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Record W2091687624 · doi:10.1073/pnas.1421536112

Plasma butyrylcholinesterase regulates ghrelin to control aggression

2015· article· en· W2091687624 on OpenAlexaff
Vicky Ping Chen, Yang Gao, Liyi Geng, Robin J. Parks, Yuan‐Ping Pang, Stephen Brimijoin

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2015
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsOttawa Hospital
FundersNational Institute on Drug Abuse
KeywordsGhrelinButyrylcholinesteraseEndocrinologyInternal medicineChemistryBiologyEnzymeBiochemistryHormoneMedicine

Abstract

fetched live from OpenAlex

Ongoing mouse studies of a proposed therapy for cocaine abuse based on viral gene transfer of butyrylcholinesterase (BChE) mutated for accelerated cocaine hydrolysis have yielded surprising effects on aggression. Further investigation has linked these effects to a reduction in circulating ghrelin, driven by BChE at levels ∼ 100-fold above normal. Tests with human BChE showed ready ghrelin hydrolysis at physiologic concentrations, and multiple low-mass molecular dynamics simulations revealed that ghrelin's first five residues fit sterically and electrostatically into BChE's active site. Consistent with in vitro results, male BALB/c mice with high plasma BChE after gene transfer exhibited sharply reduced plasma ghrelin. Unexpectedly, such animals fought less, both spontaneously and in a resident/intruder provocation model. One mutant BChE was found to be deficient in ghrelin hydrolysis. BALB/c mice transduced with this variant retained normal plasma ghrelin levels and did not differ from untreated controls in the aggression model. In contrast, C57BL/6 mice with BChE gene deletion exhibited increased ghrelin and fought more readily than wild-type animals. Collectively, these findings indicate that BChE-catalyzed ghrelin hydrolysis influences mouse aggression and social stress, with potential implications for humans.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.015
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.000
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 head0.070
GPT teacher head0.324
Teacher spread0.254 · 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

Citations110
Published2015
Admission routes1
Has abstractyes

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