Hippocampal slice cultures integrated with multi‐electrode arrays: a model for study of long‐term drug effects on synaptic activity
Bibliographic record
Abstract
Abstract Technological limitations have restricted the ability to determine chronic drug effects on synaptic function from in vitro preparations. In earlier studies, the extracellular recording duration was limited to less than 10 h and only a distinct population of neurons was examined. To address these limitations, we used organotypic hippocampal slice cultures integrated with planar multi‐electrode arrays (MEA‐OHSC), which permitted within‐slice comparisons and examination of long‐term changes across multiple populations of neurons. Long‐term potentiation (LTP) is a widely accepted measure of synaptic plasticity, and is believed to be a cellular mechanism underlying learning and memory. Amyloid‐β protein (Aβ) is a 40–42 amino acid peptide that is the primary element of senile plaques, a pathological hallmark of Alzheimer's disease (AD). In contrast to earlier studies, MEA‐OHSCs allowed for long‐term administration of Aβ1–42 to more closely model the chronic nature of AD pathogenesis. Prior to Aβ1–42 exposure, the CA1 region displayed robust potentiation, but afterwards the ability to induce LTP was nearly absent. Spatial analysis illustrated, for the first time, the substantial area of LTP induction, and clearly showed the global loss of this plasticity after long‐term Aβ exposure. The MEA‐OHSC model characterized here presents an ideal platform for examining the effects chronic exposure of a bioactive compound can have on a cellular correlate of memory. This model could also be used to screen potential therapeutics that may influence synaptic activity. Drug Dev Res 68:84–93, 2007. Published 2007 Wiley‐Liss, Inc.; Canadian Crown Copyright
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".