A new mouse model to explore therapies for preeclampsia

BACKGROUND: Pre-eclampsia, a pregnancy-specific multisystemic disorder is a leading cause of maternal and perinatal mortality and morbidity. This syndrome has been known to medical science since ancient times. However, despite considerable research, the cause/s of preeclampsia remain unclear, and there is no effective treatment. Development of an animal model that recapitulates this complex pregnancy-related disorder may help to expand our understanding and may hold great potential for the design and implementation of effective treatment. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that the CBA/J x DBA/2 mouse model of recurrent miscarriage is also a model of immunologically-mediated preeclampsia (PE). DBA/J mated CBA/J females spontaneously develop many features of human PE (primigravidity, albuminuria, endotheliosis, increased sensitivity to angiotensin II and increased plasma leptin levels) that correlates with bad pregnancy outcomes. We previously reported that antagonism of vascular endothelial growth factor (VEGF) signaling by soluble VEGF receptor 1 (sFlt-1) is involved in placental and fetal injury in CBA/J x DBA/2 mice. Using this animal model that recapitulates many of the features of preeclampsia in women, we found that pravastatin restores angiogenic balance, ameliorates glomerular injury, diminishes hypersensitivity to angiotensin II and protects pregnancies. CONCLUSIONS/SIGNIFICANCE: We described a new mouse model of PE, were the relevant key features of human preeclampsia develop spontaneously. The CBA/J x DBA/2 model, that recapitulates this complex disorder, helped us identify pravastatin as a candidate therapy to prevent preeclampsia and its related complications. We recognize that these studies were conducted in mice and that clinical trials are needed to confirm its application to humans

MO077AUTOMATIC SEGMENTATION OF ARTERIES, ARTERIOLES AND GLOMERULI IN NATIVE BIOPSIES WITH THROMBOTIC MICROANGIOPATHY AND OTHER VASCULAR DISEASES

Abstract Background and Aims Thrombotic microangiopathies (TMAs) manifest themselves in arteries, arterioles and glomeruli. Nephropathologists need to differentiate TMAs from mimickers like hypertensive nephropathy and vasculitis which can be problematic due to interobserver disagreement and poorly defined diagnostic criteria over a wide spectrum of morphological changes with partial overlap. As a first step towards a machine learning analysis of TMAs, we developed a computer vision model for segmenting arteries, arterioles and glomeruli in TMA and mimickers. Method We manually segmented n=939 arteries, n=6,023 arterioles, n=4,507 glomeruli on whole slide images (WSIs) of 34 renal biopsies and their HE, PAS, trichrome and Jones sections (19 TMA, 11 hypertensive nephropathy, 4 vasculitis with preglomerular involvement). As a segmentation model we used DeepLab V3, pretrained on 61,734 segmented glomeruli from 768 WSIs. 58 randomly chosen WSIs served as the intrainstitutional holdout testing set after training of the model on the remaining slides. Automatic segmentation accuracies were reported as Cohen's kappa, intersection over union (IoU) and Matthews correlation coefficient (MCC) against the nephropathologist's segmentation as ground truth. Results Over all classes (artery, arteriole, glomerulus) Cohen's kappa was 0.86. IoU was 0.716 for artery, 0.491 for arteriole and 0.829 for glomerulus. MCC was 0.837 for artery, 0.664 for arteriole and 0.907 for glomerulus. Conclusion We achieved good automatic segmentation of arteries, arterioles and glomeruli, even with severe pathological distortion on routine histopathological slides. We will further improve this segmentation technology in order to enable the bulk analysis of these descisive tissue compartments in large clinicopathological repositories of native kidney biopsies with TMA using supervised and unsupervised machine learning algorithms

The Contribution of Amyloid Deposition in the Aortic Valve to Calcification and Aortic Stenosis

Calcific aortic valve disease (CAVD) and stenosis have a complex pathogenesis, and no therapies are available that can halt or slow their progression. Several studies have shown the presence of apolipoprotein-related amyloid deposits in close proximity to calcified areas in diseased aortic valves. In this Perspective, we explore a possible relationship between amyloid deposits, calcification and the development of aortic valve stenosis. These amyloid deposits might contribute to the amplification of the inflammatory cycle in the aortic valve, including extracellular matrix remodelling and myofibroblast and osteoblast-like cell proliferation. Further investigation in this area is needed to characterize the amyloid deposits associated with CAVD, which could allow the use of antisense oligonucleotides and/or isotype gene therapies for the prevention and/or treatment of CAVD

