Defining the Intravital Renal Disposition of Fluorescence-Quenched Exenatide.

Despite the understanding that renal clearance is pivotal for driving the pharmacokinetics of numerous therapeutic proteins and peptides, the specific processes that occur following glomerular filtration remain poorly defined. For instance, sites of catabolism within the proximal tubule can occur at the brush border, within lysosomes following endocytosis, or even within the tubule lumen itself. The objective of the current study was to address these limitations and develop methodology to study the kidney disposition of a model therapeutic protein. Exenatide is a peptide used to treat type 2 diabetes mellitus. Glomerular filtration and ensuing renal catabolism have been shown to be its principal clearance pathway. Here, we designed and validated a Förster resonance energy transfer-quenched exenatide derivative to provide critical information on the renal handling of exenatide. A combination of in vitro techniques was used to confirm substantial fluorescence quenching of intact peptide that was released upon proteolytic cleavage. This evaluation was then followed by an assessment of the in vivo disposition of quenched exenatide directly within kidneys of living rats via intravital two-photon microscopy. Live imaging demonstrated rapid glomerular filtration and identified exenatide metabolism occurred within the subapical regions of the proximal tubule epithelia, with subsequent intracellular trafficking of cleaved fragments. These results provide a novel examination into the real-time, intravital disposition of a protein therapeutic within the kidney and offer a platform to build upon for future work.

Integrating image analysis with single cell RNA-seq data to study podocyte-specific changes in diabetic kidney disease.

Podocyte injury plays a crucial role in the progression of diabetic kidney disease (DKD). Injured podocytes demonstrate variations in nuclear shape and chromatin distribution. These morphometric changes have not yet been quantified in podocytes. Furthermore, the molecular mechanisms underlying these variations are poorly understood. Recent advances in omics have shed new lights into the biological mechanisms behind podocyte injury. However, there currently exists no study analyzing the biological mechanisms underlying podocyte morphometric variations during DKD. First, to study the importance of nuclear morphometrics, we performed morphometric quantification of podocyte nuclei from whole slide images of renal tissue sections obtained from murine models of DKD. Our results indicated that podocyte nuclear textural features demonstrate statistically significant difference in diabetic podocytes when compared to control. Additionally, the morphometric features demonstrated the existence of multiple subpopulations of podocytes suggesting a potential cause for their varying response to injury. Second, to study the underlying pathophysiology, we employed single cell RNA sequencing data from the murine models. Our results again indicated five subpopulations of podocytes in control and diabetic mouse models, validating the morphometrics-based results. Additionally, gene set enrichment analysis revealed epithelial to mesenchymal transition and apoptotic pathways in a subgroup of podocytes exclusive to diabetic mice, suggesting the molecular mechanism behind injury. Lastly, our results highlighted two distinct lineages of podocytes in control and diabetic cases suggesting a phenotypical change in podocytes during DKD. These results suggest that textural variations in podocyte nuclei may be key to understanding the pathophysiology behind podocyte injury.

PodoSighter: A Cloud-Based Tool for Label-Free Podocyte Detection in Kidney Whole-Slide Images.

BACKGROUND: Podocyte depletion precedes progressive glomerular damage in several kidney diseases. However, the current standard of visual detection and quantification of podocyte nuclei from brightfield microscopy images is laborious and imprecise. METHODS: We have developed PodoSighter, an online cloud-based tool, to automatically identify and quantify podocyte nuclei from giga-pixel brightfield whole-slide images (WSIs) using deep learning. Ground-truth to train the tool used immunohistochemically or immunofluorescence-labeled images from a multi-institutional cohort of 122 histologic sections from mouse, rat, and human kidneys. To demonstrate the generalizability of our tool in investigating podocyte loss in clinically relevant samples, we tested it in rodent models of glomerular diseases, including diabetic kidney disease, crescentic GN, and dose-dependent direct podocyte toxicity and depletion, and in human biopsies from steroid-resistant nephrotic syndrome and from human autopsy tissues. RESULTS: The optimal model yielded high sensitivity/specificity of 0.80/0.80, 0.81/0.86, and 0.80/0.91, in mouse, rat, and human images, respectively, from periodic acid-Schiff-stained WSIs. Furthermore, the podocyte nuclear morphometrics extracted using PodoSighter were informative in identifying diseased glomeruli. We have made PodoSighter freely available to the general public as turnkey plugins in a cloud-based web application for end users. CONCLUSIONS: Our study demonstrates an automated computational approach to detect and quantify podocyte nuclei in standard histologically stained WSIs, facilitating podocyte research, and enabling possible future clinical applications.

