Additional file 2 of Age and sex-associated variation in the multi-site microbiome of an entire social group of free-ranging rhesus macaques
Bibliographic record
Abstract
Additional file 1: Table S1. Pairwise adonis results – rectal. Table S2. Pairwise adonis results – oral. Table S3. Pairwise adonis results – penile. Table S4. Top ten genera in rectum, oral cavity, penis, and vagina. Table S5. Full results of DESeq2 analysis of differential expression between age groups. Table S6. Pairwise adonis results - predicted functional features in rectal community. Table S7. Pairwise adonis results - predicted functional features in oral community. Table S8. Pairwise adonis results - predicted functional features in penile community. Figure S1. Alpha-diversity (Shannon Index) of macaque (a) rectal, (b) oral, (c) penile, and (d) vaginal microbiomes across age groups. Figure S2. Alpha-diversity (Shannon Index) of the (a) rectal, (b) oral, and (c) genital microbiomes of males and females. Figure S3. Differences in alpha-diversity (Shannon Index) in the (a) rectal, (b) oral, (c) penile, and (d) vaginal microbiomes of macaques younger than 15 years or 15 years and older. Figure S4. Beta-diversity of genital samples by sex. Bray-Curtis dissimilarity ordinated with non metric multidimensional scaling (NMDS) shows clear separation of male and female genital samples. Figure S5. Differences in relative abundance of top ten genera (a) across all age groups in rectal and (b) oral communities, and between macaques ≥15 years old and <15 years old in (c) rectal and (d) oral communities. The asterisk indicates a significant difference between the groups (a, b: Kruskal-Wallis; c, d: Wilcoxon). Figure S6. Average community composition of the rectal, penile, vaginal, and oral microbiomes of free-ranging rhesus macaques. Stacked bars show mean relative abundance of each phylum across all samples for each body site. Phyla in the stacked bars and the legend follow the same order, starting with “<1% abundance” at the right of the bars and ending with “Tenericutes” on the left. Figure S7. Sex differences in genital microbiome. Figure shows bacterial taxa that are significantly differentially abundant in male genitals vs. female genitals with a log2fold change of at least +/- 2. Figure S8. Relative abundances of the phyla (a) Proteobacteria and (b) Firmicutes, and the (c) ratio of Firmicutes to Bacteroidetes do not differ across age groups. Figure S9. Differences in predicted microbial functions across age groups in (a) rectal, (b) oral, (c) vaginal, and (d) penile communities. Each vertical line is a predicted KEGG gene/function, classified by the CatFun function in FunkyTax as enhanced (frequency of function differs among groups but contributing community does not), divergent (frequency of function and contributing community differs among groups), conserved (frequency of function and contributing community does not differ among groups), or equivalent (frequency of function does not differ among groups but contributing community differs). Figure S10. Bray-Curtis distances of predicted functional features of (a) rectal, (b) oral, (c) vaginal, (d) penile, and (e) genital microbial communities ordinated by NMDS. Figure S11. Functional pathways predicted by PiCrust2 that differentiate male and female genital communities. Pathways identified by LEfSe with LDA effect size ≥2 and alpha ≤ 0.01.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.801 | 0.111 |
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".