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Record W1964322378 · doi:10.1309/7bhlahhu0n4mht7q

Podocalyxin

2005· article· fr· W1964322378 on OpenAlexaff
Todd W. Kelley, David G. Huntsman, Kelly M. McNagny, Calvin D. Roskelley, Eric D. Hsix

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2005
Typearticle
Languagefr
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsPodocalyxinMyeloid leukemiaCD34HaematopoiesisImmunohistochemistryBone marrowCancer researchMedicinePathologyMyeloidLeukemiaImmunologyBiologyStem cellInternal medicinePodocyteKidney

Abstract

fetched live from OpenAlex

Podocalyxin is a CD34 family member expressed by podocytes, vascular endothelium, mesothelium, and a subset of hematopoietic progenitors. Podocalyxin expression was not observed in the hematopoietic cells of normal adult bone marrow samples. However, podocalyxin was expressed by blasts in 30 (77%) of 39 cases of acute myeloid leukemia (AML), 22 (81%) of 27 cases of acute lymphoblastic leukemia (ALL), and 13 (87%) of 15 cases of cutaneous myeloid sarcoma. No correlation with CD34 expression by immunohistochemical analysis was seen. Wilms tumor 1 (WT1) expression was detected in blasts in 17 AML cases (44%) and 21 ALL cases (78%). There was no correlation between WT1 and podocalyxin expression. We conclude that podocalyxin is expressed commonly by blasts in ALL and AML. Analysis of the expression of CD34 and podocalyxin increases sensitivity for the immunophenotypic detection of leukemic blasts compared with the analysis of CD34 alone. Therefore, podocalyxin seems to complement CD34 as a useful hematopoietic blast marker. The physiologic role of podocalyxin in leukemic blasts remains unknown.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.367
Teacher spread0.349 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Clinical PathologySame topicRenal and related cancersFrench-language works237,207