Increased Behavioral and Histological Variability Arising From Changes in Cerebrovascular Anatomy of the Mongolian Gerbil
Bibliographic record
Abstract
The Mongolian gerbil (Meriones unguiculatus) has been used extensively as a model of forebrain ischemia. Its unique susceptibility to ischemia was suggested to be due to an incomplete circle of Willis. The relative ease to which ischemia can be induced combined with highly reproducible delayed CA1 cell death following a 5 min occlusion made the model popular in neuroprotection studies. Presently, this assumption was tested that complete forebrain ischemia occurs in all gerbils because increased variability was noticed in neuronal injury and behavioral outcome using this model in the last several years. Here it is reported that gerbils obtained from Charles River, the largest supplier in North America, show a high incidence (22.7% with bilateral and 38.6% with unilateral anastomoses) of posterior communicating arteries compared to another supplier of gerbils (High Oak Farms, 2.6% with bilateral and 13.2% with unilateral anastomoses, P<0.0001). This increased incidence of complete or partial circle of Willis led to less severe CA1 cell loss in Charles River gerbils (P<0.0001) compared to High Oak gerbils, with an unacceptably high level of inter-animal variability. Similarly, behavioral indices of CA1 ischemic injury (increased locomotion, habituation deficits) were also significantly attenuated in the Charles River animals. High Oak gerbils also displayed increased histological and behavioral variability relative to the pattern obtained several years ago. Thus, the gerbil model of forebrain ischemia, at least using Charles River animals, no longer produces consistent injury and behavioral alterations. Investigators are urged to consider adopting other models in future neuroprotection studies or ensure that their gerbil population lacks communicating arteries.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".