Characterization of Inflammatory Responses During Intranasal Colonization with <em>Streptococcus pneumoniae</em>
Bibliographic record
Abstract
Nasopharyngeal colonization by Streptococcus pneumoniae is a prerequisite to invasion to the lungs or bloodstream(1). This organism is capable of colonizing the mucosal surface of the nasopharynx, where it can reside, multiply and eventually overcome host defences to invade to other tissues of the host. Establishment of an infection in the normally lower respiratory tract results in pneumonia. Alternatively, the bacteria can disseminate into the bloodstream causing bacteraemia, which is associated with high mortality rates(2), or else lead directly to the development of pneumococcal meningitis. Understanding the kinetics of, and immune responses to, nasopharyngeal colonization is an important aspect of S. pneumoniae infection models. Our mouse model of intranasal colonization is adapted from human models(3) and has been used by multiple research groups in the study of host-pathogen responses in the nasopharynx(4-7). In the first part of the model, we use a clinical isolate of S. pneumoniae to establish a self-limiting bacterial colonization that is similar to carriage events in human adults. The procedure detailed herein involves preparation of a bacterial inoculum, followed by the establishment of a colonization event through delivery of the inoculum via an intranasal route of administration. Resident macrophages are the predominant cell type in the nasopharynx during the steady state. Typically, there are few lymphocytes present in uninfected mice(8), however mucosal colonization will lead to low- to high-grade inflammation (depending on the virulence of the bacterial species and strain) that will result in an immune response and the subsequent recruitment of host immune cells. These cells can be isolated by a lavage of the tracheal contents through the nares, and correlated to the density of colonization bacteria to better understand the kinetics of the infection.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".