Use of proliferation tests to evaluate the effects of complexing agents on beryllium toxicity
Bibliographic record
Abstract
Occupational exposure to beryllium may cause chronic beryllium disease (CBD), a granulomatous interstitial pneumonitis caused by a cell-mediated immune response with delayed hypersensitivity initiated by an electrostatic interaction with the MHC class II human leukocyte antigen (HLA). Increased research efforts focus on the development of a CBD treatment by chelation therapy. This work presents an in vitro evaluation of the beneficial effects of beryllium chelation with different organic substrates. We have used a standard beryllium lymphocyte proliferation test (BeLPT) adapted for mouse splenocytes. Three complexing agents, 4,5-dihydroxy-1,3-benzenedisulfonic acid (tiron), nitrilotripropionic acid (NTP) and nitrilotriacetic acid (NTA), were tested using different protocols of the splenocyte proliferation test (SPT). We studied their corrective effect (beryllium pre-exposed splenocytes), their protective effect (ligand pre-exposed splenocytes) and their combined effects at fixed Be:L ratio of 1:2, at fixed Be concentration and at fixed L concentration. We also studied the effect of tiron in preventing splenocyte sensitization to beryllium. All three complexing agents showed a corrective effect and proved efficient in the combined effects, except NTA in the fixed Be:L ratio. Only NTP and tiron showed a significant protection at lower beryllium concentrations, while NTA was not significant. Splenocytes pre-exposed to chelated beryllium did not show sensitization while splenocytes pre-exposed to beryllium were sensitized. We observed a strong correlation between the efficiency of the complexing agent and its affinity towards beryllium. Both tiron and NTP showed a similar affinity towards the beryllium ion that is 10(7) higher than that of NTA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".