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.

Depressive disorder is a prevalent mental illness characterized by pronounced and enduring symptoms of depression and cognitive impairment. The escalating pressures of modern society have led to a corresponding rise in the number of depressive disorder patients, particularly those exposed to adverse social, economic, political, and environmental factors which exacerbate the risk of this disorder. The pathogenesis of depressive disorder is multifaceted, encompassing oxidative stress, neuroplasticity alterations, neuroinflammation, neurotransmitter system imbalances, and intestinal microecological disruptions, among others. Clinically, conventional antidepressants are primarily predicated on the monoamine neurotransmitter hypothesis. This theory posits that depressive disorder can be ameliorated by regulating the levels of neurotransmitters within the body through a singular mechanism. However, the complex and multifaceted pathogenesis of depressive disorder results in limited selectivity for these drugs. Mitogen-activated protein kinase (MAPK) is a conserved serine/threonine kinase that plays a crucial role in various cellular physiological and pathological processes, including cell growth, differentiation, stress adaptation, and inflammatory response. It is instrumental in maintaining cellular homeostasis and regulating cellular responses. Numerous studies indicate that MAPK is involved in the pathogenesis and progression of depressive disorder through various pathogenesis. However, what deserves attention is that the interaction between the pathogenesis and dynamics of regulatory process remains unclear. Modulating MAPK has been shown to influence the onset and progression of depressive disorder, though the precise mechanism remains elusive. Within the MAPK family, aberrant activity of extracellular signal-regulated kinase (ERK) can damage hippocampal neurons and overactivate microglia, precipitating depressive disorder. Excessive activation of c-Jun N-terminal kinase (JNK) results in heightened neuronal apoptosis in the hippocampus and prefrontal cortex, and suppresses the expression of neurotrophic factors. p38, a key regulator in inflammatory reactions, can induce neuroinflammation when overactive, leading to depressive disorder. ERK, JNK, and p38 sub-pathways do not function in isolation but rather interact synergistically and/or antagonistically through shared activators and common target molecules. Consequently, these sub-pathways form a complementary and coordinated regulatory network. In addition, MAPK family members can jointly influence the process of depressive disorder by sharing upstream factors and regulating common downstream targets, and there is a lack of identification of their markers and screening for subgroups. The collective abnormal activities of these MAPK family members illuminate the underlying mechanisms of depressive disorder, suggesting that MAPK could serve as a potential therapeutic target for this disorder. As for the study of ERK, different models of depressive disorder have contradictory effects on its activity. The primary cause of these differences can be attributed to the distinct pathological environments utilized in the creation of depressive disorder models. In the future, it is suggested that we use the inducement of depressive disorder as a modeling standard to accurately simulate the onset of depressive disorder to carry out accurate treatment according to the causes of depressive disorder. Research shows that classic clinical drugs, novel MAPK inhibitors and certain traditional Chinese medicines can prevent and treat depressive disorder by regulating the MAPK signaling pathway. Research on MAPK remains limited, particularly concerning the permeability and cellular specificity across the blood-brain barrier and the identification of objective predictive markers. Although inhibitors face challenges, they also possess significant advantages and developmental potential. This paper systematically summarizes the current status of MAPK in the treatment of depressive disorder, in order to provide insights for researching the pathogenesis of depressive disorder and developing new antidepressant drugs.

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.

Depressive disorder is a prevalent mental illness characterized by pronounced and enduring symptoms of depression and cognitive impairment. The escalating pressures of modern society have led to a corresponding rise in the number of depressive disorder patients, particularly those exposed to adverse social, economic, political, and environmental factors which exacerbate the risk of this disorder. The pathogenesis of depressive disorder is multifaceted, encompassing oxidative stress, neuroplasticity alterations, neuroinflammation, neurotransmitter system imbalances, and intestinal microecological disruptions, among others. Clinically, conventional antidepressants are primarily predicated on the monoamine neurotransmitter hypothesis. This theory posits that depressive disorder can be ameliorated by regulating the levels of neurotransmitters within the body through a singular mechanism. However, the complex and multifaceted pathogenesis of depressive disorder results in limited selectivity for these drugs. Mitogen-activated protein kinase (MAPK) is a conserved serine/threonine kinase that plays a crucial role in various cellular physiological and pathological processes, including cell growth, differentiation, stress adaptation, and inflammatory response. It is instrumental in maintaining cellular homeostasis and regulating cellular responses. Numerous studies indicate that MAPK is involved in the pathogenesis and progression of depressive disorder through various pathogenesis. However, what deserves attention is that the interaction between the pathogenesis and dynamics of regulatory process remains unclear. Modulating MAPK has been shown to influence the onset and progression of depressive disorder, though the precise mechanism remains elusive. Within the MAPK family, aberrant activity of extracellular signal-regulated kinase (ERK) can damage hippocampal neurons and overactivate microglia, precipitating depressive disorder. Excessive activation of c-Jun N-terminal kinase (JNK) results in heightened neuronal apoptosis in the hippocampus and prefrontal cortex, and suppresses the expression of neurotrophic factors. p38, a key regulator in inflammatory reactions, can induce neuroinflammation when overactive, leading to depressive disorder. ERK, JNK, and p38 sub-pathways do not function in isolation but rather interact synergistically and/or antagonistically through shared activators and common target molecules. Consequently, these sub-pathways form a complementary and coordinated regulatory network. In addition, MAPK family members can jointly influence the process of depressive disorder by sharing upstream factors and regulating common downstream targets, and there is a lack of identification of their markers and screening for subgroups. The collective abnormal activities of these MAPK family members illuminate the underlying mechanisms of depressive disorder, suggesting that MAPK could serve as a potential therapeutic target for this disorder. As for the study of ERK, different models of depressive disorder have contradictory effects on its activity. The primary cause of these differences can be attributed to the distinct pathological environments utilized in the creation of depressive disorder models. In the future, it is suggested that we use the inducement of depressive disorder as a modeling standard to accurately simulate the onset of depressive disorder to carry out accurate treatment according to the causes of depressive disorder. Research shows that classic clinical drugs, novel MAPK inhibitors and certain traditional Chinese medicines can prevent and treat depressive disorder by regulating the MAPK signaling pathway. Research on MAPK remains limited, particularly concerning the permeability and cellular specificity across the blood-brain barrier and the identification of objective predictive markers. Although inhibitors face challenges, they also possess significant advantages and developmental potential. This paper systematically summarizes the current status of MAPK in the treatment of depressive disorder, in order to provide insights for researching the pathogenesis of depressive disorder and developing new antidepressant drugs.

ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

Objective To explore the clinical values of non-invasive myocardial work (MW) and tissue motion annular displacement (TMAD) in evaluation of anthracycline therapy-related cardiac dysfunction in patients with non-Hodgkin lymphoma. Methods A total of 62 patients with non-Hodgkin lymphoma who received standardized chemotherapy based on doxorubicin. Two and three dimensional transthoracic echocardiography, along with two dimensional speckle tracking echocardiography, were performed one day before chemotherapy and at 3, 6, and 9 months after chemotherapy to assess left ventricular ejection fraction, global longitudinal strain (GLS), MW parameters, and TMAD. Logistic regression analysis was used to evaluate the risk factors for cancer therapy-related cardiac dysfunction (CTRCD). The receiver operating characteristic curve was used to assess the diagnostic values of MW- and TMAD-related parameters for CTRCD. Results Compared to baseline, GLS, global work index (GWI), global constructive work (GCW), global work efficiency (GWE), TMAD at midpoint (TMADmid), and TMADmid percentage of left ventricular long-axis diameter (TMADmid%) decreased at 3 months after chemotherapy, while global wasted work (GWW) increased at 6 months after chemotherapy (P＜0.05). Logistic regression analysis showed that the relative reduction in GLS and TMADmid% at 3 months after chemotherapy were independent predictors for CTRCD （P＜0.05), while MW parameters were not independent predictors for CTRCD. GLS reduction≥10.3% and TMADmid% reduction≥15.8% at 3 months after chemotherapy predicted CTRCD with 0.866 and 0.824 of area under the curve (AUC), 92% and 75% of sensitivity, and 74% and 80% of specificity, respectively. AUC of combination of two indexes improved to 0.905, with 75% of sensitivity and 90% of specificity. Conclusions In non-Hodgkin lymphoma patients, the combination of GLS and TMADmid% is helpful of predicting CTRCD early, TMAD may be a novel diagnostic index for CTRCD, and GLS has superior predictive performance than MW for CTRCD.

AIM:To investigate the current status and influencing factors of knowledge-attitude-practice in myopia prevention and control among children and adolescents in Ningbo City, thereby providing a scientific basis for formulating targeted prevention strategies.METHODS: Children and adolescents aged 6-12 years old were selected from the medical-school collaborative myopia prevention network in Ningbo City between August 2024 and May 2025 using stratified cluster sampling. Information on myopia prevention knowledge(15 items)and practice(9 items)was collected through questionnaire surveys. Logistic regression models were used to analyze factors influencing myopia occurrence in children and adolescents.RESULTS: A total of 664 children and adolescents aged 6-12 years were enrolled in this study. Participants were divided by age into three groups: 6-7 years old(n=221), 8-9 years old(n=221), and 10-12 years old(n=222). Of the 664 questionnaires distributed, 637 valid questionnaires were returned(201 from the 6-7 age group, 235 from the 8-9 age group, and 201 from the 10-12 age group), yielding an effective response rate of 95.9%. Based on myopia screening results, the non-myopic group comprised 203 participants(31.9%), including 100 males and 103 females, with a mean age of 8.82±1.98 years old. The myopic group comprised 434 participants(68.1%), including 213 males and 221 females, with a mean age of 9.10±1.95 years old. The myopia prevalence rates in the 6-7, 8-9, and 10-12 age groups were 37.8%(76/201), 71.9%(169/235), and 94.0%(189/201), respectively(P<0.001). Regarding the knowledge and practice of myopia prevention, the overall awareness rate in the non-myopic group(59.7%±9.7%)was significantly higher than that in the myopic group(48.7%±8.5%; P<0.001). Additionally, the non-myopic group scored higher on the key practice of “regular eye examinations”(4.27±0.96)compared to the myopic group(4.10±1.05; P<0.05). Logistic regression analysis indicated that age was the primary risk factor for myopia occurrence.CONCLUSION: Age is the dominant factor in the onset of myopia, and there is a phenomenon of “knowledge-practice gap”; the traditional health education model has limitations, and a precise prevention and control system based on developmental patterns should be established.

