Evidence map›Paper›PMID 41720943›Full record

ArticleScientific reports2026

A scanning electron microscopy-based approach to explore subpodocyte space remodeling in diabetic kidneys of mice and humans.

Sara Conti, Ariela Benigni, Giuseppe Remuzzi, Susanna Tomasoni

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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sara ContiIstituto di Ricerche Farmacologiche Mario Negri IRCCS, Centro Anna Maria Astori, Science and Technology Park Kilometro Rosso, Via Stezzano, 87, Bergamo, 24126, Italy. sara.conti@marionegri.it.
Ariela BenigniIstituto di Ricerche Farmacologiche Mario Negri IRCCS, Centro Anna Maria Astori, Science and Technology Park Kilometro Rosso, Via Stezzano, 87, Bergamo, 24126, Italy.
Giuseppe RemuzziIstituto di Ricerche Farmacologiche Mario Negri IRCCS, Centro Anna Maria Astori, Science and Technology Park Kilometro Rosso, Via Stezzano, 87, Bergamo, 24126, Italy.
Susanna TomasoniIstituto di Ricerche Farmacologiche Mario Negri IRCCS, Centro Anna Maria Astori, Science and Technology Park Kilometro Rosso, Via Stezzano, 87, Bergamo, 24126, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrastructural analysis of the subpodocyte space (SPS) is essential to understanding podocyte injury in diabetic nephropathy, where SPS expansion represents an early marker of glomerular dysfunction. While traditionally assessed by transmission electron microscopy (TEM), we previously established a scanning electron microscopy (SEM) protocol enabling high-resolution SPS visualization in perfused kidney tissue. However, perfusion-based fixation, though effective in animal models, is not feasible in patients during the biopsy retrieval. To overcome these limitations, we developed a rapid SEM protocol based on secondary electron detection, specifically optimized for non-perfused samples. Using a paired design in healthy and diabetic (BTBR ob/ob) mice, we compared perfused and contralateral non-perfused kidneys, showing that SPS morphology and quantification remained accurate even in the absence of perfusion. The protocol was successfully applied to human kidney biopsies from controls and diabetic patients, allowing reliable SPS assessment and ultrastructural analysis across entire glomerular cross-sections. This optimized SEM protocol provides a reliable and versatile approach for SPS analysis in both non-perfused preclinical models and human kidney biopsies, thus broadening its applicability to clinically relevant settings.

Indexed as

Diabetes Mellitus, ExperimentalDiabetic NephropathiesKidneyMicroscopy, Electron, ScanningPodocytesAnimalsFemaleHumansKidney GlomerulusMaleMiceDiabetic nephropathyScanning electron microscopySE-SEM imagingSubpodocyte space

Identifiers

PMID41720943
PMCPMC13022479

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.