Immunogenicity Studies with Microbial Fractions of M. tuberculosis H37Rv Total Culture Filtrate
Bibliographic record
Abstract
Current study investigates the whole secretory proteome of Mycobacterium tuberculosis as culture filtrate fractions to identify immunoprotective protein antigens on the basis of protection studies in animal (mouse and guinea pig) models. Secretory culture filtrate proteins (CFPs) of M. tuberculosis H37Rv were fractionated into fifteen narrow molecular mass fractions in the order of increasing molecular size (F1-F15) by electroelution. Immunization studies revealed proteins in the molecular weight range of 20-24kDa (F7), 25-30kDa (F8) and 37-42kDa (F11) as key protective fractions against experimental tuberculosis in both the animal (mice and guinea pig) models. Amongst these fractions, F7 imparted even better protection as compared to BCG. Immunological studies with all the fractions demonstrated that although selected three protective fractions were able to induce significant immune responses in both short term culture filtrate (STCF) immunized and Mtb infected animals, there were number of other non-protective fractions also that were inducing higher immune responses either in immunized animals (e.g.F12-F15) or in Mtb challenged animals (e.g.F1-F6). These results demonstrate that only those mycobacterial proteins that are recognized by the host immune system both during immunization and infection can induce significant protection against experimental tuberculosis, however there is no direct correlation between the level of immune responses and degree of protective efficacy.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".