Occupational Asthma: New Low-Molecular-Weight Causal Agents, 2000–2010
Bibliographic record
Abstract
Background. More than 400 agents have been documented as causing occupational asthma (OA). The list of low-molecular-weight (LMW) agents that have been identified as potential causes of OA is constantly expanding, emphasizing the need to continually update our knowledge by reviewing the literature. Objective. The objective of this paper was to identify all new LMW agents causing occupational asthma reported during the period 2000-2010. Methods. A Medline search was performed using the keywords occupational asthma, new allergens, new causes, and low-molecular-weight agents. Results. We found 39 publications describing 41 new LMW causal agents, which belonged to the following categories: drugs (n = 12), wood dust (n = 11), chemicals (n = 8), metals (n = 4), biocides (n = 3), and miscellaneous (n = 3). The diagnosis of OA was confirmed through SIC for 35 of 41 agents, peak expiratory flow monitoring for three (3) agents, and the clinical history alone for three (3) agents. Immunological tests provided evidence supporting an IgE-mediated mechanism for eight (8) (20%) of the newly described agents. Conclusion. This paper highlights the importance of being alert to the occurrence of new LMW sensitizers, which can elicit OA. The immunological mechanism is explained by a type I hypersensitivity reaction in 20% of all newly described LMW agents.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".