Evidence map›Paper›PMID 36338621›Full record

ArticleFrontiers in surgery2022

Proteomics as a tool to improve novel insights into skin diseases: what we know and where we should be going.

Sheng-Yuan Zheng, Xi-Min Hu, Kun Huang, Zi-Han Li, Qing-Ning Chen, Rong-Hua Yang, Kun Xiong

Open access · goldAbstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
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, 18 citations in OpenAlex.

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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

7 authors at 4 institutions in 1 country.

Sheng-Yuan ZhengDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Xi-Min HuDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
Kun HuangClinical Medicine Eight-Year Program, Xiangya School of Medicine, Central South University, Changsha, China.
Zi-Han LiClinical Medicine Eight-Year Program, Xiangya School of Medicine, Central South University, Changsha, China.
Qing-Ning ChenClinical Medicine Eight-Year Program, Xiangya School of Medicine, Central South University, Changsha, China.
Rong-Hua YangDepartment of Burn and Plastic Surgery, Guangzhou First People's Hospital, School of 173 Medicine, South China University of Technology, Guangzhou, China.
Kun XiongDepartment of Anatomy and Neurobiology, School of Basic Medical Science, Central South University, Changsha, China.
Central South University · CNXiangya Hospital Central South University · CNGuangzhou First People's Hospital · CNHainan Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Biochemical processes involved in complex skin diseases (skin cancers, psoriasis, and wound) can be identified by combining proteomics analysis and bioinformatics tools, which gain a next-level insight into their pathogenesis, diagnosis, and therapeutic targets. Methods: Articles were identified through a search of PubMed, Embase, and MEDLINE references dated to May 2022, to perform system data mining, and a search of the Web of Science (WoS) Core Collection was utilized to conduct a visual bibliometric analysis. Results: An increased trend line revealed that the number of publications related to proteomics utilized in skin diseases has sharply increased recent years, reaching a peak in 2021. The hottest fields focused on are skin cancer (melanoma), inflammation skin disorder (psoriasis), and skin wounds. After deduplication and title, abstract, and full-text screening, a total of 486 of the 7,822 outcomes met the inclusion/exclusion criteria for detailed data mining in the field of skin disease tooling with proteomics, with regard to skin cancer. According to the data, cell death, metabolism, skeleton, immune, and inflammation enrichment pathways are likely the major part and hotspots of proteomic analysis found in skin diseases. Also, the focuses of proteomics in skin disease are from superficial presumption to depth mechanism exploration within more comprehensive validation, from basic study to a combination or guideline for clinical applications. Furthermore, we chose skin cancer as a typical example, compared with other skin disorders. In addition to finding key pathogenic proteins and differences between diseases, proteomic analysis is also used for therapeutic evaluation or can further obtain in-depth mechanisms in the field of skin diseases. Conclusion: Proteomics has been regarded as an irreplaceable technology in the study of pathophysiological mechanism and/or therapeutic targets of skin diseases, which could provide candidate key proteins for the insight into the biological information after gene transcription. However, depth pathogenesis and potential clinical applications need further studies with stronger evidence within a wider range of skin diseases.

Indexed as

bibliometric analysisdata mining studymolecular biomarkerpathogenesisproteomicsskin diseasetreatment

Identifiers

PMID36338621
PMCPMC9633964
OpenAlexW4306965073

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.