Detection of emphysema in rat lungs by using magnetic resonance measurements of <sup>3</sup> He diffusion
Bibliographic record
Abstract
Emphysema is a pulmonary disease characterized by alveolar wall destruction, resulting in enlargement of gas exchange spaces without fibrosis. This condition is a part of chronic obstructive pulmonary disease (COPD), which causes 3.5% of deaths worldwide [Anonymous (1990) World Health Stat. Q. Special, 1-51] and contributes greatly to the global burden of disease [Murray, C. J. & Lopez, A. D. (1996) Science 274, 740-743]. Alveolar regeneration has been shown in animal models and could have potential for clinical treatment of early-stage emphysema. However, current techniques for detection of emphysema are not sensitive at the initial stages. Early-stage human panacinar emphysema is modeled in elastase-treated animals. Here, we provide an in vivo imaging method for differentiating normal and emphysematous rat lungs by measuring the apparent diffusion coefficient (ADC) of hyperpolarized (3)He by using magnetic resonance imaging. These data show that the ADC is significantly larger in elastase-treated rats, indicating alveolar expansion. Whereas these rats were clinically asymptomatic, conventional histology confirmed presence of injury. Our results indicate that measurement of the hyperpolarized (3)He ADC can be a valuable research tool and has potential application in the clinical setting.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".