ArticleF1000Research2023
Validation and
Article in F1000Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Meeting report of the fifth annual workshop on Principles and Techniques for Improving Preclinical to Clinical Translation in Alzheimer's Disease Research.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Validation andF1000Research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Background: A major goal of the Target Enablement to Accelerate Therapy Development for Alzheimer's disease (TREAT-AD) program is to develop and identify high-quality tools to test target or mechanistic hypotheses. As part of this initiative, it is important that commercial reagents including research antibodies being used to interrogate drug targets have confirmed validation data in knock-out cell lines. Ideally, these antibodies should also have utility for both Methods: We evaluated commercial antibodies against TREAT-AD protein targets Moesin (Uniprot ID: P26038), CD44 (Uniprot ID: P16070), Midkine (Uniprot ID: P21741) and Secreted frizzled-related protein 1, referred to as "sFRP-1" (sFRP-1; Uniprot ID: Q8N474). Moesin, Midkine and sFRP-1, that were confirmed as selective based on data in knock-out cell lines. Western blot analysis was used to compare protein levels in brain homogenates from a mouse model with AD-relevant pathology (5XFAD) versus age-matched C57BL/6J control mice. Results: Anti-Moesin ab52490 reacted in mouse brain homogenate with a predicted molecular weight of 68 kDa. Moesin protein expression was 2.8 times higher in 5xFAD compared to WT. Anti-CD44 ab189524 reacted with a band at the predicted size of 82 kDa. CD44 protein expression was 1.9 times higher in 5xFAD compared to WT. Anti-Midkine AF7769 reacted with a band ~16 kDa and a 17.8 times greater expression in 5xFAD compared to WT. Anti-sFRP-1 ab267466 reacted with a band at 35 kDa as predicted. sFRP-1 protein expression was 11.9 times greater in 5xFAD compared to WT. Conclusions: These data confirm the utility of these selective commercially available antibodies against Moesin, CD44, Midkine, and sFRP-1 for
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Identifiers
What OpenQuestion holds
Registered trials
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.