Gut microbiota modulate distal symmetric polyneuropathy in patients with diabetes
Bibliographic record
Abstract
The pathogenic mechanisms underlying distal symmetric polyneuropathy (DSPN), a common neuropathy in patients with diabetes mellitus (DM), are not fully understood. Here, we discover that the gut microbiota from patients with DSPN can induce a phenotype exhibiting more severe peripheral neuropathy in db/db mice. In a randomized, double-blind, and placebo-controlled trial (ChiCTR1800017257), compared to 10 patients who received placebo, DSPN was significantly alleviated in the 22 patients who received fecal microbiota transplants from healthy donors, independent of glycemic control. The gut bacterial genomes that correlated with the Toronto Clinical Scoring System (TCSS) score were organized in two competing guilds. Increased guild 1, which had higher capacity in butyrate production, and decreased guild 2, which harbored more genes in synthetic pathway of endotoxin, were associated with improved gut barrier integrity and decreased proinflammatory cytokine levels. Moreover, matched enterotype between transplants and recipients showed better therapeutic efficacy with more enriched guild 1 and suppressed guild 2. Thus, changes in these two competing guilds may play a causative role in DSPN and have the potential for therapeutic targeting.
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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 | 0.000 |
| 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) | 0.001 | 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".