An evaluation of the efficiency of lymphocytic choriomeningitis virus - nucleoprotein cross priming in vivo
Bibliographic record
Abstract
During viral infections, CD8+ T cells only respond to a select few epitopes derived from the respective foreign pathogen. These epitopes can be organized into a hierarchy, based on their ability to induce T cell priming. Such phenomenon is known as immunodominance. Cytotoxic T cells can be primed through the direct pathway, or the cross-priming pathway. The latter involves exogenously derived viral epitope presentation by uninfected professional antigen presenting cells. It has been previously reported that Lymphocytic Choriomeningitis nucleoprotein expressed in HEK cells (HEK-NP) could be cross presented to CD8+ T cells. In these studies we have used this same HEK-NP model to study the effects of LCMV-NP cross priming on the LCMV immunodominance hierarchy following viral challenge. Our results provide strong evidence that cross priming is an efficient route with which to induce cell-mediated immunity. We also highlight a regulatory role for cross priming in immunodominance by showing that a single dose of HEK-NP can completely shift the immunodominance hierarchy of a typical LCMV infection. Furthermore, we see that the induction of LCMV-NP cross priming boosts anti-viral immunity to subsequent LCMV infections. This work provides strong support for the physiological role that cross priming plays in normal cell-mediated immune responses. It may also provide relevant information to the realm of immunotherapy.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".