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Record W4301225935 · doi:10.1158/1055-9965.1387.19.6

Highlights of This Issue

2010· article· en· W4301225935 on OpenAlexaboutno aff

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsGliomaMedicineMalignancyNitrosamineCarcinogenesisAstrocytomaInternal medicineCarcinogenCancerOncologyCancer researchChemistryBiochemistry

Abstract

fetched live from OpenAlex

Two studies in this issue address the development of informative astrocytoma and glioblastoma (GBM) biomarkers. In the first study, Santosh and colleagues evaluated insulin-like growth factor binding protein isoforms 2, 3, and 5 (IGFBP-2,-3, and -5) in astrocytoma samples. The authors report that mRNA and protein expression levels of these three IGFBP isoforms were associated with increasing grades of astrocytoma malignancy. In the second study, Sreekanthreddy and colleagues used information from glioma microarray databases to identify informative serum biomarkers. The authors identify several novel serum biomarkers for glioblastoma. Specifically, they report that high serum osteopontin (OPN) levels are a poor prognostic indicator in GBMs.There are significant differences in the levels of carcinogenic tobaccospecific nitrosamines (TSNA) found in cigarettes from different countries. In this study, Ashley and colleagues evaluated how TSNA levels in used cigarette butts relate to the amounts of salivary nitrosamines and urinary nitrosamine metabolites of smokers from four different countries. The study reports a direct association between salivary nitrosamine and urinary nitrosamine metabolite levels. In addition, levels of both were significantly reduced in subjects smoking cigarettes with lower TSNA levels (from Canada and Australia) compared to smokers of high TSNA cigarettes (from the United States). These findings provide incentive for countries to adopt known tobacco curing practices that can lower cigarette TSNA levels.Although the bacterium, Chlamydia pneumoniae has been implicated in lung carcinogenesis, the lack of a validated marker for chronic C. pneumoniae infection has hampered the precise estimation of its role in lung cancer. Chaturvedi and colleagues studied the relationship between C. pneumoniae infection and prospective lung cancer risk by assaying the presence of antibodies against Chlamydial heat shock protein-60 (CHSP-60). They report that individuals seropositive for CHSP-60 antibodies had significantly increased lung cancer risk. CHSP-60-related risk did not differ significantly by lung cancer histology or smoking, and CHSP-60 seropositivity was associated with increased risk 2 to 5 years prior to lung cancer diagnosis. This work highlights the potential for lung cancer risk reduction through treatments targeting chronic pulmonary infection and inflammation.To help identify biomarkers that reliably monitor oxidative stress levels in humans, Il'yasova and colleagues report on the responsiveness of urinary biomarkers in breast cancer patients undergoing doxorubicinbased chemotherapy. The study monitored five urinary biomarkers of oxidative lipid modification: four F2-isoprostanes and one oxidative product of uric acid (allantoin). This study found that in all subjects, the levels of all five urinary biomarkers increased following doxorubicin chemotherapy. These encouraging findings suggest the use of these biomarkers to measure oxidative stress levels in humans.

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)0.002
metaresearch head score (Gemma)0.010
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.263
Threshold uncertainty score0.879

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0070.004
Open science0.0030.003
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.2630.121

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 head0.021
GPT teacher head0.331
Teacher spread0.310 · 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
GenreEditorial

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

Citations0
Published2010
Admission routes1
Has abstractyes

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