Loop Diuretics Have Anxiolytic Effects in Rat Models of Conditioned Anxiety
Bibliographic record
Abstract
A number of antiepileptic medications that modulate GABA(A) mediated synaptic transmission are anxiolytic. The loop diuretics furosemide (Lasix) and bumetanide (Bumex) are thought to have antiepileptic properties. These drugs also modulate GABA(A) mediated signalling through their antagonism of cation-chloride cotransporters. Given that loop diuretics may act as antiepileptic drugs that modulate GABAergic signalling, we sought to investigate whether they also mediate anxiolytic effects. Here we report the first investigation of the anxiolytic effects of these drugs in rat models of anxiety. Furosemide and bumetanide were tested in adult rats for their anxiolytic effects using four standard anxiety models: 1) contextual fear conditioning; 2) fear-potentiated startle; 3) elevated plus maze, and 4) open-field test. Furosemide and bumetanide significantly reduced conditioned anxiety in the contextual fear-conditioning and fear-potentiated startle models. At the tested doses, neither compound had significant anxiolytic effects on unconditioned anxiety in the elevated plus maze and open-field test models. These observations suggest that loop diuretics elicit significant anxiolytic effects in rat models of conditioned anxiety. Since loop diuretics are antagonists of the NKCC1 and KCC2 cotransporters, these results implicate the cation-chloride cotransport system as possible molecular mechanism involved in anxiety, and as novel pharmacological target for the development of anxiolytics. In view of these findings, and since furosemide and bumetanide are safe and well tolerated drugs, the clinical potential of loop diuretics for treating some types of anxiety disorders deserves further investigation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".