Automated detection and quantification of Wilms' Tumor 1-positive cells in murine diabetic kidney disease.

In diabetic kidney disease (DKD), podocyte depletion, and the subsequent migration of parietal epithelial cells (PECs) to the tuft, is a precursor to progressive glomerular damage, but the limitations of brightfield microscopy currently preclude direct pathological quantitation of these cells. Here we present an automated approach to podocyte and PEC detection developed using kidney sections from mouse model emulating DKD, stained first for Wilms' Tumor 1 (WT1) (podocyte and PEC marker) by immunofluorescence, then post-stained with periodic acid-Schiff (PAS). A generative adversarial network (GAN)-based pipeline was used to translate these PAS-stained sections into WT1-labeled IF images, enabling in silico label-free podocyte and PEC identification in brightfield images. Our method detected WT1-positive cells with high sensitivity/specificity (0.87/0.92). Additionally, our algorithm performed with a higher Cohen's kappa (0.85) than the average manual identification by three renal pathologists (0.78). We propose that this pipeline will enable accurate detection of WT1-positive cells in research applications.

Unconjugated p-cresol activates macrophage macropinocytosis leading to increased LDL uptake.

Patients with chronic kidney disease (CKD) and end-stage renal disease suffer from increased cardiovascular events and cardiac mortality. Prior studies have demonstrated that a portion of this enhanced risk can be attributed to the accumulation of microbiota-derived toxic metabolites, with most studies focusing on the sulfonated form of p-cresol (PCS). However, unconjugated p-cresol (uPC) itself was never assessed due to rapid and extensive first-pass metabolism that results in negligible serum concentrations of uPC. These reports thus failed to consider the host exposure to uPC prior to hepatic metabolism. In the current study, not only did we measure the effect of altering the intestinal microbiota on lipid accumulation in coronary arteries, but we also examined macrophage lipid uptake and handling pathways in response to uPC. We found that atherosclerosis-prone mice fed a high-fat diet exhibited significantly higher coronary artery lipid deposits upon receiving fecal material from CKD mice. Furthermore, treatment with uPC increased total cholesterol, triglycerides, and hepatic and aortic fatty deposits in non-CKD mice. Studies employing an in vitro macrophage model demonstrated that uPC exposure increased apoptosis whereas PCS did not. Additionally, uPC exhibited higher potency than PCS to stimulate LDL uptake and only uPC induced endocytosis- and pinocytosis-related genes. Pharmacological inhibition of varying cholesterol influx and efflux systems indicated that uPC increased macrophage LDL uptake by activating macropinocytosis. Overall, these findings indicate that uPC itself had a distinct effect on macrophage biology that might have contributed to increased cardiovascular risk in patients with CKD.

Immunoglobulin G Is a Novel Substrate for the Endocytic Protein Megalin.

