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Record W157512105 · doi:10.14670/hh-19.1201

Toll-like receptor 4 in normal and inflamed lungs and other organs of pig, dog and cattle.

2004· article· en· W157512105 on OpenAlexaff
Adel Wassef, Kyathanahalli S. Janardhan, J. Pearce, Baljit Singh

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTLR4PathologyLungBiologyStainingSpleenEpitheliumReceptorImmunohistochemistryEndotheliumToll-like receptorInflammationImmunologyInnate immune systemMedicineEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Bacterial diseases, especially those of the lung caused by Gram-negative bacteria, inflict significant economic loss associated with mortality and morbidity in domestic animals. Toll-like receptor 4 (TLR4) has recently been recognized as a major receptor for cellular interactions with lipopolysaccharides derived from Gram-negative bacteria. However, there are no data on the expression of TLR4 in various organs of domestic animals. We performed immunohistochemistry and immuno-gold electron microscopy to localize TLR4 in lung and seven other organs from normal pig, dog and calf (n=2 each) and in inflamed lungs from calves (n=4) challenged with Mannheimia hemolytica. The data show TLR4 in macrophages in lung, small intestine, liver and spleen in all the species and pulmonary intravascular macrophages in calves and pigs. Epithelium in lung, small intestine, cornea and convoluted and straight renal tubules was stained for TLR4. Vascular endothelium of large blood vessels only in lungs and skin was positive, and skeletal muscles were negative for TLR4. In inflamed lungs, airway epithelium showed reduced staining for TLR4 while staining in macrophages remained unaltered. These are the first immunocytochemical data on TLR4 expression in domestic animal species and show similarity in TLR4 staining in macrophages, epithelium and vascular endothelium among dog, pig and cattle.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.326

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 head0.192
Teacher spread0.185 · 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

Citations56
Published2004
Admission routes1
Has abstractyes

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