Evidence map›Paper›PMID 42157065›Full record

ArticleDiagnostic pathology2026

Rapid slide-level assessment of glomerular yield using virtual staining of unstained renal biopsy sections.

Xingan Cai, Xi Chen, Jinqiu Liu, Xiaoling Yang, Liwei Xie, Linfeng Tang

Abstract read
In one paragraph

Article in Diagnostic pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Xingan Cai *Department of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, China.
Xi Chen *Department of Pathology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Jinqiu Liu *Department of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, China.
Xiaoling YangSuzhou Institute of Intelligent Computing for Industrial Technology, Institute of Computing Technology, Chinese Academy of Sciences, Suzhou, 215024, China.
Liwei XieDepartment of Radiotherapy and Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, China.
Linfeng TangDepartment of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, China. linfengtang95@qq.com.

Funding

Jiangsu Association for Science & Technology Youth Science & Technology Talents Lifting Project JSTJ-2025-833National Natural Science Foundation of China No. 82404188Suzhou Medical College-QiLu Medical Research Program of Soochow University 24QL200106the Scientific Research Pre-project Fund of the Second Affiliated Hospital of Soochow University SDFEYBS2414the Scientific Research Pre-project Fund of the Second Affiliated Hospital of Soochow University SDFEYJC2436
6 · The paper itself

Abstract

backgroundRenal biopsy remains the gold standard for the diagnosis of kidney diseases, and specimen adequacy is essential for reliable histopathological evaluation. However, confirmation of glomerular yield in routine pathology workflows often relies on histological sections after staining, which may delay feedback when deeper sectioning is required.

methodsIn this study, we investigated whether virtual staining applied to unstained renal biopsy sections could enable early assessment of glomerular adequacy. Unstained sections prepared under different mounting conditions were virtually transformed into H&E and special stains. The visibility of glomerular structures and the reliability of glomerular assessment were evaluated across multiple scanners.

resultsOptimized preparation of unstained sections enabled stable virtual staining with preserved morphological features. Virtual special stains enhanced the visualization of glomerular basement membranes and mesangial regions, allowing reliable identification of glomeruli on unstained tissue sections. This approach demonstrated robustness across different scanning systems, outperforming direct assessment on raw unstained images.

conclusionsVirtual staining of unstained renal biopsy sections provides a rapid and reagent-free strategy for early slide-level assessment of glomerular yield. By enabling feedback at the sectioning stage before routine staining, this method may improve efficiency and quality control in routine renal pathology workflows.

Indexed as

Kidney DiseasesKidney GlomerulusStaining and LabelingBiopsyHumansReproducibility of ResultsComputational pathologyDeep learningGlomerular detectionRenal biopsyUnstained tissueVirtual staining

Identifiers

PMID42157065
PMCPMC13366873

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.