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International audience; Functional properties of the paracellular pathway depend critically on the set of claudins (CLDN) expressed at the tight junction. Two syndromes are causally linked to loss-of-function mutations of claudins: hypohidrosis, electrolyte imbalance, lacrimal gland dysfunction, ichthyosis, and xerostomia (HELIX) syndrome caused by genetic variations in the CLDN10 gene and familial hypomagnesemia with hypercalciuria and nephrocalcinosis caused by genetic variations in the CLDN16 or CLDN19 genes. All three genes are expressed in the kidney, particularly in the thick ascending limb (TAL). However, localization of these claudins in humans and rodents remains to be delineated in detail. We studied the segmental and subcellular expression of CLDN10, CLDN16, and CLDN19 in both paraffin-embedded and frozen kidney sections from the adult human, mouse, and rat using immunohistochemistry and immunofluorescence, respectively. Here, CLDN10 was present in a subset of medullary and cortical TAL cells, localizing to basolateral domains and tight junctions in human and rodent kidneys. Weak expression was detected at the tight junction of proximal tubular cells. CLDN16 was primarily expressed in a subset of TAL cells in the cortex and outer stripe of outer medulla, restricted to basolateral domains and tight junctional structures in both human and rodent kidneys. CLDN19 predominantly colocalized with CLDN16 in tight junctions and basolateral domains of the TAL but was also found in basolateral and junctional domains in more distal sites. CLDN10 expression at tight junctions almost never overlapped with that of CLND16 and CLDN19, consistent with distinct junctional pathways with different permeation profiles in both human and rodent kidneys.NEW & NOTEWORTHY This study used immunohistochemistry and immunofluorescence to investigate the distribution of claudin 10, 16, and 19 in the human, mouse, and rat kidney. The findings showed distinct junctional pathways in both human and rodent kidneys, supporting the existence of different permeation profiles in all species investigated.

Tumour diagnosis relies on the visual examination of histological slides by pathologists through a microscope eyepiece. Digital pathology, the digitalization of histological slides at high magnification with slides scanners, has raised the opportunity to extract quantitative information due to image analysis. In the last decade, medical image analysis has made exceptional progress due to the development of artificial intelligence (AI) algorithms. AI has been successfully used in the field of medical imaging and more recently in digital pathology. The feasibility and usefulness of AI assisted pathology tasks have been demonstrated in the very last years and we can expect those developments to be applied to routine histopathology in the future. In this review, we will describe and illustrate this technique and present the most recent applications in the field of tumour histopathology. LINKED ARTICLES: This article is part of a themed issue on Molecular imaging - visual themed issue. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.21/issuetoc.