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Record W4307967176 · doi:10.1038/s41467-022-34157-0

The immune synapses reveal aberrant functions of CD8 T cells during chronic HIV infection

2022· article· en· W4307967176 on OpenAlexfundno aff
Nadia Anikeeva, Maria Steblyanko, Leticia Kuri-Cervantes, Marcus Buggert, Michael R. Betts, Yuri Sykulev

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthCenter for AIDS Research, University of WashingtonUniversity of TorontoNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesPhiladelphia FoundationUniversity of Pennsylvania
KeywordsDegranulationCytotoxic T cellImmunological synapseImmune systemBiologyCell biologyCD8EffectorImmunologyInflammationT cellReceptorIn vitroT-cell receptorGenetics

Abstract

fetched live from OpenAlex

Chronic HIV infection causes persistent low-grade inflammation that induces premature aging of the immune system including senescence of memory and effector CD8 T cells. To uncover the reasons of gradually diminished potency of CD8 T cells from people living with HIV, here we expose the T cells to planar lipid bilayers containing ligands for T-cell receptor and a T-cell integrins and analyze the cellular morphology, dynamics of synaptic interface formation and patterns of the cellular degranulation. We find a large fraction of phenotypically naive T cells from chronically infected people are capable to form mature synapse with focused degranulation, a signature of a differentiated T cells. Further, differentiation of aberrant naive T cells may lead to the development of anomalous effector T cells undermining their capacity to control HIV and other pathogens that could be contained otherwise.

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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Same venueNature Communications→Same topicHIV Research and Treatment→French-language works237,207→