The role of Fecal Microbiota Transplantation (FMT) in treating patients with multiple sclerosis
Bibliographic record
Abstract
Introduction The associations between multiple sclerosis (MS) and altered intestinal microbiomes have clinicians considering the use of fecal microbiota transplantation (FMT). Animal data suggests that administering FMT from people with MS into healthy mice results in a microbiome with decreased abundance of Sutterella, reduced anti-inflammatory signals, increase in inflammation and experimental autoimmune encephalomyelitis (EAE). Animal studies that administered FMT (from normal healthy donors) into mice resulted in slowing down EAE development relieving symptoms, improving BBB integrity and restoration of microbiota diversity. Human studies indicated clinical benefits of FMT (from healthy donors) in people with MS including: improved intestinal motility and motor ability which lasted at least for the duration of the studies, ranging from 2 to 15 years.Areas covered The authors discuss the efficacy and safety of FMT in treatment of experimental MS in animals and humans with MS. A literature search was performed via PubMed (up to July 2023), using the key words: multiple sclerosis, fecal microbiota transplantation, microbiome.Expert opinion Limited associative data do not provide an understanding of role of FMT in the treatment for MS. Until appropriately designed randomized comparative trials which are underway, are completed, we cannot recommend routine use of FMT in people with MS.
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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 | 0.000 | 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".