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      Molecular nephrology: types of acute tubular injury

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          Abstract

          The acute loss of kidney function has been diagnosed for many decades using the serum concentration of creatinine — a muscle metabolite that is an insensitive and non-specific marker of kidney function, but is now used for the very definition of acute kidney injury (AKI). Fortunately, myriad new tools have now been developed to better understand the relationship between acute tubular injury and elevation in serum creatinine (SCr). These tools include unbiased gene and protein expression analyses in kidney, urine and blood, the localization of specific gene transcripts in pathological biopsy samples by rapid in-situ RNA technology and single-cell RNA-sequencing analyses. However, this molecular approach to AKI has produced a series of unexpected problems, because the expression of specific kidney-derived molecules that are indicative of injury often do not correlate with SCr levels. This discrepancy between kidney injury markers and SCr level can be reconciled by the recognition that many separate subtypes of AKI exist, each with distinct patterning of molecular markers of tubular injury and SCr data. In this Review, we describe the weaknesses of isolated SCr-based diagnoses, the clinical and molecular subtyping of acute tubular injury, and the role of non-invasive biomarkers in clinical phenotyping. We propose a conceptual model that synthesizes molecular and physiological data along a time course spanning from acute cellular injury to organ failure.

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          Most cited references108

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          KDIGO Clinical Practice Guidelines for Acute Kidney Injury

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            Prediction of Creatinine Clearance from Serum Creatinine

            A formula has been developed to predict creatinine clearance (C cr ) from serum creatinine (S cr ) in adult males: Ccr = (140 – age) (wt kg)/72 × S cr (mg/100ml) (15% less in females). Derivation included the relationship found between age and 24-hour creatinine excretion/kg in 249 patients aged 18–92. Values for C cr were predicted by this formula and four other methods and the results compared with the means of two 24-hour C cr’s measured in 236 patients. The above formula gave a correlation coefficient between predicted and mean measured Ccr·s of 0.83; on average, the difference between predicted and mean measured values was no greater than that between paired clearances. Factors for age and body weight must be included for reasonable prediction.
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              The neutrophil lipocalin NGAL is a bacteriostatic agent that interferes with siderophore-mediated iron acquisition.

              First identified as a neutrophil granule component, neutrophil gelatinase-associated lipocalin (NGAL; also called human neutrophil lipocalin, 24p3, uterocalin, or neu-related lipocalin) is a member of the lipocalin family of binding proteins. Putative NGAL ligands, including neutrophil chemotactic agents such as N-formylated tripeptides, have all been refuted by recent biochemical and structural results. NGAL has subsequently been implicated in diverse cellular processes, but without a characterized ligand, the molecular basis of these functions remained mysterious. Here we report that NGAL tightly binds bacterial catecholate-type ferric siderophores through a cyclically permuted, hybrid electrostatic/cation-pi interaction and is a potent bacteriostatic agent in iron-limiting conditions. We therefore propose that NGAL participates in the antibacterial iron depletion strategy of the innate immune system.
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                Author and article information

                Journal
                Nature Reviews Nephrology
                Nat Rev Nephrol
                Springer Science and Business Media LLC
                1759-5061
                1759-507X
                August 22 2019
                Article
                10.1038/s41581-019-0184-x
                7303545
                31439924
                1649ccb2-0ac3-4b59-bd96-3dfdfbe2f13d
                © 2019

                http://www.springer.com/tdm

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