Avi Z. Rosenberg

The paper identifies the CXCL9-CXCR3 axis and NAMPT as key drivers of inflammation and kidney injury in acute interstitial nephritis using spatial transcriptomics and imaging.

This paper develops a serial immunohistochemistry method to detect multiple antigens on kidney biopsy slides, enabling high-dimensional single-cell spatial analysis.

CODAvision provides a user-friendly interface for rapid, customizable medical image segmentation using deep learning, enabling non-experts to train and evaluate models across diverse imaging modalities.

This study shows that deleting ERRγ in podocytes accelerates aging-related kidney disease by impairing mitochondrial function and increasing albuminuria.

This study identifies DNA damage-driven senescence and ZBP1-cGAS-STING signaling as conserved mechanisms linking cardiovascular-kidney-metabolic comorbidities to HFpEF.

This study creates a mouse model of SFPQ-TFE3-driven renal tumors and shows it induces lineage plasticity through mTORC1 activation.

The paper presents a multi-modal atlas of human kidney disease, identifying cellular and spatial mechanisms of injury resolution or failure and linking them to clinical outcomes.

FUSION is a web-based tool that integrates spatial -omics data with histology to analyze tissue states and identify spatial linkages between molecular and histopathologic features.

This study examines inflammation in fibrotic areas of kidney biopsies from lupus nephritis patients and finds that the degree of inflammation correlates with future kidney function decline.

The paper investigates the role of APOL1 variants in cardiovascular and neurological diseases using mice, finding APOL1-G1 contributes to hydrocephalus but not atherosclerosis.

This study shows that NAD+ supplementation protects against CKD in Alport syndrome by restoring FAO in proximal tubule cells and reveals sex differences in transcriptional responses.

The paper uses ontologies to integrate clinical, pathological, and molecular kidney data for precision medicine analysis.

ComPRePS improves renal pathology analysis by automating WSI processing and AI-assisted interpretation, enhancing precision and interobserver agreement in key lesion assessments.

This study uses mouse models to show that fetal APOL1-G1 variants cause preeclampsia by inducing pro-inflammatory responses in placental and maternal monocyte cells.

This paper uses deep learning to label 17 kidney microstructures in 3D fetal rhesus macaque kidneys, revealing spatial relationships between glomeruli, arteries, and nephrons.

The paper creates a high-resolution cellular atlas of healthy and injured kidney cell states and niches using single-cell and spatial technologies, identifying molecular signatures and pathways related to kidney injury.

The paper optimizes an expression microdissection method to improve miRNA yield and in vivo cell-type specificity for qPCR analysis.

The paper performs deconvolution on GTEx coronary artery data using CIBERSORT to assess challenges and limitations in estimating tissue composition from gene expression data.

The paper analyzes matrisome gene expression patterns across tissues, age, sex, and disease using GTEx and TCGA data, finding that transcriptomics can recapitulate proteomic patterns and identify tissue-specific and sex/age-related expression variations.

The paper integrates proteomic and genomic data from skeletal muscle myocytes to identify gene and protein expression differences between slow and fast-twitch fiber types.

The paper identifies basal contamination in GTEx data, showing that highly expressed tissue-specific genes contaminate samples, affecting eQTL assignments and analysis accuracy.

The paper introduces xMD-miRNA-seq to obtain in vivo miRNA expression from colon epithelial cells using FFPE tissues, showing cell-specific miRNA profiles comparable to other epithelial sources.

The paper establishes the landscape of human cell-specific microRNA expression using small RNA-seq data from diverse cell types and tissues, identifying novel microRNA loci and patterns correlated with super-enhancer activity.