Analysis of the oral microbiome during hormonal cycle and its alterations in menopausal women: the “AMICA” project
Bibliographic record
Abstract
The maintenance of human health is dependent on a symbiotic relationship between humans and associated bacteria. The diversity and abundance of each habitat's signature microbes vary widely among body areas and among them the oral microbiome plays a key role. Significant changes in the oral cavity, predominantly at salivary and periodontal level, have been associated with changes in estrogen levels. However, whether the oral microbiome is affected by hormonal level alterations is understudied. Hence the main objective pursued by AMICA project was to characterize the oral microbiome (saliva) in healthy women through: profiling studies using "omics" technologies (NMR-based metabolomics, targeted lipidomics by LC-MS, metagenomics by NGS); SinglePlex ELISA assays; glycosidase activity analyses and bioinformatic analysis. For this purpose, thirty-nine medically healthy women aged 26-77 years (19 with menstrual cycle and 20 in menopause) were recruited. Participants completed questionnaires assessing detailed medical and medication history and demographic characteristics. Plasmatic and salivary levels of sexual hormones were assessed (FSH, estradiol, LH and progesteron) at day 3 and 14 for women with menstrual cycle and only once for women in menopause. Salivary microbiome composition was assessed through meta-taxonomic 16S sequencing and overall, the salivary microbiome of most women remained relatively stable throughout the menstrual cycle and in menopause. Targeted lipidomics and untargeted metabolomics profiling were assessed through the use of LC-MS and NMR spectroscopy technologies, respectively and significant changes in terms of metabolites were identified in saliva of post-menopausal women in comparison to cycle. Moreover, glycosyl hydrolase activities were screened and showed that the β-D-hexosaminidase activity was the most present among those analyzed. Although this study has not identified significant alterations in the composition of the oral microbiome, multiomics analysis have revealed a strong correlation between 2-AG and α-mannosidase. In conclusion, the use of a multidisciplinary approach to investigate the oral microbiome of healthy women provided some indication about microbiome-derived predictive biomarkers that could be used in the future for developing new strategies to help to re-establish the correct hormonal balance in post-menopausal women.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 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".