Diabetic neuropathy and the sensory neuron: new molecular targets (P2.010)
Bibliographic record
Abstract
OBJECTIVE: To explore new pathways and molecules that contribute to experimental diabetic neuropathy and sensory neuron degeneration. BACKGROUND: Polyneuropathy involving sensory neurons is a common complication of diabetes mellitus that may target neuron gene output and function. Cajal bodies (CBs), nucleoli and nuclear speckles are unique nuclear bodies known to be altered with the changes of mRNA metabolism in stress conditions. CB colocalizes with SMN, the depletion of which is responsible for motor neuron degeneration in spinal muscular atrophy. Nuclear speckles colocalize with CWC22, which is an essential pre-mRNA splicing factor. DESIGN/METHODS: We analyzed L4 and L5 dorsal root ganglion (DRG) sensory neurons in a 16 week model of type 1 (STZ) diabetes in C57BL/6 mice with experimental neuropathy. Methods included DRG gene expression microarray, behavior, electrophysiology, and immunohistochemistry. Diabetic mice were treated by near nerve and intraplantar injection of siRNA to silence CWC22 in one limb. RESULTS: Diabetic mice showed sensory neuron atrophy and conduction slowing at a 16 weeks of diabetes. mRNA expression microarray data in diabetic sensory neurons identified upregulation of CWC22. The nuclei in diabetic sensory neurons were associated with a rise in the number of CBs per neuron, while the nucleoli and nuclear speckles were not structurally altered. Typically, part of CBs colocalized with the SMN foci and the number of SMN-positive CBs per neuron was substantially reduced in diabetic sensory neurons. CWC22 siRNA in vivo unilaterally improved sensory conduction slowing and thermal sensitivity. CONCLUSIONS: In this study, the increase of CWC22 and CBs expression might reflect an aberrant mRNA splicing demand in experimental diabetic neuropathy whereas loss of SMN may lead to sensory neuron degeneration. Taken together, our findings identify novel degenerative mechanisms that include two new molecular targets relevant to diabetic neuropathy. Supported by: CDA, CIHR, Denyse Lajoie-Lake fellowship.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".