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Record W2094988852 · doi:10.1074/mcp.m114.040113

Targeting Synaptic Pathology with a Novel Affinity Mass Spectrometry Approach

2014· article· en· W2094988852 on OpenAlexaff
Ann Brinkmalm, Gunnar Brinkmalm, William G. Honer, Julie A. Moreno, Joel Jakobsson, Giovanna R. Mallucci, Henrik Zetterberg, Kaj Blennow, Annika Öhrfelt

Bibliographic record

VenueMolecular & Cellular Proteomics · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of British Columbia
FundersDemensfondenSwedish Brain Power
KeywordsSynaptic membraneNeuroscienceProteomicsChemistryMembrane proteinFunction (biology)BiologyCell biologyBiochemistryMembrane

Abstract

fetched live from OpenAlex

We report a novel strategy for studying synaptic pathology by concurrently measuring levels of four SNARE complex proteins from individual brain tissue samples. This method combines affinity purification and mass spectrometry and can be applied directly for studies of SNARE complex proteins in multiple species or modified to target other key elements in neuronal function. We use the technique to demonstrate altered levels of presynaptic proteins in Alzheimer disease patients and prion-infected mice.

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)0.000
metaresearch head score (Gemma)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.023
GPT teacher head0.255
Teacher spread0.232 · 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

Citations30
Published2014
Admission routes1
Has abstractyes

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