Infection of Newborn Piglets with <i>Bordetella pertussis</i> : a New Model for Pertussis
Bibliographic record
Abstract
Bordetella pertussis is the causative agent of pertussis or whooping cough. This bacterium is a human pathogen that under experimental conditions also infects selected rodents and primates. Here, we show for the first time that newborn piglets can be infected with B. pertussis when it is delivered intrapulmonarily. Infected piglets displayed fever and respiratory symptoms, such as nasal discharge, nonparoxysmal coughing, and breathing difficulties. Eventually, all infected animals developed severe bronchopneumonia, which in some cases was combined with a fibrinous pleuritits. Immunohistochemical staining revealed the presence of large numbers of B. pertussis cells within airways, adhering to the epithelial lining or phagocytosed by macrophages and neutrophils. Viable bacteria were reisolated from bronchoalveolar lavages and lung lesions for more than 10 days postinfection. The systemic presence of pertussis toxin was shown by hypoglycemia, lymphocytosis, and induction of a clustered pattern of CHO cells by serum and bronchoalveolar lavage samples. Thus, a large-animal model for pertussis was developed, which should complement existing rodent models for identifying the immune responses relevant to the design of new vaccines. In particular, this model should help researchers analyze the roles of both maternal and mucosal immunity in disease protection against pertussis and should ultimately assist in the design of new vaccines for early life protection.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".