Monoclonal antibodies specific to heat‐treated porcine blood
Bibliographic record
Abstract
BACKGROUND: Porcine blood is potentially being utilized in food as a binder, gelling agent, emulsifier or colorant. However, for certain communities, the usage of animal blood in food is strictly prohibited owing to religious concerns and health reasons. This study reports the development of monoclonal antibodies (MAbs) against heat-treated soluble proteins (HSPs) of autoclaved porcine blood; characterization of MAbs against blood, non-blood and plasma from different animal species using qualitative indirect non-competitive enzyme-linked immunosorbent assay (ELISA); and immunoblotting of antigenic components in HSPs of porcine blood. RESULTS: Fifteen MAbs are specific to heat-treated and raw porcine blood and not cross-reacted with other animal blood and non-blood proteins (meat and non-meat). Twelve MAbs are specific to porcine plasma, while three MAbs specific to porcine plasma are cross-reacted with chicken plasma. Immunoblotting revealed antigenic protein bands (∼60, ∼85-100 and ∼250 kDa) in porcine blood and plasma recognized by the MAbs. CONCLUSION: Selection of MAbs that recognized 60 kDa HSPs of porcine blood and plasma as novel monoclonal antibodies would be useful for detection of porcine plasma in processed food using the immunoassay method. © 2015 Society of Chemical Industry.
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 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 | 0.000 | 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".