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Record W2028170369 · doi:10.1128/jvi.01828-12

The N-Terminal Region of IFITM3 Modulates Its Antiviral Activity by Regulating IFITM3 Cellular Localization

2012· article· en· W2028170369 on OpenAlexafffund
Rui Jia, Qinghua Pan, Shilei Ding, Liwei Rong, Shan‐Lu Liu, Yunqi Geng, Wentao Qiao, Chen Liang

Bibliographic record

VenueJournal of Virology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsBiologyEndosomeTransmembrane proteinAmino acidVirologyVirusCell biologyInfluenza A virusViral replicationMutantInterferonCellGeneticsGeneReceptor

Abstract

fetched live from OpenAlex

Interferon-inducible transmembrane (IFITM) protein family members IFITM1, -2, and -3 restrict the infection of multiple enveloped viruses. Significant enrichment of a minor IFITM3 allele was recently reported for patients who were hospitalized for seasonal and 2009 H1N1 pandemic flu. This IFITM3 allele lacks the region corresponding to the first amino-terminal 21 amino acids and is unable to inhibit influenza A virus. In this study, we found that deleting this 21-amino-acid region relocates IFITM3 from the endosomal compartments to the cell periphery. This finding likely underlies the lost inhibition of influenza A virus that completes its entry exclusively within endosomes at low pH. Yet, wild-type IFITM3 and the mutant with the 21-amino-acid deletion inhibit HIV-1 replication equally well. Given the pH-independent nature of HIV-1 entry, our results suggest that IFITM3 can inhibit viruses that enter cells via different routes and that its N-terminal region is specifically required for controlling pH-dependent viruses.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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 designBench or experimental
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

Citations189
Published2012
Admission routes2
Has abstractyes

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