THE POTENTIAL USE OF ANTIBODIES FROM EGG YOLKS OF BIRD EGGS IN THE CONTEXT OF FOOD SECURITY OF THE RUSSIAN FEDERATION
Bibliographic record
Abstract
Bering E. proposed the principle of passive immunization at the end of the 19th century. Today, it is still used to treat tetanus, diphtheria, botulism, rabies and poisonous animal bites (snakes, spiders and scorpions). As before, equine antibodies or their fragments are used as an antidote. But the unique properties of antibodies from the yolks of chicken eggs (IgY) make it possible to use them for a wide range of therapeutic and prophylactic purposes. IgY-antibodies are used in several countries (Canada, Germany, Japan, China) on an industrial scale to produce medical and veterinary drugs to protect humans and animals against pathogens, providing highly effective immunological protection. The Romanian Romvac Company SA is a separate company in the series of manufacturers of these drugs. This company produces IgY preparations in limited batches against many antigens and practices the production of personalized antibodies directed at pathogens of a particular patient. This approach is guaranteed to damage the pathogen, however unique it may be. The authors have analyzed many review articles on the use of IgY-technology. These antibodies are nonaddictive, non-toxic, do not interact with rheumatoid factor, complement, or Fc-fragments of immunocompetent cells, and do not cause antibody-dependent reinforcement of infection. Oral administration of specific IgY-antibodies significantly reduces the manifestations of celiac disease and pathological conditions caused by activation of pathogens in the gastrointestinal tract. Passive immunization of young farm animals with IgY-antibodies is economical and practical against many mammals, birds and aquatic animals. The great potential of this new direction can provide a rapid and cost-effective breakthrough in improving the adequate food security of the Russian Federation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".