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Record W2167249941 · doi:10.3892/ol.2012.989

Expression of β-adrenergic receptors in pediatric malignant brain tumors

2012· article· en· W2167249941 on OpenAlexaff
Iacopo Sardi, Laura Giunti, Cecilia Bresci, Anna Maria Buccoliero, Duccio Rossi Degl’Innocenti, S. Cardellicchio, Gianna Baroni, Franca Castiglione, Martina Da Ros, Patrizio Fiorini, Sabrina Giglio, Lorenzo Genitori, Maurizio Aricò, Luca Filippi

Bibliographic record

VenueOncology Letters · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsPediatric Oncology Group
FundersAssociazione Italiana per la Ricerca sul Cancro
KeywordsOncogeneReceptorBiologyImmunohistochemistryCellCell cultureBrain tumorCell cycleCancer researchMolecular medicinePathologyApoptosisMolecular biologyMedicineImmunologyGenetics

Abstract

fetched live from OpenAlex

β-adrenergic receptors (β-ARs) are G protein-coupled receptors that activate signal transduction pathways involved in angiogenesis, resulting in enhanced tumor vascularization and more aggressive growth. In this study, we evaluated the expression of β-ARs in a population of 12 children affected by malignant primary brain tumors. We found a significant expression of β1- and β2-ARs in all 12 samples as well as the 3 cell lines tested (U87MG, T98G and DAOY). The mean absolute β1-AR mRNA level standardized to GAPDH was 5.81 (range, -7.91 to 11.29) for brain tumors and 8.59 (range, 6.046 to 12.59) for cell lines (U87MG, DAOY and T98G), respectively. The mean absolute β2-AR mRNA level was 4.74 (range, -9.30 to 8.45) for tumor specimens and 7.64 (range, 5.85 to 8.88) for cell lines. These real-time quantitative (qRT)-PCR expression data were confirmed by immunohistochemical analysis. Our study evaluated the presence of β1- and β2-ARs in malignant pediatric brain tumors and brain tumor cell lines.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.277
Teacher spread0.263 · 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 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

Citations15
Published2012
Admission routes1
Has abstractyes

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