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.

Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

High altitude heart disease(HAHD)is a chronic mountain sickness in which the body is exposed to high altitude(＞2 500 m)hypobaric hypoxia environment for a long time.HAHD has high morbidity and poor prognosis,and pulmonary hypertension is the main causative mechanism for its develop-ment.The phosphodiesterase-5 inhibitor sildenafil has become a hot drug for the treatment of pulmonary hypertension.This paper reviews the progress of HAHD and discusses the mechanism of action and effectiveness of sildenafil in the treatment of HAHD,with a view to providing a basis for the treatment of HAHD with sildenafil.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.

Objective:To explore the value of fetal heart quantification technology in assessing the morphology and function of the fetal heart during normal pregnancy.Methods:This prospective cohort study selected normal fetuses from healthy pregnant women who underwent prenatal ultrasound examinations at Hunan Provincial People's Hospital from January 2023 to October 2024. Using the GE Voluson E10 color Doppler diasonography, routine obstetric ultrasound and fetal echocardiography were performed to assess fetal growth and development and to exclude intracardiac and extracardiac malformations. Clear four-chamber view (4CV) dynamic images of the heart showing the endocardium (duration ≥3 s) were collected. Speckle-tracking analysis was performed using fetal heart quantification software. The measured indicators included the global spherical index (GSI), end-diastolic length of the heart (L-ED), end-diastolic width of the heart (W-ED), and the global longitudinal strain (GLS), fractional area change (FAC), and 24-segment spherical index (SI) of the left ventricle (LV) and right ventricle (RV). The cases were divided into five groups based on gestational age at the time of prenatal ultrasound: 20 +0 to 23 +6, 24 +0 to 27 +6, 28 +0 to 31 +6, 32 +0 to 35 +6, and 36 +0 to 40 +6 weeks. One-way analysis of variance, two independent samples t-test, univariate linear regression analysis, and Pearson correlation analysis were used to explore the differences in the above indicators among different gestational age groups and their correlation with gestational age. Results:A total of 200 pregnant women were included in the cohort, four cases were excluded due to poor image quality that prevented accurate tracking and measurement of relevant indicators. Ultimately, 196 cases (20 +0 to 23 +6 weeks 40 cases, 24 +0 to 27 +6 weeks 34 cases, 28 +0 to 31 +6 weeks 41 cases, 32 +0 to 35 +6 weeks 48 cases, and 36 +0 to 40 +6 weeks 33 cases) were included in the study, with a successful image analysis rate of 98.0%. (1) There were statistically significant differences in 4CV L-ED, 4CV W-ED, LV-FAC, and RV-FAC among the groups at 20 +0 to 23 +6, 24 +0 to 27 +6, 28 +0 to 31 +6, 32 +0 to 35 +6, and 36 +0 to 40 +6 weeks [4CV L-ED: 28.0±3.0, 32.6±4.3, 40.9±4.3, 46.7±4.8, 53.1±5.8, F=3.72; 4CV W-ED: 21.9±1.8, 25.1±4.2, 31.7±3.0, 37.4±4.0, 42.0±4.9, F=2.61; LV-FAC: (51.4±8.0)%, (49.0±10.4)%, (47.3±7.3)%, (43.1±7.5)%, (40.7±8.2)%, F=2.94; RV-FAC: (49.9±10.8)%, (46.2±12.0)%, (46.3±8.3)%, (43.2±8.0)%, (41.9±5.6)%, F=3.09; all P<0.05].(2) The size of the normal fetal heart gradually increased with gestational age, while the heart morphology remained relatively stable (4CV L-ED and 4CV W-ED were positively correlated with gestational age, with regression coefficients of 1.313 and 1.325, respectively, both P<0.001;LV-FAC and RV-FAC were negatively correlated with gestational age with regression coefficients of -0.783 and -0.552, respectively, both P<0.001; GSI, LV-GLS and RV-GLS had no correlations with gestational age, all P>0.05). (3) The SI of LV segments 1 to 17 were higher than the SI of the corresponding RV segments, and the SI of RV segments 20-24 were higher than that of the corresponding LV segments (all P<0.001). Conclusion:Fetal heart quantification technology has a certain value in the assessment of fetal cardiac morphology and function.

This study aims to establish a convenient,new and visual detection method for the field diagnosis of Pasteurella multocida(Pm).With reference to the Pm kmt1 gene conserved sequence published in GenBank,PCR amplification primers were designed,the amplified kmt1 gene was cloned into pMD19-T vector,and the recombinant plasmid standard pMD19-T-kmt 1 was estab-lished and identified by PCR and sequencing.Using pMD1 9-T-kmt 1 plasmid as template and kmt1 gene as target gene,basic primers were designed and synthesized.According to the requirements of LFD,a probe(Pm-P)was designed,and the RPA-LFD method for Pm detection was established by optimizing the reaction conditions.Specificity and sensitivity tests were carried out,and 64 clini-cal samples were tested by the method.The results showed that the established Pm RPA-LFD method could be amplified at 37 ℃ for 15 min.Escherichia coli(E.coli),Salmonella enteriditis(SE),Riemerella anatipestifer(RA),Staphylococcus,goose parvovirus(GPV),duck plague virus(DPV),Muscovy duck parvovirus(MDPV)DNA was extracted as the template,and plasmid standard pMD19-T-kmt 1 was used as the positive control.All the positive controls were negative,indicating that the method had good specificity.The plasmid standard pMD1 9-T-kmt 1 was diluted with a 10-fold ratio,and the plasmid standard with a concentration of 107-100 copies/μL was used as the template.The sensitivity was 1.50×101 copies/μ,,which was 100 times higher than that of PCR.A total of 64 clinical samples with suspected RA were subjected to testing using PCR,RPA and LAMP-LFD,with a 100％compliance rate for all three detection tests.The results show that the established RPA-LFD method has the characteristics of strong specificity,high sensitivity,fast speed and visualization,and can be applied to the field detection of Pm.

High altitude heart disease(HAHD)is a chronic mountain sickness in which the body is exposed to high altitude(＞2 500 m)hypobaric hypoxia environment for a long time.HAHD has high morbidity and poor prognosis,and pulmonary hypertension is the main causative mechanism for its develop-ment.The phosphodiesterase-5 inhibitor sildenafil has become a hot drug for the treatment of pulmonary hypertension.This paper reviews the progress of HAHD and discusses the mechanism of action and effectiveness of sildenafil in the treatment of HAHD,with a view to providing a basis for the treatment of HAHD with sildenafil.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.