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Record W2143509027 · doi:10.1002/sia.3536

Tracing propionic acid infused to rat brain via deuterium tagging—further development of a novel rodent model of autism spectrum disorders

2010· article· en· W2143509027 on OpenAlexaff
Heng‐Yong Nie, Alison R. Taylor, J. T. Francis, Mary Jane Walzak, W. M. Lau, Derrick F. MacFabe

Bibliographic record

VenueSurface and Interface Analysis · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsWestern University
FundersAutism Research Institute
KeywordsChemistryOxidative stressHippocampusAutismRodentWhite matterBiochemistryNeuroscienceBiologyMedicine

Abstract

fetched live from OpenAlex

Abstract MacFabe et al. have proposed a novel rat model of autism spectrum disorders (ASDs) with intraventricular infusions of propionic acid (PPA), a gut bacterial metabolic end product and common food preservative, which produces reversible behavioral and electrographic effects coupled with increased oxidative stress and innate neuroinflammatory changes consistent with findings in ASD patients. PPA appears to be a potential environmental trigger linking the disparate behavioral, dietary, gut, metabolic and immune factors implicated in ASD. These previous studies used traditional immunohistochemical and biochemical techniques to examine increased oxidative stress and visualize neurons, reactive astrocytes, and activated microglia in hippocampus and adjacent external capsule white matter from coronally sectioned rat brain. As PPA is also an important metabolic intermediate of fatty acid beta oxidation, we have repeated the experiments with deuterium‐tagged PPA (DPPA) and employed ToF‐SIMS to trace the deuterium decoration of comparable brain regions ipsilateral to the DPPA infusion. In the present case of revealing DPPA‐induced changes in brain regions, ToF‐SIMS imaging of deuterium confirms the effectiveness of the methodology and the imaging results support the PPA‐triggered ASD rodent model. Copyright © 2010 John Wiley & Sons, Ltd.

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 score0.139
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.261
Teacher spread0.243 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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