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Record W2036757786 · doi:10.1159/000054957

Effects of Acute Nicotine Administration on Cognitive Event-Related Potentials in Tacrine-Treated and Non-Treated Patients with Alzheimer’s Disease

2002· article· en· W2036757786 on OpenAlexaff
Verner Knott, Erich Mohr, Colleen Mahoney, Christopher G. Engeland, Vadim Ilivitsky

Bibliographic record

VenueNeuropsychobiology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsWestern UniversityRoyal Ottawa Mental Health CentreUniversity of Ottawa
Fundersnot available
KeywordsTacrineNicotinePlaceboPsychologyAudiologyNicotinic agonistAnesthesiaCholinergicCognitionCholinesteraseMedicineNeuroscienceInternal medicineAcetylcholinesterase

Abstract

fetched live from OpenAlex

Earlier studies of cognitive event-related brain potentials (ERPs) reporting diminished amplitudes and delayed latencies of the P300 potential in dementia of the Alzheimer type (DAT), together with independent findings of the P300- and performance-enhancing properties of nicotine in normal adults, stimulated this study to explore the single-dose effects of nicotine on auditory and visual P300s in DAT. Thirteen patients, 6 currently receiving treatment with the cholinesterase inhibitor tacrine (tetrahydroaminoacridine; THA) and the remaining being medication free, were administered 2 mg of nicotine polacrilex under double-blind, randomized, placebo-controlled conditions. Prior to nicotine administration, THA-treated patients exhibited shorter auditory P300 latencies than non-treated patients. Acutely administered nicotine failed to alter auditory P300, but increased the amplitudes of visual P300s in both DAT patient groups. Neither THA treatment nor single-dose nicotine altered behavioural performance in the visual and auditory task paradigms. The results are discussed in relation to nicotinic cholinergic, attentional and cognitive processes in DAT.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.946

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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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 designObservational
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

Citations25
Published2002
Admission routes1
Has abstractyes

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