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Record W2963002070 · doi:10.1016/j.clinms.2019.07.003

Detection and characterization of TDP-43 in human cells and tissues by multiple reaction monitoring mass spectrometry

2019· article· en· W2963002070 on OpenAlexafffund
Taylor D. Pobran, Lauren M. Forgrave, Yu Zi Zheng, John G. Lim, Ian R. Mackenzie, Mari L. DeMarco

Bibliographic record

VenueClinical mass spectrometry · 2019
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsSt. Paul's HospitalProvidence Health CareVancouver General HospitalUniversity of British Columbia
FundersAlzheimer SocietyAssociation for Frontotemporal DegenerationAlzheimer's Drug Discovery Foundation
KeywordsChemistryMass spectrometryWestern blotHuman brainTandem mass spectrometryAmyotrophic lateral sclerosisNucleic acidMultiplexCharacterization (materials science)Frontotemporal dementiaComputational biologyMolecular biologyBiologyCell biologyBiochemistryDementiaNeurosciencePathologyChromatographyNanotechnologyBioinformaticsMedicine

Abstract

fetched live from OpenAlex

Transactive response DNA-binding protein 43 kDa (TDP-43) is a highly conserved and widely expressed protein in human tissues that regulates nucleic acid processing. In frontotemporal dementia and amyotrophic lateral sclerosis, however, TDP-43 forms insoluble aggregates in central nervous tissues. These pathological deposits of TDP-43 have been primarily studied by ligand binding, namely western blot analysis, and, thus, methods with greater structural resolution are needed to aid in our understanding of the pathological processes associated with TDP-43 misfolding and aggregation. Toward this goal, we have developed a selective and multiplex method for the detection and characterization of TDP-43 using liquid chromatography tandem mass spectrometry. As proof-of-concept, the method was applied to the detection and characterization of TDP-43 in human cell lines and human brain tissue.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.033
GPT teacher head0.344
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2019
Admission routes2
Has abstractyes

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