JDP2 overexpression provokes cardiac dysfunction in mice

The transcriptional regulator JDP2 (Jun dimerization protein 2) has been identified as a prognostic marker for patients to develop heart failure after myocardial infarction. We now performed in vivo studies on JDP2-overexpressing mice, to clarify the impact of JDP2 on heart failure progression. Therefore, during birth up to the age of 4 weeks cardiac-specific JDP2 overexpression was prevented by doxycycline feeding in transgenic mice. Then, JDP2 overexpression was started. Already after 1 week, cardiac function, determined by echocardiography, decreased which was also resembled on the cardiomyocyte level. After 5 weeks blood pressure declined, ejection fraction and cardiac output was reduced and left ventricular dilatation developed. Heart weight/body weight, and mRNA expression of ANP, inflammatory marker genes, collagen and fibronectin increased. Collagen 1 protein expression increased, and fibrosis developed. As an additional sign of elevated extracellular matrix remodeling, matrix metalloproteinase 2 activity increased in JDP2 mice. Thus, JDP2 overexpression is deleterious to heart function in vivo. It can be concluded that JDP2 overexpression provokes cardiac dysfunction in adult mice that is accompanied by hypertrophy and fibrosis. Thus, induction of JDP2 is a maladaptive response contributing to heart failure development

Basin-scale transport of hydrothermal dissolved metals across the South Pacific Ocean

Hydrothermal venting along mid-ocean ridges exerts an important control on the chemical composition of sea water by serving as a major source or sink for a number of trace elements in the ocean(1-3). Of these, iron has received considerable attention because of its role as an essential and often limiting nutrient for primary production in regions of the ocean that are of critical importance for the global carbon cycle(4). It has been thought that most of the dissolved iron discharged by hydrothermal vents is lost from solution close to ridge-axis sources(2,5) and is thus of limited importance for ocean biogeochemistry(6). This long-standing view is challenged by recent studies which suggest that stabilization of hydrothermal dissolved iron may facilitate its longrange oceanic transport(7-10). Such transport has been subsequently inferred from spatially limited oceanographic observations(11-13). Here we report data from the US GEOTRACES Eastern Pacific Zonal Transect (EPZT) that demonstrate lateral transport of hydrothermal dissolved iron, manganese, and aluminium from the southern East Pacific Rise (SEPR) several thousand kilometres westward across the South Pacific Ocean. Dissolved iron exhibits nearly conservative (that is, no loss from solution during transport and mixing) behaviour in this hydrothermal plume, implying a greater longevity in the deep ocean than previously assumed(6,14). Based on our observations, we estimate a global hydrothermal dissolved iron input of three to four gigamoles per year to the ocean interior, which is more than fourfold higher than previous estimates(7,11,14). Complementary simulations with a global-scale ocean biogeochemical model suggest that the observed transport of hydrothermal dissolved iron requires some means of physicochemical stabilization and indicate that hydrothermally derived iron sustains a large fraction of Southern Ocean export productio

In situ guided tissue regeneration in musculoskeletal diseases and aging: Implementing pathology into tailored tissue engineering strategies

In situ guided tissue regeneration, also addressed as in situ tissue engineering or endogenous regeneration, has a great potential for population-wide “minimal invasive” applications. During the last two decades, tissue engineering has been developed with remarkable in vitro and preclinical success but still the number of applications in clinical routine is extremely small. Moreover, the vision of population-wide applications of ex vivo tissue engineered constructs based on cells, growth and differentiation factors and scaffolds, must probably be deemed unrealistic for economic and regulation-related issues. Hence, the progress made in this respect will be mostly applicable to a fraction of post-traumatic or post-surgery situations such as big tissue defects due to tumor manifestation. Minimally invasive procedures would probably qualify for a broader application and ideally would only require off the shelf standardized products without cells. Such products should mimic the microenvironment of regenerating tissues and make use of the endogenous tissue regeneration capacities. Functionally, the chemotaxis of regenerative cells, their amplification as a transient amplifying pool and their concerted differentiation and remodeling should be addressed. This is especially important because the main target populations for such applications are the elderly and diseased. The quality of regenerative cells is impaired in such organisms and high levels of inhibitors also interfere with regeneration and healing. In metabolic bone diseases like osteoporosis, it is already known that antagonists for inhibitors such as activin and sclerostin enhance bone formation. Implementing such strategies into applications for in situ guided tissue regeneration should greatly enhance the efficacy of tailored procedures in the future

