Targeting immunometabolism in host defence against <i>Mycobacterium tuberculosis</i>
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
In the face of ineffective vaccines, increasing antibiotic resistance and the decline in new antibacterial drugs in the pipeline, tuberculosis (TB) still remains pandemic. Exposure to Mycobacterium tuberculosis (Mtb), which causes TB, results in either direct elimination of the pathogen, most likely by the innate immune system, or infection and containment that requires both innate and adaptive immunity to form the granuloma. Host defence strategies against infectious diseases are comprised of both host resistance, which is the ability of the host to prevent invasion or to eliminate the pathogen, and disease tolerance, which is defined by limiting the collateral tissue damage. In this review, we aim to examine the metabolic demands of the immune cells involved in both host resistance and disease tolerance, chiefly the macrophage and T-lymphocyte. We will further discuss how baseline metabolic heterogeneity and inflammation-driven metabolic reprogramming during infection are linked to their key immune functions containing mycobacterial growth and instructing protective immunity. Targeting key players in immune cellular metabolism may provide a novel opportunity for treatments at different stages of TB disease.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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