Background-Cell-based therapies to augment endothelial cells (ECs) hold great therapeutic promise. Here, we report a novel approach to generate functional ECs directly from adult fibroblasts. Methods and Results-Eleven candidate genes that are key regulators of endothelial development were selected. Green fluorescent protein (GFP)-negative skin fibroblasts were prepared from Tie2-GFP mice and infected with lentiviruses allowing simultaneous overexpression of all 11 factors. Tie2-GFP + cells (0.9%), representing Tie2 gene activation, were detected by flow cytometry. Serial stepwise screening revealed 5 key factors (Foxo1, Er71, Klf2, Tal1, and Lmo2) that were required for efficient reprogramming of skin fibroblasts into Tie2-GFP + cells (4%). This reprogramming strategy did not involve pluripotency induction because neither Oct4 nor Nanog was expressed after 5 key factor transduction. Tie2-GFP + cells were isolated using fluorescence-activated cell sorting and designated as induced ECs (iECs). iECs exhibited endothelium-like cobblestone morphology and expressed EC molecular markers. iECs possessed endothelial functions such as Bandeiraea simplicifolia-1 lectin binding, acetylated low-density lipoprotein uptake, capillary formation on Matrigel, and nitric oxide production. The epigenetic profile of iECs was similar to that of authentic ECs because the promoters of VE-cadherin and Tie2 genes were demethylated. mRNA profiling showed clustering of iECs with authentic ECs and highly enriched endothelial genes in iECs. In a murine model of hind-limb ischemia, iEC implantation increased capillary density and enhanced limb perfusion, demonstrating the in vivo viability and functionality of iECs. Conclusions-We

The inhibitors of CD26 (dipeptidyl peptidase-4; DPP4) have been widely prescribed to control glucose level in diabetic patients. DPP4-inhibitors, however, accumulate stromal cell-derived factor-1α (SDF-1α), a well-known inducer of vascular leakage and angiogenesis both of which are fundamental pathophysiology of diabetic retinopathy. The aim of this study was to investigate the effects of DPP4-inhibitors on vascular permeability and diabetic retinopathy. DPP4-inhibitor (diprotin A or sitagliptin) increased the phosphorylation of Src and vascular endothelial-cadherin (VE-cadherin) in human endothelial cells and disrupted endothelial cell-to-cell junctions, which were attenuated by CXCR4 (receptor of SDF-1α)-blocker or Src-inhibitor. Disruption of endothelial cell-to-cell junctions in the immuno-fluorescence images correlated with the actual leakage of the endothelial monolayer in the transwell endothelial permeability assay. In the Miles assay, vascular leakage was observed in the ears into which SDF-1α was injected, and this effect was aggravated by DPP4-inhibitor. In the model of retinopathy of prematurity, DPP4-inhibitor increased not only retinal vascularity but also leakage. Additionally, in the murine diabetic retinopathy model, DPP4-inhibitor increased the phosphorylation of Src and VE-cadherin and aggravated vascular leakage in the retinas. Collectively, DPP4-inhibitor induced vascular leakage by augmenting the SDF-1α/CXCR4/Src/VE-cadherin signaling pathway. These data highlight safety issues associated with the use of DPP4-inhibitors.

Numerical simulation of flow and transport in heterogeneous formations has long been studied, especially for uncertainty quantification and risk assessment. The high computational cost associated with running large‐scale numerical simulations in a Monte Carlo sense has motivated the development of surrogate models, which aim to capture the important input‐output relations of physics‐based models but require only a fraction of the cost of full model runs. In this work, we formulate a conditional deep convolutional generative adversarial network (cDC‐GAN) surrogate model to learn the dynamic functional mappings in multiphase models. The cDC‐GAN belongs to a class of semisupervised learning methods that can be used to learn the data generation processes. Like the original GAN, a main strength of the cDC‐GAN is that it includes a self‐training scheme for improving the quality of generative modeling in a game theoretic framework, without requiring extensive statistical knowledge and assumptions on input data distributions. In particular, our cDC‐GAN model is designed to learn cross‐domain mappings between high‐dimensional input (e.g., permeability) and output (e.g., phase saturations) pairs, with the ability to incorporate conditioning information (e.g., prediction time). As a use case, we demonstrate the performance of cDC‐GAN for predicting the migration of carbon dioxide (CO2) plume in heterogeneous carbon storage reservoirs, which has both numerical and practical significance because of the safe storage requirements now mandated in many countries. Results show that cDC‐GAN achieves high accuracy in predicting the spatial and temporal evolution patterns of the injected CO2 plume, as compared to the original results obtained using a compositional reservoir simulator. The performance of cDC‐GAN models, trained using the same number of training samples, stays relatively robust when the level of spatial heterogeneity is increased. Our cDC‐GAN is pattern based and is not limited by the underlying physics. Thus, it provides a general framework for developing surrogate models, and for conducting uncertainty analyses for a wide range of physics‐based models used in both groundwater and subsurface energy exploration applications.

We present the design, fabrication, and measurement results of an electromagnetic biaxial microscanner with mechanical amplification mechanism. A gimbaled scanner with two distinct single-crystal silicon layer thicknesses and integrated copper coils has been fabricated with combination of surface and bulk micromachining processes. A magnet assembly consisting of an array of permanent magnets and a pole piece has been placed under the substrate to provide high strength lateral magnetic field oriented 45° to two perpendicular scanning axes. Micromirror has been supported by additional gimbal to implement a mechanical amplification. A 1.2mm-diameter mirror with aluminum reflective surface has been actuated at 60Hz for vertical scan and at 21kHz for horizontal scan. Maximum scan angle of 36.12° at 21.19kHz and 17.62° at 60Hz have been obtained for horizontal and vertical scans, respectively.