Therapeutic immunoglobulin G (IgG) antibodies comprise the largest class of protein therapeutics. Several factors that influence their overall disposition have been well-characterized, including target-mediated mechanics and convective flow. What remains poorly defined is the potential for non-targeted entry into various tissues or cell types by means of uptake via cell surface receptors at those sites. Megalin and cubilin are large endocytic receptors whose cooperative function plays important physiological roles at the tissues in which they are expressed. One such example is the kidney, where loss of either results in significant declines in proximal tubule protein reabsorption. Due to their diverse ligand profile and broad tissue expression, megalin and cubilin represent potential candidates for receptor-mediated uptake of IgG into various epithelia. Therefore, the objective of the current work was to determine if IgG was a novel ligand of megalin and/or cubilin. Direct binding was measured for human IgG with both megalin and the cubilin/amnionless complex. Additional work focusing on the megalin-IgG interaction was then conducted to build upon these findings. Cell uptake studies using megalin ligands for competitive inhibition or proximal tubule cells stably transduced with megalin-targeted shRNA constructs supported a role for megalin in the endocytosis of human IgG. Furthermore, a pharmacokinetic study using transgenic mice with a kidney-specific mosaic knockout of megalin demonstrated increased urinary excretion of human IgG in megalin knockout mice when compared to wild-type controls. These findings indicate that megalin is capable of binding and internalizing IgG via a high affinity interaction.

Megalin-mediated albumin endocytosis in cultured murine mesangial cells.

Endocytosis by podocytes is gaining increased attention as a biologic means of removing large proteins such as serum albumin from the glomerular barrier. Some of this function has been attributed to the megalin/cubilin (Lrp2/Cubn) receptor complex and the albumin recycling protein FcRn (Fcgrt). However, whether other glomerular cells possess the potential to perform this same phenomenon or express these proteins remains uncharacterized. Mesangial cells are uniquely positioned in glomeruli and represent a cell type capable of performing several diverse functions. Here, the expression of megalin and FcRn in murine mesangial cells along with the megalin adaptor protein Dab-2 (Dab2) was shown for the first time. Cubilin mRNA expression was detected, but the absence of the cubilin partner amnionless (Amn) suggested that cubilin is minimally functional, if at all, in these cells. Mesangial cell endocytosis of albumin was characterized and shown to involve a receptor-mediated process. Albumin endocytosis was significantly impaired (p < 0.01) under inducible megalin knockdown conditions in stably transduced mesangial cells. The current work provides both the novel identification of megalin and FcRn in mesangial cells and the functional demonstration of megalin-mediated albumin endocytosis.

The Presence and Location of Podocytes in Glomeruli as Affected by Diabetes Mellitus.

The primary purpose of the kidney, specifically the glomerulus, is filtration. Filtration is accomplished through the glomerular filtration barrier, which consists of the fenestrated endothelium, glomerular basement membrane, and specialized epithelial cells called podocytes. In pathologic states, such as Diabetes Mellitus (DM) and diabetic kidney disease (DKD), variable glomerular conditions result in podocyte injury and depletion, followed by progressive glomerular injury and DKD progression. In this work we quantified glomerulus and podocyte structural changes in histopathology image data derived from a murine model of DM. Using a variety of image processing techniques, we studied changes in podocyte morphology and intra-glomerular distribution across healthy, mild DM, and DM glomeruli. Our feature analysis provided feature trends which we believe are reflective of DKD pathology; while glomerular area peaked in mild DM, average podocyte number and distance from the urinary pole continued to decrease and increase, respectively, throughout DM. Ultimately, this study aims to augment the set of quantifiable image biomarkers used for evaluation of DKD progression in digital pathology, as well as underscore the importance of engineering biologically-inspired image features.

Computational Segmentation and Classification of Diabetic Glomerulosclerosis.

