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.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

Aim To investigate the role of corylin in angiotensin Ⅱ(Ang Ⅱ)-induced cardiomyocyte hy-pertrophy and its underlying mechanisms.Methods An Ang Ⅱ-induced cardiomyocyte hypertrophy model was established and treated with corylin.Real-time PCR was employed to assess hypertrophic gene mRNA expression,and immunofluorescence was used to meas-ure cardiomyocyte surface area.Western blot and en-zyme activity assay kits were used to evaluate SIRT1 expression and activity.Results Corylin markedly mitigated Ang Ⅱ-induced hypertrophic gene expression and cardiomyocyte surface area enlargement.Moreo-ver,it prevented the Ang Ⅱ-mediated decline in SIRT1 protein levels and deacetylase activity.Further investi-gation indicated that corylin inhibited Ang Ⅱ-driven NF-κB transcriptional activity and the expression of its downstream target genes,such as TNF-α,IL-6,and IL-1β.Notably,SIRT1 silencing abolished the protective effects of corylin against cardiomyocyte hypertrophy,as well as its regulation of the SIRT1/NF-κB signaling pathway.Conclusion Corylin suppresses cardiomyo-cyte hypertrophy by modulating the SIRT1-dependent NF-κB signaling pathway.

Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.

Objective:To characterize the epidemiology, antimicrobial susceptibility, and molecular mechanisms of carbapenem-resistant Enterobacterales (CRE) carrying multiple carbapenemase genes in China, and to provide evidence for infection control and antibiotic stewardship.Methods:From 2016 to 2023, 115 CRE isolates harboring at least two carbapenemase genes were collected from 41 hospitals in 18 provinces across China. Species identification, antimicrobial susceptibility testing, and whole-genome sequencing were performed. Multilocus sequence typing (MLST) and capsular typing were conducted using Kleborate, plasmid replicon types were identified with PlasmidFinder, and a core genome phylogenetic tree was constructed.Results:The majority of isolates belonged to Klebsiella spp. (80.0%, 92/115), followed by E. cloacae (8.7%, 10/115) and E. coli (6.1%, 7/115). The isolates were mainly from Hebei, Beijing, Shandong, and Hunan (60.9%, 70/115), and sputum was the predominant specimen (43.5%, 50/115). The most common genotype was bla KPC+bla NDM (73.0%, 84/115), primarily in Klebsiella spp. (79.8%, 67/84), followed by bla NDM+bla IMP (15.7%, 18/115). The prevalent plasmid replicon types were IncFII (77.5%, 86/111), IncFIB (68.5%, 76/111), IncR (51.4%, 57/111), and IncX3 (20.7%, 23/111). Notably, 88.6% (31/35) of ST11-KL64 K. pneumoniae strains co-harbored IncFII, IncFIB, and IncR plasmids simultaneously. Between 2016 and 2022, the dominant subtype among Klebsiella spp. isolates was bla KPC-2+bla NDM-1 (56.2%, 36/64). In 2023, the bla KPC-2+bla NDM-13 subtype (29.5%, 19/64) emerged and exhibited clonal transmission (single nucleotide polymorphism 2?74 bp) in Hebei, Beijing, and Jilin. Susceptibility testing showed widespread resistance to β-lactams (90.2%-100%). Aztreonam-avibactam, tigecycline, and colistin retained high activity, with susceptibility rates of 90.16%-98.36%. Conclusions:In China, the majority of clinical Enterobacteriaceae strains that harbor multiple carbapenemases are Klebsiella spp. co-producing KPC and NDM enzymes. Dissemination is driven by both clonal expansion of ST11-KL64 and horizontal transfer of IncFII, IncFIB, and IncR plasmids. The recent emergence and regional clonal spread of the bla KPC-2+bla NDM-13 genotype underscore the urgent need for strengthened surveillance and containment measures.

