The understanding of the regulation of glucagon secretion by pancreatic islet α-cells remains elusive. We aimed to develop an in vitro model for investigating the function of human α-cells under direct influence of glucose and other potential regulators. Highly purified human α-cells from islets of deceased donors were re-aggregated in the presence or absence of β-cells in culture, evaluated for glucagon secretion under various treatment conditions, and compared to that of intact human islets and non-sorted islet cell aggregates. The pure human α-cell aggregates maintained proper glucagon secretion capability at low concentrations of glucose, but failed to respond to changes in ambient glucose concentration. Addition of purified β-cells, but not the secreted factors from β-cells at low or high concentrations of glucose, partly restored the responsiveness of α-cells to glucose with regulated glucagon secretion. The EphA stimulator ephrinA5-fc failed to mimic the inhibitory effect of β-cells on glucagon secretion. Glibenclamide inhibited glucagon secretion from islets and the α- and β-mixed cell-aggregates, but not from the α-cell-only aggregates, at 2.0 mM glucose. This study validated the use of isolated and then re-aggregated human islet cells for investigating α-cell function and paracrine regulation, and demonstrated the importance of cell-to-cell contact between α- and β-cells on glucagon secretion. Loss of proper β- and α-cell physical interaction in islets likely contributes to the dysregulated glucagon secretion in diabetic patients. Re-aggregated select combinations of human islet cells provide unique platforms for studying islet cell function and regulation.

Background: Diabetes is a multi-factorial disorder and related complications constitute one of the principal causes of global mortality and disability. The role of ferroptosis in diabetes and its complications is intricate and significant. This study endeavors to disclose the role of ferroptosis in the aforementioned diseases from multiple perspectives through multi-omics. Methods: We performed genetic correlation analyses via the Linkage Disequilibrium Score and High-Definition Likelihood approaches for type 2 diabetes (T2D) and its complications. The data concerning the expression of ferroptosis-related genes (FRGs) were obtained from the meta-analysis of studies on gene expression and protein abundance. Mendelian randomization analyses and cross-validation were implemented using the discovery cohort, replication cohort, and imaging genomics cohort of T2D and its complications. Moreover, we conducted colocalization analyses on T2D and tissue-specific single-cell RNA sequencing investigations on the complications to complement the results. Results: Genetic association analysis indicated that the selected datasets could be incorporated into a secondary analysis of T2D complications. In the primary analysis, six FRGs (CDKN1A, ENO3, FURIN, RARRES2, TYRO3, and YTHDC2) were found to be positively associated with T2D risk. Conversely, eight FRGs (ARNTL, CAMKK2, CTSB, FADS2, KDM5A, MEG3, SREBF1, and STAT3) were inversely associated with T2D risk. The 14 FRGs were included in the secondary analysis. Within the FRGs, which received full support from both the discovery and replication cohorts, and were further validated by imaging genomics, higher levels of CDKN1A were positively associated with DKD risk. Higher levels of CAMKK2 and KDM5A were associated with a decreased risk of DKD. For DCM, higher levels of CTSB were positively associated with DCM risk. And genetically predicted higher levels of ARNTL and SREBF1 were associated with a decreased risk of NAFLD. Finally, we validated the tissue-specific expression of each complication with scRNA-seq datasets. Conclusions: This study identified FRGs in relation to T2D and its complications, which may enhance the understanding of the pathogenic mechanisms of their development. Meanwhile, it offers cross-validation for imaging genomics and further indicates the direction for non-invasive diagnosis. Graphical

Introduction: We aimed to investigate the relationship between nuclear factor erythroid 2-related factor 2 (Nrf2) protein expression levels, lupus nephritis (LN) disease activity, and the degree of renal injury (based on the estimated glomerular filtration rate [eGFR]) in patients with LN.Methods: We selected 40 healthy control participants and 102 patients with LN who were treated in the Second Hospital of Jilin University, China, for inclusion in this study. Patients with LN were classified into LN with high-eGFR and LN with low-eGFR groups. Nrf2 protein levels were measured in the serum and renal tissues of the participants in both groups to assess the correlation between Nrf2 protein levels and different LN disease states.Results: There was a significantly positive correlation between serum Nrf2 protein levels, the degree of renal injury, and systemic lupus erythematosus disease activity index (SLEDAI) scores in patients with LN. Nrf2 protein levels were higher in the LN with high-eGFR group than in the healthy control and LN with low-eGFR groups. In follow-up patients in the LN high eGFR group, Nrf2 protein levels decreased significantly after remission of disease activity.Conclusion: Nrf2 protein expression has a dual role in patients with LN. Nrf2 protein levels not only correlate with disease activity in patients with LN, but also with the degree of kidney injury. Before implementing targeted therapy for Nrf2, evaluating both Nrf2 protein expression and the disease state in patients with LN is necessary to better identify and place each patient in an appropriate patient group.

This study evaluates the association between intrinsic capacity domains and incident cardiovascular disease across three nationally representative aging cohorts from the United States, the United Kingdom, and China. Harmonized data from HRS, ELSA, and CHARLS were analyzed using multivariable cause-specific Cox models with time-varying covariates where available. Among intrinsic capacity domains, muscle function showed the most consistent inverse association with cardiovascular risk across cohorts. Higher levels of systemic inflammatory and metabolic burden, including elevated C-reactive protein, diabetes, and non-HDL cholesterol, were associated with higher risk and with attenuation of the modeled muscle–cardiovascular association, with the strongest modification observed in CHARLS. A three-dimensional Metabolism–Inflammation–Muscle surface was used to visualize this interaction structure. These findings support muscle function as a cross-cohort marker of lower cardiovascular risk while highlighting its context-dependent magnitude under systemic stress. The proposed surface is descriptive and requires external validation before clinical application.