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Record W2118727684 · doi:10.2174/157488906775245273

The Astrocytic GABAA/Benzodiazepine-Like Receptor: The Joker Receptor for Benzodiazepine-Mimetic Drugs?

2006· review· en· W2118727684 on OpenAlexaff
Leif Hertz, Zhong Zhao, Ye Chen

Bibliographic record

VenueRecent Patents on CNS Drug Discovery · 2006
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsNickel Institute
Fundersnot available
KeywordsBenzodiazepineFlumazenilGABAA receptorPharmacologyReceptorAntagonistNeuroscienceMedicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

Long-term use of benzodiazepines as hypnotics, anxiolytics, anticonvulsants and muscle relaxing drugs is jeopardized by adverse effects on memory, addictive properties, and development of tolerance. Major efforts have gone into developing 'benzodiazepine-like' drugs that are more selective in their therapeutic effect, have additional uses and/or lack the adverse effects of benzodiazepines. The reviewed prototype patent exemplifies such efforts. Newer drugs are thought to act selectively on one of the two neuronal benzodiazepine receptors, on the astrocytic mitochondrial benzodiazepine receptor and/or on GABA(A)/benzodiazepine receptor complexes displaying specific subunits. It is overlooked that astrocytes also express benzodiazepine receptors that enhance depolarization-mediated entry of Ca(2+) by interacting with membrane-associated GABA(A)-like receptors, mediating depolarization because of a high Cl(-) concentration within astrocytes. The resulting increase in free cytosolic Ca(2+), which stimulates glycogenolysis, is inhibited not only by the 'peripheral-type" benzodiazepine antagonist PK11195 but also by the 'neuronal' antagonist flumazenil. Increasing awareness of the role(s) of astrocytic Ca(2+) homeostasis and energy metabolism for CNS function suggests that activation of this receptor might contribute to both therapeutic and adverse effects of benzodiazepine-like drugs. This receptor should be kept in mind when developing and testing new drugs; in turn these drugs may help elucidating its functional role.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0050.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.002

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 head0.092
GPT teacher head0.369
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2006
Admission routes1
Has abstractyes

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