MétaCan
Menu
Back to cohort
Record W4388793794 · doi:10.1016/j.cimid.2023.102095

Organ distribution and early pathogenesis of Streptococcus equi subsp. zooepidemicus in swine

2023· article· en· W4388793794 on OpenAlexafffund
Arthur Nery Finatto, Sulove Koirala, Fernanda Luiza Facioli, J. A. R. Barbosa, Roman Nosach, Matheus de Oliveira Costa

Bibliographic record

VenueComparative Immunology Microbiology and Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsMcGill UniversityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyStreptococcus equiPathogenesisTonsilMesenteric lymph nodesMicrobiologySpleenInoculationPathogenOutbreakVirologyVeterinary medicineBacteriaImmunologyMedicine

Abstract

fetched live from OpenAlex

Streptococcus equi subsp. zooepidemicus is an emerging pathogen of pigs, resulting in high-mortality outbreaks of septicaemia and abortions. Here, we investigated the early pathogenesis of S. zooepidemicus in pigs following oronasal inoculation. Fourteen pigs were inoculated with live cultures of S. zooepidemicus ST-194, and monitored at 2,4, 8, and 24 h post-inoculation. Necropsies were performed to assess gross lesions and collect samples for bacterial culture and PCR analysis at each time point. Our findings revealed that S. zooepidemicus was detectable in various organs as early as 2 h post-inoculation, including liver and spleen, demonstrating rapid dissemination within the host. Tonsil samples consistently harboured live S. zooepidemicus throughout the study period, suggesting their potential for epidemiological sampling and diagnostics. Moreover, the presence of varying bacterial loads in mesenteric lymph nodes indicated persistence, replication, and a potential source for shedding. Further studies are required to determine the initial site of replication.

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 score0.106
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueComparative Immunology Microbiology and Infectious DiseasesSame topicStreptococcal Infections and TreatmentsFrench-language works237,207