Evidence map›Paper›PMID 41217665›Full record

ArticleMolecular neurobiology2025

miR-133b-3p Mitigates D-Galactose-Induced Hippocampal Neuron Aging Through Autophagy Regulation via the MAPK/ERK Signaling Pathway.

Yang Cao, Chen Zhao, Jiaxin Li, Qiang Gao, Chunmei Lv, Jiao Wang, Na Qiang, Wenwen Zhang, Huiyu Su, Xinyu Min and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular neurobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Yang Cao *Department of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Chen Zhao *Department of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Jiaxin Li *Department of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Qiang GaoDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Chunmei LvDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Jiao WangDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Na QiangDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Wenwen ZhangDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Huiyu SuDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Xinyu MinDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China.
Jinfeng LiuPain Department of the Second Affiliated Hospital of Harbin Medical University, Harbin, 150081, China.
Xiaoqi DaiPain Department of the Second Affiliated Hospital of Harbin Medical University, Harbin, 150081, China. daixiaoqi@hrbmu.edu.cn.
Hui ZhuDepartment of Physiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, 150081, China. zhuhui@ems.hrbmu.edu.cn.

Funding

Natural Science Foundation of Heilongjiang Province LH2024H019Scientific Research Project of Basic Scientific Research Business of Heilongjiang Provincial Colleges and Universities in 2023 2023-KYYWF-0251Scientific Research Project of the Provincial Scientific Research Institute of Heilongjiang Province CZKYF2023-1-A011
6 · The paper itself

Abstract

Although remarkable progress has been achieved in contemporary medical research, effective drugs or prophylactic approaches targeting neurodegenerative diseases associated with aging are still limited. Increasing evidence suggests that microRNAs (miRNAs) are closely associated with age-related neurological diseases, positioning them as novel therapeutic targets. Autophagy in neurons participates in the renewal of damaged or aged endoplasmic reticulum, mitochondria, other organelles, and aggregated proteins during aging. This study evaluated the anti-aging mechanism of miR-133b-3p in D-galactose (D-gal)-induced hippocampal neurons. A mouse aging model was established by long-term D-gal injection and compared with 18-month-old naturally aged mice to verify and confirm the successful establishment of the aging model, providing a more reliable experimental basis for exploring the changes in mechanisms during aging.Compared with young mice, the D-gal group and the 18 M group showed decreased learning and memory abilities, altered neuronal structures, downregulated miR-133b-3p expression, and inhibited MAPK/ERK signaling pathway and autophagy. In addition, in the D-gal-induced HT22 cell senescence model, autophagy was inhibited, and the expression of the age-related protein p53 was downregulated. We also found that miR-133b-3p overexpression under aging conditions can activate autophagy via the MAPK/ERK signaling pathway and exert neuroprotection in hippocampal neurons. However, the effect of miR-133b-3p in reducing cellular aging damage was weakened when the MAPK/ERK signaling pathway was blocked or autophagy was inhibited.This study revealed the significant mechanism whereby miR-133b-3p protects hippocampal neurons in aging mice. miR-133b-3p alleviates D-gal-induced cellular aging damage by activating autophagy through the MAPK/ERK signaling pathway.

Indexed as

AgingAutophagyCellular SenescenceGalactoseHippocampusMAP Kinase Signaling SystemMicroRNAsNeuronsAnimalsCell LineMaleMiceMice, Inbred C57BLGalactoseMicroRNAsMirn133 microRNA, mouseAgingAutophagyHippocampal neuronMAPK/ERKmiR-133b-3p

Identifiers

What Socratic holds

Textmetadata
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.