Long-term actions of BDNF on inhibitory synaptic transmission in identified neurons of the rat substantia gelatinosa
Bibliographic record
Abstract
Peripheral nerve injury promotes the release of brain-derived neurotrophic factor (BDNF) from spinal microglial cells and primary afferent terminals. This induces an increase in dorsal horn excitability that contributes to "central sensitization" and to the onset of neuropathic pain. Although it is accepted that impairment of GABAergic and/or glycinergic inhibition contributes to this process, certain lines of evidence suggest that GABA release in the dorsal horn may increase after nerve injury. To resolve these contradictory findings, we exposed rat spinal cord neurons in defined-medium organotypic culture to 200 ng/ml BDNF for 6 days to mimic the change in spinal BDNF levels that accompanies peripheral nerve injury. Morphological and electrophysiological criteria and glutamic acid decarboxylase (GAD) immunohistochemistry were used to distinguish putative inhibitory tonic-islet-central neurons from putative excitatory delay-radial neurons. Whole cell recording in the presence of 1 μM tetrodotoxin showed that BDNF increased the amplitude of GABAergic and glycinergic miniature inhibitory postsynaptic currents (mIPSCs) in both cell types. It also increased the amplitude and frequency of spontaneous, action potential-dependent IPSCs (sIPSCs) in putative excitatory neurons. By contrast, BDNF reduced sIPSC amplitude in inhibitory neurons but frequency was unchanged. This increase in inhibitory drive to excitatory neurons and decreased inhibitory drive to inhibitory neurons seems inconsistent with the observation that BDNF increases overall dorsal horn excitability. One of several explanations for this discrepancy is that the action of BDNF in the substantia gelatinosa is dominated by previously documented increases in excitatory synaptic transmission rather than by impediment of inhibitory transmission.
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) | 0.000 | 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) | 0.001 | 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".