Evidence map›Paper›PMID 34526890›Full record

ArticleFrontiers in aging neuroscience2021

Efficacy of Δ

Prakash Nidadavolu, Andras Bilkei-Gorzo, Michael Krämer, Britta Schürmann, Michela Palmisano, Eva C Beins, Burkhard Madea, Andreas Zimmer

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 14% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Ageing, Neurodegeneration and the Endocannabinoid System.Current topics in behavioral neurosciences · 2026
    Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Chronic low-dose ΔScientific reports · 2023
    Article
  19. Article
  20. Article
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

8 authors at 1 institution in 1 country.

Prakash NidadavoluInstitute of Molecular Psychiatry, Medical Faculty, University of Bonn, Bonn, Germany.
Andras Bilkei-GorzoInstitute of Molecular Psychiatry, Medical Faculty, University of Bonn, Bonn, Germany.
Michael KrämerInstitute of Forensic Medicine, Medical Faculty, University of Bonn, Bonn, Germany.
Britta SchürmannInstitute of Molecular Psychiatry, Medical Faculty, University of Bonn, Bonn, Germany.
Michela PalmisanoInstitute of Molecular Psychiatry, Medical Faculty, University of Bonn, Bonn, Germany.
Eva C BeinsInstitute of Molecular Psychiatry, Medical Faculty, University of Bonn, Bonn, Germany.
Burkhard MadeaInstitute of Forensic Medicine, Medical Faculty, University of Bonn, Bonn, Germany.
Andreas ZimmerInstitute of Molecular Psychiatry, Medical Faculty, University of Bonn, Bonn, Germany.
University of Bonn · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Decline in cognitive performance, an aspect of the normal aging process, is influenced by the endocannabinoid system (ECS). Cannabinoid receptor 1 (CB1) signaling diminishes with advancing age in specific brain regions that regulate learning and memory and abolishing CB1 receptor signaling accelerates cognitive aging in mice. We recently demonstrated that prolonged exposure to low dose (3 mg/kg/day) Δ

Indexed as

agingcannabidiolcognitionendocannabinoid systemΔ9-tetrahydrocannabinol

Identifiers

PMID34526890
PMCPMC8435893
OpenAlexW3198119351

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.