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Record W2739417980 · doi:10.1149/ma2017-02/55/2325

(Invited) Detection of D-Serine Using an Enzymatic Amperometric Biosensor and Its Localized Detection Using Scanning Electrochemical Microscopy

2017· article· en· W2739417980 on OpenAlexaff
David Polcari, Samuel C. Perry, Loredano Pollegioni, Matthias Geißler, Janine Mauzeroll

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmino Acid Enzymes and Metabolism
Canadian institutionsNational Research Council CanadaMcGill University
Fundersnot available
KeywordsScanning electrochemical microscopySerineBiosensorBiophysicsChemistryIn vivoBiochemistryXenopusEnzymeBiologyElectrochemistryElectrode

Abstract

fetched live from OpenAlex

D-Serine acts as an endogenous co-agonist for N -methyl-D-aspartate receptors at synapses, making it essential for proper brain development and function. This amino acid has also been linked to several neurodegenerative diseases such as Alzheimer’s disease and dementia. Nevertheless, the primary site and mechanism of D-serine release remains unclear. We recently demonstrated the use of an enzymatic amperometric biosensor for the in vivo quantification of endogenous D-serine release in Xenopus laevis tadpoles. We also investigate the effect of the permselective polymer layer thickness on the biosensor’s response time and selectivity. Finally, scanning electrochemical microscopy (SECM) is then used with the optimized biosensor to measure localized release of D-serine from a model system. This SECM methodology, which provides high spatial and temporal resolution, could be useful to investigate the primary site and mechanism of D-serine release in other biological samples.

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)0.001
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 score0.014
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.022
GPT teacher head0.288
Teacher spread0.266 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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