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Effect of Pregnancy and Human Immunodeficiency Virus Infection on Intracellular Interleukin-2 Production Patterns

2004· article· en· W2163901766 on OpenAlexaff
Madeline Y. Sutton, Bart Holland, Thomas N. Denny, Ambrosia Garcia, Z Garcia, Dana Stein, Arlene Bardeguez

Bibliographic record

VenueClinical and Vaccine Immunology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsWomen's Health Research Institute
FundersNational Center for Research ResourcesNational Institutes of Health
KeywordsPregnancyImmunologyImmune systemBiologyCD8IntracellularHuman immunodeficiency virus (HIV)ImmunopathologyInterleukin 2MedicineVirology

Abstract

fetched live from OpenAlex

Human immunodeficiency virus type 1 (HIV-1) infection decreases the production of interleukin-2 (IL-2) from CD4+ and CD8+ T cells. Recombinant IL-2 (rIl-2) has been given to HIV-infected individuals to generate significant increases in CD4+ T-cell counts. There are limited data regarding the effects of pregnancy and HIV infection on IL-2 production in humans. To investigate the effects of human pregnancy, HIV infection, and HIV therapy on IL-2 production, we evaluated 61 women. Intracellular IL-2 production by CD4+ T cells from nonpregnant HIV-infected women was significantly lower than in that in uninfected women (45% +/- 8% versus 52% +/- 8%, P = 0.04). In contrast, there was no difference in levels of intracellular IL-2 production between HIV-infected and uninfected pregnant women. These observations suggest that pregnancy may down-regulate IL-2 production regardless of HIV infection status. Future studies should evaluate IL-2 production patterns in larger cohorts of women so that the physiological significance of IL-2 down-regulation in pregnancy can be further evaluated. This information is essential to assess the possible use of IL-2 supplementation therapy as a means of enhancing immune responses among HIV-infected pregnant women.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.017
GPT teacher head0.311
Teacher spread0.293 · 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 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

Citations4
Published2004
Admission routes1
Has abstractyes

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