BACKGROUND: Pathologists use visual classification of glomerular lesions to assess samples from patients with diabetic nephropathy (DN). The results may vary among pathologists. Digital algorithms may reduce this variability and provide more consistent image structure interpretation. METHODS: We developed a digital pipeline to classify renal biopsies from patients with DN. We combined traditional image analysis with modern machine learning to efficiently capture important structures, minimize manual effort and supervision, and enforce biologic prior information onto our model. To computationally quantify glomerular structure despite its complexity, we simplified it to three components consisting of nuclei, capillary lumina and Bowman spaces; and Periodic Acid-Schiff positive structures. We detected glomerular boundaries and nuclei from whole slide images using convolutional neural networks, and the remaining glomerular structures using an unsupervised technique developed expressly for this purpose. We defined a set of digital features which quantify the structural progression of DN, and a recurrent network architecture which processes these features into a classification. RESULTS: Our digital classification agreed with a senior pathologist whose classifications were used as ground truth with moderate Cohen's kappa κ = 0.55 and 95% confidence interval [0.50, 0.60]. Two other renal pathologists agreed with the digital classification with κ1 = 0.68, 95% interval [0.50, 0.86] and κ2 = 0.48, 95% interval [0.32, 0.64]. Our results suggest computational approaches are comparable to human visual classification methods, and can offer improved precision in clinical decision workflows. We detected glomerular boundaries from whole slide images with 0.93±0.04 balanced accuracy, glomerular nuclei with 0.94 sensitivity and 0.93 specificity, and glomerular structural components with 0.95 sensitivity and 0.99 specificity. CONCLUSIONS: Computationally derived, histologic image features hold significant diagnostic information that may augment clinical diagnostics.

An integrated iterative annotation technique for easing neural network training in medical image analysis.

Neural networks promise to bring robust, quantitative analysis to medical fields. However, their adoption is limited by the technicalities of training these networks and the required volume and quality of human-generated annotations. To address this gap in the field of pathology, we have created an intuitive interface for data annotation and the display of neural network predictions within a commonly used digital pathology whole-slide viewer. This strategy used a 'human-in-the-loop' to reduce the annotation burden. We demonstrate that segmentation of human and mouse renal micro compartments is repeatedly improved when humans interact with automatically generated annotations throughout the training process. Finally, to show the adaptability of this technique to other medical imaging fields, we demonstrate its ability to iteratively segment human prostate glands from radiology imaging data.

The role of chronic kidney disease-associated dysbiosis in cardiovascular disease.

IMPACT STATEMENT: Negative alterations, or dysbiosis, in the intestinal microbial community balance in response to chronic kidney disease is emerging as a substantial and important factor in inducing and exacerbating multiple comorbid conditions. Patients with renal insufficiency experience a substantial increase in cardiovascular risk, and recent evidence is shedding light on the close interaction between microbiome dysbiosis and increased cardiovascular events in this population. Previous association and recent causality studies utilizing experimental animal models have enriched our understanding and confirmed the impact of microbial community imbalance on cardiac health in both the general population and in patients with renal impairment.

Fecal microbiota analysis of polycystic kidney disease patients according to renal function: A pilot study.

IMPACT STATEMENT: The heterogeneity of the renal disease, therapeutic interventions, and the original cause of the renal failure, all directly affect the microbiota. We delineate in this report the direct effect of decreased renal function on the bacterial composition following stringent criteria to eliminate the possibilities of other confounding factors and dissect the direct effects of the uremic milieu. We analyzed the microbiome following three different approaches to further evaluate the effects of mild, moderate and advanced renal insufficiency on the microbiome. We also present here a detailed functional analysis of the projected altered pathways secondary to changes in the microbiome composition.

Increased megalin expression in early type 2 diabetes: role of insulin-signaling pathways.

