Rodent models of Alzheimer's disease: Critical analysis of current hypotheses and pathways for future research
Bibliographic record
Abstract
Alzheimer's disease (AD) was first described over a century ago. However, the mechanisms underlying the disease are not well understood to this day. This has negatively impacted our ability to create animal models to design and test targeted reliable treatments for the disease. Amyloid β plaque accumulation, aggregation of neurofibrillary tangles, neuroinflammation, neurodegeneration, and, of course, cognitive decline, are few of the many observed pathological features associated with AD. However, there is a concern that the animal models of AD that are based on these frameworks may not be accurately representing AD in people. As such, the results from preclinical trials have not historically translated well to the clinic. In this article, we review the current major hypotheses to describe AD; we outline the major strengths and weaknesses of the commonly used rodent models used to replicate features of these hypotheses; and we provide a strategy for the field for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".