Evidence map›Paper›PMID 26697327›Full record

ArticleGenomics data2015

Transcriptional profiling of radiation damage and preventive treatments in a 3-dimensional (3D) human cell culture model of oral mucositis.

Maria P Lambros, Michael K DeSalvo, Jonathan Moreno, Hari Chandana Mulamalla, Lavanya Kondapalli

Open access · goldAbstract read
In one paragraph

Article in Genomics data, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 97% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. In vitro three-dimensional organotypic culture models of the oral mucosa.In vitro cellular & developmental biology. Animal · 2021
    Review
  2. The pathogenesis of mucositis: updated perspectives and emerging targets.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2019
    Review
  3. 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

5 authors at 1 institution in 1 country.

Maria P LambrosCollege of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA.
Michael K DeSalvoGran, LLC, Fullerton, CA 92835, USA.
Jonathan MorenoCollege of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA.
Hari Chandana MulamallaCollege of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA.
Lavanya KondapalliCollege of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA.
Western University of Health Sciences · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer patients who receive radiation are often afflicted by oral mucositis, a debilitating disease, characterized by mouth sores and difficulty in swallowing. Oftentimes, cancer patients afflicted with mucositis must stop life-saving therapies. Thus it is very important to prevent mucositis before it develops. Using a validated organotypic model of human oral mucosa, a 3-dimensional cell culture model of human oral keratinocytes, it has been shown that a mixture (NAC-QYD) of N-acetyl cysteine (NAC) and a traditional Chinese medicine, Qingre Liyan decoction (QYD), prevented radiation damage (Lambros et al., 2014). Here we provide detailed methods and analysis of microarray data for non-irradiated and irradiated human oral mucosal tissue with and without pretreatment with NAC, QYD and NAC-QYD. The microarray data been deposited in Gene Expression Omnibus (GEO): GSE62397. These data can be used to further elucidate the mechanisms of irradiation damage in oral mucosa and its prevention.

Identifiers

PMID26697327
PMCPMC4664678
OpenAlexW1075603440

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.