Bibliographic record
Abstract
PURPOSE OF REVIEW: The current review addresses one of the most common neurological disorders, diabetic polyneuropathy (DPN). DPN is debilitating, irreversible and dwarfs the prevalence of most other chronic disorders of the nervous system. Its complications include foot ulceration, amputation, falling and intractable neuropathic pain. Moreover, tight control of hyperglycemia reduces the incidence of DPN in type 1 diabetes mellitus but its role in type 2 diabetes mellitus is less clear. RECENT FINDINGS: New therapeutic options to reverse the development of DPN or its associated pain have been proposed but none have significantly changed the clinical approach. The cause of DPN remains controversial traditionally focused on the impact of metabolic abnormalities, polyol flux, microvascular changes, mitochondria, oxidative stress, lipid biology and others. In particular, there has been less attention toward how this chronic disorder alters peripheral neurobiology. It is now clear that in chronic models of diabetes mellitus there exists a unique form of neurodegeneration with a range of protein, mRNA and microRNA alterations to consider. How to reconcile these molecular and structural alterations with metabolic mechanisms is a challenge. In sensory neurons alone, a primary target of DPN, both central perikaryal cytoplasmic and nuclear changes and altered distal sensory axon terminal plasticity may be involved. SUMMARY: In this review, the current therapeutic status of DPN is described with greater emphasis on some new but selected thoughts on its neurobiology. New mechanistic understanding will be essential to developing precision therapeutics for DPN.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".