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Record W2509161532 · doi:10.1038/ncomms12412

Identification of Siglec-1 null individuals infected with HIV-1

2016· article· en· W2509161532 on OpenAlexaff
Javier Martínez‐Picado, Paul J. McLaren, Itziar Erkizia, Maureen P. Martin, Susana Benet, Margalida Rotger, Judith Dalmau, Dan Ouchi, Steven M. Wolinsky, Sudhir Penugonda, Huldrych F. Günthard, Jacques Fellay, Mary Carrington, Nuria Izquierdo‐Useros, Amalio Telenti

Bibliographic record

VenueNature Communications · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
FundersNational Institute of Allergy and Infectious DiseasesJohns Hopkins Bloomberg School of Public HealthUniversity of California, Los AngelesFrederick National Laboratory for Cancer ResearchUniversity of PittsburghJohns Hopkins UniversityNorthwestern UniversityNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungGilead SciencesStyrelsen för Internationellt UtvecklingssamarbeteNational Cancer InstituteamfAR, The Foundation for AIDS ResearchNational Science Foundation
KeywordsSIGLECBiologyEx vivoIn vivoPopulationImmunologyPhenotypeGeneticsImmune systemMedicineGene

Abstract

fetched live from OpenAlex

Siglec-1/CD169 is a myeloid-cell surface receptor critical for HIV-1 capture and infection of bystander target cells. To dissect the role of SIGLEC1 in natura, we scan a large population genetic database and identify a loss-of-function variant (Glu88Ter) that is found in ∼1% of healthy people. Exome analysis and direct genotyping of 4,233 HIV-1-infected individuals reveals two Glu88Ter homozygous and 97 heterozygous subjects, allowing the analysis of ex vivo and in vivo consequences of SIGLEC1 loss-of-function. Cells from these individuals are functionally null or haploinsufficient for Siglec-1 activity in HIV-1 capture and trans-infection ex vivo. However, Siglec-1 protein truncation does not have a measurable impact on HIV-1 acquisition or AIDS outcomes in vivo. This result contrasts with the known in vitro functional role of Siglec-1 in HIV-1 trans-infection. Thus, it provides evidence that the classical HIV-1 infectious routes may compensate for the lack of Siglec-1 in fuelling HIV-1 dissemination within infected individuals.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.015
GPT teacher head0.294
Teacher spread0.279 · 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

Citations34
Published2016
Admission routes1
Has abstractyes

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