MétaCan
Menu
Back to cohort

Expression of toll-like receptor 9 in lungs of pigs, dogs and cattle

2010· article· en· W1954407400 on OpenAlexafffund
David Schneberger, Danyse Lewis, Sarah Caldwell, Baljit Singh

Bibliographic record

VenueInternational Journal of Experimental Pathology · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsTLR9Innate immune systemImmunostainingToll-Like Receptor 9BiologyTLR4ReceptorAntibodyToll-like receptorImmune systemPathologyBlotImmunohistochemistryImmunologyGene expressionMedicineGeneBiochemistry

Abstract

fetched live from OpenAlex

Toll-like receptors (TLRs) are important components of the innate immune system. Compared with other TLRs such as TLR4, there is less data on the expression and function of TLR9, which binds to unmethylated DNA. Because there is no data on the cell-specific protein expression of TLR9 in lungs of cattle, dog and pigs, and pulmonary diseases are the major cause of economic losses, we studied TLR9 expression in lungs using Western blotting, immunohistology and immuno-electron microscopy. We characterized a mouse TLR9 antibody to detect TLR9 in lung extracts from pigs, dogs, and cattle. The TLR9 peptide used to raise the mouse TLR9 antibody had significant homology with TLR9 amino acid sequences from these species. Light and electron microscopic immunostaining localized TLR9 in airway epithelium, vascular endothelium, alveolar macrophages, and pulmonary intravascular monocytes/macrophages in all three species. These data are of potential importance for the understanding of pulmonary immune responses in these veterinary species.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.492

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 head0.007
GPT teacher head0.271
Teacher spread0.264 · 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

Citations24
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Experimental PathologySame topicImmune Response and InflammationFrench-language works237,207