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Record W3179482189

CD34 protein is expressed in murine, canine, and porcine lungs.

2021· article· en· W3179482189 on OpenAlexaff
Gurpreet Kaur Aulakh, Sushmita Maltare, Nguyen Phuong Khanh Le, Baljit Singh

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCD34BiologyPathologyImmunostainingMolecular biologyBronchoalveolar lavageImmunohistochemistryImmunofluorescenceHaematopoiesisAntibodyLungStem cellImmunologyCell biologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

The cell surface protein CD34 is expressed in various human tissues and cells, including hematopoietic stem cells, vascular endothelial cells, mucosal dendritic cells, mast cells, eosinophils, microglia, fibrocytes, muscle satellite cells, and platelets. There is a lack of data on the expression of CD34 in canine and porcine tissues. Therefore, we designed a series of immunoblotting, immunohistochemistry, and immunofluorescence experiments to observe CD34 expression in murine, canine, and porcine lungs. We used a rabbit antibody (clone EP373Y) to target the conserved human CD34 C-terminal region and validated its immunoreactivity against mouse lung homogenates. The data showed diffuse bronchiolar and alveolar epithelial localization of CD34 protein in normal murine, canine, and porcine lungs. At 9 or 24 h after bacterial endotoxin exposure, murine CD34 protein shifted to specific bronchoalveolar cells with a punctate pattern, as quantified by CD34 fluorescence. Specific porcine bronchoalveolar cells and leukocytes had significant CD34-positive immunostaining after H3N1 influenza infection. Thus, our study provides fundamental data on the expression of CD34 in lungs and validates an antibody for use in further experiments in these animal 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.312
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2021
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicNeonatal Respiratory Health Research→French-language works237,207→