Structural changes in dendritic spine morphology in early co-morbid behaviours in a mouse model of MS
Bibliographic record
Abstract
Multiple sclerosis (MS) is a devastating disease usually characterized by its physical symptoms caused by central nervous system inflammation and demyelination. Behavioral and cognitive co-morbid symptoms frequently afflict those living with MS and precede the onset of physical symptoms. This suggests these co-morbidities may be caused by a mechanism independent of demyelination. Structural changes in small projections extending off of dendrites (dendritic spines), the post-synaptic portion of a synapse, may underlie the functional deficits in behaviour and cognition seen in MS. Spines will be imaged from the mouse basolateral amygdala due to its regulation of anxiety, emotionality and fear memory, which coincide with the observed co-morbid symptomology. Dendritic spines will be measured using ImarisTM software to separate spines into three groups: thin, mushroom or stubby, based on the ratio of spine diameter to spine length. It is hypothesized that at day 7 post induction, to correlate with the onset of co-morbid symptoms, there will be a pronounced shift in spine morphology from more infantile (thin) classifications to more mature (mushroom) structures. This research aims to examine dendritic spine morphological changes as a potential mechanism for the onset of co-morbid symptoms in individuals afflicted with MS. * Indicates faculty mentor.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".