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.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

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.

OBJECTIVES: Hypertriglyceridemic acute pancreatitis (HTG-AP) has a rapid onset and is associated with a high risk of progression and recurrence. Early identification of patients at risk of severe disease can help reduce the likelihood of multiple organ failure and mortality. This study aims to investigate the changes in inflammatory composite markers and D-dimer (D-D) levels in young and middle-aged/elderly patients with HTG-AP and to evaluate their predictive value for disease progression. METHODS: A total of 230 patients with HTG-AP admitted to Chongqing University Jiangjin Hospital (Jiangjin Central Hospital) between 2017 and 2023 were retrospectively enrolled. Patients were first divided into a young group (≤45 years) and a middle-aged/elderly group (>45 years), and then stratified into mild and severe groups based on disease severity. Inflammatory composite markers, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), C-reactive protein-to-lymphocyte ratio (CLR), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), as well as D-D levels, were compared among groups. Least absolute shrinkage and selection operator (LASSO) regression and Logistic regression were used to identify independent risk factors for disease progression in each age group. Receiver operating characteristic (ROC) curves and the DeLong test were used to assess and compare the predictive performance (area under the curve, AUC) of risk factors. Internal validation was performed using the bootstrap method (n=1 000). RESULTS: No significant differences in NLR, PLR, MLR, SIRI, SII, CLR, or D-D levels were observed between the young (n=127) and middle-aged/elderly (n=103) groups (all P>0.05). Among young patients, the severe group (n=59) had significantly higher NLR, SIRI, SII, CLR, and D-D levels compared to the mild group (n=68) (all P<0.05). Among middle-aged/elderly patients, CLR and D-D levels were significantly higher in the severe group (n=49) than in the mild group (n=54) (P<0.05). LASSO and Logistic regression analyses identified elevated D-D as an independent risk factor for disease progression in young patients (P=0.007, OR=1.458, 95% CI 1.107 to 1.920), while both D-D (P=0.001, OR=2.267, 95% CI 1.413 to 3.637) and CLR (P=0.003, OR=1.007, 95% CI 1.003 to 1.012) were independent risk factors in middle-aged/elderly patients. ROC analysis showed that D-D predicted disease progression in young and middle-aged/elderly patients with AUCs of 0.653 and 0.741, sensitivities of 67.8% and 57.1%, and specificities of 72.1% and 88.9%, respectively. CLR predicted progression in middle-aged/elderly patients with an AUC of 0.687, sensitivity of 63.3%, and specificity of 70.4%. DeLong test showed no significant difference in AUC between D-D and CLR for middle-aged/elderly patients (Z=0.993, P=0.321). Internal validation via bootstrap analysis yielded a D-D AUC of 0.732, with sensitivity and specificity of 68.1% and 91.0%, respectively. CONCLUSIONS Differences in inflammatory response and coagulation function exist across age groups and disease severities in HTG-AP patients. Elevated D-D is an independent predictor of disease progression in both young and middle-aged/elderly patients, while CLR also predicts progression in the latter group. D-D, in particular, demonstrates strong predictive value for severe disease in middle-aged/elderly patients with HTG-AP.
Humans ; Fibrin Fibrinogen Degradation Products/metabolism* ; Disease Progression ; Middle Aged ; Pancreatitis/etiology* ; Male ; Female ; Retrospective Studies ; Adult ; Biomarkers/blood* ; Hypertriglyceridemia/blood* ; Acute Disease ; Predictive Value of Tests ; Aged ; Inflammation ; C-Reactive Protein/analysis* ; Neutrophils ; Age Factors

