On the Mechanism Determining the Th1/Th2 Phenotype of an Immune Response, and its Pertinence to Strategies for the Prevention, and Treatment, of Certain Infectious Diseases
Bibliographic record
Abstract
It is well recognized that the physiological/pathological consequences of an immune response, against a foreign or a self-antigen, are often critically dependent on the class of immunity generated. Here we focus on how antigen interacts with the cells of the immune system to determine whether antigen predominantly generates Th1 or Th2 cells. We refer to this mechanism as the 'decision criterion' controlling the Th1/Th2 phenotype of the immune response. A plausible decision criterion should account for the variables of immunization known to affect the Th1/Th2 phenotype of the ensuing immune response. Documented variables include the nature of the antigen, in terms of its degree of foreignness, the dose of antigen and the time after immunization at which the Th1/Th2 phenotype of the immune response is assessed. These are quantitative variables made at the level of the system. In addition, the route of immunization is also critical. I describe a quantitative hypothesis as to the nature of the decision criterion, referred to as the Threshold Hypothesis. This hypothesis accounts for the quantitative variables of immunization known to affect the Th1/Th2 phenotype of the immune response generated. I suggest and illustrate how this is not true of competing, contemporary hypotheses. I outline studies testing predictions of the hypothesis and illustrate its potential utility in designing strategies to prevent or treat medical situations where a predominant Th1 response is required to contain an infection, such as those caused by HIV-1 and by Mycobacterium tuberculosis, or to contain cancers.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".