The 3-dimensional structure of the secondary pulmonary lobule within the human lung
Bibliographic record
Abstract
Introduction: To date there is limited understanding of the distal secondary pulmonary lobule structure within the lung due to its complex 3-dimensional structure which cannot be assessed by histology. Understanding the size and structural variations within the secondary pulmonary lobule may improve development of more effective aerosolized drug delivery in disease. Aims: Determine the morphometry of the secondary pulmonary lobules and acini using ultra-resolution micro-computed tomography (micro-CT). Methods: Seven lungs from healthy donors (28 - 65 years old) were sampled using systematic uniform random sampling to obtain 4 samples per lung (48 x 23mm), that were imaged frozen using micro-CT at 10µm resolution. Secondary pulmonary lobule septae were manually traced in 3D using ImageJ to estimate their volume. The airway tree was segmented and the number of terminal bronchioles and transitional bronchioles were counted. Results: Within the normal human lung, the average volume of the secondary pulmonary lobule was 2.5ml and contained an average of 11 terminal bronchioles, 20 transitional bronchioles and 20 acini. The main conducting airway generation leading into the secondary pulmonary lobule was 2.5mm in diameter and was between 1 and 7 generations proximal to the terminal bronchiole. Conclusions: This is the first study to quantitatively assess the structure of the secondary pulmonary lobules within the human lung. By establishing the normal morphometry of secondary pulmonary lobules and acini, we seek to provide critical data that can guide the development of novel drug delivery strategies for more efficient drug delivery to the distal lung.
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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 | 0.000 |
| 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".