MétaCan
Menu
Back to cohort
Record W2143440342 · doi:10.1089/aid.2013.0098

HIV and Interferon Regulatory Factor 1: A Story of Manipulation and Control

2013· review· en· W2143440342 on OpenAlexaff
Aida Sivro, Ruey‐Chyi Su, Francis A. Plummer, T. Blake Ball

Bibliographic record

VenueAIDS Research and Human Retroviruses · 2013
Typereview
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsPublic Health Agency of CanadaUniversity of Manitoba
Fundersnot available
KeywordsIRF1BiologyImmune systemInterferon regulatory factorsImmunologyInterferonViral replicationInnate immune systemVirologyVirusTranscription factorGeneticsGene

Abstract

fetched live from OpenAlex

Members of the interferon regulatory factor (IRF) family control the expression of numerous proteins, many of which are central to regulating host immune responses. IRF1 is one of the central mediators of the innate and adaptive immune responses required for antigen processing and presentation, Th1/Th2 differentiation, and natural killer (NK) cell and macrophage function. Many viruses have evolved mechanisms to target the IRF1 pathway in order to promote viral pathogenesis. During early HIV infection, IRF1 acts as a double-edged sword, critical for driving viral replication as well as eliciting antiviral responses. In this review, we describe the strategies that HIV-1 has evolved to modulate IRF1 in order to enhance viral replication and to disarm the host immune system. IRF1 has been shown to be an important factor in natural protection against HIV in highly exposed seronegative (HESN) individuals and is crucial in regulating the initial stages of HIV replication and HIV disease progression, as well as the establishment of latency. An understanding of how the protective effects of IRF1 responses are controlled in HESN individuals, naturally resistant to HIV infection, may provide important clues on how to regain control of HIV and tip the balance of immunity in favor of the host, or provide new opportunities to eliminate HIV in its host altogether.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

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

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 head0.142
GPT teacher head0.393
Teacher spread0.251 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAIDS Research and Human RetrovirusesSame topicHIV Research and TreatmentFrench-language works237,207