MétaCan
Menu
Back to cohort
Record W4221036645 · doi:10.1097/qad.0000000000003218

Ibalizumab shows in-vitro activity against group A and group B HIV-2 clinical isolates

2022· article· en· W4221036645 on OpenAlexaff

Bibliographic record

VenueAIDS · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsTheratechnologies (Canada)
Fundersnot available
KeywordsGroup BIn vitroGroup AGroup (periodic table)Multiple drug resistanceAntibacterial agent

Abstract

fetched live from OpenAlex

OBJECTIVE: Treatment of multidrug-resistant HIV-2 is an emerging issue, because of the rapid selection of mutations at time of virological failure and the low number of antiretrovirals active on HIV-2. The aim of this study was to determine the susceptibility of HIV-2 primary isolates to ibalizumab, a long-acting monoclonal antibody that binds to CD4 that is approved for the treatment of MDR HIV-1. METHODS: In-vitro phenotypic susceptibility of 16 HIV-2 primary isolates was measured using a modified version of the ANRS peripheral blood mononuclear cells (PBMC) assay. Susceptibility to ibalizumab was assessed through 50% inhibitory concentrations and maximum percentage inhibitions (MPI), and gp105 was sequenced to look for determinants of reduced susceptibility. RESULTS: Ibalizumab inhibited viral replication of all 16 isolates, with a median IC 50 value of 0.027 μg/ml (range = 0.001-0.506 μg/ml), and a median MPI of 93%. Although two isolates presented higher IC 50 (above 0.1 μg/ml), they did not exhibit a loss of potential N-linked glycosylation sites in V5 loop, as reported in HIV-1 strains with reduced susceptibility. However, both presented shorter V1 and V2 loops than the HIV-2 reference strain. CONCLUSION: Ibalizumab inhibits HIV-2 replication, with IC 50 and MPI in the range of those reported for HIV-1. These in vitro data support the use of ibalizumab in patients with MDR HIV-2, in combination with an optimized background regimen.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.485
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.296
Teacher spread0.273 · 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 teacher head, 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

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAIDSSame topicHIV Research and TreatmentFrench-language works237,207