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Record W4289947621 · doi:10.1152/ajpheart.00325.2022

Implications of <i>Sm22α</i>-Cre expression in keratinocytes and unanticipated inflammatory skin lesion in a model of atherosclerosis

2022· article· en· W4289947621 on OpenAlexafffund
Mei Hu, Sho Hiroyasu, David J. Granville, Zamaneh Kassiri

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2022
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaInternational Collaboration On Repair DiscoveriesVancouver Coastal HealthUniversity of Alberta
FundersCanadian Institutes of Health ResearchInstitute of Health Services and Policy ResearchHeart and Stroke Foundation of CanadaGovernment of Canada
KeywordsLDL receptorInflammationLesionReceptorEctopic expressionBiologyCholesterolEndocrinologyMedicineInternal medicinePathologyImmunologyLipoproteinGeneGenetics

Abstract

fetched live from OpenAlex

Although Sm22α-Cre is commonly used to target gene deletion in smooth muscle cells, Sm22α-derived Adam17 deletion resulted in unexpected severe skin lesions following high-fat diet feeding in a model of atherosclerosis. Adam17 deletion by a different SMC driver, Myh11-Cre, did not result in skin lesions in the same atherosclerosis model. Sm22α is highly expressed in keratinocytes, causing ectopic loss of ADAM17 in keratinocytes that caused significant epidermal lesions when combined with a high-fat diet.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.296
Teacher spread0.266 · 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

Citations4
Published2022
Admission routes2
Has abstractyes

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