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.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

The Chinese Pharmacopoeia is the legal technical standard which should be followed during the research, production, use, and administration of drugs. At present, the new edition of the Chinese Pharmacopoeia is planned to be promulgated and implemented. This article summarizes and analyzes the main characteristics and the content of updates and amendments of the Chinese Pharmacopoeia 2025 Edition(Volume Ⅰ), to provide a reference for the correct understanding and accurate implementation the new edition of the pharmacopoeia.

AIM To study the chemical constituents from Tetrastigma hemsleyanum Diels et Gilg and their antitumor activity in vitro.METHODS Silica gel,ODS,Sephadex LH-20 and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activity in vitro was determined by MTT mothod.RESULTS Twenty-eight compounds were isolated and identified as triphyllin A(1),eruberin B(2),(2S,4R)-5,7-dihydroxy-4,4'-dimethyl-6,8-dimethyl-flavan-5-O-β-D-6-acetylglucopyranoside-7-O-β-D-glucopyranoside(3),eruberin A(4),abacopterin Ⅰ(5),matteucinol(6),homoerodictyol(7),(2S)-5,3',4'-trihydroxy-7-methoxy-flavanone(8),(2S)-5,2',5'-trihydroxy-7-methoxyflavanone(9),galinsonside B(10),quercetin-3-O-β-D-glucopyranoside(11),kaempferol 3-O-robinobioside(12),rutin(13),geniposide(14),jasminoside A(15),β-sitostenone(16),sitosterol palmitate(17),β-sitosterol(18),ursolic acid(19),hyptadienic acid(20),3,4-dihydroxybenzoic acid(21),3,4-dimethoxybenzoic acid(22),gallic acid(23),dibutylphthalate(24),bis-(2-ethylhexyl)phthalate(25),9-nonadecenoic acid(26),triacylglycerol(27),crocin Ⅰ(28).The IC50 values of compound 1 for human gastric adenocarcinoma cells BGC-823 and human colon cancer cells HCT-116 were(22.07±0.38),(20.67±0.11)μmol/L,respectively.The IC50 value of compound 9 for BGC-823 cells was(21.58±0.05)μmol/L,and the IC50 value of compound 4 for HCT-116 cells was(16.67±0.36)μmol/L.CONCLUSION Compounds 1-10,14-15 and 28 are first isolated from Tetrastigma genus.Compounds 1,4,9 have weak antitumor activity in vitro.

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.

Objective To investigate the effect of different exercise modes on people with nonalcoholic fatty liver disease(NAFLD)and obesity,thereby providing evidence-based exercise prescriptions for the rehabilitation of this population.Methods Patients diagnosed with NAFLD and obesity through health screenings at the Physical Examination Center of First Affiliated Hospital of Army Medical University from January to September 2023 were selected and assigned into three groups by random number table method,with 52 cases in each group.The aerobic group underwent aerobic exercise,the resistance group underwent resistance exercise,and the combined group underwent a combination of aerobic and resistance exercise for a duration of 12 weeks.The liver function indicators[including alanine aminotransferase(ALT),gamma-glutamyl transferase(GGT),aspartate aminotransferase(AST),albumin,and bilirubin],BMI,waist circumference,blood glucose,and triglyceride(TG)levels in each group were detected and compared.The improvement effect of different exercise modes on the above various indexes in patients with NAFLD and obesity was analyzed.Results After intervention,BMI and waist circumference were significantly decreased in each group(P<0.05);and the ALT,GGT,albumin,bilirubin,TG and blood glucose of the combined group were significantly improved compared with those before intervention(P<0.05).Resistance exercise had a better improvement effect on the ALT,GGT,AST and TG than aerobic exercise(P<0.05),while which had no significant difference in the albumin,bilirubin,BMI,waist circumference or blood glucose compared with aerobic exercise(P>0.05).The improvement effects of aerobic+resistance combined exercise on the BMI,waist circumference,albumin,bilirubin and TG were better than those of aerobic exercise and resistance exercise alone(P<0.05),while which had no significant difference in the improvement of the ALT,GGT or AST compared with resistance exercise alone(P>0.05).Conclusion For people with NAFLD and obesity,a combined aerobic and resistance exercise intervention is recommended,which can improve the liver function,body fat distribution and related metabolic indexes of patients,with better treatment results.

Depression is a prevalent mental and emotional disor-der that often results in significant emotional disturbances,cog-nitive dysfunction,and memory impairments.It is characterized by a high incidence rate,a substantial disability burden,and limited therapeutic efficacy.Currently,the long-term use of medications for the treatment of depression can result in a range of adverse reactions,highlighting the urgent need to explore no-vel approaches that can effectively alleviate depressive symptoms while minimizing side effects.Curcumin,a natural polyphenolic compound derived from the rhizome of turmeric,demonstrates considerable potential in the prevention and treatment of depres-sion,owing to its diverse array of biological activities.In recent years,numerous studies have investigated the use of curcumin for the treatment of depression.This article aims to provide a comprehensive review of the mechanisms of action underlying curcumin's efficacy in treating depression.Specifically,it focu-ses on its ability to improve neurotransmitter imbalances,restore neural plasticity,alleviate neural damage,mitigate dysfunction of the hypothalamic-pituitary-adrenal(HPA)axis,regulate in-flammatory factors and neuroinflammatory signaling pathways,and inhibit oxidative stress.This review is intended to offer in-sights and methodological references for basic research on curcu-min,as well as for the development of novel therapeutic agents for the treatment of depression.

Objective:To observe the clinical effect of aripiprazole combined with non-convulsive electroshock(MECT)for children and adolescents with first episode schizophrenia.Methods:94 children and adolescents with first episode schizophrenia who were admitted to Yiling Kangning Mental Hospital of Yichang from August 2022 to August 2024 were divided into control group(received aripiprazole,n=47)and study group(received aripiprazole combined with MECT,n=47)by using random number table method.The clinical efficacy,dysfunction scale[Positive and Negative Symptom Scale(PANSS),Montreal Cognitive Assessment Scale(MoCA),Wechsler Memory Scale(WMS)],glucose and lipid metabolism indexes[low density lipoprotein cholesterol(LDL-C),glycated hemoglobin(HbAlc),total cholesterol(TC),fasting blood glucose(FBG),High density lipoprotein cholesterol(HDL-C),inflammatory factor indexes[interleukin-1β(IL-1β),tumor necrosis factor-α(TNF-α),interleukin-6(IL-6)],neurocytokine levels[serum brain-derived neurotrophic factor(BDNF),s100βprotein(s100β),homocysteine(Hcy)]and the occurrence of adverse reactions were compared between the two groups.Results:Compared with the control group after treatment,the clinical total effective rate,MoCA,WMS score,HDL-C,BDNF were higher,PANSS score,HbAlc,FBG,TC,LDL-C,TNF-α,IL-1β,IL-6,s100β and Hcy were lower in the study group(P＜0.05).There was no difference in the incidence of adverse reactions between the two groups(P＞0.05).Conclusion:Aripiprazole combined with MECT in the treatment of in children and adolescents with first episode schizophrenia can reduce the degree of inflammation,regulate glucose and lipid metabolism,improve clinical symptoms and neurological function of children,with good safety.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.