Evaluation of Silica- and Sepharose-Based Immunoaffinity Sorbents for Sample Cleanup in Determination of Fumonisins B1 and B2 in Corn Products
Bibliographic record
Abstract
Anti-fumonisin B1 polyclonal antibodies were isolated from the serum of rabbits, immobilized onto the surface of glutaraldehyde-activated silica or Sepharose CL-4B particles, and placed into empty small plastic solid-phase extraction cartridges. The immobilized antibodies were evaluated for their ability to retain fumonisin B1 and fumonisin B2. Cartridge capacity and elution conditions were determined, and the results were compared to those obtained with a commercially available cartridge. The cartridges, which were tested for their effectiveness to isolate the fumonisins from extracts of corn flour and nacho chips, detected fumonisins down to levels of about 20 ng/g. However, additional cleanup was required for detection at lower concentrations. With the use of a strong anion-exchange cartridge as a preliminary cleanup before immunoaffinity chromatography, the detection limit reached 2-5 ng/g in the products tested. The silica sorbent material exhibited strong interactions with the fumonisins, requiring acidified ethanol-water mixtures for elution and resulting in an additional degree of selectivity in isolating fumonisins from sample extracts. The silica-based immunoaffinity cartridges were successfully reused more than 10 times; the Sepharose-based cartridges were less robust. Liquid chromatography with fluorescence detection was used after prechromatographic derivatization with o-phthaldialdehyde-mercaptoethanol.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".