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Record W2339432134 · doi:10.1007/978-1-60761-938-3_7

Detection of Multiple Proteins in Intracerebral Vessels by Confocal Microscopy

2010· article· en· W2339432134 on OpenAlexaff
Janet L. Manias, Anish Kapadia, Sukriti Nag

Bibliographic record

VenueMethods in molecular biology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConfocal microscopyConfocalChemistryCell biologyBlood–brain barrierContext (archaeology)Fluorescence microscopeBlood proteinsBiophysicsFluorescenceBiologyBiochemistryNeuroscienceCentral nervous system

Abstract

fetched live from OpenAlex

Assessment of the blood-brain barrier (BBB) may involve the localization of endothelial proteins within the context of endothelial permeability to plasma proteins. The use of antibodies conjugated to fluorescent dyes, coupled with analysis by confocal microscopy, allows for the detection of multiple proteins in components of the neurovascular unit including endothelium and astrocytes. This chapter provides a detailed protocol for detection of three proteins in fixed or frozen sections of rat brain using three fluorophores with unique excitation/emission spectra. Also included is a protocol for tyramide signal amplification, which is useful for detecting proteins of low abundance, and methods for quantitation of intracerebral vessels expressing a particular protein of interest with and without BBB breakdown to plasma proteins.

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)0.000
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.372
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.364
Teacher spread0.346 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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