Cognitive function improvement after fecal microbiota transplantation in in Alzheimer’s dementia patient: a case report
Why this work is in the frame
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Bibliographic record
Abstract
After fecal microbiota transplantation (FMT) to treat <i>Clostridioides difficile</i> infection (CDI), cognitive improvement is noticeable, suggesting an essential association between the gut microbiome and neural function. Although it is known that the gut microbiome is linked with cognitive function, whether FMT may lead to cognitive improvement in patients with neurodegenerative disorders remains to be elucidated. We present the case of a 90-year-old woman with Alzheimer's dementia and severe CDI who underwent FMT. Cognitive function testing (Mini-Mental State Examination, Montreal Cognitive Assessment, and Clinical Dementia Rating assessment) was performed one month before FMT and one week and one month after FMT. We collected the patients’ fecal samples before FMT and 3 weeks after FMT to compare the microbiota composition. The 16S rRNA gene amplicons were analyzed using the QIIME2 platform (version 2020.2) and Phyloseq R package. The linear discriminant analysis effect size was performed to determine the taxonomic difference between pre- and post-FMT. Functional biomarker analysis using the Kruskal-Wallis H test was performed between the pre- and post-FMT. The cognitive function tests after FMT showed an improvement compared to the tests before the procedure. FMT changed the microbiota composition in recipient feces. We found that the genera were reported to be associated with cognitive function. In addition, short-chain fatty acids was found to be significantly different between before and after FMT. This finding suggests the presence of an association between the gut microbiome and cognitive function. Further, it emphasizes the need for clinical awareness regarding the effect of FMT on the brain-gut-microbiome axis and its potential as a therapy for patients with dementia.
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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 | 0.001 |
| 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) | 0.079 | 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 it