Immune Vulnerability of Infants to Tuberculosis
Bibliographic record
Abstract
One of the challenges faced by the infant immune system is learning to distinguish the myriad of foreign but nonthreatening antigens encountered from those expressed by true pathogens. This balance is reflected in the diminished production of proinflammatory cytokines by both innate and adaptive immune cells in the infant. A downside of this bias is that several factors critical for controlling Mycobacterium tuberculosis infection are significantly restricted in infants, including TNF, IL-1, and IL-12. Furthermore, infant T cells are inherently less capable of differentiating into IFN- γ -producing T cells. As a result, infected infants are 5-10 times more likely than adults to develop active tuberculosis (TB) and have higher rates of severe disseminated disease, including miliary TB and meningitis. Infant TB is a fundamentally different disease than TB in immune competent adults. Immunotherapeutics, therefore, should be specifically evaluated in infants before they are routinely employed to treat TB in this age group. Modalities aimed at reducing inflammation, which may be beneficial for adjunctive therapy of some forms of TB in older children and adults, may be of no benefit or even harmful in infants who manifest much less inflammatory disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".