Evidence map›Paper›PMID 39734533›Full record

ReviewFundamental research2024

Macrophage migration inhibitory factor (MIF) in CNS diseases: Functional regulation and potential therapeutic indication.

Yu Zhang, Zhexiang Yu, Na Ye, Xuechu Zhen

Abstract readReview
In one paragraph

Review in Fundamental research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Immune-proteo-metabolomic changes link to Aβ and tau pathology in Alzheimer disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

4 authors.

Yu ZhangJiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.
Zhexiang YuJiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.
Na YeJiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.
Xuechu ZhenJiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macrophage migration inhibitory factor (MIF) is a multifunctional protein that possesses cytokine, enzyme, and endocrine activities and acts as a chaperone-like molecule. Owing to its immune-inflammatory regulatory properties, the role of MIF has long been an attractive target in research on various autoimmune and inflammatory disorders. MIF is also widely expressed in the central nervous system (CNS), and its potential roles in CNS disorders have become a focus to elucidate the physiological and pathological effects of MIF and to explore its potential significance in the treatment of CNS diseases. Previously, the majority of work on MIF functional regulation was focused on MIF tautomerase inhibitors. However, mounting information has indicated that the functions of MIF extend far beyond its tautomerase activity. Here, we review the recent advances in understanding the complex roles of MIF in the pathogenesis of CNS disorders as well as the discovery and design of small molecules targeted to tautomerase and nuclease of MIF.

Indexed as

Central nervous system diseasesDrug discoveryInflammationMacrophage migration inhibitory factorSmall molecular inhibitors

Identifiers

PMID39734533
PMCPMC11670708

What OpenQuestion holds

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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.