Characterization of the anterior cingulate cortex in adult tree shrew
Bibliographic record
Abstract
The anterior cingulate cortex (ACC) is a key brain region for the perception of pain and emotion. Cellular and molecular mechanisms of the ACC are usually investigated in rodents such as mice and rats. Studies of synaptic mechanisms in primates are limited. To facilitate the translation of basic results from rodents to humans, it is critical to use a primate-like animal model for the investigation of the ACC. The tree shrew presents a great opportunity for this as they have similar genome sequences to primates and are considered to have many similarities to primates. In the present study, by combining anatomy, immunostaining and micro-optical sectioning tomography methods, we examined the morphological properties of the ACC in the tree shrew and compared them with the mouse and rat. We found that the ACC in the tree shrew is significantly larger than those found in the mouse and rat. The sizes of cell bodies of ACC pyramidal cells in tree shrew are also larger than that found in the mouse or rat. Furthermore, there are significantly more apical/basal dendritic branches and apical dendritic spines of ACC pyramidal neurons in tree shrew. These results demonstrate that pyramidal cells of the ACC in tree shrews are more advanced than those found in rodents (mice and rats), indicating that the tree shrew can be used as a useful animal model for studying the cellular mechanism for ACC-related physiological and pathological changes in humans.
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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 | 0.000 |
| 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".