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Record W2329734853 · doi:10.1021/ac404111u

Disk-Shaped Amperometric Enzymatic Biosensor for in Vivo Detection of <scp>d</scp>-serine

2014· article· en· W2329734853 on OpenAlexafffund
David Polcari, Annie Kwan, Marion R. Van Horn, Laurence Danis, Loredano Pollegioni, Edward S. Ruthazer, Janine Mauzeroll

Bibliographic record

VenueAnalytical Chemistry · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmino Acid Enzymes and Metabolism
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsChemistrySerineBiosensorIn vivoAmperometryGlycineD-amino acid oxidaseNMDA receptorBiophysicsDetection limitEnzymeBiochemistryReceptorOxidase testAmino acidChromatographyElectrochemistry

Abstract

fetched live from OpenAlex

At the synapse, D-serine is an endogenous co-agonist for the N-methyl-D-aspartate receptor (NMDAR). It plays an important role in synaptic transmission and plasticity and has also been linked to several pathological diseases such as schizophrenia and Huntington's. The quantification of local changes in D-serine concentration is essential to further understanding these processes. We report herein the development of a disk-shaped amperometric enzymatic biosensor for detection of D-serine based on a 25 μm diameter platinum disk microelectrode with an electrodeposited poly-m-phenylenediamine (PPD) layer and an R. gracilis D-amino acid oxidase (RgDAAO) layer. The disk-shaped D-serine biosensor is 1-5 orders of magnitude smaller than previously reported probes and exhibits a sensitivity of 276 μA cm(-2) mM(-1) with an in vitro detection limit of 0.6 μM. We demonstrate its usefulness for in vivo applications by measuring the release of endogenous D-serine in the brain of Xenopus laevis tadpoles.

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: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.646

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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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

Citations37
Published2014
Admission routes2
Has abstractyes

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