MétaCan
Menu
Back to cohort
Record W2019812632 · doi:10.2174/157016209789346273

Natural Killer Cell Receptors in Human Immunodeficiency Virus Infection: Pathways to Protection or Doors to Disappointment?

2009· review· en· W2019812632 on OpenAlexafffund
Matthew Parsons, Michael D. Grant

Bibliographic record

VenueCurrent HIV Research · 2009
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsHuman immunodeficiency virus (HIV)DisappointmentVirologyReceptorDoorsBiologyGeneticsComputer science

Abstract

fetched live from OpenAlex

In the absence of effective treatment, infection with the human immunodeficiency virus (HIV) ultimately leads to the acquired immune deficiency syndrome (AIDS). Many attempts have been made to prevent and attenuate HIV infection. While antiretroviral therapies for infected individuals have had great success, preventative and therapeutic vaccines focused on both humoral and cellular-mediated immunity have failed. Recently, several natural killer cell receptor (NKR) genotypes, in concert with certain class I human histompatibility-linked antigens (HLA) were found to be associated with protection from HIV infection and/or disease progression. These receptors are expressed on both natural killer (NK) cells and subsets of T lymphocytes. As HIV infection is often associated with attenuation of NK cells and much remains unknown about the basic functions of NKR, it remains undetermined whether the protective effect of these receptors relates to their expression on NK cells, T lymphocytes or both. This review summarizes current literature regarding NKR and HIV infection, and addresses several major questions remaining about the role of these receptors in protection against infection and disease progression.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.015

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 head0.153
GPT teacher head0.416
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCurrent HIV ResearchSame topicImmune Cell Function and InteractionFrench-language works237,207