Bibliographic record
Abstract
We read with great interest the Report “Diversity of the human intestinal microbial flora” by P. B. Eckburg et al. (10 June, p. [1635][1]; published online 14 Apr.). We applaud the authors for advancing this important field by undertaking comprehensive 16S rDNA sequencing to describe the composition of the microbiota in stools and at six sites of the colon in each of three human volunteers. The analyzed 13,355 prokaryotic ribosomal RNA gene sequences represent the largest 16S rDNA microflora data set reported to date in any species. On the basis of their analysis, the authors suggest that “differences between stool and mucosa community composition” exist. We question the validity of this conclusion, based on our own observation that stool microflora composition can vary significantly in stool samples collected before and after a colonoscopy ([1][2]). The authors compare microflora composition in colon biopsy samples obtained during colonoscopy with a stool sample collected a month afterwards. The authors acknowledge potential problems with their interpretation because of the delayed stool collection, but a rationale for collecting delayed stool samples is not given. This Report has significantly expanded our knowledge of the diversity of the intestinal microflora in a few subjects. However, if we ever want to correlate microflora composition with health or disease, we will have to design studies aimed at understanding the variation in the microflora composition in a large cohort of human subjects. 1. 1.[↵][3]1. V. Mai, 2. O. C. Stine, 3. J. G. Morris Jr. , unpublished data. # Response {#article-title-2} Our large-scale comparative analysis of bacterial and archaeal 16S rDNA sequences in the colon and stool revealed significant intersubject variability and patchy heterogeneity among the colonic mucosal bacterial populations. Regarding the statistical differences we reported between stool and adherent mucosal populations, subjects B and C harbored different bacterial populations in their colonic mucosa compared with their stool samples collected 4 weeks later, while the mucosal populations in subject A were subsets of the population observed in stool collected 4 weeks after colonoscopy. Each subject's stool community was more similar to the communities of their own mucosal samples than to any community from a different subject. We acknowledged that the statistically significant difference between the bacterial composition of the stool and colonic mucosa may have been due to the 4-week delay in stool collection after colonoscopy. The collection of stool was not originally planned in the large Canadian population-based case control study from which the control subjects were selected. For this study of three healthy subjects, from whom the colonic tissue biopsies had already been collected, we chose to obtain stool samples 1 month after colonoscopy when each subject had full recovery of stable, baseline bowel function. Despite the original study design, we agree with Mai et al. that stool samples before endoscopy may provide more reliable representations of the steady-state stool bacterial population. However, a controlled comparative study is needed to reveal the degree to which stools are microbiologically dissimilar at various time intervals before and after bowel cleansing. A small study using denaturing gradient gel electrophoresis has suggested that the bacterial composition in colonic mucosal biopsies differs significantly from that in stool collected prior to the procedure ([1][4]), supporting our conclusions that significant differences exist between these microbial communities. Future studies should address these issues with high-resolution molecular methods and a greater number of subjects. 1. 1.[↵][5]1. E. G. Zoetendal 2. et al. , Appl. Environ. Microbiol. 68, 3401 (2002). [OpenUrl][6][Abstract/FREE Full Text][7] [1]: /lookup/doi/10.1126/science.1110591 [2]: #ref-1 [3]: #xref-ref-1-1 View reference 1. in text [4]: #ref-2 [5]: #xref-ref-2-1 View reference 1. in text [6]: {openurl}?query=rft.jtitle%253DApplied%2Band%2BEnvironmental%2BMicrobiology%26rft.stitle%253DAppl.%2BEnviron.%2BMicrobiol.%26rft.aulast%253DZoetendal%26rft.auinit1%253DE.%2BG.%26rft.volume%253D68%26rft.issue%253D7%26rft.spage%253D3401%26rft.epage%253D3407%26rft.atitle%253DMucosa-Associated%2BBacteria%2Bin%2Bthe%2BHuman%2BGastrointestinal%2BTract%2BAre%2BUniformly%2BDistributed%2Balong%2Bthe%2BColon%2Band%2BDiffer%2Bfrom%2Bthe%2BCommunity%2BRecovered%2Bfrom%2BFeces%26rft_id%253Dinfo%253Adoi%252F10.1128%252FAEM.68.7.3401-3407.2002%26rft_id%253Dinfo%253Apmid%252F12089021%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [7]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjk6IjY4LzcvMzQwMSI7czo0OiJhdG9tIjtzOjIzOiIvc2NpLzMxMC81NzUxLzExMTguYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9
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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.016 |
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".