Estimation of the reference lead (Pb) concentration levels affecting immune cells in the blood of Black-headed Gulls (Chroicocephalus ridibundus, Laridae)
Bibliographic record
Abstract
The biological effects of lead (Pb) contamination have been reported in various species. There are no restrictions on the use of Pb products, including bullets, in the areas south of Hokkaido, Japan. Local governments have announced the presence of Pb in the soil sediments of water bodies. Previous studies have confirmed the relationship between blood Pb level (BLL) and immune cells. This study was performed with the aim of clarifying the effect of Pb contamination on immune cells. In total, 170 Black-headed Gulls (Chroicocephalus ridibundus) were captured, including a population in Tokyo Bay between November 2018 and April 2021 and a population in Mikawa Bay between January 2019 and April 2021. Linear regression analysis was performed with the white blood cell count (WBC), proportion of heterophils (Het), proportion of lymphocytes (Lym), ratio of heterophils and lymphocytes (H/L ratio), copy number of CD4 messenger RNA, and copy number of CD8α messenger RNA as the objective variables, and the BLL as the explanatory variable. The group with BLL < 1.0 µg/dL had a significantly lower Het and higher Lym than that with BLL > 3.5 µg/dL (P < 0.05). In addition, the group with BLL < 1.0 µg/dL had a significantly lower H/L ratio than that with BLL > 3.5 µg/dL. CD8α and WBC were higher in the group with BLL ranging from 1.0 to 3.5 µg/dL than in the group with BLL < 1.0 µg/dL. This study suggests that the effect of Pb pollution on the immune cells of Black-headed Gulls is lower than some previous criteria values. It is possible that gulls affected by Pb contamination suffer indirect negative effects on immune function, possibly making them more susceptible to infectious diseases. Pb is a major environmental pollutant, against which measures must be taken.
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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) | 0.000 | 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".