The Astrocytic GABAA/Benzodiazepine-Like Receptor: The Joker Receptor for Benzodiazepine-Mimetic Drugs?
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".