Evidence map›Paper›PMID 36389813›Full record

ArticleFrontiers in immunology2022

Establishment and validation of evaluation models for post-inflammatory pigmentation abnormalities.

Yushan Zhang, Hongliang Zeng, Yibo Hu, Ling Jiang, Chuhan Fu, Lan Zhang, Fan Zhang, Xiaolin Zhang, Lu Zhu, Jinhua Huang and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. IL-33 and IL-37: A Possible Axis in Skin and Allergic Diseases.International journal of molecular sciences · 2022
    Review
  6. 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

12 authors.

Yushan ZhangDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Hongliang ZengInstitute of Chinese Materia Medica, Hunan Academy of Chinese Medicine, Changsha, China.
Yibo HuDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Ling JiangDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Chuhan FuDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Lan ZhangDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Fan ZhangDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Xiaolin ZhangDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Lu ZhuDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Jinhua HuangDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Jing ChenDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Qinghai ZengDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Post-inflammatory skin hyper- or hypo-pigmentation is a common occurrence with unclear etiology. There is currently no reliable method to predict skin pigmentation outcomes after inflammation. In this study, we analyzed the 5 GEO datasets to screen for inflammatory

Indexed as

MelaninsSkin PigmentationCytokinesMonophenol MonooxygenaseSkinCytokinesMelaninsMonophenol Monooxygenaseevaluation modelsIL-37machine learningmelanogenesispost-inflammatory pigmentation abnormalities

Identifiers

PMID36389813
PMCPMC9646533

What OpenQuestion holds

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Registered trials

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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.