Characterization of a <i>Mapt</i> knock‐out rat: Sex‐dependent effects on LTP and object location memory
Bibliographic record
Abstract
Abstract Background An emerging strategy for treating Alzheimer's disease is tau lowering therapeutics. These aim to reduce the levels of pathological tau species to prevent cognitive decline through approaches with RNA therapeutics, immunotherapy, small molecule inhibitors, or AAV‐based gene therapy. By studying the consequence of tau reduction in animal models one can understand the impact on learning and memory and physiological processes, potentially offering a way to optimize more targeted tau‐lowering therapeutics. Methods Using our novel microtubule‐associated protein tau homozygous knock‐out ( Mapt ‐/‐ ) rat model, we studied the impact of lack of tau on object‐location memory (OLM) in older adult (12‐to‐16‐month‐old) rats. Results We have previously found that in the Schaffer collateral‐commissural pathway of older adult rats, deletion of tau enhances long‐term potentiation, the strengthening of synaptic efficacy, in female but not male Mapt ‐/‐ rats, relative to sex‐matched littermate WT rats (Ralph et al., 2023, CAN). In line with this enhanced synaptic plasticity, we now report that OLM is significantly improved in female Mapt ‐/‐ older adult rats relative to age‐matched female WT rats ( n = 9 per group). This is while OLM is similar between WT and Mapt ‐/‐ male older adult rats ( n = 7 per group). Furthermore, this effect is age‐dependent since neither female nor male Mapt ‐/‐ young adult rats (2‐to‐3‐month‐olds) exhibit any significant changes in OLM performance relative to sex‐matched WT rats (Young et al., 2025, CAN). Conclusion Our findings provide evidence of a beneficial impact of long‐term tau deletion on synaptic plasticity and OLM, underscoring the potential for tailoring tau‐lowering therapeutics by age, sex and brain region once the underlying mechanism is fully elucidated.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".