Dendritic Spines and Pre-Synaptic Boutons Are Stable Despite Local Deep Hypothermic Challenge and Re-Warming In Vivo
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Deep hypothermia to 20°C is used clinically for major pediatric and adult surgical procedures. In particular, it is used in the "standstill operation" where blood flow is stopped for up to 30 min. Patients recovering from these procedures can exhibit neurological deficits. Such deficits could arise from changes to dendritic spines and plasticity-induced changes in network function as a result of cooling and/or re-warming. In the brain, each dendritic spine represents a single excitatory synapse and their number can be reflective of injury or plasticity-induced changes in network function. This research sought to determine whether deep hypothermia and re-warming have detrimental effects on synaptic stability and network function. METHODS: In vivo 2-photon (2-P) imaging in green/yellow fluorescent protein (GFP/YFP)-expressing transgenic mice was performed to determine whether 4 hours of deep hypothermia and 2 hours of re-warming can have relatively covert effects on dendritic spine and presynaptic bouton stability. At the same time, electroencephalographic (EEG) activity was recorded to evaluate network function during deep hypothermia and re-warming. RESULTS: We report that deep hypothermia and subsequent re-warming did not change the stability of dendritic spines or presynaptic boutons in mouse somatosensory cortex measured over 8 hours. As expected, deep hypothermia attenuated ongoing EEG activity over 0.1-80 Hz frequencies. The effects on EEG activity were fully reversible following re-warming. CONCLUSION: These results are consistent with deep hypothermia being a safe treatment which could be applied clinically to those undergoing major elective surgical procedures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".