Within and beyond immunomodulatory strategies against autoimmune diabetes : antigen-specific tolerance and endothelial regeneration

Type 1 diabetes (T1D) is a chronic disorder in which the cells of the immune system mediate selective destruction of the insulin-producing [beta]-cells in the islets of Langerhans in the pancreas. CD4+ effector T cells, including Th1 and Th17 cells, are crucial mediators during disease development. Therefore, therapeutic strategies against T1D should target both T cell subtypes. The mechanisms underlying the control of Th1 cells are well-defined, but those operating modulation of Th17 cells remain largely unknown due to the fact that Th17 cells are plastic and can drive the disease as convertible (Th17 to Th1) or stable T cells. To overcome these limitations, a tolerance induction model was developed to analyze the mechanisms underlying modulation of plastic Th17 cells. Indeed, upon induction of tolerance, convertible (Th17 to Th1) cells displayed downregulation of the chemokine receptor CXCR3 that was associated with diminished T-bet expression, leading to retention of the cells in the spleen and inhibition of trafficking to the pancreas. In contrast, stable Th17 cells downregulated RORγt but increased FasL expression and died by apoptosis under the same antigen-specific tolerance. Thus, the final signature transcription factor shapes the mechanism of tolerance in plastic Th17 cells. These findings suggest that effective strategies against T1D will require regimens that could drive both mechanisms of tolerance to overcome the disease. A core feature of autoimmune diabetes is the loss of the majority of insulin-producing [beta] cells. Therefore, reversal of overt T1D requires restoration of [beta]-cell mass in addition to effective control of islet inflammation. It has been established that [beta]-cell turnover relies on self-replication of pre-existing [beta]-cells; however, the diabetic state is tightly associated with a striking decrease of the islet endothelial cells, leading to poor [beta]-cell survival and function. Given that the endothelial progenitor cells (EPCs) reside in the bone marrow and th

Single-cell RNA sequencing of murine islets shows high cellular complexity at all stages of autoimmune diabetes

Tissue-specific autoimmune diseases are driven by activation of diverse immune cells in the target organs. However, the molecular signatures of immune cell populations over time in an autoimmune process remain poorly defined. Using single-cell RNA sequencing, we performed an unbiased examination of diverse islet-infiltrating cells during autoimmune diabetes in the nonobese diabetic mouse. The data revealed a landscape of transcriptional heterogeneity across the lymphoid and myeloid compartments. Memory CD4 and cytotoxic CD8 T cells appeared early in islets, accompanied by regulatory cells with distinct phenotypes. Surprisingly, we observed a dramatic remodeling in the islet microenvironment, in which the resident macrophages underwent a stepwise activation program. This process resulted in polarization of the macrophage subpopulations into a terminal proinflammatory state. This study provides a single-cell atlas defining the staging of autoimmune diabetes and reveals that diabetic autoimmunity is driven by transcriptionally distinct cell populations specialized in divergent biological functions

Reversal of severe autoimmune diabetes at the stem cell level by bone marrow-derived endothelial progenitors

This poster presents the process for treating severe autoimmune diabetes in mice through the use of bone marrow-derived endothelial cells

Pancreatic islets communicate with lymphoid tissues via exocytosis of insulin peptides.

Tissue-specific autoimmunity occurs when selected antigens presented by susceptible alleles of the major histocompatibility complex are recognized by T cells. However, the reason why certain specific self-antigens dominate the response and are indispensable for triggering autoreactivity is unclear. Spontaneous presentation of insulin is essential for initiating autoimmune type 1 diabetes in non-obese diabetic mice1,2. A major set of pathogenic CD4 T cells specifically recognizes the 12-20 segment of the insulin B-chain (B:12-20), an epitope that is generated from direct presentation of insulin peptides by antigen-presenting cells3,4. These T cells do not respond to antigen-presenting cells that have taken up insulin that, after processing, leads to presentation of a different segment representing a one-residue shift, B:13-214. CD4 T cells that recognize B:12-20 escape negative selection in the thymus and cause diabetes, whereas those that recognize B:13-21 have only a minor role in autoimmunity3-5. Although presentation of B:12-20 is evident in the islets3,6, insulin-specific germinal centres can be formed in various lymphoid tissues, suggesting that insulin presentation is widespread7,8. Here we use live imaging to document the distribution of insulin recognition by CD4 T cells throughout various lymph nodes. Furthermore, we identify catabolized insulin peptide fragments containing defined pathogenic epitopes in β-cell granules from mice and humans. Upon glucose challenge, these fragments are released into the circulation and are recognized by CD4 T cells, leading to an activation state that results in transcriptional reprogramming and enhanced diabetogenicity. Therefore, a tissue such as pancreatic islets, by releasing catabolized products, imposes a constant threat to self-tolerance. These findings reveal a self-recognition pathway underlying a primary autoantigen and provide a foundation for assessing antigenic targets that precipitate pathogenic outcomes by systemically sensitizing lymphoid tissues

Finite-time synchronization of Markovian neural networks with proportional delays and discontinuous activations

