Evidence map›Paper›PMID 42019501›Full record

ArticleCell reports methods2026

A multi-tiered workflow for examining organic acid profiles delineates tissue-specific changes in fatty acyl partitioning during aging.

Zhiyang Zhou, Chenyin Cao, Taochao Lu, Yuyuan Ruan, Bowen Li, Mingjun Cao, Luyue Mo, Guanghou Shui, Sin Man Lam

Abstract read
In one paragraph

Article in Cell reports methods, 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

9 authors.

Zhiyang ZhouLipidALL Technologies Company Limited, Jiangsu Provincial Key Laboratory of Molecular Targets and Intervention for Metabolic Diseases, Changzhou 213022, China.
Chenyin CaoInstitute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China; Guangzhou National Laboratory, Guangzhou, Guangdong 510005, China.
Taochao LuLipidALL Technologies Company Limited, Jiangsu Provincial Key Laboratory of Molecular Targets and Intervention for Metabolic Diseases, Changzhou 213022, China.
Yuyuan RuanLipidALL Technologies Company Limited, Jiangsu Provincial Key Laboratory of Molecular Targets and Intervention for Metabolic Diseases, Changzhou 213022, China.
Bowen LiLipidALL Technologies Company Limited, Jiangsu Provincial Key Laboratory of Molecular Targets and Intervention for Metabolic Diseases, Changzhou 213022, China.
Mingjun CaoInstitute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
Luyue MoInstitute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China.
Guanghou ShuiInstitute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China; Guangzhou National Laboratory, Guangzhou, Guangdong 510005, China. Electronic address: shui_guanghou@gzlab.ac.cn.
Sin Man LamGuangzhou Institute of Cancer Research, the Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou 510095, China; LipidALL Technologies Company Limited, Jiangsu Provincial Key Laboratory of Molecular Targets and Intervention for Metabolic Diseases, Changzhou 213022, China. Electronic address: smlam@lipidall.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fatty acids (FAs), as the predominant organic acids, form a major component of the metabolome. We present a multi-tiered method that comprehensively captures FA diversity-including chain lengths (C2-C34), unsaturation, isomers, and endogenous forms-within a single biological specimen. This workflow quantifies the broadest range of free FAs reported to date. Integrated with two complementary tiers profiling the total FA pool from alkaline hydrolysis and esterified acyl compositions across lipid classes, our multi-tiered workflow enables the investigation of differential fatty acyl partitioning. Applying this platform to quantify >540 unique lipids (free and esterified forms) and polar carboxylic acids, we investigated FA remodeling in the brain, retina (eyeball), and skeletal muscles of young and aged mice. We found that aged glycolytic tissues preferentially partition odd-chain and diunsaturated FAs (with lower β-oxidizability) into triacylglycerols. Additionally, aging shifts the FA18:1 partitioning into diacylglycerols over anionic phospholipids, which may mitigate pro-aging lipid signatures in the skeletal muscle.

Indexed as

AgingFatty AcidsAnimalsBrainMiceMice, Inbred C57BLMuscle, SkeletalOrgan SpecificityWorkflowFatty Acidsagingbrain agingCP: metabolismfatty acidsLCFAlipidomicsorganic acidsSCFAskeletal muscle agingVLCFA

Identifiers

PMID42019501
PMCPMC13198126

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.