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Record W2128905231 · doi:10.1186/1477-7819-8-60

Malignant mixed Mullerian tumors of the uterus: histopathological evaluation of cell cycle and apoptotic regulatory proteins

2010· article· en· W2128905231 on OpenAlexaffabout
Rani Kanthan, Jenna‐Lynn Senger, Dana Diudea

Bibliographic record

VenueWorld Journal of Surgical Oncology · 2010
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health Authority
Fundersnot available
KeywordsSurgical oncologyMedicineUterusCell cycleApoptosisPathologyCancer researchCellOncologyInternal medicineCancerBiologyGenetics

Abstract

fetched live from OpenAlex

AIM: The aim of our study was to evaluate survival outcomes in malignant mixed Mullerian tumors (MMMT) of the uterus with respect to the role of cell cycle and apoptotic regulatory proteins in the carcinomatous and sarcomatous components. METHODS: 23 cases of uterine MMMT identified from the Saskatchewan Cancer Agency (1970-1999) were evaluated. Immunohistochemical expression of Bad, Mcl-1, bcl-x, bak, mdm2, bax, p16, p21, p53, p27, EMA, Bcl-2, Ki67 and PCNA was correlated with clinico-pathological data including survival outcomes. RESULTS: Histopathological examination confirmed malignant epithelial component with homologous (12 cases) and heterologous (11 cases) sarcomatous elements. P53 was strongly expressed (70-95%) in 15 cases and negative in 5 cases. The average survival in the p53+ve cases was 3.56 years as opposed to 8.94 years in p53-ve cases. Overexpression of p16 and Mcl-1 were observed in patients with longer survival outcomes (>2 years). P16 and p21 were overexpressed in the carcinomatous and sarcomatous elements respectively. Cyclin-D1 was focally expressed only in the carcinomatous elements. CONCLUSIONS: Our study supports that a) cell cycle and apoptotic regulatory protein dysregulation is an important pathway for tumorigenesis and b) p53 is an important immunoprognostic marker in MMMT of the uterus.

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)0.001
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 score0.760
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.294
Teacher spread0.273 · 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

Citations33
Published2010
Admission routes2
Has abstractyes

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