The megalin/cubilin complex is responsible for the majority of serum protein reclamation in the proximal tubules. The current study examined if decreases in their renal expression, along with the albumin recycling protein neonatal Fc receptor (FcRn) could account for proteinuria/albuminuria in the Zucker diabetic fatty rat model of type 2 diabetes. Immunoblots of renal cortex samples obtained at worsening disease stages demonstrated no loss in megalin, cubilin, or FcRn, even when proteinuria was measured. Additionally, early diabetic rats exhibited significantly increased renal megalin expression when compared with controls (adjusted P < 0.01). Based on these results, the ability of insulin to increase megalin was examined in a clonal subpopulation of the opossum kidney proximal tubule cell line. Insulin treatments (24 h, 100 nM) under high glucose conditions significantly increased megalin protein ( P < 0.0001), mRNA ( P < 0.0001), and albumin endocytosis. The effect on megalin expression was prevented with inhibitors against key effectors of insulin intracellular signaling, phosphatidylinositide 3-kinase and Akt. Studies using rapamycin to inhibit the mechanistic target of rapamycin complex 1 (mTORC1) resulted in a loss of insulin-induced megalin expression. However, subsequent evaluation demonstrated these effects were independent of initial mTORC1 suppression. The presented results provide insight into the expression of megalin, cubilin, and FcRn in type 2 diabetes, which may be impacted by elevated insulin and glucose. Furthermore, proximal tubule endocytic activity in early diabetics may be enhanced, a process that could have a significant role in proteinuria-induced renal damage.

Chronic kidney disease, uremic milieu, and its effects on gut bacterial microbiota dysbiosis.

Several lines of evidence suggest that gut bacterial microbiota is altered in patients with chronic kidney disease (CKD), though the mechanism of which this dysbiosis takes place is not well understood. Recent studies delineated changes in gut microbiota in both CKD patients and experimental animal models using microarray chips. We present 16S ribosomal RNA gene sequencing of both stool pellets and small bowel contents of C57BL/6J mice that underwent a remnant kidney model and establish that changes in microbiota take place in the early gastrointestinal tract. Increased intestinal urea concentration has been hypothesized as a leading contributor to dysbiotic changes in CKD. We show that urea transporters (UT)-A and UT-B mRNA are both expressed throughout the whole gastrointestinal tract. The noted increase in intestinal urea concentration appears to be independent of UTs' expression. Urea supplementation in drinking water resulted in alteration in bacterial gut microbiota that is quite different than that seen in CKD. This indicates that increased intestinal urea concentration might not fully explain the CKD- associated dysbiosis.

Multi-radial LBP Features as a Tool for Rapid Glomerular Detection and Assessment in Whole Slide Histopathology Images.

We demonstrate a simple and effective automated method for the localization of glomeruli in large (~1 gigapixel) histopathological whole-slide images (WSIs) of thin renal tissue sections and biopsies, using an adaptation of the well-known local binary patterns (LBP) image feature vector to train a support vector machine (SVM) model. Our method offers high precision (>90%) and reasonable recall (>70%) for glomeruli from WSIs, is readily adaptable to glomeruli from multiple species, including mouse, rat, and human, and is robust to diverse slide staining methods. Using 5 Intel(R) Core(TM) i7-4790 CPUs with 40 GB RAM, our method typically requires ~15 sec for training and ~2 min to extract glomeruli reproducibly from a WSI. Deploying a deep convolutional neural network trained for glomerular recognition in tandem with the SVM suffices to reduce false positives to below 3%. We also apply our LBP-based descriptor to successfully detect pathologic changes in a mouse model of diabetic nephropathy. We envision potential clinical and laboratory applications for this approach in the study and diagnosis of glomerular disease, and as a means of greatly accelerating the construction of feature sets to fuel deep learning studies into tissue structure and pathology.

Lupus: The microbiome angle.

