Culture and molecular-based profiles show shifts in bacterial communities of the upper respiratory tract that occur with age
Bibliographic record
Abstract
The upper respiratory tract (URT) is a crucial site for host defense, as it is home to bacterial communities that both modulate host immune defense and serve as a reservoir of potential pathogens. Young children are at high risk of respiratory illness, yet the composition of their URT microbiota is not well understood. Microbial profiling of the respiratory tract has traditionally focused on culturing common respiratory pathogens, whereas recent culture-independent microbiome profiling can only report the relative abundance of bacterial populations. In the current study, we used both molecular profiling of the bacterial 16S rRNA gene and laboratory culture to examine the bacterial diversity from the oropharynx and nasopharynx of 51 healthy children with a median age of 1.1 years (range 1-4.5 years) along with 19 accompanying parents. The resulting profiles suggest that in young children the nasopharyngeal microbiota, much like the gastrointestinal tract microbiome, changes from an immature state, where it is colonized by a few dominant taxa, to a more diverse state as it matures to resemble the adult microbiota. Importantly, this difference in bacterial diversity between adults and children accompanies a change in bacterial load of three orders of magnitude. This indicates that the bacterial communities in the nasopharynx of young children have a fundamentally different structure from those in adults and suggests that maturation of this community occurs sometime during the first few years of life, a period that includes ages at which children are at the highest risk for respiratory disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".