Evidence map›Paper›PMID 38964475›Full record

ArticleJournal of neuroscience methods2024

A Systematic Online Living Evidence Summary of experimental Alzheimer's disease research.

Kaitlyn Hair, Emma Wilson, Olena Maksym, Malcolm R Macleod, Emily S Sena

Abstract read
In one paragraph

Article in Journal of neuroscience methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. 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

5 authors.

Kaitlyn HairCentre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK.
Emma WilsonCentre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK.
Olena MaksymCentre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK.
Malcolm R MacleodCentre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK.
Emily S SenaCentre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK. Electronic address: Emily.Sena@ed.ac.uk.

Funding

Wellcome Trust 204804
6 · The paper itself

Abstract

backgroundDespite extensive investment, the development of effective treatments for Alzheimer's disease (AD) has been largely unsuccessful. To improve translation, it is crucial to ensure the quality and reproducibility of foundational evidence generated from laboratory models. Systematic reviews play a key role in providing an unbiased overview of the evidence, assessing rigour and reporting, and identifying factors that influence reproducibility. However, the sheer pace of evidence generation is prohibitive to evidence synthesis and assessment. NEW

methodTo address these challenges, we have developed AD-SOLES, an integrated workflow of automated tools that collect, curate, and visualise the totality of evidence from in vivo experiments.

resultsAD-SOLES is a publicly accessible interactive dashboard aiming to surface and expose data from in vivo experiments. It summarises the latest evidence, tracks reporting quality and transparency, and allows research users to easily locate evidence relevant to their specific research question. COMPARISON WITH EXISTING

methodsUsing automated screening methodologies within AD-SOLES, systematic reviews can begin at an accelerated starting point compared to traditional approaches. Furthermore, through text-mining approaches within the full-text of publications, users can identify research of interest using specific models, outcomes, or interventions without relying on details in the title and/or abstract.

conclusionsBy automating the collection, curation, and visualisation of evidence from in vivo experiments, AD-SOLES addresses the challenges posed by the rapid pace of evidence generation. AD-SOLES aims to offer guidance for research improvement, reduce research waste, highlight knowledge gaps, and support informed decision making for researchers, funders, patients, and the public.

Indexed as

Alzheimer DiseaseAnimalsBiomedical ResearchData MiningDisease Models, AnimalHumansInternetAlzheimer’s diseaseBiocurationEvidence synthesisLaboratory modelsReproducibilitySystematic reviewTransparency

Identifiers

PMID38964475
PMCPMC7617163

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.