Evidence map›Paper›PMID 28240526›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2017

Expression Changes of Apoptotic Genes in Tissues from Mice Exposed to Nicotine

Cyrus Jalili, Mohammad Reza Salahshoor, Mohammad Taher Moradi, Maryam Ahookhash, Mehdi Taghadosi, Maryam Sohrabi

Abstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Effect of Harmine on Nicotine-Induced Kidney Dysfunction in Male Mice.International journal of preventive medicine · 2019
    Article
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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

6 authors at 1 institution in 1 country.

Cyrus JaliliFertility and Infertility Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran. Email:mery_sohrabi@yahoo.com
Mohammad Reza Salahshoor
Mohammad Taher Moradi
Maryam Ahookhash
Mehdi Taghadosi
Maryam Sohrabi
Kermanshah University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Smoking is the leading preventable cause of various diseases such as lung cancer, chronic obstructive pulmonary disease and cardiovascular disease. Nicotine, one of the major toxic components of tobacco, contributes to the pathogenesis of different diseases. Methods: Given the controversy about nicotine toxicity, the present study was conducted to determine apoptotic effects of nicotine on the heart, kidney, lung and liver of male mice. Real-time PCR was performed to identify mRNA expression changes in apoptotic-related genes between nicotine treated and control mice. Result: In the heart and lung, nicotine caused significant decrease in P53, Bax and Caspase-3 mRNA expression levels compared to the control group. However, in the kidney and liver, the result was significant increase in Bax, Caspase-2, Caspase-3 and a significant decrease in P53 mRNA expression (p<0.01). DNA fragmentation assays indicated no fragmentation in the heart and lung, but in the kidney and liver of nicotine treated mice, isolated DNA was fragmented. Conclusion: Our study provided insight into the molecular mechanisms of nicotine anti-apoptotic effects on the heart and lung as well as pro-apoptotic effects on kidney and liver via a P53-independent pathway.

Indexed as

apoptosiscaspase-2liverNicotineP53

Identifiers

PMID28240526
PMCPMC5563107
OpenAlexW2587379217

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.