Evidence map›Paper›PMID 42904741›Full record

ArticleASN neuro2026

Employing the Role of SLC40A1-Mediated Microglia Inflammatory Response in Diabetic Retinopathy Based on Single-Cell Transcriptomics Technology.

Hui Cao, Yujia Gong

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Hui CaoDepartment of Ophthalmology, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China.
Yujia GongDepartment of Ophthalmology, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic retinopathy (DR) is one of the most severe complications of diabetes. Existing treatments are effective but still have many limitations. Thus, it is particularly crucial to uncover novel therapeutic targets and develop more efficacious treatment strategies. In this study, single-cell datasets of retinal and normal retinal tissues of DR patients were obtained from the Gene Expression Omnibus (GEO) database. Using cell annotation, Gene Ontology (GO) pathway enrichment analysis, and cell trajectory analysis, key cell subgroups and their enriched pathways affecting DR progression were selected. DR model mice was constructed. Co-localization between SLC40A1 and microglial cell marker IBA1 was assessed through immunofluorescence detection. qPCR, Western Blot, and ELISA were used to evaluate the expression levels of inflammatory factors. Bioinformatics analysis revealed that in retinal tissues of DR patients, SLC40A1+ microglia exhibited abnormal accumulation and were tightly correlated with inflammatory pathways. Animal experiments showed that the co-localization level of SLC40A1 with IBA1 increased in DR model mice. Further research revealed that knocking out the SLC40A1 gene in microglia can reduce the expression levels of pro-inflammatory factors, including IL-6, TNF-α, and IL-1β. It effectively alleviated the pathologic characteristics of DR. SLC40A1+ microglia modulated inflammatory responses to control DR progression, offering promising avenues for new therapeutic targets in DR treatment.

Indexed as

Diabetic RetinopathyMicrogliaAnimalsCalcium-Binding ProteinsHumansInflammationMaleMiceMice, Inbred C57BLMice, KnockoutMicrofilament ProteinsRetinaSingle-Cell Gene Expression AnalysisTranscriptomeCalcium-Binding ProteinsMicrofilament ProteinsDiabetic retinopathyinflammationmicrogliaSLC40A1

Identifiers

PMID42904741
PMCPMC13690280

What OpenQuestion holds

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Registered trials

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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.