Immunological responses in C3H/HeJ mice following nose‐only inhalation exposure to different sizes of beryllium metal particles
Bibliographic record
Abstract
Beryllium is used in a wide variety of industries. Chronic beryllium disease is the most common occupational disease among workers following exposure to Be. The objective of this study was to determine the immunologic effects of two different particle sizes of Be metal, <2.5 microm (fine Be or Be-F) and <10 microm (inhalable Be or Be-I) on C3H/HeJ mice following 3 weeks of nose-only inhalation exposure at a target concentration of 250 microg m(-3). Mice were sacrificed either on day 28 or day 42 (Be-F group only) after exposure. The mass median aerodynamic diameter obtained in the inhalation chamber was 1.5 +/- 0.1 microm for Be-F and 4.1 +/- 0.6 microm for Be-I. Results showed peri-bronchial inflammation with early granulomatous changes in exposed mice. The extent of the inflammation appeared more severe for mice sacrificed at day 42. Splenocyte proliferation was higher for mice exposed to fine particles compared with Be-I and control animals. Flow-cytometric analysis indicated a significantly greater expression of CD4(+), CD8(+) and intracellular IFN-gamma expression for both Be particle sizes, particularly for fine particles. Cytokine assays of bronchoalveolar lavage revealed significantly greater levels of IL-12, TNF-alpha and IFN-gamma for mice exposed to fine particles. Our findings suggest that exposure to fine particles may induce more pronounced immunological effects than inhalable particles.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".