Evidence map›Paper›PMID 35741736›Full record

ArticleGenes2022

Genome-Wide RNA Sequencing Analysis in Human Dermal Fibroblasts Exposed to Low-Dose Ultraviolet A Radiation.

Jinyun Wang, Satoshi Yano, Kun Xie, Yoshihisa Ohata, Taichi Hara

Open access · goldAbstract read
In one paragraph

Article in Genes, 2022. 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
0.4field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Jinyun WangLaboratory of Food and Life Science, Faculty of Human Sciences, Waseda University, Tokorozawa 359-1192, Japan.
Satoshi YanoLaboratory of Food and Life Science, Faculty of Human Sciences, Waseda University, Tokorozawa 359-1192, Japan.
Kun XieLaboratory of Food and Life Science, Faculty of Human Sciences, Waseda University, Tokorozawa 359-1192, Japan.
Yoshihisa OhataLaboratory of Food and Life Science, Faculty of Human Sciences, Waseda University, Tokorozawa 359-1192, Japan.
Taichi HaraLaboratory of Food and Life Science, Faculty of Human Sciences, Waseda University, Tokorozawa 359-1192, Japan.ORCID 0000-0002-4722-6336
Waseda University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultraviolet A (UVA) radiation can pass through the epidermis and reach the dermal skin layer, contributing to photoaging, DNA damage, and photocarcinogenesis in dermal fibroblasts. High-dose UVA exposure induces erythema, whereas low-dose, long-term UVA exposure causes skin damage and cell senescence. Biomarkers for evaluating damage caused by low-dose UVA in fibroblasts are lacking, making it difficult to develop therapeutic agents for skin aging and aging-associated diseases. We performed RNA-sequencing to investigate gene and pathway alterations in low-dose UVA-irradiated human skin-derived NB1RGB primary fibroblasts. Differentially expressed genes were identified and subjected to Gene Ontology and reactome pathway analysis, which revealed enrichment in genes in the senescence-associated secretory phenotype, apoptosis, respiratory electron transport, and transcriptional regulation by tumor suppressor p53 pathways. Insulin-like growth factor binding protein 7 (IGFBP7) showed the lowest

Indexed as

FibroblastsUltraviolet RaysHumansRNASequence Analysis, RNASkinRNAbiomarkerdifferentially expressed geneFosIGFBP7low-dose UVAsenescence-associated secretory phenotypeultraviolet A

Identifiers

PMID35741736
PMCPMC9222854
OpenAlexW4281646907

What OpenQuestion 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 OpenQuestion graph.