A Plausible Framework Reveals Potential Similarities in the Regulation of Immunity against Some Cancers and Some Infectious Agents: Implications for Prevention and Treatment
Bibliographic record
Abstract
Different frameworks, which are currently employed to understand how immune responses are regulated, can account for different observations reported in the classical literature. I have argued that the predominant frameworks, employed over the last two/three decades to analyze the circumstances that determine whether an immune response is generated or this potential is ablated, and that determine the class of immunity an antigen induces, are inconsistent with diverse classical observations. These observations are "paradoxical" within the context of these frameworks and, consequently, tend to be ignored by most contemporary researchers. One such observation is that low and high doses of diverse types of antigen result, respectively, in cell-mediated and IgG antibody responses. I suggest these paradoxes render these frameworks implausible. An alternative framework, The Threshold Hypothesis, accounts for the paradoxical observations. Some frameworks are judged more plausible when found to be valuable in understanding findings in fields beyond their original compass. I explore here how the Threshold Hypothesis, initially based on studies with chemically well-defined and "simple antigens", most often a purified protein, can nevertheless shed light on diverse classical and more recent observations in the fields of immunity against cancer and against infectious agents, thus revealing common, immune mechanisms. Most cancers and some pathogens are best contained by cell-mediated immunity. The success of the Threshold Hypothesis has encouraged me to employ it as a basis for proposing strategies to prevent and to treat cancer and those infectious diseases caused by pathogens best contained by a cell-mediated attack.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| 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".