Effects of sex and chronic cigarette smoke exposure on the mouse cecal microbiome
Bibliographic record
Abstract
RATIONALE: Chronic smoke exposure is associated with weight loss in patients with Chronic Obstructive Pulmonary Disease (COPD). However, the biological contribution of chronic smoking and sex on the cecal microbiome has not been previously investigated. METHODS: Adult male, female and ovariectomized mice were exposed to air (control group) or smoke for six months using a standard nose-only smoke exposure system. DNA was extracted from the cecal content using the QIAGEN QIAamp® DNA Mini Kit. Droplet digital PCR was used to generate total 16S bacterial counts, followed by Illumina MiSeq® analysis to determine microbial community composition. The sequencing data were resolved into Amplicon Sequence Variants and analyzed with the use of QIIME2®. Alpha diversity measures (Richness, Shannon Index, Evenness and Faith's Phylogenetic Diversity) and beta diversity (based on Bray-Curtis distances) were assessed and compared according to smoke exposure and sex. RESULTS: The microbial community was different between male and female mice, while ovariectomy made the cecal microbiome similar to that of male mice. Chronic smoke exposure led to significant changes in the cecal microbial community in both male and female mice. The organism, Alistipes, was the most consistent bacteria identified at the genus level in the cecal content that was reduced with chronic cigarette exposure and its expression was positively related to the whole-body weight of these mice. CONCLUSION: Chronic smoke exposure is associated with changes in the cecal content microbiome; these changes may play a role in the weight changes that are observed in cigarette smokers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".