Bibliographic record
Abstract
Plant-produced vaccines and therapeutic agents offer enormous potential for providing relief to developing countries by reducing the incidence of infant mortality caused by infectious diseases. Vaccines derived from plants have been demonstrated to effectively elicit an immune response. Biopharmaceuticals produced in plants are inexpensive to produce, require fewer expensive purification steps, and can be stored at ambient temperatures for prolonged periods of time. As a result, plant-produced biopharmaceuticals have the potential to be more accessible to the rural poor. This review describes current progress with respect to plant-produced biopharmaceuticals, with a particular emphasis on those that target developing countries. Specific emphasis is given to recent research on the production of plant-produced vaccines toward human immunodeficiency virus, malaria, tuberculosis, hepatitis B virus, Ebola virus, human papillomavirus, rabies virus and common diarrheal diseases. Production platforms used to express vaccines in plants, including nuclear and chloroplast transformation, and the use of viral expression vectors, are described in this review. The review concludes by outlining the next steps for plant-produced vaccines to achieve their goal of providing safe, efficacious and inexpensive vaccines to the developing world.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".