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Record W2401850857

Immunohistochemical study on tumor angiogenic factors in non-small cell lung cancer.

2000· article· en· W2401850857 on OpenAlexaff
Hirokazu Aikawa, Hiroto Takahashi, Shigefumi Fujimura, Masami Sato, Chiaki Endo, Akira Sakurada, Takashi Kondo, Tatsuo Tanita, Yuji Matsumura, Sadafumi Ono, Yasuki Saito, Motoyasu Sagawa

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsAngiogenesisLung cancerPathologyImmunohistochemistryCarcinogenesisVascular endothelial growth factorCarcinomaNeovascularizationMedicineLungCancerMicrovesselBiologyCancer researchInternal medicineVEGF receptors
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: In order to elucidate the roles of tumor angiogenesis in lung carcinogenesis, the expressions of several angiogenic factors in lung carcinoma tissues were examined. MATERIALS AND METHODS: Tissue specimens from 112 cases of resected non-small cell lung cancer (NSCLC) were studied. The expressions of platelet-derived endothelial cell growth factor (PD-ECGF) and vascular endothelial growth factor (VEGF) were examined immunohistochemically. Microvessel density (MVD) was also evaluated. RESULTS: VEGF-positive cases were observed more frequently in advanced stage lung cancers than in early cancers, and VEGF-positive tumors had higher MVD than VEGF-negative tumors, while such differences were not observed for PD-ECGF. In squamous cell carcinoma, the patients with high-MVD tumor had significantly worse survival than those with low-MVD tumor. CONCLUSIONS: Our results suggest that VEGF plays an important role in angiogenesis of lung cancers, while the contribution of PD-ECGF may be limited.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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

Citations27
Published2000
Admission routes1
Has abstractyes

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