Objective:To observe and analyze the correlation between ectopic foveal inner layer (EIFL) and the EIFL-based idiopathic epiretinal membrane (ERM) staging system and the anatomic and functional prognosis of ERM eyes post pars plana vitrectomy (PPV).Methods:A retrospective study. From January 1, 2020 to October 30, 2023, 345 eyes of 330 patients diagnosed with idiopathic ERM in Department of Ophthalmology of Peking University People's Hospital and treated with standard transciliary flat three-channel 25G PPV combined with ERM and internal limiting membrane exfoliation were included in the study. Among them, 96 were males (111 eyes) and 234 were females (234 eyes). The mean age was (66.8±7.7) years. All study eyes received standard three-port 25G PPV combined with ERM and internal limiting membrane peeling. All study eyes underwent best corrected visual acuity (BCVA) and optical coherence tomography (OCT) examinations. BCVA was performed using a standard logarithmic visual acuity chart and converted to logarithm of the minimum angle of resolution visual acuity for statistical analysis. EIFL thickness and central foveal thickness (CFT) on OCT were measured. ERM eyes were grouped into stage Ⅰ, Ⅱ, Ⅲ and Ⅳ according to ERM staging scheme based on EIFL; disorganization of the retinal inner layers (DRIL) of study eyes were assessed and grouped into no, mild and severe groups. The correlation between ERM staging as well as EIFL thickness and the anatomical and functional prognosis 6 months post-PPV were analyzed.Results:Among 345 study eyes, 12, 87, 174 and 72 eyes were stage Ⅰ-Ⅳ ERM respectively, 63 with no DRIL, 216 with mild DRIL and 66 with severe DRIL. Among the 153 eyes with macular edema, the edema subsided in 66 eyes (43.1%, 66/153) 6 months after the operation. Eighty-seven eyes (56.9%, 87/153) did not regress. The edema subsided 6 months after the operation was not significantly correlated with the ERM stage before the operation ( χ2=3.331, R=?0.145, P=0.304) or the degree of DRIL ( χ2=0.655, R=?0.108, P=0.445). The results of the correlation analysis showed that logMAR BCVA 6 months after the surgery was positively correlated with the degree of DRIL before the surgery ( Tau-b=0.236), ERM stage ( Tau-b=0.194), CFT ( r=0.383), and EIFL thickness ( r=0.317) ( P<0.05). There was no significant correlation with the thickness of the outer nuclear layer before the operation ( r=0.004, P>0.05). Preoperative ERM stage ( Tau-b=0.303, P<0.001) and DRIL severity ( Tau-b= 0.238, P=0.001) were positively correlated with CFT at 6 months after surgery. Conclusion:The ERM stage and EIFL thickness before the operation are positively correlated with logMAR BCVA and CFT 6 months after the operation.

Objective:To evaluate the clinical efficacy of methylation sensitive-high resolution melting curve (MS-HRM) detection of IFN-induced protein 44-like (IFI44L) gene methylation in the diagnosis of systemic lupus erythematosus (SLE), as well as the relationship between IFI44L gene markers and the early onset of SLE.Methods:From February 2020 to September 2022, the MS-HRM was used to detect the methylation level of the IFI44L gene in peripheral blood mononuclear cells of 602 SLE patients and 524 other autoimmune disease patients (excluding SLE) from Beijing Peking Union Medical College Hospital, Guangdong Provincial People′s Hospital, and Shenzhen People′s Hospital, totaling 1 126 patients. Compared with the 2012 SLICC criteria, the suspected cases were followed up for 6 months until the onset and clinical diagnosis of SLE were confirmed. The measurement data of normal distribution were expressed as mean±SD, and the consistency analysis was performed using the Kappa consistency test. The clinical diagnostic efficacy indicators were calculated using the receiver operating characteristic (ROC) curve. Results:RR (95% CI) of early suspected cases was 17.06 (9.43, 30.82). The results of IFI44L gene methylation level were in good agreement with the 2012 SLICC criteria, and the sensitivity, specificity and total coincidence rate were 90.53%, 92.56% and 91.47%, respectively. The Kappa value (95% CI) was 0.829(0.796, 0.862) ( P<0.001). The diagnostic efficiency of IFI44L gene methylation level ( Kappa value 0.817) was superior to anti-nuclear antibody, anti-SM antibody and anti-dsDNA antibody ( Kappa value 0.418, 0.216 and 0.440, respectively). The Kappa values (95% CI) of methylation between MS-HRM and pyrosequencing was 0.861(0.806, 0.916), P<0.001. Conclusion:The hypomethylation of IFI44L gene methylation level detected by MS-HRM is closely related to the occurrence and development of SLE, and its diagnostic performance is better than that of three autoantibodies in SLE diagnosis, which can be used for the early diagnosis of SLE.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.