Microbiota consists of more than 1014 microorganisms that inhabit different areas of the body including the gastrointestinal tract, mainly the mouth and gut. It includes viruses, fungi, protozoa, archaea and bacteria. The microbiota interacts closely with host leading to a dynamic relationship that results in the biological effects observed. Its diverse genetic material (microbiome) interacts closely with the host immune system and cells, and therefore is closely associated with inflammation, immune tolerance, adaptive immunity and autoimmune diseases. Bacterial microbiota, which is the mostly studied lives in harmony with the host and maintains a symbiotic relationship. Therefore it plays an important role in immunological, metabolic, and neurological aspects and thereby the well-being of the host. Alteration of the homeostatic environment or the dynamic balance of microorganisms can result in dysbiosis or disease. However, does dysbiosis cause disease, aggravate disease or is the result of the disease remains to be defined, it could be a bit of all three factors. More recently, a number of studies demonstrate that these microorganisms could contribute to disease. Alteration of the tightly balanced composition of bacterial microbiota (dysbiosis) leads to exacerbation, rapid progression and worsening of disease states. It is important to identify the 'healthy' microbes that maintain a healthy environment, the 'sensitive' microbes that go awry with disease, the 'bad' microbes that cause disease and the 'therapeutic' microbes that can help rectify the changes. Increased relative abundance of certain bacterial species has been linked to triggering autoimmune diseases. Despite the burgeoning literature in the field, the molecular mechanisms by which the microbiota impacts the body in health and disease remain largely unknown. In this review, we will discuss recent advancements in our understanding of the gut bacterial microbiota associated with inflammatory and immunological processes and the role they play in the autoimmune disease, systemic lupus erythematosus.

Analysis of OPTN/UNOS registry suggests the number of HLA matches and not mismatches is a stronger independent predictor of kidney transplant survival.

HLA matching and mismatching, while inversely related, are not exact opposites. Here we determined the independent effects of HLA matching and mismatching on outcomes in deceased donor kidney transplant recipients. The United Network for Organ Sharing database (1995-2012) was utilized and analyzed for delayed graft function, one-year acute rejection, and death-censored graft survival using combined multivariable models including HLA matching and mismatching. Sensitivity analyses were performed using the subgroup of deceased donor kidney transplant patients after 2003 with more uniform HLA nomenclature and resampling analyses using bootstrapping on complete data available from 96,236 recipients. Individually, both HLA matching and mismatching showed significant associations with graft survival. Adjusting the model to take into account both matching and mismatching simultaneously, the degree of HLA mismatching lost significance while matching continued to have a significant prediction for delayed graft function, the one-year acute rejection rate, and graft survival. Sensitivity analyses and bootstrapping showed similar results for all studied outcomes. Thus, analysis of this large cohort demonstrates the apparent greater association of HLA matching over HLA mismatching on both early allograft events as well as graft survival. Future analyses should preferentially utilize HLA matching as a covariate over mismatching for accurately reflecting impact on graft outcomes.

Advanced glycation end products dietary restriction effects on bacterial gut microbiota in peritoneal dialysis patients; a randomized open label controlled trial.

The modern Western diet is rich in advanced glycation end products (AGEs). We have previously shown an association between dietary AGEs and markers of inflammation and oxidative stress in a population of end stage renal disease (ESRD) patients undergoing peritoneal dialysis (PD). In the current pilot study we explored the effects of dietary AGEs on the gut bacterial microbiota composition in similar patients. AGEs play an important role in the development and progression of cardiovascular (CVD) disease. Plasma concentrations of different bacterial products have been shown to predict the risk of incident major adverse CVD events independently of traditional CVD risk factors, and experimental animal models indicates a possible role AGEs might have on the gut microbiota population. In this pilot randomized open label controlled trial, twenty PD patients habitually consuming a high AGE diet were recruited and randomized into either continuing the same diet (HAGE, n = 10) or a one-month dietary AGE restriction (LAGE, n = 10). Blood and stool samples were collected at baseline and after intervention. Variable regions V3-V4 of 16s rDNA were sequenced and taxa was identified on the phyla, genus, and species levels. Dietary AGE restriction resulted in a significant decrease in serum Nε-(carboxymethyl) lysine (CML) and methylglyoxal-derivatives (MG). At baseline, our total cohort exhibited a lower relative abundance of Bacteroides and Alistipes genus and a higher abundance of Prevotella genus when compared to the published data of healthy population. Dietary AGE restriction altered the bacterial gut microbiota with a significant reduction in Prevotella copri and Bifidobacterium animalis relative abundance and increased Alistipes indistinctus, Clostridium citroniae, Clostridium hathewayi, and Ruminococcus gauvreauii relative abundance. We show in this pilot study significant microbiota differences in peritoneal dialysis patients' population, as well as the effects of dietary AGEs on gut microbiota, which might play a role in the increased cardiovascular events in this population and warrants further studies.

