Development of a Chlamydia trachomatis T cell 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
The immune correlates of protection for most of the currently used vaccines are based on long-lived humoral immunity. Vaccines based on humoral immunity alone are unlikely to protect against infections caused by intracellular pathogens and today's most pressing infectious diseases of public health importance are caused by intracellular infections that not only include Chlamydia trachomatis but also tuberculosis, malaria, and HIV/AIDS. For these infections, vaccines that induce cellular immune responses are essential. Major impediments in developing such vaccines include difficulty in identifying relevant T cell antigens and delivering them in ways that elicit protective cellular immunity. In turn this is compounded by the complexity and plasticity of T cell developmental pathways that often correlate with specific aspects of protective immunity. Genomics and proteomics now provide tools to allow unbiased selection of candidate T cell antigens. This review mainly focuses on an immunoproteomic approach used in our laboratory to identify Chlamydia T cell antigens and how these T cell antigens can be developed into a future human Chlamydia vaccine.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 0.002 |
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