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Record W3047143629 · doi:10.5430/jst.v10n2p7

Prognostic significance of annexin II , human epididymis protein (HE-4) and claudin in endometrial carcinoma

2020· article· en· W3047143629 on OpenAlexvenueno aff
Noha F. Elaidy, Hanan Lotfy Mohammed, Mona Salah, Abd El Motaleb Mohamed

Bibliographic record

VenueJournal of Solid Tumors · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsnot available
Fundersnot available
KeywordsClaudinAnnexinImmunohistochemistryEndometrial cancerCarcinomaMedicineAnnexin A2Cancer researchEpididymisCancerStainingInternal medicineOncologyPathologyAndrologyTight junctionBiologyCell biology

Abstract

fetched live from OpenAlex

Introduction: Endometrial cancer (EC) is one of the most prevalent malignant tumors of the female reproductive system worldwide. Annexins are membrane binding proteins with important role in tumor development and progression. Human Epididymis Protein (HE-4) is a novel marker for gynecolgical tumors. Claudins are proteins of tight junction category playing an important role in cell adhesion and tumor spread.Material and methods: Seventy blocks of paraffin-embedded tissues of endometrial carcinoma cases. Immunohistochemical evaluation of Annexin II , HE- 4 and Claudin-7 staining was performed. Clinical follow-up to all cases was done every three months.Results: Positive Annexin II,HE-4 expression were observed in 88.6% and 77.1% of EC respectively. Significant correlation was found between expression of both Annexin II and HE-4 and FIGO stage, decreased both overall and disease free survival rates. Positive Claudin-7 expression was observed in 40% of EC, with significant correlation with high grade only, however, no correlation with other clinical parameters or survival analysis was detected.Conclusion: Annexin II, HE-4 and Claudin-7 are prognostic factors for endometrial carcinoma and could be used in molecular targeted therapy.

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)0.001
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 score0.015
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.020
GPT teacher head0.264
Teacher spread0.244 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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