Evidence map›Paper›PMID 42741086›Full record

ArticleFrontiers in pharmacology2026

Generation of a glycogen storage disease mouse model with fatty liver and its treatment by PPAR-α agonist bezafibrate.

Yixia Xie, Guoquan Fu, Caixia Fan, Huarong Huang, Junyan Yan, Lifang Jin

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 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

6 authors.

Yixia XieSchool of Life and Environmental Sciences, Shaoxing University, Shaoxing, Zhejiang, China.
Guoquan FuSchool of Life and Environmental Sciences, Shaoxing University, Shaoxing, Zhejiang, China.
Caixia FanSchool of Life and Environmental Sciences, Shaoxing University, Shaoxing, Zhejiang, China.
Huarong HuangCollege of Life and Environmental Science, Hangzhou Normal University, Hangzhou, China.
Junyan YanSchool of Life and Environmental Sciences, Shaoxing University, Shaoxing, Zhejiang, China.
Lifang JinSchool of Life and Environmental Sciences, Shaoxing University, Shaoxing, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Fatty liver is considered the pathological basis for the development of glycogen storage disease type Ia (GSDIa); however, due to the lack of suitable animal models, the mechanism underlying fatty liver development in GSDIa is largely unknown. Methods: This study employed surrogate breastfeeding to enable the survival of glucose-6-phosphatase catalytic ( Results: KO-6 and KO-9 mice exhibited typical fatty liver phenotypes, and upregulation of glucose-6-phosphate (G6P). Moreover, both Western blot and qRT-PCR analysis showed significant upregulation of ChREBP, SREBP1 and fatty acid synthesis enzymes. RNA-seq heat maps revealed that KO-6 and KO-9 mice exhibited similar expression patterns, distinct from those observed in the wild-type (WT) and KO-3 groups. GO and KEGG analysis further revealed changes in lipid metabolism pathways in KO-6 and KO-9 mice, as well as PI3K-Akt, AMPK, and MAPK signaling. Western blot analysis showed that the Akt and mTOR pathways were activated, while the AMPK pathway was downregulated, indicating impaired autophagy. Finally, bezafibrate, a proliferator-activated receptor α (PPAR-α) agonist, enhanced autophagic activity and attenuated inflammatory responses, fat deposition, and glycogen storage in Conclusion: This study successfully generated a fatty liver model using

Indexed as

fatty liverglucose-6-phosphatase catalytic (G6PC)glycogen storage disease type ia (GSDIa)mouse modelppar-α agonist

Identifiers

PMID42741086
PMCPMC13572639

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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.