Evidence map›Paper›PMID 35510038›Full record

ArticleDisease markers2022

Liraglutide Alleviates Diabetic Atherosclerosis through Regulating Calcification of Vascular Smooth Muscle Cells.

Li-Li Shi, Ming Hao, Zhou-Yun Jin, Gui-Fang Peng, Ying-Ying Tang, Hong-Yu Kuang

Open access · hybridFull text read
In one paragraph

Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
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

10 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Li-Li ShiDepartment of Cadre Ward, The First Affiliated Hospital of Harbin Medical University, Harbin 150081, China.
Ming HaoDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin 150081, China.
Zhou-Yun JinDepartment of Cadre Ward, The First Affiliated Hospital of Harbin Medical University, Harbin 150081, China.
Gui-Fang PengDepartment of Cadre Ward, The First Affiliated Hospital of Harbin Medical University, Harbin 150081, China.
Ying-Ying TangDepartment of Endocrinology, The Heilongjiang Provincial Hospital, Harbin 150001, China.ORCID https://orcid.org/0000-0001-9319-3486
Hong-Yu KuangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin 150081, China.ORCID https://orcid.org/0000-0001-7502-8321
Harbin Medical University · CNHeilongjiang Provincial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetes mellitus (DM) is a group of metabolic diseases characterized by hyperglycemia, which can induce the development of atherosclerosis (AS). Calcification of vascular smooth muscle cells (VSMCs) exerts an important role in the process of AS. In this study, the effects of liraglutide (LIRA) on VSMC under high-glucose condition and its mechanism were explored. Method: After VSMC was treated by high glucose with or without LIRA Result: The positive rate of SM Conclusion: LIRA inhibited the abnormalities in VSMC calcification mediated by the GLP-1R, which was related to PI3K/Akt and ERK1/2 MAPK pathways. Therefore, the prospect and significance of LIRA in the treatment of DM complicated with AS were clarified.

Indexed as

AtherosclerosisCalcinosisDiabetes MellitusAnimalsCells, CulturedGlucoseHumansLiraglutideMuscle, Smooth, VascularMyocytes, Smooth MusclePhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktRatsGlucoseLiraglutidePhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-akt

Identifiers

PMID35510038
PMCPMC9061067
OpenAlexW4224441884

What Socratic holds

Textfull text, public
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.