Reduction in podocyte SIRT1 accelerates kidney injury in aging mice.

Both the incidence and prevalence of chronic kidney disease are increasing in the elderly population. Although aging is known to induce kidney injury, the underlying molecular mechanisms remain unclear. Sirtuin 1 (Sirt1), a longevity gene, is known to protect kidney cell injury from various cellular stresses. In previous studies, we showed that the podocyte-specific loss of Sirt1 aggravates diabetic kidney injury. However, the role of Sirt1 in aging-induced podocyte injury is not known. Therefore, in this study we sought to determine the effects of podocyte-specific reduction of Sirt1 in age-induced kidney injury. We employed the inducible podocyte-specific Sirt1 knockdown mice that express shRNA against Sirt1 (Pod-Sirt1RNAi) and control mice that express shRNA for luciferase (Pod-LuciRNAi). We found that reduction of podocyte Sirt1 led to aggravated aging-induced glomerulosclerosis and albuminuria. In addition, urinary level of 8-hydroxy-2'-deoxyguanosine (8-OHdG), a marker of oxidative stress, was markedly increased in aged Pod-Sirt1RNAi mice compared with aged Pod-LuciRNAi mice. Although podocyte-specific markers decreased in aged mice compared with the young controls, the decrease was further exacerbated in aged Pod-Sirt1RNAi compared with Pod-LuciRNAi mice. Interestingly, expression of cellular senescence markers was significantly higher in the glomeruli of Pod-Sirt1RNAi mice than Pod-LuciRNAi mice, suggesting that cellular senescence may contribute to podocyte loss in aging kidneys. Finally, we confirmed that Pod-Sirt1RNAi glomeruli were associated with reduced activation of the transcription factors peroxisome proliferator-activated receptor (PPAR)-α coactivador-1 (PGC1α)/PPARγ, forkhead box O (FOXO)3, FOXO4, and p65 NF-κB, through SIRT1-mediated deacetylation. Together, our data suggest that SIRT1 may be a potential therapeutic target to treat patients with aging-related kidney disease.

Unsupervised labeling of glomerular boundaries using Gabor filters and statistical testing in renal histology.

The glomerulus is the blood filtering unit of the kidney. Each human kidney contains [Formula: see text] glomeruli. Several renal conditions originate from structural damage to glomerular microcompartments, such as proteinuria, the excessive loss of blood proteins into urine. The gold standard for evaluating structural damage in renal pathology is histopathological and immunofluorescence examination of needle biopsies under a light microscope. This method is limited by qualitative or semiquantitative manual scoring approaches to the evaluation of glomerular structural features. Computational quantification of equivalent features promises to improve the precision of glomerular structural analysis. One large obstacle to the computational quantification of renal tissue is the identification of complex glomerular boundaries automatically. To mitigate this issue, we developed a computational pipeline capable of extracting and exactly defining glomerular boundaries. Our method, composed of Gabor filtering, Gaussian blurring, statistical [Formula: see text]-testing, and distance transform, is able to accurately identify glomerular boundaries with mean sensitivity/specificity of [Formula: see text] and accuracy of 0.92, on [Formula: see text] glomeruli images stained with standard renal histological stains. Our method will simplify computational partitioning of glomerular microcompartments hidden within dense textural boundaries. Automatic quantification of glomeruli will streamline structural analysis in clinic and can pioneer real-time diagnoses and interventions for renal care.