Deep learning-based segmentation and quantification in experimental kidney histopathology

Background Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiased, reproducible, and efficient histopathologic analyses, which will require novel high-throughput tools. A deep learning technique, the convolutional neural network, is increasingly applied in pathology because of its high performance in tasks like histology segmentation. Methods We investigated use of a convolutional neural network architecture for accurate segmentation of periodic acid-Schiff-stained kidney tissue from healthy mice and five murine disease models and from other species used in preclinical research. We trained the convolutional neural network to segment six major renal structures: glomerular tuft, glomerulus including Bowman’s capsule, tubules, arteries, arterial lumina, and veins. To achieve high accuracy, we performed a large number of expert-based annotations, 72,722 in total. Results Multiclass segmentation performance was very high in all disease models. The convolutional neural network allowed high-throughput and large-scale, quantitative and comparative analyses of various models. In disease models, computational feature extraction revealed interstitial expansion, tubular dilation and atrophy, and glomerular size variability. Validation showed a high correlation of findings with current standard morphometric analysis. The convolutional neural network also showed high performance in other species used in research—including rats, pigs, bears, and marmosets—as well as in humans, providing a translational bridge between preclinical and clinical studies. Conclusions We developed a deep learning algorithm for accurate multiclass segmentation of digital whole-slide images of periodic acid-Schiff-stained kidneys from various species and renal disease models. This enables reproducible quantitative histopathologic analyses in preclinical models that also might be applicable to clinical studies

Next-Generation Morphometry for pathomics-data mining in histopathology

Pathology diagnostics relies on the assessment of morphology by trained experts, which remains subjective and qualitative. Here we developed a framework for large-scale histomorphometry (FLASH) performing deep learning-based semantic segmentation and subsequent large-scale extraction of interpretable, quantitative, morphometric features in non-tumour kidney histology. We use two internal and three external, multi-centre cohorts to analyse over 1000 kidney biopsies and nephrectomies. By associating morphometric features with clinical parameters, we confirm previous concepts and reveal unexpected relations. We show that the extracted features are independent predictors of long-term clinical outcomes in IgA-nephropathy. We introduce single-structure morphometric analysis by applying techniques from single-cell transcriptomics, identifying distinct glomerular populations and morphometric phenotypes along a trajectory of disease progression. Our study provides a concept for Next-generation Morphometry (NGM), enabling comprehensive quantitative pathology data mining, i.e., pathomics

Pro-cachectic factors link experimental and human chronic kidney disease to skeletal muscle wasting programs

Skeletal muscle wasting is commonly associated with chronic kidney disease (CKD), resulting in increased morbidity and mortality. However, the link between kidney and muscle function remains poorly understood. Here, we took a complementary interorgan approach to investigate skeletal muscle wasting in CKD. We identified increased production and elevated blood levels of soluble pro-cachectic factors, including activin A, directly linking experimental and human CKD to skeletal muscle wasting programs. Single-cell sequencing data identified the expression of activin A in specific kidney cell populations of fibroblasts and cells of the juxtaglomerular apparatus. We propose that persistent and increased kidney production of pro-cachectic factors, combined with a lack of kidney clearance, facilitates a vicious kidney/muscle signaling cycle, leading to exacerbated blood accumulation and, thereby, skeletal muscle wasting. Systemic pharmacological blockade of activin A using soluble activin receptor type IIB ligand trap as well as muscle-specific adeno-associated virus-mediated downregulation of its receptor ACVR2A/B prevented muscle wasting in different mouse models of experimental CKD, suggesting that activin A is a key factor in CKD-induced cachexia. In summary, we uncovered a crosstalk between kidney and muscle and propose modulation of activin signaling as a potential therapeutic strategy for skeletal muscle wasting in CKD