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Record W4205640669 · doi:10.3410/f.13371099.15541056

Faculty Opinions recommendation of A potent and broad neutralizing antibody recognizes and penetrates the HIV glycan shield.

2012· dataset· en· W4205640669 on OpenAlexfundaboutno aff
Lai‐Xi Wang

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2012
Typedataset
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
FundersSLAC National Accelerator LaboratoryBiological and Environmental ResearchBasic Energy SciencesNational Institute of Allergy and Infectious DiseasesNational Center for Research ResourcesInternational AIDS Vaccine InitiativeNational Institute of General Medical SciencesEngineering and Physical Sciences Research CouncilCanadian Institutes of Health ResearchNational Cancer InstituteRagon Institute of MGH, MIT and HarvardOffice of ScienceNational Institutes of HealthU.S. Department of Energy
KeywordsGlycanHuman immunodeficiency virus (HIV)AntibodyChemistryVirologyPolitical scienceMedicineGlycoproteinImmunologyBiochemistry

Abstract

fetched live from OpenAlex

The HIV envelope (Env) protein gp120 is protected from antibody recognition by a dense glycan shield. However, several of the recently identified PGT broadly neutralizing antibodies appear to interact directly with the HIV glycan coat. Crystal structures of antigen-binding fragments (Fabs) PGT 127 and 128 with Man(9) at 1.65 and 1.29 angstrom resolution, respectively, and glycan binding data delineate a specific high mannose-binding site. Fab PGT 128 complexed with a fully glycosylated gp120 outer domain at 3.25 angstroms reveals that the antibody penetrates the glycan shield and recognizes two conserved glycans as well as a short β-strand segment of the gp120 V3 loop, accounting for its high binding affinity and broad specificity. Furthermore, our data suggest that the high neutralization potency of PGT 127 and 128 immunoglobulin Gs may be mediated by cross-linking Env trimers on the viral surface. PMID: 21998254 Funding information This work was supported by: NCI NIH HHS, United States Grant ID: U01 CA128416 NIAID NIH HHS, United States Grant ID: AI082362 NCI NIH HHS, United States Grant ID: Y1-CO-1020 NIAID NIH HHS, United States Grant ID: R01 AI033292 NIAID NIH HHS, United States Grant ID: AI74372 NIAID NIH HHS, United States Grant ID: R37 AI033292 NIAID NIH HHS, United States Grant ID: AI84817 NIAID NIH HHS, United States Grant ID: R56 AI084817 NIAID NIH HHS, United States Grant ID: R01 AI033292-14 NCRR NIH HHS, United States Grant ID: P41 RR017573 CIHR, Canada Grant ID: HFE-224662 NIAID NIH HHS, United States Grant ID: R01 AI084817 NCRR NIH HHS, United States Grant ID: P41RR001209 NCRR NIH HHS, United States Grant ID: RR017573 NIAID NIH HHS, United States Grant ID: F32 AI074372 NIAID NIH HHS, United States Grant ID: P01 AI082362 NIAID NIH HHS, United States Grant ID: AI33292 NCRR NIH HHS, United States Grant ID: P41 RR001209 NIAID NIH HHS, United States Grant ID: P01 AI082362-04 NIAID NIH HHS, United States Grant ID: F32 AI074372-03 NIAID NIH HHS, United States Grant ID: R01 AI084817-04 NIAID NIH HHS, United States Grant ID: P01 AI082362-03 NIGMS NIH HHS, United States Grant ID: Y1-GM-1104 More Less keyboard_arrow_down

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.551
Threshold uncertainty score0.640

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.5510.417

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 head0.034
GPT teacher head0.358
Teacher spread0.324 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2012
Admission routes2
Has abstractyes

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