Evidence map›Paper›PMID 27696362›Full record

ArticleCurrent protocols in neuroscience2016

Cigarette Smoke Extract: A Preclinical Model of Tobacco Dependence.

Candice A Gellner, Daisy D Reynaga, Frances M Leslie

Abstract read
In one paragraph

Article in Current protocols in neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
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

34 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Relationship between Pulmonary Gas Exchange Function and Brain Uptake Dynamics Investigated with HyperpolarizedMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Potential Utilisation ofTropical life sciences research · 2024
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

3 authors.

Candice A GellnerDepartment of Pharmacology, University of California, Irvine, Irvine, California.
Daisy D ReynagaDepartment of Pharmacology, University of California, Irvine, Irvine, California.
Frances M LeslieDepartment of Pharmacology, University of California, Irvine, Irvine, California.

Funding

The role of non-nicotine tobacco smoke constituents in withdrawal and cravingR01DA040440 · NIDA · UNIVERSITY OF CALIFORNIA-IRVINE · PI LESLIE, FRANCES M. · 2015 to 2018
$1.3M
NIDA NIH HHS R01 DA040440
6 · The paper itself

Abstract

Animal models are used to study many human diseases, one of which is tobacco addiction. Most preclinical models use nicotine alone, although there are >7000 constituents present in tobacco smoke. The clinical literature suggests that cigarettes have a strong addictive potential, which is not paralleled in preclinical studies using nicotine alone. In order to address the gap between clinical and preclinical literature on tobacco dependence, cigarette smoke extracts containing tobacco constituents have been developed. This unit describes a procedure for producing an aqueous cigarette smoke extract (CSE) which animals readily self-administer. In addition, we describe how to make the apparatus for producing CSE and how to analyze the solution for nicotine content. © 2016 by John Wiley & Sons, Inc.

Indexed as

Tobacco ProductsTobacco Use DisorderAnimalsBehavior, AddictiveDrug Evaluation, PreclinicalModels, AnimalNicotineSmokingNicotinenicotineself-administrationsmokingtobacco constituents

Identifiers

PMID27696362
PMCPMC5113292

What OpenQuestion holds

Textmetadata
LicenceTDM
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.