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Record W2401279933 · doi:10.1007/978-1-59745-559-6_22

Poxvirus Tropism for Primary Human Leukocytes and Hematopoietic Cells

2009· article· en· W2401279933 on OpenAlexaff
Qigui Yu, Ningjie Hu, Mario Ostrowski

Bibliographic record

VenueMethods in molecular biology · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsUniversity of Toronto
FundersNational Center for Research ResourcesNational Institute of Allergy and Infectious Diseases
KeywordsTropismHaematopoiesisVirologyPrimary cellPrimary (astronomy)BiologyCell biologyCell cultureVirusStem cellGenetics

Abstract

fetched live from OpenAlex

Poxviruses including canarypox (ALVAC) and vaccinia viruses have, in recent years, received considerable attention as live vectors for the development of vaccines against infectious diseases such as AIDS, malaria, and tuberculosis. However, the cellular targets for viral infection within the human immune system and the consequences of infection for cells involved in the generation of immune responses have not been clearly delineated. Using recombinant enhanced green fluorescence protein (EGFP)-expressing ALVAC and vaccinia viruses, we have focused here on a side-by-side comparison of ALVAC and vaccinia virus tropism for cells from human peripheral blood and bone marrow. Both ALVAC and vaccinia viruses showed a strong bias toward monocyte infection. ALVAC minimally infected CD19(+) B cells and was unable to infect ex vivo NK cells and T lymphocytes, whereas vaccinia virus could infect B lymphocytes and NK cell populations. Vaccinia virus was also able to infect T lymphocytes at low but detectable levels which could be enhanced upon their activation. Both ALVAC and vaccinia viruses could infect immature monocyte-derived dendritic cells (MDDCs), but only ALVAC infection induced their subsequent maturation. Infection in human bone marrow cells showed that ALVAC infection was restricted to a myelomonocytoid cell-specific CD33(+) cell population, while vaccinia virus showed a strong, but not exclusive, preference for these cells.

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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.072
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.023
GPT teacher head0.384
Teacher spread0.361 · 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
GenreMethods

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

Citations18
Published2009
Admission routes1
Has abstractyes

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