Overexpression of thioredoxin in islets transduced by a lentiviral vector prolongs graft survival in autoimmune diabetic NOD mice

<p>Abstract</p> <p>Pancreatic islet transplantation is considered an appropriate treatment to achieve insulin independence in type I diabetic patients. However, islet isolation and transplantation-induced oxidative stress and autoimmune-mediated destruction are still the major obstacles to the long-term survival of graft islets in this potential therapy. To protect islet grafts from inflammatory damage and prolong their survival, we transduced islets with an antioxidative gene <it>thioredoxin (TRX) </it>using a lentiviral vector before transplantation. We hypothesized that the overexpression of TRX in islets would prolong islet graft survival when transplanted into diabetic non-obese diabetic (NOD) mice.</p> <p>Methods</p> <p>Islets were isolated from NOD mice and transduced with lentivirus carrying <it>TRX </it>(Lt-<it>TRX</it>) or enhanced green fluorescence protein (Lt-e<it>GFP</it>), respectively. Transduced islets were transplanted under the left kidney capsule of female diabetic NOD mice, and blood glucose concentration was monitored daily after transplantation. The histology of the islet graft was assessed at the end of the study. The protective effect of TRX on islets was investigated.</p> <p>Results</p> <p>The lentiviral vector effectively transduced islets without altering the glucose-stimulating insulin-secretory function of islets. Overexpression of TRX in islets reduced hydrogen peroxide-induced cytotoxicity <it>in vitro</it>. After transplantation into diabetic NOD mice, euglycemia was maintained for significantly longer in Lt-TRX-transduced islets than in Lt-eGFP-transduced islets; the mean graft survival was 18 vs. 6.5 days (n = 9 and 10, respectively, p < 0.05).</p> <p>Conclusion</p> <p>We successfully transduced the <it>TRX </it>gene into islets and demonstrated that these genetically modified grafts are resistant to inflammatory insult and survived longer in diabetic recipients. Our results further support the concept that the reactive oxygen species (ROS) scavenger and antiapoptotic functions of TRX are critical to islet survival after transplantation.</p

Understanding the Influence of Receptive Field and Network Complexity in Neural-Network-Guided TEM Image Analysis

Trained neural networks are promising tools to analyze the ever-increasing amount of scientific image data, but it is unclear how to best customize these networks for the unique features in transmission electron micrographs. Here, we systematically examine how neural network architecture choices affect how neural networks segment, or pixel-wise separate, crystalline nanoparticles from amorphous background in transmission electron microscopy (TEM) images. We focus on decoupling the influence of receptive field, or the area of the input image that contributes to the output decision, from network complexity, which dictates the number of trainable parameters. We find that for low-resolution TEM images which rely on amplitude contrast to distinguish nanoparticles from background, the receptive field does not significantly influence segmentation performance. On the other hand, for high-resolution TEM images which rely on a combination of amplitude and phase contrast changes to identify nanoparticles, receptive field is a key parameter for increased performance, especially in images with minimal amplitude contrast. Our results provide insight and guidance as to how to adapt neural networks for applications with TEM datasets.Comment: 11 pages, 8 figure

Immunologic Regulation in Pregnancy: From Mechanism to Therapeutic Strategy for Immunomodulation

The immunologic interaction between the fetus and the mother is a paradoxical communication that is regulated by fetal antigen presentation and/or by recognition of and reaction to these antigens by the maternal immune system. There have been significant advances in understanding of abnormalities in the maternal-fetal immunologic relationship in the placental bed that can lead to pregnancy disorders. Moreover, immunologic recognition of pregnancy is vital for the maintenance of gestation, and inadequate recognition of fetal antigens may cause abortion. In this paper, we illustrate the complex immunologic aspects of human reproduction in terms of the role of human leukocyte antigen (HLA), immune cells, cytokines and chemokines, and the balance of immunity in pregnancy. In addition, we review the immunologic processes of human reproduction and the current immunologic therapeutic strategies for pathological disorders of pregnancy

A robust synthetic data generation framework for machine learning in high-resolution transmission electron microscopy (HRTEM)

Machine learning techniques are attractive options for developing highly-accurate analysis tools for nanomaterials characterization, including high-resolution transmission electron microscopy (HRTEM). However, successfully implementing such machine learning tools can be difficult due to the challenges in procuring sufficiently large, high-quality training datasets from experiments. In this work, we introduce Construction Zone, a Python package for rapid generation of complex nanoscale atomic structures which enables fast, systematic sampling of realistic nanomaterial structures and can be used as a random structure generator for large, diverse synthetic datasets. Using Construction Zone, we develop an end-to-end machine learning workflow for training neural network models to analyze experimental atomic resolution HRTEM images on the task of nanoparticle image segmentation purely with simulated databases. Further, we study the data curation process to understand how various aspects of the curated simulated data—including simulation fidelity, the distribution of atomic structures, and the distribution of imaging conditions—affect model performance across three benchmark experimental HRTEM image datasets. Using our workflow, we are able to achieve state-of-the-art segmentation performance on these experimental benchmarks and, further, we discuss robust strategies for consistently achieving high performance with machine learning in experimental settings using purely synthetic data. Construction Zone and its documentation are available at https://github.com/lerandc/construction_zone

Genetically Engineered Islets and Alternative Sources of Insulin-Producing Cells for Treating Autoimmune Diabetes: Quo Vadis?

Islet transplantation is a promising therapy for patients with type 1 diabetes that can provide moment-to-moment metabolic control of glucose and allow them to achieve insulin independence. However, two major problems need to be overcome: (1) detrimental immune responses, including inflammation induced by the islet isolation/transplantation procedure, recurrence autoimmunity, and allorejection, can cause graft loss and (2) inadequate numbers of organ donors. Several gene therapy approaches and pharmaceutical treatments have been demonstrated to prolong the survival of pancreatic islet grafts in animal models; however, the clinical applications need to be investigated further. In addition, for an alternative source of pancreatic β-cell replacement therapy, the ex vivo generation of insulin-secreting cells from diverse origins of stem/progenitor cells has become an attractive option in regenerative medicine. This paper focuses on the genetic manipulation of islets during transplantation therapy and summarizes current strategies to obtain functional insulin-secreting cells from stem/progenitor cells

Role of T Cells in Type 2 Diabetic Nephropathy

Type 2 diabetic nephropathy (DN) is the most common cause of end-stage renal disease and is increasingly considered as an inflammatory disease characterized by leukocyte infiltration at every stage of renal involvement. Inflammation and activation of the immune system are closely involved in the pathogenesis of diabetes and its microvascular complications. Macrophage has been well recognized to play an important role in type 2 DN, leukocyte infiltration, and participated in process of DN, as was proposed recently. Th1, Th2, Th17, T reg, and cytotoxic T cells are involved in the development and progression of DN. The purpose of this review is to assemble current information concerning the role of T cells in the development and progression of type 2 DN. Specific emphasis is placed on the potential interaction and contribution of the T cells to renal damage. The therapeutic strategies involving T cells in the treatment of type 2 DN are also reviewed. Improving knowledge of the recognition of T cells as significant pathogenic mediators in DN reinforces the possibility of new potential therapeutic targets translated into future clinical treatments