Sex differences in chloride homeostasis of c-fiber primary afferents in the spinal cord dorsal horn
Bibliographic record
Abstract
Introduction: Intracellular Cl- concentration ([Cl-]i) is high in primary sensory neurons due to the activity of the Na+-K+-Cl- cotransporter 1 (NKCC1), causing greater Cl- accumulation than typically seen in CNS neurons. Consequently, central terminals of primary afferents in the spinal dorsal horn experience depolarization upon activation of GABAA receptors (GABAAR). Thus, regulation of [Cl-]i in these terminals may significantly affect transmitter release. Determining the exact [Cl-]i in C-fiber terminals is pivotal to understand sensory processing. Methods: To image [Cl-]i we used the genetically-encoded ratiometric Cl- sensor, superclomeleon, using 2-photon microscopy in acute spinal cord slices. Superclomeleon was virally transduced selectively in C-fibers in NaV1.8-cre mice. The GABAAR agonist and antagonist muscimol and bicuculline, as well as the NKCC1 antagonist bumetanide, were used to modulate [Cl-]i in afferent terminals in the dorsal horn. NKCC1 mRNA levels in the dorsal root ganglia was evaluated with RNAScope. Results: We found that [Cl-]i in C-fibers was significantly higher in males than females. Bumetanide significantly decreased [Cl-]i in males but not in females. Bicuculline did not significantly affect [Cl-]i in C-fibers indicating a minimal contribution of tonic GABAA signaling to [Cl-]i. NKCC1 mRNA was also significantly lower in females than males, consistent with the functional data. Conclusion: Presynaptic inhibition appears to be under distinct control by GABAergic inhibition between sexes, which should be taken into consideration in future studies.
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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 | 0.001 | 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) | 0.005 | 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".