Unraveling the socio-cognitive consequences of KCC2 disruption in zebrafish: implications for neurodevelopmental disorders and therapeutic interventions
Bibliographic record
Abstract
During postnatal brain development, maintaining a delicate balance between excitation and inhibition (E/I) is essential for the precise formation of neuronal circuits. The K+/cl− cotransporter 2 (KCC2) is instrumental in this process, and its dysregulation is implicated in various neurological disorders. This study utilized zebrafish (Danio rerio) to investigate the socio-cognitive consequences of KCC2 disruption. Through CRISPR-Cas9 technology, biallelic kcc2a knockout zebrafish larvae were generated, revealing behavioral abnormalities, including impaired social interactions and memory deficits. Molecular analyses unveiled alterations in key genes associated with the GABAergic and glutamatergic systems, potentially contributing to E/I imbalance. Additionally, KCC2 disruption influenced the expression of oxytocin and BDNF, crucial regulators of social behaviors, synaptic plasticity, and memory formation. The study also explored the therapeutic potential of KCC2 modulation using pharmaceuticals, showing the rescuing effects of CLP-290 and LIT-001 on social abnormalities. However, the selective impact of LIT-001 on social behaviors, not memory, highlights the complexity of neurobehavioral modulation. In summary, this study sheds light on the pivotal role of KCC2 in shaping socio-cognitive functions and suggests potential therapeutic avenues for KCC2-related neurological disorders.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".