Immunohistochemical characterization of GluN2 NMDA receptor subunit expression in the dorsal horn of rats and humans
Bibliographic record
Abstract
NMDA receptors (NMDARs) are excitatory ionotropic glutamate receptors expressed throughout the CNS, including in the superficial dorsal horn (SDH) of the spinal cord.The GluN2 subtypes of NMDAR subunit, GluN2A, GluN2B and GluN2D, confer NMDARs with structural and functional variability, enabling heterogeneity in synaptic transmission and plasticity.Despite essential roles for NMDARs in physiological and pathological pain processing within the SDH, the distribution and function of specific GluN2 isoforms across SDH laminae remains poorly understood.Surprisingly, there is a complete lack of knowledge on GluN2 expression in female rodent or human spinal cord.In this study we therefore aimed to investigate the relative expression of specific GluN2 variants in the L4/L5 lumbar SDH of both male and female rats and humans.To detect synaptic GluN2 isoforms that are expressed in the SDH (GluN2A, 2B and 2D), we used a spinal cord immunohistochemistry approach combined with pepsin antigen-retrieval to unmask these highly cross-linked protein complexes.We found a dominant expression of both GluN2B and GluN2D subunits in the SDH of male rats, while only GluN2B was preferentially localized to the SDH of females.Surprisingly, we also identified that the GluN2B NMDAR subtype was more abundantly expressed in the medial compared to the lateral, but in male rats only.Finally, we successfully adapted the staining approaches from rodent to human spinal tissue in order to investigate whether the specific expression patterns for NMDAR GluN2 subtypes are conserved in the human SDH in future studies.These specific localization patterns of GluN2-NMDARs subtypes to pain-processing regions of the SDH has important implications for both the understanding and treatment of pain.Expression of NMDAR subunits in the dorsal horn of rats and humans iii Acknowledgments I would like to express my gratitude to my supervisor, Dr. Michael Hildebrand, for his dedicated guidance and support throughout this project.A huge thank you also for having revised and provided insightful feedback to this thesis.I would like to thank Dr. Chris Rudyk who collaborated on this project and took care of the confocal image acquisition.Thank you for the encouragement during critical moments
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 | 0.001 | 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) | 0.002 | 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".