Does diabetes target ganglion neurones?: Progressive sensory neurone involvement in long-term experimental diabetes
Bibliographic record
Abstract
Targeting of dorsal root ganglia by diabetes could account for the selective sensory abnormalities that patients with early diabetic polyneuropathy develop. In this work, we addressed survival, phenotype and gene expression in sensory neurones in lumbar dorsal root ganglia in a long-term model of experimental streptozotocin-induced diabetes in rats, designed to reflect human disease. Motor and sensory conduction slowing developed early, by the 2-month time point. At 2 months, sensory neurones had no detectable alterations in their calibre or gene expression, assessed using quantitative in situ hybridization studies for mRNA markers that included alpha CGRP, beta CGRP, NFM, t alpha 1-tubulin, SP, VIP, B50 (GAP43), galanin, somatostatin, PACAP, HSP27, c-jun, SNAP 25, p75, TrkA, TrkB and TrkC. By 12 months, however, diabetics had developed neurone perikaryal and distal axon atrophy, accompanied by generalized downregulation of mRNA expression, particularly of CGRP transcripts, PACAP, SP, NFM, p75, trkA and trkC. With the exception of HSP-27, no elevation in mRNAs that increase after injury, such as VIP, galanin, CCK, PACAP, B50 and t alpha 1-tubulin, was observed and constitutive levels, when detectable, trended towards lower rather than increased levels. There was relative preservation of neurone numbers at 12 months; only a non-significant trend towards fewer diabetic neurones was detected using a rigorous and systematic physical dissector counting approach through the entire L5 ganglia. There was no change in the relative populations of CGRP- and SP-immunoreactive neurones. Our findings indicate that even long-term experimental diabetes is associated with relative preservation of sensory neurone populations, but the neurones are atrophic and their gene expression is altered. This pattern of change differs from that following axotomy, implies a degenerative rather than an injury phenotype and has important implications for how such neurones might be rescued.
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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 | 0.001 | 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".