Plant‐derived pharmaceuticals for the developing world
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
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.
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.
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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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