Partition-Controlled Delivery of Toxicants: A Novel In Vivo Approach for Embryo Toxicity Testing
Bibliographic record
Abstract
In conventional static or semi-static embryo toxicity assays with fish, the nominal concentrations of hydrophobic chemicals are often used to establish the toxic thresholds, which often far exceed the solubility limits of test compounds. Saturators and continuous-flow diluters have been used to provide stable concentrations below solubility but are complex, use large amounts of test substance, and produce large volumes of waste. We present a partition-controlled delivery (PCD) method that maintains the concentrations of chemicals in test solutions at or below solubility limits for extended exposure times. Concentrations are maintained by equilibrium partitioning of test chemicals from a series of poly(dimethylsiloxane) films loaded with a range of concentrations of each chemical. The efficacy of the PCD assay was tested by comparisons with static (no renewal) and semi-static (24-h renewal) embryo-larval toxicity tests. The test species was Japanese medaka (Oryzias latipes) exposed to retene (7-isopropyl-1-methylphenanthrene), a compound causing blue sac disease (BSD) in fish embryos. In the PCD assay, the median effective concentration (EC50) for BSD was 10 microg/L, below retene's solubility of 17 microg/L. In contrast, the nominal EC50 values for the semi-static 24-h and static assays were about 10 (150 microg/L) and 150 times (2500 microg/L) greater than solubility, respectively. The PCD method is a more sensitive and realistic method for assessing toxicity of nonpolar compounds than (semi)-static assays.
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) | 0.001 | 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 | 0.001 | 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".