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Record W4401633762 · doi:10.1371/journal.pcbi.1011940

Spatial kinetics and immune control of murine cytomegalovirus infection in the salivary glands

2024· article· en· W4401633762 on OpenAlexafffund
Catherine Byrne, Ana Márquez, Bing Cai, Daniel Coombs, Soren Gantt

Bibliographic record

VenuePLoS Computational Biology · 2024
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsUniversité de MontréalUniversity of British ColumbiaBC Children's HospitalBC Centre for Disease Control
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsImmune systemBiologyVirologyViral replicationCytomegalovirusImmunologyHuman cytomegalovirusViral loadSpleenImmunityVirus latencyHerpesviridaeVirusViral disease

Abstract

fetched live from OpenAlex

Human cytomegalovirus (HCMV) is the most common congenital infection. Several HCMV vaccines are in development, but none have yet been approved. An understanding of the kinetics of CMV replication and transmission may inform the rational design of vaccines to prevent this infection. The salivary glands (SG) are an important site of sustained CMV replication following primary infection and during viral reactivation from latency. As such, the strength of the immune response in the SG likely influences viral dissemination within and between hosts. To study the relationship between the immune response and viral replication in the SG, and viral dissemination from the SG to other tissues, mice were infected with low doses of murine CMV (MCMV). Following intra-SG inoculation, we characterized the viral and immunological dynamics in the SG, blood, and spleen, and identified organ-specific immune correlates of protection. Using these data, we constructed compartmental mathematical models of MCMV infection. Model fitting to data and analysis indicate the importance of cellular immune responses in different organs and point to a threshold of infection within the SG necessary for the establishment and spread of infection.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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 designObservational
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

Citations2
Published2024
Admission routes2
Has abstractyes

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