Bibliographic record
Abstract
Diabetic neuropathy is characterized by slowing of conduction velocity and axonal atrophy. Both of these cardinal features of neuropathy might be linked to impaired neurofilament investment of axons. Since neurofilaments form the critical structural latticework of axons, their importance in neuropathy is of interest. We tested directly the relationship of neurofilaments to diabetic neuropathy by superimposing streptozotocin-generated diabetes on a unique but viable transgenic mouse described by Eyer and Peterson. These mice express a fusion protein in which the carboxyl terminus of the high molecular weight neurofilament protein (Nf-H) was replaced by beta-galactosidase, in turn blocking normal neurofilament export and rendering axons completely lacking neurofilaments. Despite similar levels of hyperglycaemia, diabetic mice lacking neurofilaments developed progressive slowing of conduction velocity in their motor and sensory fibres between 4 and 8 weeks after the onset of diabetes (P < 0.05), unlike diabetic mice with normal neurofilaments, who developed only mild evidence of neuropathy over the same time-frame. Diabetic mice without neurofilaments, but not those with neurofilaments, had a progressive decline in the amplitude of the caudal nerve compound action potential and there were trends toward increased axonal atrophy in diabetics lacking neurofilaments. Single daily doses of insulin that restored normoglycaemia (0.1 IU subcutaneous insulin daily 5 of 7 days weekly for 4 weeks) reversed conduction slowing and restored sensory axon calibre. Our findings indicate that abnormalities in neurofilament export or transport alone cannot account for features of diabetic neuropathy. Instead, neurofilaments may allow axons to better resist the ravages of diabetes. Our findings also confirm the impact of insulin on reversing the phenotype.
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) | 0.000 | 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".