Acute slice preparation for electrophysiology increases spine numbers equivalently in the male and female juvenile hippocampus: a DiI labeling study
Bibliographic record
Abstract
Hippocampal slices are widely used for in vitro electrophysiological experiments to study underlying mechanisms for synaptic transmission and plasticity, and there is a growing appreciation for sex differences in synaptic plasticity. To date, several studies have shown that the process of making slices from male animals can induce synaptogenesis in cornu ammonis area 1 (CA1) pyramidal cells, but there is a paucity of data for females and other brain regions. In the current study we use microcrystals of the lipophilic carbocyanine dye DiI (1,1′-dioctadecyl-3,3,3′,3′-tetramethylindocarbocyanine perchlorate) to stain individual neurons in the CA1 and dentate gyrus (DG) hippocampal subfields of postnatal day 21 male and female rats. We show that the preparation of sections for electrophysiology produces significant increases in spines in sections obtained from females, similar to that observed in males. We also show that the procedures used for in vitro electrophysiology also result in significant spine increases in the DG and CA1 subfields. These results demonstrate the utility of this refined DiI procedure for staining neuronal dendrites and spines. They also show, for the first time, that in vitro electrophysiology slice preparations enhance spine numbers on hippocampal cells equivalently in both juvenile females and males. NEW & NOTEWORTHY This study introduces a new DiI technique that elucidates differences in spine numbers in juvenile female and male hippocampus, and shows that slice preparations for hippocampal electrophysiology in vitro may mask these differences.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".