2-Deoxyglucose<i>–</i>Induced Long-Term Potentiation of Monosynaptic IPSPs in CA1 Hippocampal Neurons
Bibliographic record
Abstract
In previous experiments on excitatory synaptic transmission in CA1, temporary (10-20 min) replacement of glucose with 10 mM 2-deoxyglucose (2-DG) consistently caused a marked and very sustained potentiation (2-DG LTP). To find out whether 2-DG has a similar effect on inhibitory synapses, we recorded pharmacologically isolated mononosynaptic inhibitory postsynaptic potentials (IPSPs; under current clamp) and inhibitory postsynaptic currents (IPSCs; under voltage clamp); 2-DG was applied both in the presence and the absence of antagonists of N-methyl-D-aspartate (NMDA). In spite of sharply varied results (some neurons showing large potentiation, lasting for >1 h, and many little or none), overall there was a significant and similar potentiation of IPSP conductance, both for the early (at approximately 30 ms) and later (at approximately 140 ms) components of IPSPs or IPSCs: by 35.1 +/- 10.25% (mean +/- SE; for n = 24, P = 0.0023) and 36.5 +/- 16.3% (for n = 19, P = 0.038), respectively. The similar potentiation of the early and late IPSP points to a presynaptic mechanism of LTP. Overall, the LTP was statistically significant only when 2-DG was applied in the absence of glutamate antagonists. Tetanic stimulations (in presence or absence of glutamate antagonists) only depressed IPSPs (by half). In conclusion, although smaller and more variable, 2-DG-induced LTP of inhibitory synapses appears to be broadly similar to the 2-DG-induced LTP of excitatory postsynaptic potentials previously observed in CA1.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".