Development of competitive ELISAs for 17β-estradiol and 17β-estradiol +estrone+estriol using rabbit polyclonal antibodies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Estrogens are a family of feminizing hormones that are excreted by vertebrates. It has been documented that their presence in surface waters, even in the ng/L range, can have detrimental impacts on fish reproduction. Two competitive enzyme-linked immunosorbent assays using rabbit polyclonal antibodies were developed: one for 17beta-estradiol and a second one for 17beta-estradiol (E2)+estrone (E1)+estriol (E3). Two different conjugates were synthesized using the Mixed-anhydride (for the 17beta-estradiol ELISA) and the Mannich (for the E1 + E2 + E3 ELISA) reactions. The 17beta-estradiol ELISA was highly specific with an IC(50) of 243 ng/mL for 17beta-estradiol. The E1 + E2 + E3 ELISA exhibited cross-reactivity with estrone (85%) and estriol (62%) with an IC(50) of 18 ng/mL for 17beta-estradiol. Cross-reactivity was tested against 13 chemically related compounds and both immunoassays showed significant cross-reactivity with two estradiol conjugates: beta estradiol-17-valerate and beta estradiol-3-benzoate (from 57 to 84 %) for which, to our knowledge, there are currently no commercially available ELISA. Characteristics (sensitivity, inter and intra assay variation, and cross-reactivity) of the E1 + E2 + E3 ELISA were further compared to those from a commercial Estriol ELISA. The commercial ELISA was more specific, sensitive and its inter-assay variation was less (9.5% compared to 10% for the E1 + E2 + E3 ELISA) but the E1 + E2 + E3 ELISA had less intra-assay variation (4% compared to 5% for the commercial ELISA). Finally, a solid-phase extraction method compatible with the E1 + E2 + E3 immunoassay demonstrated that this combined approach of extraction and immunoassay had good potential for determining estrogen concentrations in environmental samples such as surface water in urban and agricultural ecosystems.
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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 | 0.001 |
| 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 it