Non-Invasive Immunization on the Skin Using DNA Vaccine
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
Skin has evolved to protect not only by acting as a physical barrier, but also by its role in our powerful immune system. As a frontline of the host's defense against pathogens, skin is well equipped for immune surveillance. For example, compared to many other tissues, the epidermis of the skin contains a high population of Langerhans cells, which are very potent immature dendritic cells. Thus, targeting antigens to the skin epidermis should be able to efficiently induce strong immune responses. However, the forbidden barrier posed by the stratum corneum layer of the epidermis prevents effective entrance of antigens into the epidermis. Nevertheless, non-invasive immunization onto the skin has proven in the last several years to be a viable immunization modality. DNA vaccine is a vaccine made of bacterial plasmid DNA encoding an antigen of interest. Upon uptake of the plasmid, host express and process the encoding antigen, and then mount immune responses against it. DNA vaccine is advantageous over many other types of vaccines. The feasibility of non-invasive immunization onto the skin with DNA vaccine has been confirmed. Although the potency of the immune response has proven to be weak, many skin stratum corneum disrupting chemical and physical approaches and DNA vaccine carriers/adjuvants that significantly enhance the resulting immune response have been reported. In addition, research on elucidating the mechanism of immune induction from non-invasively, topically applied DNA vaccine has also been carried out. With further improvement and optimization, non-invasive immunization onto the skin with DNA vaccine should be able to elicit reliable and efficacious immune response to a variety of antigens.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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