Enhancing the potassium chloride co-transporter KCC2 reverses functional deficits associated with Alzheimer's disease-related mutations in mice
Bibliographic record
Abstract
Growing evidence indicates that during early stages of Alzheimer's disease (AD) abnormal brain activity occurs due to disruption of GABAA-mediated transmission. While disrupted GABAA signaling may result from several mechanisms, recent evidence points to deficits in the potassium-chloride cotransporter KCC2, responsible for maintaining low intracellular chloride in neurons to maintain robust inhibition. In this study, we validate whether KCC2 is downregulated in two transgenic mouse lines that develop AD-like amyloid-beta pathology and symptoms. Further, we examine whether by restoring KCC2 function we can alleviate deficits associated with AD. We found a decrease in the global and membrane protein levels of KCC2 in layer II/III of the prefrontal cortex of 5xFAD mice. In addition, ex vivo chloride imaging revealed impaired Cl- transport in the 5xFAD mice. Moreover, the power of hippocampal gamma oscillations was decreased in the APPNL-G-F mice, as predicted from deficits in KCC2. Consistent with this prediction, treatment with CLP290, a KCC2 activity enhancer, restored the power of the higher band gamma oscillations. Finally, short-term administration of CLP290 in the 5xFAD mice improved spatial memory in the Morris Water Maze (MWM) test whereas it improved learning performance in the MWM and episodic memory in the Contextual Fear Conditioning test in the APPNL-G-F mice as compared to vehicle-treated controls. These results indicate that KCC2 may be a viable target for reversing deficits in GABAA-mediated inhibition in AD and attenuating several symptoms associated with AD pathology.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".