Objective: To explore the correlation between traditional Chinese medicine (TCM) constitution and depressive symptom among school aged children and adolescents, so as to provide evidences for informing constitution based regulation and prevention of depressive symptom. Methods: From June to December 2024, a total of 4 729 students aged 6-14 were recruited by cluster random sampling from 10 primary schools in Baoding (Hebei Province), Heze and Liaocheng (Shandong Province). General information, TCM constitution and depressive symptom were collected. Restricted cubic spline (RCS) models were used to analyze related factors and threshold effects of depressive symptom. Binary Logistic regression was applied to examine the association between depressive symptom and TCM constitution, with subgroup analyses conducted. Results: The detection rate of depressive symptom among the included children and adolescents was 25.82%. RCS analyses indicated non linear associations between depressive symptom and age (inflection point at 10 years old), bedtime (inflection point at 22:00), and wake up time (inflection point at 6:30 ) (all P non linearity <0.01). Linear associations were observed with body mass index (BMI) and sleep duration (all P non linearity > 0.05 ). After adjusting for covariates such as age, BMI and sleep status, binary Logistic regression analyses showed that Yin deficient constitution ( OR =1.26, 95% CI =1.09-1.45) and Phlegm-dampness constitution ( OR =1.42, 95% CI =1.11-1.82) were significantly associated with depressive symptom among children and adolescents (all P <0.05). Conclusions Depressive symptom among school aged children and adolescents is primarily associated with Yin deficiency and Phlegm dampness constitutions in TCM constitution. Active attention should be paid to susceptible TCM constitution among children and adolescents. Targeted health guidance and interventions should be implemented to improve TCM constitution health status for preventing the occurrence of depressive symptom.

Objective To analyze the gene expression characteristics of chronic rhinosinusitis with nasal polyps(CRSwNP)using bioinformatics methods,aim to investigate the potential biomarkers and their diagnostic value of CRSwNP.Methods(1)The CRSwNP Gene expression data set was downloaded from the American Gene Expression Omnibus(GEO)database.The differentially expressed genes(DEGs)between CRSwNP patients and healthy controls were screened through data analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were performed on the identified DEGs.Protein-protein interaction(PPI)networks were constructed utilizing the STRING database,and the key genes were identified by using the cytoHubba plugin.The"Cibersort"package was used to analyze the influence of key genes on common immune cells.(2)Thirty-two patients diagnosed with CRSwNP in the First Affiliated Hospital of Hebei North University from June 2022 to June 2023 were selected as the CRSwNP group,and 21 patients with simple deviation of nasal septum without a history of sinusitis during the same period were selected as control group.The pathological characteristics of specimens in the two groups were examined using hematoxylin-eosin(HE)staining.Immunohistochemistry and Western blotting were used to detect the expression levels of key genes in CRSwNP.The levels of key proteins in plasma were detected using ELISA,and ROC curve was used to analyze its efficacy in diagnosing CRSwNP.Results(1)Analysis of three gene expression database sets(GSE36830,GSE23552,and GSE194282)showed that there were 156 DEGs in CRSwNP.GO functional enrichment and KEGG pathway analysis indicated that the functions of the above DEGs were mostly related to immune functions.Key genes such as cytochrome b-245 β chain(CYBB)and colony-stimulating factor 1 receptor(CSF1R)were identified.(2)The results of HE staining revealed that the epithelial of CRSwNP tissue was metaplastic into stratified squamous epithelium with interstitial edema.Both immunohistochemistry and Western blotting analyses indicated that the expression levels of CYBB and CSF1R in the CRSwNP group were significantly increased compared to control group(P＜0.05).ELISA results demonstrated that CYBB[(21.20±3.00)μg/ml vs.(17.66±1.66)μg/ml,P＜0.05]and CSF1[(477.37±86.63)pg/ml vs.(370.71±66.24)pg/ml,P＜0.05]in CRSwNP group were significantly increased compare to control group.ROC curve analysis showed that plasma concentrations of CYBB and CSF1 had AUCs of 0.888(95%CI 0.802-0.974)and 0.821(95%CI 0.711-0.931)for diagnosing of CRSwNP,respectively;their combined AUC was 0.927(95%CI 0.851-1.000).Conclusions CYBB and CSF1R may be involved in the occurrence and development of CRSwNP.Plasma CYBB and CSF1 have high diagnostic value for CRSwNP.

Drug-induced liver injury(DILI)is a common adverse drug reaction in clinical practice,which can lead to acute liver failure and even death in severe cases.In recent years,with the continuous introduction of new drugs and the expansion of their usage,the incidence and mortality rates of DILI have shown an upward trend,posing significant challenges to public health and clinical treatment.Macrophages,as a crucial component of the innate immune system,exhibit high plasticity and heterogeneity.They can polarize into pro-inflammatory M1 type or anti-inflammatory M2 type in response to microenvironmental signals.Research has demonstrated that macrophage polarization plays a central regulatory role in the occurrence and progression of DILI by influencing various processes such as inflammatory responses,cell apoptosis,and tissue repair.This review focuses on elucidating the regulatory mechanisms and roles of macrophage polarization in DILI,providing a theoretical framework for developing precise immunotherapeutic strategies.