Restoring neuronal chloride extrusion reverses cognitive decline linked to Alzheimer’s disease mutations
Bibliographic record
Abstract
Disinhibition during early stages of Alzheimer's disease is postulated to cause network dysfunction and hyperexcitability leading to cognitive deficits. However, the underlying molecular mechanism remains unknown. Here we show that, in mouse lines carrying Alzheimer's disease-related mutations, a loss of neuronal membrane potassium-chloride cotransporter KCC2, responsible for maintaining the robustness of GABAA-mediated inhibition, occurs pre-symptomatically in the hippocampus and prefrontal cortex. KCC2 downregulation was inversely correlated with the age-dependent increase in amyloid-β 42 (Aβ42). Acute administration of Aβ42 caused a downregulation of membrane KCC2. Loss of KCC2 resulted in impaired chloride homeostasis. Preventing the decrease in KCC2 using long term treatment with CLP290 protected against deterioration of learning and cortical hyperactivity. In addition, restoring KCC2, using short term CLP290 treatment, following the transporter reduction effectively reversed spatial memory deficits and social dysfunction, linking chloride dysregulation with Alzheimer's disease-related cognitive decline. These results reveal KCC2 hypofunction as a viable target for treatment of Alzheimer's disease-related cognitive decline; they confirm target engagement, where the therapeutic intervention takes place, and its effectiveness.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".