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Record W2031590292 · doi:10.4061/2011/216464

Modulation of Tyrosine Hydroxylase, Neuropeptide Y, Glutamate, and Substance P in Ganglia and Brain Areas Involved in Cardiovascular Control after Chronic Exposure to Nicotine

2011· article· en· W2031590292 on OpenAlexfundno aff
M Ferrari, Emerson Filipino Coelho, Karen L. G. Farizatto, Gerson Chadi, Débora Rejane Fior-Chadi

Bibliographic record

VenueInternational Journal of Hypertension · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsnot available
FundersBrock UniversityConselho Nacional de Desenvolvimento Científico e TecnológicoUniversidade de São PauloFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsNicotineNeuropeptide Y receptorInternal medicineEndocrinologyMedicineGlutamate receptorTyrosine hydroxylaseNeuropeptideCentral nervous systemSubstance PNucleusDopamineReceptor

Abstract

fetched live from OpenAlex

Considering that nicotine instantly interacts with central and peripheral nervous systems promoting cardiovascular effects after tobacco smoking, we evaluated the modulation of glutamate, tyrosine hydroxylase (TH), neuropeptide Y (NPY), and substance P (SP) in nodose/petrosal and superior cervical ganglia, as well as TH and NPY in nucleus tractus solitarii (NTS) and hypothalamic paraventricular nucleus (PVN) of normotensive Wistar Kyoto (WKY) and spontaneously hypertensive rats (SHR) after 8 weeks of nicotine exposure. Immunohistochemical and in situ hybridization data demonstrated increased expression of TH in brain and ganglia related to blood pressure control, preferentially in SHR, after nicotine exposure. The alkaloid also increased NPY immunoreactivity in ganglia, NTS, and PVN of SHR, in spite of decreasing its receptor (NPY1R) binding in NTS of both strains. Nicotine increased SP and glutamate in ganglia. In summary, nicotine positively modulated the studied variables in ganglia while its central effects were mainly constrained to SHR.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.390

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 head0.026
GPT teacher head0.218
Teacher spread0.192 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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