Utility of Immunoassay in Drug Screening in Skeletal Tissues: Sampling Considerations in Detection of Ketamine Exposure in Femoral Bone and Bone Marrow Following Acute Administration Using ELISA*
Bibliographic record
Abstract
Detection of ketamine exposure in skeletal tissues by automated enzyme-linked immunosorbent assay (ELISA) and gas chromatography with electron capture detection (GC-ECD) is described. Rats (n = 18) received 0, 15, 30, or 75 mg/kg ketamine hydrochloride acutely (i.p.), and were euthanized within 15 min or 1 h. Ketamine was extracted from ground femoral bone by methanolic incubation followed by liquid-liquid extraction (LLE), while marrow was homogenized in alkaline solution, and then underwent LLE. Extracts were analyzed by ELISA, and subsequently by GC-ECD following derivatization with trifluoroacetic acid anhydride. The effect of tissue type (i.e., diaphyseal bone vs. epiphyseal bone vs. bone marrow) on the immunoassay response was examined through determination of binary classification test sensitivity (S) and measurement of the relative decrease in absorbance (%DA, drug-positive tissues vs. drug-free controls) in each tissue type. The %DA varied significantly between different tissues examined under a given dose condition, and generally decreased in the order marrow > epiphyseal bone > diaphyseal bone, at all dose levels examined. Measured S values for marrow, epiphyseal bone, and diaphyseal bone were 100%, 77%, and 23%, respectively (75 mg/kg dose). These results suggest that the type of skeletal tissue sampled and position sampled within a given bone (diaphyses vs. epiphyses) are important parameters in drug screening of skeletal tissues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".