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Record W2163474517 · doi:10.1080/152873901300018057

ALTERATIONS OF K-ras AND p53 MUTATIONS IN COLORECTAL CANCER PATIENTS IN CENTRAL EUROPE

2001· article· en· W2163474517 on OpenAlexaff
Edwin A. König, István Köves, Angela Răşinariu, Anghel R. Popp, Wolfgang Kusser, Ken Soyonki, Ágota Kovács, Barry W. Glickman, A. Jéney, Z Marcsek

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2001
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsExonColorectal cancerCancer researchBiologySingle-strand conformation polymorphismOncogeneGeneSuppressorTumor suppressor geneCarcinogenesisMutationTumor progressionMalignancyPolymerase chain reactionGeneticsCancerCell cycle

Abstract

fetched live from OpenAlex

Many molecular investigations of colorectal cancer (CRC) have suggested that the accumulation of specific mutations in proto-oncogenes and tumor suppressor genes regulating cell growth via signal transduction trigger the stagewise progression to malignancy. In this study, the frequency, location, and type of mutations of the K-ras proto-oncogene exon I and p53 tumor suppressor gene exons 5-8 were analyzed in colorectal carcinomas of 65 patients from Central Europe, using polymerase chain reaction (PCR)-cold single-strand conformation polymorphism (SSCP) screening and direct sequencing. The incidence of K-ras activating mutations in these Central European samples was lower (25%) compared to that obtained in American and western European populations (40-50% at least), while the incidence of p53 inactivating mutations was similar (58%). These results suggest that some other genetically linked mechanisms may play a role in CRC development and progression, and hence K-ras and p53 mutations cannot be considered to be universal genetic markers for CRC.

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)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.290
Teacher spread0.276 · 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

Citations9
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Toxicology and Environmental HealthSame topicGenetic factors in colorectal cancerFrench-language works237,207