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Validation and in vivo characterization of research antibodies for Moesin, CD44, Midkine, and sFRP-1.

2023· preprint· en· W4386325591 on OpenAlexafffund
Suzanne Doolen, Riham Ayoubi, Carl Laflamme, Ranjita Betarbet, Elizabeth Zoeller, Sean-Paul G. Williams, Haian Fu, Allan I. Levey, Stacey J. Sukoff Rizzo

Bibliographic record

VenueF1000Research · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsMcGill University
FundersGenome CanadaOntario GenomicsMitacsGovernment of CanadaNational Institute on AgingEmory University
KeywordsMidkineIn vivoOpen peer reviewMedicineMoesinNeuroscienceAntibodyPlant biologyBiologyImmunologyInternal medicineBiotechnologyGeneticsCytoskeletonCellBotany

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Background:</ns4:bold> 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 <ns4:italic>in vitro</ns4:italic> and <ns4:italic>in vivo</ns4:italic> studies such that the levels of target proteins in target tissues can be quantified. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> 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. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> 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. </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> These data confirm the utility of these selective commercially available antibodies against Moesin, CD44, Midkine, and sFRP-1 for <ns4:italic>in vivo</ns4:italic> studies in mice and provide insight into the use of 5XFAD mice for <ns4:italic>in vivo</ns4:italic> target engagement studies for these target proteins. </ns4:p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.093
GPT teacher head0.412
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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