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Record W4308835047 · doi:10.1080/22221751.2022.2147021

Offspring affected with <i>in utero</i> Zika virus infection retain molecular footprints in the bone marrow and blood cells

2022· article· en· W4308835047 on OpenAlexafffund
Daniel Udenze, Ivan Trus, Sean Lipsit, Scott Napper, Uladzimir Karniychuk

Bibliographic record

VenueEmerging Microbes & Infections · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchCanada Foundation for InnovationInnovation SaskatchewanUniversity of Saskatchewan
KeywordsOffspringZika virusIn uteroImmunologyBone marrowFetusContext (archaeology)RubellaPregnancyInflammationBiologyMedicineVirusGeneticsMeasles

Abstract

fetched live from OpenAlex

Congenital virus infections, for example cytomegalovirus and rubella virus infections, commonly affect the central nervous and hematological systems in fetuses and offspring. However, interactions between emerging congenital Zika virus and hematological system—bone marrow and blood—in fetuses and offspring are mainly unknown. Our overall goal was to determine whether silent in utero Zika virus infection can cause functional and molecular footprints in the bone marrow and blood of fetuses and offspring. We specifically focused on silent fetal infection because delayed health complications in initially asymptomatic offspring were previously demonstrated in animal and human studies. Using a well-established porcine model for Zika virus infection and a set of cellular and molecular experimental tools, we showed that silent in utero infection causes multi-organ inflammation in fetuses and local inflammation in the fetal bone marrow. In utero infection also caused footprints in the offspring bone marrow and PBMCs. These findings should be considered in a broader clinical context because of growing concerns about health sequelae in cohorts of children affected with congenital Zika virus infection in the Americas. Understanding virus-induced molecular mechanisms of immune activation and inflammation in fetuses may provide targets for early in utero interventions. Also, identifying early biomarkers of in utero-acquired immunopathology in offspring may help to alleviate long-term sequelae.

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 score0.485
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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