Effect of Electroacupuncture on Gut Microbiota in Participants With Knee Osteoarthritis
Bibliographic record
Abstract
A close relationship between knee osteoarthritis (KOA) and gut microbiota has recently been described. Herein, we aim to investigate the effect of electroacupuncture (EA) on gut microbiota in participants with KOA. We conducted a study of 60 participants with KOA and 30 matched healthy controls (HCs). Sixty participants were allocated to either EA group (n=30) or sham acupuncture (SA) group (n=30). Five obligatory acupoints and three adjunct acupoints were punctured in the EA group. Eight non-acupoints that were separated from conventional acupoints or meridians were used for the SA group. Participants in both groups received 24 sessions within eight weeks. Fecal microbial analyses by 16S ribosomal RNA gene sequencing were carried out after collecting stools at T 0 and T 8 weeks (Four samples with changed defecation habits were excluded). The results showed that both Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score ( P= 0.043) and NRS score ( P= 0.002) decreased more in EA group than those in SA group. Moreover, EA could reverse more KOA-related bacteria including Bacteroides , [Eubacterium]_hallii_group , Agathobacte r and Streptococcus . The number of significantly different genera between KOA patients and HCs were less after EA treatment than that after SA treatment. This meant that EA modified the composition of the gut microbiome, making it closer to healthy people, while not significantly affecting the microbial diversity. Two genera including Agathobacter ( P =0.0163), Lachnoclostridium ( P =0.0144) were statistically increased than baseline in EA group (paired Wilcoxon rank sum test). After EA treatment, Bacteroides ( P= 0.0394) was more abundant and Streptococcus ( P= 0.0306) was significantly reduced in patients who demonstrated adequate response than in those with inadequate response (Wilcoxon rank-sum test). Spearman correlation test between gut microbe and KOA clinical outcomes indicated that Bacteroides and Agathobacter was negatively correlated with NRS score, WOMAC total score, and WOMAC pain, stiffness and pain scores ( P <0.001 or 0.05 or 0.01), while Streptococcus was positively correlated with them ( P <0.05 or 0.01). Our study suggests that EA contributes to the improvement of KOA and gut microbiota could be a potential therapeutic target.
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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 | 0.000 | 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".