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Record W27779761 · doi:10.1113/jp273291

PROGRAM PROPOSAL FOR EARLY CONTACT OF PREGRADUATE STUDENTS WITH THE RESEARCH WORLD: HOW TO MAKE THE RIGHT DECISION AT THE RIGHT TIME

2009· article· en· W27779761 on OpenAlexfundno aff
Isabel González‐Álvarez, M. González-Álvarez, M. Bermejo

Bibliographic record

VenueINTED2009 Proceedings · 2009
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsRight to educationPolitical scienceHuman rightsLaw

Abstract

fetched live from OpenAlex

Acetylcholine (ACh) released at the vertebrate nerve-muscle synapse is hydrolysed rapidly to choline (Cho), so endplate receptors (AChRs) are exposed to high concentrations of both of these structurally related ligands. To understand how these receptors distinguish ACh and Cho, we used single-channel electrophysiology to measure resting affinities (binding free energies) of these and other agonists in adult-type mouse AChRs having a mutation(s) at the transmitter-binding sites. The aromatic rings of αY190, αW149 and αY198 each provide ∼50% less binding energy for Cho compared to ACh. At αY198 a phenylalanine substitution had no effect, but at αY190 this substitution caused a large, agonist-independent loss in binding energy that depended on the presence of αK145. The results suggest that (1) αY190 is deprotonated by αK145 to strengthen the interaction between this benzene ring and the agonist's quaternary ammonium (QA) and (2) AChRs respond strongly to ACh because an H-bond positions the QA to interact optimally with the rings, and weakly to Cho because a different H-bond tethers the ligand to misalign the QA and form weaker interactions with the aromatic groups. The results suggest that the difference in ACh versus Cho binding energies is determined by different ligand positions within a fixed protein structure.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.408
Teacher spread0.374 · 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 designNot applicable
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

Citations0
Published2009
Admission routes1
Has abstractyes

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