A novel method to sort and enrich sensory neurons
Bibliographic record
Abstract
Abstract Peripheral sensory neurons, residing in the dorsal root ganglia (DRG), relay sensory information from the periphery to the central nervous system. Although single-cell transcriptomic studies have identified over 20 distinct sensory neuron subtypes, functional analysis and assessment of subtype-specific pathological changes remain difficult. Effective isolation and enrichment of sensory neurons are challenging yet essential for functional studies. Therefore, we used single-cell transcriptomic data from DRG to identify a panel of neuronal surface markers, including Nrxn2 and Pirt . Using these markers, we developed a fluorescence-activated cell sorting (FACS) panel for neuronal enrichment and analysis that does not rely on transgenic mouse strains and can be broadly applied. The panel was validated by microscopy and single-cell RNA (scRNA) sequencing, which also revealed broad representation of neuronal subtypes. Expression of these markers in human DRG underscores the translational value of this isolation method for sensory and pain studies. Overall, this study provides a valuable tool for isolating DRG neurons, advancing research on sensory neuron function and pain biology, and facilitating neuroimmune studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".