Age-dependent decrease in inhibitory drive on the excitatory superficial spinal dorsal horn neurons
Bibliographic record
Abstract
The excitatory and inhibitory interneurons of superficial laminae I-II of the spinal dorsal horn (SDH) receive and process pain-related information from the primary afferents and transmit it to the brain via the projection neurons. Thus, the interaction between excitatory and inhibitory SDH interneurons is crucial in determining the output from the spinal cord network. Disruption of this interaction in pathological conditions leads to increased SDH output to the higher brain centers, which could underlie pathological pain. Here, we examined whether the changes in the intrinsic SDH connectivity also occur with age, possibly underlying age-related increase in pain sensitivity. Using Vgat;tdTomato transgenic mouse line, we compared the spontaneous inhibitory postsynaptic currents (sIPSCs) in inhibitory tdTomato+ and excitatory tdTomato− interneurons between adult (3-5 m.o.) and aged (12-13 m.o.) mice. We demonstrate that in adult mice, the amplitude and frequency of the sIPSCs in the excitatory interneurons were significantly higher than in inhibitory interneurons. These differences were annulled in aged mice. Further, we show that in aged mice, excitatory neurons receive less inhibition than in adult mice. This could lead to overall disinhibition of the SDH network, which might underlie increased pain perception among the aged population.
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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) | 0.001 | 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".