Evidence map›Paper›PMID 39684358›Full record

ArticleInternational journal of molecular sciences2024

Trehalose Alleviates D-Galactose-Induced Aging-Related Granulosa Cell Death in Ovaries.

Huaming Xi, Xinyu Chen, Kai Liang, Xianglong Wang, Feng Jiang, Yuan Li, Dong Niu

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

7 authors.

Huaming XiKey Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang A&F University, Hangzhou 311300, China.
Xinyu ChenKey Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang A&F University, Hangzhou 311300, China.
Kai LiangKey Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang A&F University, Hangzhou 311300, China.
Xianglong WangKey Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang A&F University, Hangzhou 311300, China.
Feng JiangKey Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang A&F University, Hangzhou 311300, China.
Yuan LiKey Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang A&F University, Hangzhou 311300, China.ORCID 0009-0002-5304-2127
Dong NiuKey Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Laboratory for Animal Health Inspection & Internet Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang A&F University, Hangzhou 311300, China.

Funding

2024 National College Student Innovation and Entrepreneurship Training Program 202410341010National Natural Science Foundation of China 32402753Zhejiang A&F University Talent Initiative Project 2022LFR066Zhejiang Provincial Natural Science Foundation of China LQ24C170001
6 · The paper itself

Abstract

Ovarian dysfunction caused by aging restricts female reproductive capacity and is accompanied by oxidative stress and impaired autophagy. Recent studies have shown that trehalose (Tre) can activate autophagy and have antioxidant effects. However, whether Tre can be used to attenuate ovarian aging remains unclear. Therefore, the anti-aging effects of Tre on the ovary were explored both in vivo and in vitro. D-galactose (D-gal) was administered i.p. daily (200 mg/kg body weight) for 8 weeks to establish the mouse ovarian aging model (n = 10). We found that Tre significantly reversed ovarian weight loss and reduced the number of TUNEL-positive granulosa cells caused by D-gal in mouse ovaries. Tre elevated the protein expression levels of LC3-II, Parkin, PINK1, Beclin1, and LAMP2 in ovaries. Mitochondrial-related proteins TOM20 and COX IV expression levels were increased by Tre administration. In vitro studies further supported these findings, showing that Tre treatment significantly reduced the number of SA-β-gal and PI-positive cells, and decreased ROS levels in cultured granulosa cells. Thus, Tre alleviates ovarian aging by activating mitophagy and reducing oxidative stress, suggesting its potential as an anti-aging agent for ovarian health.

Indexed as

AgingGalactoseGranulosa CellsOvaryOxidative StressTrehaloseAnimalsAutophagyCell DeathFemaleMiceMitophagyReactive Oxygen SpeciesGalactoseReactive Oxygen SpeciesTrehaloseaginggranulosa cellmitophagyovarytrehalose

Identifiers

PMID39684358
PMCPMC11641667

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.