Transoral intratracheal inoculation method for use with neonatal rats.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Studying the effects of toxic and infective compounds on the respiratory system requires a reliable method for delivering inoculum into the distal region of the lung. Although transoral intratracheal inoculation methods have been well documented for adult rats, to the authors' knowledge, a reliable method has not been validated for neonatal rats. The purpose of the study reported here was to develop a simple method for transoral inoculation in rat neonates. METHODS: Seven-day-old Fischer 344 rats were anesthetized with halothane, and a spinal needle was inserted in the tracheal lumen, by use of illumination and a modified otoscope. Meconium was injected into the lungs as a marker, and the neonates were kept under close observation. After euthanasia at 24 h, lungs were removed and fixed in formalin, and the microscopic distribution of the inoculum was assessed in the left, right cranial, middle, median, and caudal lung lobes. RESULTS: Microscopic examination of lungs indicated that intratracheal inoculation was achieved in 100% of neonatal lungs and the inoculum was consistently distributed in the alveoli of all pulmonary lobes. Important complications or mortality were not observed in the neonates. CONCLUSIONS: Intratracheal inoculation of neonatal rats is possible by use of a modified otoscope for transoral illumination. This technique is simple and reproducible and ensures, without complications, widespread distribution of inoculum in the lungs of neonatal rats.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".