Analysis of Macrophages and Peptidergic Fibers in the Skin of Patients With Painful Diabetic Polyneuropathy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The mechanisms of pain in patients with diabetic polyneuropathy are unknown. Studies have suggested a role of inflammation and increased neuropeptides peripherally in pain generation. This study examined the possible skin markers of painful diabetic polyneuropathy (P-DPN): macrophages, substance P (SP), and calcitonin gene-related peptide (CGRP). METHODS: The participants were included from a large Danish cross-sectional clinical study of type 2 diabetes. We diagnosed definite diabetic polyneuropathy using the Toronto criteria and used the Neuropathic Pain Special Interest Group classification for defining P-DPN. We included 60 skin biopsies from patients with diabetic polyneuropathy-30 with P-DPN and 30 with nonpainful diabetic polyneuropathy (NP-DPN)-and 30 biopsies from healthy controls of similar age and sex. The biopsies were stained using PGP 9.5, IbA1, and SP and CGRP primary markers. RESULTS: = 0.64 and 0.49, respectively). The difference between P-DPN and NP-DPN for SP and CGRP was significant only in female patients, although a trend was seen in male patients. DISCUSSION: The findings point to a possible involvement of the innate immune system in the pathogenesis of neuropathic pain in patients with DPN, although markers of activated macrophages were not measured in this study.
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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 | 0.001 | 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) | 0.000 | 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".