Is ragweed pollen allergenicity governed by environmental conditions during plant growth and flowering?
Bibliographic record
Abstract
Pollen allergenicity is one of the main factors influencing the prevalence and/or severity of allergic diseases. However, how genotype and environment contribute to ragweed pollen allergenicity has still to be established. To throw some light on the factors governing allergenicity, in this work 180 ragweed plants from three Regions (Canada, France, Italy) were grown in both controlled (constant) and standard environmental conditions (seasonal changes in temperature, relative humidity and light). Pollen from single plants was characterized for its allergenic potency and for the underlying regulation mechanisms by studying the qualitative and quantitative variations of the main isoforms of the major ragweed allergen Amb a 1. Results showed a statistically higher variability in allergenicity of pollen from standard conditions than from controlled conditions growing plants. This variability was due to differences among single plants, regardless of their origin, and was not ascribed to differences in the expression and IgE reactivity of individual Amb a 1 isoforms but rather to quantitative differences involving all the studied isoforms. It suggests that the allergenic potency of ragweed pollen and thus the severity of ragweed pollinosis mainly depends on environmental conditions during plant growth and flowering, which regulate the total Amb a 1 content.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".