Decreased Microstructural Integrity of the Central Somatosensory Tracts in Diabetic Peripheral Neuropathy
Bibliographic record
Abstract
CONTEXT: Although diabetic peripheral neuropathy (DPN) is predominantly considered a disorder of the peripheral nerves, some evidence for central nervous system involvement has recently emerged. However, whether or to what extent the microstructure of central somatosensory tracts may be injured remains unknown. OBJECTIVE: This work aimed to detect the microstructure of central somatosensory tracts in type 2 diabetic patients and to correlate it with the severity of DPN. METHODS: A case-control study at a tertiary referral hospital took place with 57 individuals with type 2 diabetes (25 with DPN, 32 without DPN) and 33 nondiabetic controls. The fractional anisotropy (FA) values of 2 major somatosensory tracts (the spinothalamic tract and its thalamocortical [spino-thalamo-cortical, STC] pathway, the medial lemniscus and its thalamocortical [medial lemnisco-thalamo-cortical, MLTC] pathway) were assessed based on diffusion tensor tractography. Regression models were further applied to detect the association of FA values with the severity of DPN in diabetic patients. RESULTS: The mean FA values of left STC and left MLTC pathways were significantly lower in patients with DPN than those without DPN and controls. Moreover, FA values of left STC and left MLTC pathways were significantly associated with the severity of DPN (expressed as Toronto Clinical Scoring System values) in patients after adjusting for multiple confounders. CONCLUSION: Our findings demonstrated the axonal degeneration of central somatosensory tracts in type 2 diabetic patients with DPN. The parallel disease progression of the intracranial and extracranial somatosensory system merits further attention to the central nerves in diabetic patients with DPN.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".