MétaCan
Menu
Back to cohort
Record W2990852929 · doi:10.1128/mbio.02767-19

CD71 <sup>+</sup> Erythroid Cells Exacerbate HIV-1 Susceptibility, Mediate <i>trans</i> -Infection, and Harbor Infective Viral Particles

2019· article· en· W2990852929 on OpenAlexafffund
Afshin Namdar, Garett Dunsmore, Shima Shahbaz, Petya Koleva, Lai Xu, Juan Jovel, Stan Houston, Shokrollah Elahi

Bibliographic record

VenuemBio · 2019
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsThe Metabolomics Innovation CentreUniversity of Alberta
FundersGovernment of CanadaCanadian Institutes of Health ResearchWomen and Children's Health Research Institute
KeywordsCord bloodHuman immunodeficiency virus (HIV)VirologyBiologyViral replicationPathogenesisRed blood cellImmunologyVirus

Abstract

fetched live from OpenAlex

erythroid cells) have a wide range of immunomodulatory properties. In this study, we found that these erythroid precursors are abundant in the human cord blood/placental tissues, in the blood of HIV-infected and anemic individuals. We observed that these cells exacerbate HIV-1 replication/infection in target cells and even make HIV target cells more permissible to HIV infection. In addition, we found that HIV gets a free ride by binding on the surface of these cells and thus can travel to different parts of the body. In agreement, we noticed a positive correlation between the plasma viral load and the frequency of these cells in HIV patients. More importantly, we observed that infective HIV particles reside inside these erythroid precursors but not mature red blood cells. Therefore, these cells by harboring HIV can play an important role in HIV pathogenesis.

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 score0.003
Threshold uncertainty score0.011

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)0.0030.000

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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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

Citations48
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuemBioSame topicErythrocyte Function and PathophysiologyFrench-language works237,207