Segmentation of diagnostic tissue compartments on whole slide images with renal thrombotic microangiopathies (TMAs)

The thrombotic microangiopathies (TMAs) manifest in renal biopsy histology with a broad spectrum of acute and chronic findings. Precise diagnostic criteria for a renal biopsy diagnosis of TMA are missing. As a first step towards a machine learning- and computer vision-based analysis of wholes slide images from renal biopsies, we trained a segmentation model for the decisive diagnostic kidney tissue compartments artery, arteriole, glomerulus on a set of whole slide images from renal biopsies with TMAs and Mimickers (distinct diseases with a similar nephropathological appearance as TMA like severe benign nephrosclerosis, various vasculitides, Bevacizumab-plug glomerulopathy, arteriolar light chain deposition disease). Our segmentation model combines a U-Net-based tissue detection with a Shifted windows-transformer architecture to reach excellent segmentation results for even the most severely altered glomeruli, arterioles and arteries, even on unseen staining domains from a different nephropathology lab. With accurate automatic segmentation of the decisive renal biopsy compartments in human renal vasculopathies, we have laid the foundation for large-scale compartment-specific machine learning and computer vision analysis of renal biopsy repositories with TMAs.Comment: 12 pages, 3 figure

Selective Alpha-Particle Mediated Depletion of Tumor Vasculature with Vascular Normalization

BACKGROUND: Abnormal regulation of angiogenesis in tumors results in the formation of vessels that are necessary for tumor growth, but compromised in structure and function. Abnormal tumor vasculature impairs oxygen and drug delivery and results in radiotherapy and chemotherapy resistance, respectively. Alpha particles are extraordinarily potent, short-ranged radiations with geometry uniquely suitable for selectively killing neovasculature. METHODOLOGY AND PRINCIPAL FINDINGS: Actinium-225 ((225)Ac)-E4G10, an alpha-emitting antibody construct reactive with the unengaged form of vascular endothelial cadherin, is capable of potent, selective killing of tumor neovascular endothelium and late endothelial progenitors in bone-marrow and blood. No specific normal-tissue uptake of E4G10 was seen by imaging or post-mortem biodistribution studies in mice. In a mouse-model of prostatic carcinoma, (225)Ac-E4G10 treatment resulted in inhibition of tumor growth, lower serum prostate specific antigen level and markedly prolonged survival, which was further enhanced by subsequent administration of paclitaxel. Immunohistochemistry revealed lower vessel density and enhanced tumor cell apoptosis in (225)Ac-E4G10 treated tumors. Additionally, the residual tumor vasculature appeared normalized as evident by enhanced pericyte coverage following (225)Ac-E4G10 therapy. However, no toxicity was observed in vascularized normal organs following (225)Ac-E4G10 therapy. CONCLUSIONS: The data suggest that alpha-particle immunotherapy to neovasculature, alone or in combination with sequential chemotherapy, is an effective approach to cancer therapy

The classification of glomerulonephritis in systemic lupus erythematosus revisited

The classification of glomerulonephritis in systemic lupus erythematosus revisited.The currently used classification reflects our understanding of the pathogenesis of the various forms of lupus nephritis, but clinicopathologic studies have revealed the need for improved categorization and terminology. Based on the 1982 classification published under the auspices of the World Health Organization (WHO) and subsequent clinicopathologic data, we propose that class I and II be used for purely mesangial involvement (I, mesangial immune deposits without mesangial hypercellularity; II, mesangial immune deposits with mesangial hypercellularity); class III for focal glomerulonephritis (involvin

Minimal Change Disease as a Secondary and Reversible Event of a Renal Transplant Case with Systemic Lupus Erythematosus

Secondary causes of minimal change disease (MCD) account for a minority of cases compared to its primary or idiopathic form and provide ground for consideration of common mechanisms of pathogenesis. In this paper we report a case of a 27-year-old Latina woman, a renal transplant recipient with systemic lupus erythematosus (SLE), who developed nephrotic range proteinuria 6 months after transplantation. The patient had recurrent acute renal failure and multiple biopsies were consistent with MCD. However, she lacked any other features of the typical nephrotic syndrome. An angiogram revealed a right external iliac vein stenosis in the region of renal vein anastomosis, which when restored resulted in normalization of creatinine and relief from proteinuria. We report a rare case of MCD developing secondary to iliac vein stenosis in a renal transplant recipient with SLE. Additionally we suggest that, in the event of biopsy-proven MCD presenting as an atypical nephrotic syndrome, alternative or secondary, potentially reversible, causes should be considered and explored