Harnessing Innate Immunity to Treat Mycobacterium tuberculosis Infections: Heat-Killed Caulobacter crescentus as a Novel Biotherapeutic
Bibliographic record
Abstract
Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is a serious and devastating infectious disease worldwide. Approximately a quarter of the world population harbors latent Mtb infection without pathological consequences. Exposure of immunocompetent healthy individuals with Mtb does not result in active disease in more than 90% individuals, suggesting a defining role of host immunity to prevent and/or clear early infection. However, innate immune stimulation strategies have been relatively underexplored for the treatment of tuberculosis. In this study, we used cell culture and mouse models to examine the role of a heat-killed form of a non-pathogenic microbe, Caulobacter crescentus (HKCC), in inducing innate immunity and limiting Mtb infection. We also examined the added benefits of a distinct chemo-immunotherapeutic strategy that incorporates concurrent treatments with low doses of a first-line drug isoniazid and HKCC. This therapeutic approach resulted in highly significant reductions in disseminated Mtb in the lungs, liver, and spleen of mice compared to either agent alone. Our studies demonstrate the potential of a novel innate immunotherapeutic strategy with or without antimycobacterial drugs in controlling Mtb infection in mice and open new avenues for the treatment of tuberculosis in humans.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 0.018 |
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; both teacher heads agree on what is shown here.
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".