In this paper, finite-time synchronization of neural networks (NNs) with discontinuous activation functions (DAFs), Markovian switching, and proportional delays is studied in the framework of Filippov solution. Since proportional delay is unbounded and different from infinite-time distributed delay and classical finite-time analytical techniques are not applicable anymore, new 1-norm analytical techniques are developed. Controllers with and without the sign function are designed to overcome the effects of the uncertainties induced by Filippov solutions and further synchronize the considered NNs in a finite time. By designing new Lyapunov functionals and using M-matrix method, sufficient conditions are derived to guarantee that the considered NNs realize synchronization in a settling time without introducing any free parameters. It is shown that, though the proportional delay can be unbounded, complete synchronization can still be realized, and the settling time can be explicitly estimated. Moreover, it is discovered that controllers with sign function can reduce the control gains, while controllers without the sign function can overcome chattering phenomenon. Finally, numerical simulations are given to show the effectiveness of theoretical results

Blood leukocytes recapitulate diabetogenic peptide-MHC-II complexes displayed in the pancreatic islets

Assessing the self-peptides presented by susceptible major histocompatibility complex (MHC) molecules is crucial for evaluating the pathogenesis and therapeutics of tissue-specific autoimmune diseases. However, direct examination of such MHC-bound peptides displayed in the target organ remains largely impractical. Here, we demonstrate that the blood leukocytes from the nonobese diabetic (NOD) mice presented peptide epitopes to autoreactive CD4 T cells. These peptides were bound to the autoimmune class II MHC molecule (MHC-II) I-Ag7 and originated from insulin B-chain and C-peptide. The presentation required a glucose challenge, which stimulated the release of the insulin peptides from the pancreatic islets. The circulating leukocytes, especially the B cells, promptly captured and presented these peptides. Mass spectrometry analysis of the leukocyte MHC-II peptidome revealed a series of β cell-derived peptides, with identical sequences to those previously identified in the islet MHC-II peptidome. Thus, the blood leukocyte peptidome echoes that found in islets and serves to identify immunogenic peptides in an otherwise inaccessible tissue

Class-switched anti-insulin antibodies originate from unconventional antigen presentation in multiple lymphoid sites

Autoantibodies to insulin are a harbinger of autoimmunity in type 1 diabetes in humans and in non-obese diabetic mice. To understand the genesis of these autoantibodies, we investigated the interactions of insulin-specific T and B lymphocytes using T cell and B cell receptor transgenic mice. We found spontaneous anti-insulin germinal center (GC) formation throughout lymphoid tissues with GC B cells binding insulin. Moreover, because of the nature of the insulin epitope recognized by the T cells, it was evident that GC B cells presented a broader repertoire of insulin epitopes. Such broader recognition was reproduced by activating naive B cells ex vivo with a combination of CD40 ligand and interleukin 4. Thus, insulin immunoreactivity extends beyond the pancreatic lymph node–islets of Langerhans axis and indicates that circulating insulin, despite its very low levels, can have an influence on diabetogenesis

Antimicrobial photodynamic inactivation as an alternative approach to inhibit the growth of Cronobacter sakazakii by fine-tuning the activity of CpxRA two-component system

Cronobacter sakazakii is an opportunistic foodborne pathogen primarily found in powdered infant formula (PIF). To date, it remains challenging to control the growth of this ubiquitous bacterium. Herein, antimicrobial photodynamic inactivation (aPDI) was first employed to inactivate C. sakazakii. Through 460 nm light irradiation coupled with hypocrellin B, the survival rate of C. sakazakii was diminished by 3~4 log. The photokilling effect was mediated by the attenuated membrane integrity, as evidenced by PI staining. Besides, scanning electron microscopy showed the deformed and aggregated cell cluster, and intracellular ROS was augmented by 2~3 folds when light doses increase. In addition to planktonic cells, the biofilm formation of C. sakazakii was also affected, showing an OD590nm decline from 0.85 to 0.25. In terms of molecular aspects, a two-component system called CpxRA, along with their target genes, was deregulated during illumination. Using the knock-out strain of ΔCpxA, the bacterial viability was reduced by 2 log under aPDI, a wider gap than the wildtype strain. Based on the promoted expression of CpxR and OmpC, aPDI is likely to play its part through attenuating the function of CpxRA-OmpC pathway. Finally, the aPDI system was applied to PIF, and C. sakazakii was inactivated under various desiccated or heated storage conditions. Collectively, aPDI serves as an alternative approach to decontaminate C. sakazakii, providing a new strategy to reduce the health risks caused by this prevalent foodborne pathogen

Application and development of Deuterium Metabolic Imaging in tumor glucose metabolism: visualization of different metabolic pathways

Cancer metabolism has emerged as a pivotal area of research recently. The ability to visualize and comprehend the metabolic processes of cancer holds immense clinical value, particularly in the diagnosis of malignant tumors and the assessment of treatment responses. Deuterium Metabolic Imaging (DMI), as a robust, simple, and versatile MR spectroscopic imaging tool, demonstrates promise in tumor diagnosis and treatment efficacy assessment. This review explored the latest developments and applications of DMI in oncology across various tumor metabolic axes, with a specific emphasis on its potential for clinical translation. DMI offers invaluable insights into tumor biology, treatment responses, and prognostic outcomes. Notably, DMI can identify early responses to immunotherapy, a prominent area of current research interest. In conclusion, DMI harbors the potential to evolve into a convenient and efficient imaging technique in clinical practice, thereby advancing precision medicine and improving the diagnosis and evaluation of cancer treatments