Evidence map›Paper›PMID 37781514›Full record

ReviewInternational journal of biological sciences2023

Deciphering The Emerging Role of Programmed Cell Death in Diabetic Wound Healing.

Jingyu Song, Keyu Zhu, Haiping Wang, Min Wu, Yiping Wu, Qi Zhang

Abstract readReview
In one paragraph

Review in International journal of biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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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.

Jingyu SongDepartment of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Keyu ZhuDepartment of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Haiping WangDepartment of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Min WuDepartment of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Yiping WuDepartment of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Qi ZhangDepartment of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic wounds are characterized by delayed and incomplete healing. As one of the most common complications of diabetes, diabetic wounds can be fatal in some cases. Programmed cell death (PCD) is an active and ordered cell death mode determined by genes, including apoptosis, autophagy, pyroptosis, necroptosis, ferroptosis, and cuproptosis. It is currently believed that PCD plays a crucial role in diabetic wound healing. Diabetic hyperglycemic environments can lead to abnormal PCD in various cells during healing processes, thereby affecting the activity and function of cells and interfering with diabetic wound healing. Therefore, this review focuses on the new roles and mechanisms of PCD in diabetic wound healing. Moreover, the challenges and perspectives related to PCD in diabetic wound healing are presented, which will bring new insights to improve diabetic wound healing.

Indexed as

Diabetes MellitusWound HealingApoptosisCell DeathHumansPyroptosisApoptosisAutophagy.Diabetic Wound HealingProgrammed Cell Death

Identifiers

PMID37781514
PMCPMC10539695

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.