Evidence map›Paper›PMID 21152696›Full record

ArticleMolecular medicine (Cambridge, Mass.)

Mammal cells double their total RNAs against diabetes, ischemia reperfusion and malaria-induced oxidative stress.

Zhong-Wei Zhang, Jian Cheng, Fei Xu, Ming Yuan, Jun-Bo Du, Jing Shang, Yong Wang, Lei Du, Zi-Lin Li, Shu Yuan

Open access · goldAbstract read
In one paragraph

Article in Molecular medicine (Cambridge, Mass.). 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
0.5field-weighted citation impact, top 31% 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, 4 citations in OpenAlex.

  1. Review
  2. Article
  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

10 authors at 4 institutions in 1 country.

Zhong-Wei ZhangCollege of Resources and Environmental Sciences, Sichuan Agriculture University, Chengdu, China.
Jian Cheng
Fei Xu
Ming Yuan
Jun-Bo Du
Jing Shang
Yong Wang
Lei Du
Zi-Lin Li
Shu Yuan
Sichuan University · CNSouthwest Minzu University · CNSichuan Agricultural University · CNXijing Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Total cellular RNA level is stable usually, although it may increase gradually during growth or decrease gradually under certain stressors. However, we found that mammal cell RNAs could be doubled within 24 h in response to free heme accumulation (ischemia reperfusion and malaria infection) or a high level of glucose treatment (diabetes). Clinical investigations in rats showed that pretreatment with heme (24 h for doubling total RNAs) alleviated oxidative damages caused by diabetes, and pretreatment with glucose (24 h for trebling total RNAs) alleviated oxidative damages caused by ischemia reperfusion or malaria infection. Therefore, this rapid RNA amplification may play an important role in mammal adaptation to diabetes, ischemia reperfusion and malaria infection-derived oxidative stress. This rapid RNA amplification is derived from glucose and heme, but not from their accompanying reactive oxygen species. Hexokinases endure glucose-derived reactive oxygen species accumulation but are not related glucose-derived RNA amplification. In contrast, the TATA box-binding protein (TBP) mediates all glucose- and heme-induced RNA amplification in mammal cells.

Indexed as

AnimalsBlotting, WesternCell LineDiabetes Mellitus, ExperimentalGlucoseHemeHumansHydrogen PeroxideMalaria, FalciparumOxidative StressPolymerase Chain ReactionRatsRats, Sprague-DawleyReperfusion InjuryRNASucroseGlucoseHemeHydrogen PeroxideRNASucroseSuperoxides

Identifiers

PMID21152696
PMCPMC3105149
OpenAlexW2396330921

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.