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Record W4297347588 · doi:10.3390/ani12192576

Marine-Sulfated Polysaccharides Extracts Exhibit Contrasted Time-Dependent Immunomodulatory and Antiviral Properties on Porcine Monocytes and Alveolar Macrophages

2022· article· en· W4297347588 on OpenAlexaff
Caroline Hervet, Frédérick Bussy, Claude Le Goff, Déborah Ménard, Pi Nyvall Collén, Matthieu Le Goff, François Meurens, Nicolas Bertho

Bibliographic record

VenueAnimals · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of Saskatchewan
FundersConseil Régional des Pays de la Loire
KeywordsPorcine reproductive and respiratory syndrome virusImmune systemIn vivoIn vitroVirusBiologyAntimicrobialMacrophageViral replicationMicrobiologyRespiratory systemPolysaccharideImmunologyVirologyBiotechnologyBiochemistry

Abstract

fetched live from OpenAlex

Porcine respiratory complex syndrome has a strong economic impact on the swine breeding sector, as well as a clear repercussion on the wellbeing of the animals, leading to overuse of antimicrobial molecules. Algal extracts used in short-term treatments are empirically recognized by farmers as having a positive effect on pigs' health, however, their mechanisms of action are not well known and more research is needed. Herein we studied the short and median term impact of three algal extracts, in vitro, on the pro-inflammatory and antiviral responses of porcine primary blood monocytes and alveolar macrophages, as well as the susceptibility of the treated cells to infection by Porcine Respiratory and Reproductive Syndrome Virus (PRRSV) and the Aujeszky's Disease Virus (ADV). All extracts presented a pro-inflammatory short-term effect, associated for two of them, with an inhibition of the PRRSV replication. Conversely, the three extracts presented an anti-inflammatory median term effect, with no impact on PRRSV replication. The observed immune modulation prompts us to test, in vivo, the anti-PRRSV action of algal extracts and strengthen the interest for this natural resource.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.675

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.194
Teacher spread0.177 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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