Diabetic neuropathy and the sensory neuron: New aspects of pathogenesis and their treatment implications
Bibliographic record
Abstract
Diabetic polyneuropathy (DPN) continues to be generally considered as a "microvascular" complication of diabetes mellitus alongside nephropathy and retinopathy. The microvascular hypothesis, however, might be tempered by the concept that diabetes directly targets dorsal root ganglion sensory neurons. This neuron-specific concept, supported by accumulating evidence, might account for important features of DPN, such as its early sensory neuron degeneration. Diabetic sensory neurons develop neuronal atrophy alongside a series of messenger ribonucleic acid (RNA) changes related to declines in structural proteins, increases in heat shock protein, increases in the receptor for advanced glycation end-products, declines in growth factor signaling and other changes. Insulin is recognized as a potent neurotrophic factor, and insulin ligation enhances neurite outgrowth through activation of the phosphoinositide 3-kinase-protein kinase B pathway within sensory neurons and attenuates phenotypic features of experimental DPN. Several interventions, including glucagon-like peptide-1 agonism, and phosphatase and tensin homolog inhibition to activate growth signals in sensory neurons, or heat shock protein overexpression, prevent or reverse neuropathic abnormalities in experimental DPN. Diabetic sensory neurons show a unique pattern of microRNA alterations, a key element of messenger RNA silencing. For example, let-7i is widely expressed in sensory neurons, supports their growth and is depleted in experimental DPN; its replenishment improves features of DPN models. Finally, impairment of pre-messenger RNA splicing in diabetic sensory neurons including abnormal nuclear RNA metabolism and structure with loss of survival motor neuron protein, a neuron survival molecule, and overexpression of CWC22, a splicing factor, offer further novel insights. The present review addresses these new aspects of DPN sensory neurodegeneration.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".