MétaCan
Menu
Back to cohort
Record W2987098750 · doi:10.1002/anie.201909430

In Vivo Solid‐Phase Microextraction for Sampling of Oxylipins in Brain of Awake, Moving Rats

2019· article· en· W2987098750 on OpenAlexafffund
Alexander Napylov, Nathaly Reyes‐Garcés, Germán Augusto Gómez‐Ríos, Mariola Olkowicz, Sofia Lendor, Cian Monnin, Barbara Bojko, Clement Hamani, Janusz Pawliszyn, Dajana Vuckovic

Bibliographic record

VenueAngewandte Chemie International Edition · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsHealth Sciences CentreCentre for Addiction and Mental HealthSunnybrook Health Science CentreUniversity of WaterlooConcordia University
FundersOntario Brain Institute
KeywordsSolid-phase microextractionIn vivoChemistryChromatographySampling (signal processing)Phase (matter)Gas chromatography–mass spectrometryComputer scienceBiologyOrganic chemistryBiotechnologyComputer visionMass spectrometry

Abstract

fetched live from OpenAlex

Oxylipins are key lipid mediators of important brain processes, including pain, sleep, oxidative stress, and inflammation. For the first time, an in-depth profile of up to 52 oxylipins can be obtained from the brains of awake moving animals using in vivo solid-phase microextraction (SPME) chemical biopsy tool in combination with liquid chromatography-high resolution mass spectrometry. Among these, 23 oxylipins are detectable in the majority of healthy wildtype samples. This new approach successfully eliminates the changes in oxylipin concentrations routinely observed during the analysis of post-mortem samples, allows time-course monitoring of their concentrations with high spatial resolution in specific brain regions of interest, and can be performed using the same experimental set-up as in vivo microdialysis (MD) thus providing a new and exciting tool in neuroscience and drug discovery.

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)0.000
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 score0.008
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.021
GPT teacher head0.351
Teacher spread0.330 · 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

Citations94
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueAngewandte Chemie International EditionSame topicEicosanoids and Hypertension PharmacologyFrench-language works237,207