Evidence map›Paper›PMID 40641997›Full record

ArticleFrontiers in pharmacology2025

Effects of

Nanzhi Hu, Kaiyue Wang, Xing Ge, Xin Zhang, Xiaojie Zheng, Shifang Sun

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 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

6 authors.

Nanzhi HuDepartment of Geriatrics, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Kaiyue WangDepartment of Geriatrics, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Xing GeDepartment of Food Science and Engineering, Ningbo University, Ningbo, China.
Xin ZhangDepartment of Food Science and Engineering, Ningbo University, Ningbo, China.
Xiaojie ZhengWenzhou Vocational College of Science and Technology, Wenzhou, China.
Shifang SunDepartment of Geriatrics, The First Affiliated Hospital of Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As we get older, we experience a variety of symptoms such as memory and cognitive decline in learning. In the process of aging, neuroinflammatory response is one of the main reasons for the occurrence of cognitive dysfunction. Methods: DOFF samples were extracted by water extraction assisted ultrasonic ethanol method. The DOFF composition was determined by LC-MS/MS method. An aging mouse model was established using D-galactose (D-gal) induced mice. 16S rDNA sequencing was used to analyze intestinal flora, hematoxylin/eosin staining (H&E) and immunohistochemical staining were used to analyze colonic and hippocampal tissue damage and related proteins, and ElISA was used to determine related inflammatory factors. The Y-maze experiment was used to test the cognitive ability of mice, the expression of related synaptic protein was detected by WB, and Iba-1 was labeled by immunofluorescence to study the effects of DOFF on inflammatory response and cognitive function by regulating intestinal microbiota. Results: The results showed that DOFF intervention could regulate the relative abundance of intestinal flora in D-gal mice, including the relative abundance of Discussion: DOFF can improve cognitive dysfunction by regulating intestinal microbiota composition, enhancing intestinal barrier integrity in D-GAL-induced aging mice, improving neuroinflammation, and alleviating hippocampal neuron damage.

Indexed as

agingcognitionDendrobium officinale Kimura & Migo flower flavonoidsinflammationintestinal flora

Identifiers

PMID40641997
PMCPMC12240995

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.