Transgenic Rat Model of Alzheimer's Disease : Electrophysiological and Morphological Properties of Lateral and Medial Entorhinal Cortex Layer ll Neurons
Bibliographic record
Abstract
Alzheimer’s disease is the premier neurodegenerative disorder and form of dementia affecting tens of millions today. Animal models have provided vital insights into the mechanism and course of this pathology but answers regarding the vulnerability of select brain areas to the disease, which can direct efforts towards an effective treatment, remain elusive. What we do know is that the cognitive dysfunction leading to death in the late stages is mediated by the spread of amyloid- β pathology and formation of neurofibrillary tangles in the brain. This pathology first presents itself and most likely take root in the entorhinal cortex.In this study, we used the McGill-R-Thy1-APP rat model to perform single-cell whole cell electrophysiological recordings to find whether there is a difference in entorhinal cortex neurons belonging to transgenic rats positive for the Alzheimer’s phenotype compared to normal rats. Recordings in 37 layer II neurons from the medial and lateral entorhinal cortices revealed no overall differences in physiological or morphological properties. However, we did find medial entorhinal cells from transgenic brains to be significantly depolarized in comparison to the rest. Further studies in rats from a range of ages would be required to confirm this finding and have the potential to reveal early changes in the intrinsic network of the probed region at a cellular level. This work also identified different cell types in the LEC and MEC, information that will undoubtedly be useful in further characterisation of this novel rat model.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".