Renal recovery following orthotopic liver transplant after prolonged kidney injury: Perspectives on diagnosing hepatorenal syndrome and determining which patients should undergo simultaneous liver kidney transplantation

We present a case of an individual with cirrhosis and renal failure. This case is notable because the patient was found to have hepatorenal syndrome (HRS) superimposed on Immunoglobulin A (IgA) nephropathy. After 8 months of dialysis, the patient had significant renal recovery following orthotopic liver transplant (OLT). Cases such as this are not likely to be rare, as case series have shown that IgA deposits are a common occurrence in patients with cirrhosis, including those who have HRS. While current diagnostic criteria for HRS emphasize the importance of excluding glomerular lesions, we argue that this approach should be reconsidered. More specifically, we feel that the diagnostic approach to HRS should be more inclusive of cases in which patients have simultaneous HRS and glomerular injury. In addition, our case highlights the challenges in determining which patients will benefit most from simultaneous liver–kidney transplants over OLTs alone

Hypertonic stress and cell death. Focus on "Multiple cell death pathways are independently activated by lethal hypertonicity in renal epithelial cells"

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Application of digital pathology and machine learning in the liver, kidney and lung diseases

The development of rapid and accurate Whole Slide Imaging (WSI) has paved the way for the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the recent years allowed the rapid development of various AI technologies to blossom. WSI-based digital pathology combined with neural networks can automate arduous and time-consuming tasks of slide evaluation. Machine Learning (ML)-based AI has been demonstrated to outperform pathologists by eliminating inter- and intra-observer subjectivity, obtaining quantitative data from slide images, and extracting hidden image patterns that are relevant to disease subtype and progression. In this review, we outline the functionality of different AI technologies such as neural networks and deep learning and discover how aspects of different diseases make them benefit from the implementation of AI. AI has proven to be valuable in many different organs, with this review focusing on the liver, kidney, and lungs. We also discuss how AI and image analysis not only can grade diseases objectively but also discover aspects of diseases that have prognostic value. In the end, we review the current status of the integration of AI in pathology and share our vision on the future of digital pathology

Urea promotes TonEBP expression and cellular adaptation in extreme hypertonicity

The transcriptional activator TonEBP is a central regulator of osmolality in the renal medulla and whole body water homeostasis. In order to understand the regulation of TonEBP in the renal medulla, we examined MDCK cells, a kidney-derived epithelial cell line, under conditions mimicking the renal medulla. Moderate changes in ambient tonicity, which was tolerated without prior adaptation, displayed lasting effects on TonEBP in bidirectional manner-stimulated by hypertonicity and inhibited by hypotonicity. TonEBP expression was further enhanced by extreme hypertonicity observed in the inner medullae of antidiuretic animals. Urea stimulated TonEBP expression and promoted cellular proliferation under the conditions of extreme hypertonicity. On the other hand, the TonEBP activity was negatively modulated under these conditions presumably to temper the highly abundant TonEBP. We conclude that urea is critical to the cellular adaptation to extreme hypertonicity and the high level of TonEBP expression in the inner medulla.close4