ObjectiveTo verify the association between the Ddit3-Trib3-Akt signaling pathway and rat spermatogenesis by constructing an in vitro co-culture system of testis. MethodsTesticular tissue blocks from 20-25-day-old male rats were placed in an in vitro culture system， and the culture medium was replaced every 2 to 3 days. PCR was used to verify the expression of marker genes of various spermatogenic cells. RNA interference technology was employed to verify the correlation between the Ddit3-Trib3-Akt signaling pathway and rat spermatogenesis. ResultsThe co-culture system could be continuously cultured for more than 2.5 months in vitro. RT-PCR showed that specific marker genes of spermatogonia， spermatocyte and spermoblast were expressed. The RNA and protein expression of Trib3 and Akt changed after the knocking down of Ddit3 and Trib3， respectively. It demonstrated the existence of Ddit3-Trib3-Akt signaling pathway in rat spermatogenesis. ConclusionThe culture time of more than 2.5 months indicates that the culture system can temporarily maintain the proliferation and differentiation of stem cells， and simultaneously maintain and stabilize spermatogenesis in a simple system. The successful validation of the Ddit3-Trib3-Akt signaling pathway also confirms that this culture system can be used to study possible molecular mechanisms of spermatogenesis in vitro.

ObjectiveTo investigate somatization symptoms in adolescents during frequent earthquakes in Hefei， and to explore their correlation with earthquake experiences. MethodsA cross-sectional survey was used to select 324 adolescents in Hefei as the survey objects. The self-rating scale of somatization symptoms （SSS） and the fatigue intensity scale （FIS） were used to evaluate the somatization symptoms and fatigue degree of middle school students， and multivariate Logistic regression analysis was used to explore the related factors of somatization symptoms and fatigue among middle school students. ResultsA total of 324 adolescents were included， and the overall detection rate of somatization symptoms was 6.5%， and the detection rate of moderate or above fatigue was 20.1%. The results of regression analysis showed that adolescents who were concerned about the earthquake for a longer time （≥1 h） had a higher risk of somatization symptoms （OR=5.430， 95%CI： 1.547-19.058）， and adolescents who received pre-earthquake training had a lower degree of fatigue （OR=0.535， 95%CI： 0.292-0.981） （P<0.05）. ConclusionDuring the frequent earthquakes， adolescents have more somatization symptoms and fatigue. Therefore， it is crucial to enhance health education， reduce the emphasis on event-related reports， and implement earthquake prevention and disaster reduction training to improve the physical and mental health of adolescents.

[摘 要] 目的：探讨高良姜素（Gal）调控AMPK/mTOR/ULK1信号通路对胃癌细胞凋亡和自噬的影响及其机制。方法：将胃癌NCI-N87细胞分为对照组、多索吗啡（DM）组、Gal低剂量（Gal-L）组、Gal高剂量（Gal-H）组、Gal-H + DM组。采用MTT法、流式细胞术、划痕愈合实验和Transwell实验分别检测各组细胞的增殖、凋亡、迁移和侵袭能力，WB法检测PCNA、C-caspase-3、免疫逃逸相关蛋白（B7H1）、EMT和AMPK/mTOR/ULK1信号通路蛋白的表达水平。建立裸鼠NCI-N87细胞移植瘤模型，观察Gal和5-FU对移植瘤的抑制效果。结果：与对照组比较，DM组NCI-N87细胞增殖活性、划痕愈合率和侵袭细胞数、N-cadherin、vimentin、PCNA、B7H1、p62和p-mTOR/mTOR蛋白表达均显著升高（均P < 0.05），细胞凋亡率、C-caspase-3、E-cadherin、LC3Ⅱ/LC3Ⅰ、p-AMPK/AMPK和p-ULK1/ULK1蛋白表达均显著降低（均P < 0.05）；Gal-L组和Gal-H组NCI-N87细胞的增殖活性、划痕愈合率和侵袭细胞数、N-cadherin、vimentin、PCNA、B7H1、p62和p-mTOR/mTOR蛋白表达均显著降低（均P < 0.05），细胞凋亡率、C-caspase-3、E-cadherin、LC3Ⅱ/LC3Ⅰ、p-AMPK/AMPK和p-ULK1/ULK1蛋白表达均显著升高（均P < 0.05）；DM可部分逆转Gal对NCI-N87细胞恶性生物学行为的抑制作用（P < 0.05）；与对照组比较，Gal组和5-FU组裸鼠移植瘤体积和质量均显著降低，肿瘤组织细胞凋亡率显著升高（P < 0.05）。结论：Gal可促进胃癌NCI-N87细胞自噬和凋亡，抑制其增殖、迁移和侵袭，可能与激活AMPK/mTOR/ULK1信号通路有关。