MétaCan
Menu
Back to cohort
Record W2087587774 · doi:10.1586/1744666x.2014.907742

Future considerations for dendritic cell immunotherapy against chronic viral infections

2014· review· en· W2087587774 on OpenAlexafffund
Ethel Atanley, Sylvia van Drunen Littel‐van den Hurk

Bibliographic record

VenueExpert Review of Clinical Immunology · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsMedicineImmunotherapyImmunologyAdjuvantDendritic cellCancer immunotherapyImmune systemViral loadVaccinationAntigenVirologyHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

Dendritic cells (DCs) are multifunctional cells that are pivotal in immune defense. As such they have been explored as vaccine carriers, largely in cancer immunotherapy and against some infectious diseases including HIV and viral hepatitis. However, while the use of DCs as vaccine carrier has shown some promise in cancer immunotherapy, this approach is laborious and is subject to strict quality control, which makes it expensive. Furthermore, in some individuals chronically infected with HIV, HCV and/or HBV the numbers of circulating DCs are reduced and/or their functions impaired. In vivo expansion and mobilization of DCs with Flt3L in combination with antigen and/or adjuvant targeting to critical DC receptors may be a more effective approach to control viral replication in chronically infected HIV, HBV and/or HCV patients than current DC immunotherapy approaches.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.005

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 head0.049
GPT teacher head0.414
Teacher spread0.365 · 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 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

Citations11
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueExpert Review of Clinical ImmunologySame topicImmunotherapy and Immune ResponsesFrench-language works237,207