Characterization of immune responses of human PBMCs infected with Mycobacterium tuberculosis H37Ra: Impact of donor declared BCG vaccination history on immune responses and M. tuberculosis growth
Bibliographic record
Abstract
This study characterized the immune responses in early Mycobacterium tuberculosis (Mtb) H37Ra infection of human peripheral blood mononuclear cell (PBMC)-collagen matrix culture and the impact of Bacille Calmette-Guérin (BCG) vaccination history of donor PBMCs on the immune responses to Mtb infection. Aggregates of PBMCs were initially observed on day 3 and the size of aggregates continued to increase on day 8 post-infection, where macrophages and T cell subsets were identified to be present. Similarly, mycobacterial load progressively increased in infected PBMCs during the 8 days of culture but were significantly lower in infected PBMCs from BCG vaccinated (BCG+) donors compared to unvaccinated (BCG-) donors. The levels of INF-γ, TNF-α, IL-4, IL-6, IL-10 and IL-17 in the supernatants of Mtb-infected PBMCs peaked at day 3 and decreased on days 5 and 8. The levels of these cytokines except IL-10 were significantly lower in Mtb-infected PBMCs from BCG+ donors compared to infected PBMCs from BCG- donors. The percentages of activated naïve Th cells, activated effector memory Th cells and activated central memory Tc cells were significantly higher in Mtb-infected PBMCs compared to uninfected PBMCs at day 8 post-infection. Further, the proportion of activated central memory Tc cells was significantly higher in infected PBMCs from BCG+ donors compared to the BCG- donors. This study highlights the possibility that BCG vaccination may confound results that utilize human PBMCs to study Mtb infection.
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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) | 0.001 | 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".