The Nature of Selection on the Major Histocompatibility Complex
Bibliographic record
Abstract
Only natural selection can account for the extreme genetic diversity of genes of the major histocompatibility complex (MHC). Although the structure and function of classic MHC genes is well understood at the molecular and cellular levels, there is controversy about how MHC diversity is selectively maintained. The diversifying selection can be driven by pathogen interactions and inbreeding avoidance mechanisms. Pathogen-driven selection can maintain MHC polymorphism based on heterozygote advantage or frequency-dependent selection due to pathogen evasion of MHC-dependent immune recognition. Empirical evidence demonstrates that specific MHC haplotypes are resistant to certain infectious agents, while susceptible to others. These data are consistent with both heterozygote advantage and frequency-dependent models. Additional research is needed to discriminate between these mechanisms. Infectious agents can precipitate autoimmunity and can potentially contribute to MHC diversity through molecular mimicry and by favoring immunodominance. MHC-dependent abortion and mate choice, based on olfaction, can also maintain MHC diversity and probably functions both to avoid genome-wide inbreeding and produce MHC-heterozygous offspring with increased immune responsiveness. Although this diverse set of hypotheses are often treated as competing alternatives, we believe that they all fit into a coherent, internally consistent thesis. It is likely that at least in some species, all of these mechanisms operate, leading to the extreme diversification found in MHC genes.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".