Evidence map›Paper›PMID 41958541›Full record

ArticleJournal of translational autoimmunity2026

Ruxolitinib reverses alopecia areata via a triple mechanism: JAK-STAT inhibition, localized oxidative stress attenuation and selective apoptosis modulation.

Meiling Zhu, Hao Mu, Bo Wang, Mengting Han, Zhao Ma, Xiaopan Nie, Tong Wang, Liyuan Zhang, Feng Liang

Abstract read
In one paragraph

Article in Journal of translational autoimmunity, 2026. 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. Review
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

9 authors.

Meiling ZhuPharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.
Hao MuPharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.
Bo WangPharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.
Mengting HanPharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.
Zhao MaPharmaron Inc, No. 456 Bin-Hai 6th Road, Ningbo Hangzhou Bay New Area, Ningbo, 315336, P.R. China.
Xiaopan NiePharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.
Tong WangPharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.
Liyuan ZhangPharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.
Feng LiangPharmaron, Inc, No. 6 Taihe Road, Beijing Economic-Technological Development Area, Beijing, 100176, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alopecia areata (AA) is an autoimmune hair loss disorder driven by the IFN-γ-JAK-STAT signaling and cytotoxic T-cell attack. Although JAK inhibitors like ruxolitinib show clinical efficacy, their integrated mechanism remains unclear. This study elucidated ruxolitinib's therapeutic actions in a C3H/HeJ mouse model of AA induced by adoptive transfer of activated lymph node cells. Mice were treated daily with ruxolitinib or vehicle for 98 days, with weekly clinical scoring of hair loss. Comprehensive analyses quantified systemic and skin cytokines (IFN-γ, TNF-α, IL-5, IL-6, IL-10, and CXCL1/KC), oxidative stress markers (malondialdehyde [MDA] and superoxide dismutase), apoptosis (cleaved caspase-3), autophagy (LC3-II), immune infiltration (CD3

Indexed as

Alopecia areataApoptosisIFN-γJAK-STAT pathwayOxidative stressRuxolitinib

Identifiers

PMID41958541
PMCPMC13059316

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.