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Regulation of blood vessels by ATP in the ventral medullary surface in a rat model of Parkinson’s disease

2022· article· en· W4283692549 on OpenAlexfundno aff
Luíz M. Oliveira, Silvio A. Fernandes‐Junior, Laís M. Cabral, Nicole C. Miranda, Catherine Czeisler, José Javier Otero, Thiago S. Moreira, Ana C. Takakura

Bibliographic record

VenueBrain Research Bulletin · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsnot available
FundersNational Institutes of HealthConselho Nacional de Desenvolvimento Científico e TecnológicoInstituto SerrapilheiraCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorNational Heart, Lung, and Blood InstituteFundação de Amparo à Pesquisa do Estado de São PauloCMC Microsystems
KeywordsEndocrinologyBiologyParkinson's diseasePurinergic receptorInternal medicineCerebral blood flowNeurosciencePharmacologyMedicineDiseaseAdenosine

Abstract

fetched live from OpenAlex

-induced vascular constriction after ARL67156 (an ectonucleotidase inhibitor) in control and PD-induced animals. In addition, we also report that weighted gene correlational network analysis of the proteomic data showed a protein expression module differentially represented between both groups. This module showed that gene ontology enrichment for components of the ATP machinery were reduced in our PD-model compared to control animals. Altogether, our data indicate that dysfunction in purinergic signaling, potentially through altered ATP bioavailability in the VMS region, may compromise the RTN neuroglial vascular unit in a PD animal model.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.329
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2022
Admission routes1
Has abstractno

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