Evidence map›Paper›PMID 42346414›Full record

ArticleMetabolites2026

Lactate Metabolism Dysregulation Drives the Pathogenesis of Acute Kidney Injury.

Yongchen Li, Jingwen Liu, Diman Mai, Renzhi Tan, Chao Wang, Zengnan Mo

Abstract read
In one paragraph

Article in Metabolites, 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
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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.

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

6 authors.

Yongchen LiCenter for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China.
Jingwen LiuDepartment of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China.
Diman MaiDepartment of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China.
Renzhi TanDepartment of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China.
Chao WangCenter for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China.
Zengnan MoCenter for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China.ORCID 0000-0002-3047-3138

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) remains a condition with limited effective therapeutic options, partly due to challenges in early diagnosis and timely intervention. While lactate accumulation is a hallmark of ischemic and septic AKI, the underlying mechanisms remain unclear.

methodsThis study integrated single-cell RNA sequencing data from AKI patients (GEO database) with lactate metabolism-related genes (LMRGs) to identify key therapeutic targets.

resultsCollecting duct (CD) cells exhibited the highest LMRG expression. Machine learning algorithms and validation in bilateral ischemia/reperfusion injury (bIRI) and lipopolysaccharide (LPS)-induced AKI mouse models, as well as hypoxia/reoxygenation (H/R)-stimulated renal cells, identified

conclusionsThese findings reveal that lactate metabolism is reprogrammed in AKI, particularly in CD cells, and identify LDHB as a novel potential therapeutic target for this condition, though further mechanistic studies are required to establish causality.

Indexed as

acute kidney injurycollecting duct celllactate dehydrogenase Blactate metabolismmetabolic reprogrammingsingle-cell RNA sequencing

Identifiers

PMID42346414
PMCPMC13303532

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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.