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Record W2142215232 · doi:10.1126/science.1209202

The Shaping of Modern Human Immune Systems by Multiregional Admixture with Archaic Humans

2011· article· en· W2142215232 on OpenAlexaff
Laurent Abi‐Rached, Matthew J. Jobin, Subhash Kulkarni, Alasdair McWhinnie, Klara Dalva, Loren Gragert, Farbod Babrzadeh, Baback Gharizadeh, Ma Luo, Francis A. Plummer, Joshua Kimani, Mary Carrington, Derek Middleton, Raja Rajalingam, Meral Beksaç, Steven G. E. Marsh, Martin Maiers, Lisbeth A. Guethlein, Sofia Tavoularis, Ann‐Margaret Little, Richard E. Green, Paul J. Norman, Peter Parham

Bibliographic record

VenueScience · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsCanadian Blood ServicesUniversity of ManitobaPublic Health Agency of Canada
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Institutes of HealthNational Center for Research ResourcesWellcome Trust
KeywordsBiologyIntrogressionGenotypingAlleleHuman leukocyte antigenEvolutionary biologyBalancing selectionHaplotypeGeneticsGenomeNatural selectionHuman genomeSelection (genetic algorithm)GeneGenotypeAntigen

Abstract

fetched live from OpenAlex

Whole genome comparisons identified introgression from archaic to modern humans. Our analysis of highly polymorphic human leukocyte antigen (HLA) class I, vital immune system components subject to strong balancing selection, shows how modern humans acquired the HLA-B*73 allele in west Asia through admixture with archaic humans called Denisovans, a likely sister group to the Neandertals. Virtual genotyping of Denisovan and Neandertal genomes identified archaic HLA haplotypes carrying functionally distinctive alleles that have introgressed into modern Eurasian and Oceanian populations. These alleles, of which several encode unique or strong ligands for natural killer cell receptors, now represent more than half the HLA alleles of modern Eurasians and also appear to have been later introduced into Africans. Thus, adaptive introgression of archaic alleles has significantly shaped modern human immune systems.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.032
GPT teacher head0.237
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations560
Published2011
Admission routes1
Has abstractyes

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