Evidence map›Paper›PMID 21537472›Full record

ArticleWorld journal of biological chemistry2010

Suofu Qin's work on studies of cell survival signaling in cancer and epithelial cells.

Suofu Qin

Open access · hybridAbstract read
In one paragraph

Article in World journal of biological chemistry, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 89% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Suofu QinSuofu Qin, Retinal Disease Research, Department of Biological Sciences, Allergan, Inc., 2525 Dupont Drive, Irvine, CA 92612-1599, United States.
Allergan (Ireland) · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reactive oxygen species (ROS) encompass a variety of diverse chemical species including superoxide anions, hydrogen peroxide, hydroxyl radicals and peroxynitrite, which are mainly produced via mitochondrial oxidative metabolism, enzymatic reactions, and light-initiated lipid peroxidation. Over-production of ROS and/or decrease in the antioxidant capacity cause cells to undergo oxidative stress that damages cellular macromolecules such as proteins, lipids, and DNA. Oxidative stress is associated with ageing and the development of age-related diseases such as cancer and age-related macular degeneration. ROS activate signaling pathways that promote cell survival or lead to cell death, depending on the source and site of ROS production, the specific ROS generated, the concentration and kinetics of ROS generation, and the cell types being challenged. However, how the nature and compartmentalization of ROS contribute to the pathogenesis of individual diseases is poorly understood. Consequently, it is crucial to gain a comprehensive understanding of the molecular bases of cell oxidative stress signaling, which will then provide novel therapeutic opportunities to interfere with disease progression via targeting specific signaling pathways. Currently, Dr. Qin's work is focused on inflammatory and oxidative stress responses using the retinal pigment epithelial (RPE) cells as a model. The study of RPE cell inflammatory and oxidative stress responses has successfully led to a better understanding of RPE cell biology and identification of potential therapeutic targets.

Indexed as

CancerInflammationOxidative stressRetinal pigment epithelial cellsSignal transductionTherapeutic target

Identifiers

PMID21537472
PMCPMC3083942
OpenAlexW2064401161

What OpenQuestion holds

Textmetadata
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.