Evidence map›Paper›PMID 38318145›Full record

ReviewFrontiers in pharmacology2024

Research progress on antidepressant effects and mechanisms of berberine.

Yang Gao, Kexin Nie, Hongzhan Wang, Hui Dong, Yueheng Tang

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 pooled it
–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

10 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Pooled it
  4. Review
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  7. Article
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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

5 authors.

Yang GaoInstitute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Kexin NieInstitute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Hongzhan WangInstitute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Hui DongInstitute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yueheng TangInstitute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Depression, a global health problem with growing prevalence, brings serious impacts on the daily life of patients. However, the antidepressants currently used in clinical are not perfectly effective, which greatly reduces the compliance of patients. Berberine is a natural quaternary alkaloid which has been shown to have a variety of pharmacological effects, such as hypoglycemic, lipid-regulation, anti-cancer, antibacterial, anti-oxidation, anti-inflammatory, and antidepressant. This review summarizes the evidence of pharmacological applications of berberine in treating depression and elucidates the mechanisms of berberine regulating neurotransmitter levels, promoting the regeneration of hippocampal neurons, improving hypothalamic-pituitary-adrenal axis dysfunction, anti-oxidative stress, and suppressing inflammatory status in order to provide a reference for further research and clinical application of berberine.

Indexed as

berberinecell regenerationdepressionHPA axisinflammationneurotransmitteroxidative stress

Identifiers

PMID38318145
PMCPMC10839030

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.