patients with difficult-to-match and rare blood types in the region, effectively enhances the level of transfusion safety in the region, and offers a practical paradigm for constructing a comprehensive blood transfusion support system.

Objective To analyze the disease burden of chronic kidney diseases (CKD) attributed to high body mass index (BMI) in China from 1992 to 2021 and predict the disease burden for the next decade, and to provide evidence for the prevention and treatment of CKD. Methods Using the Global Burden of Disease (GBD) database and the Joinpoint model, the average annual percentage rate change (AAPC) of the mortality rate and disability-adjusted life year (DALY) rate was calculated to describe and analyze the CKD disease burden attributed to high BMI in China from 1992 to 2021. The ARIMA model was employed to predict and analyze the change trend of the CKD disease burden. Results From 1992 to 2021, the mortality rate and DALY rate attributed to high BMI-induced chronic kidney disease showed an upward trend. Compared to 1992, the attributed number of deaths increased by 324.38%, and DALYs increased by 268.56%; the mortality rate increased by 64.00%, and the DALY rate grew by 51.62%. From 1992 to 2021, the mortality rate and DALY rate for males were lower than those for females, but the growth rate for males exceeded that of females. From 1992 to 2021, the mortality rate and DALY rate of chronic kidney disease attributed to high BMI in China increased with age. The average annual change rate of chronic kidney disease attributed to high BMI in China from 1992 to 2021 (mortality rate: 1.40 per 100,000 (95% CI: 1.04–1.76), DALY rate: 1.43 per 100 000 (95% CI: 1.17–1.70)) was higher than thHuaiyin Normal University, Huai'anher social demographic index (SDI) regions. The ARIMA model predicted that the age-standardized mortality rate increased from 2.91 per 100 000 in 2022 to 3.05 per 100 000 in 2026, and the age-standardized DALY rate increased from 69.65 per 100 000 in 2022 to 73.58 per 100 000 in 2026. Conclusion Chronic kidney disease attributed to high BMI in China is on the rise, and it will continue to grow in the future. The focus of CKD prevention and control should be on males and the elderly, while active measures should be taken to reduce the occurrence and progression of chronic kidney disease.