Gene expression microarray analysis and genome databases facilitate the characterization of a chromosome 22 derived homogenously staining region
Why this work is in the frame
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Bibliographic record
Abstract
Karyotype and fluorescence in situ hybridization (FISH) analyses previously identified a homogeneously staining region (HSR) derived from chromosome 22 in OV90, an epithelial ovarian cancer (EOC) cell line. Affymetrix expression microarrays in combination with the UniGene and Human Genome Browser databases were used to identify the candidate genes comprising the amplicon of the HSR, based on comparison of expression profiles of OV90, EOC cell lines lacking HSRs and primary cultures of normal ovarian surface epithelial (NOSE) cells. A group of probe sets displaying a minimum 3-fold overexpression with a high reliability score (P-call) in OV90 were identified which represented genes that mapped within a 1-2 Mb interval on chromosome 22. A large number of probe sets, some of which represent the same genes, displayed no evidence of overexpression and/or low reliability scores (A-call). An investigation of the probe set sequences with the Affymetrix and Sanger Institute Chromosome 22 Group databases revealed that some of the probe sets displaying discordant results for the same gene were complementary to intronic sequences and/or the antisense strand. Microarray results were validated by RT-PCR. Genomic analysis suggests that the HSR was derived from the amplification of a 1.1 Mb interval defined by the chromosomal map positions of ZNF74 and Hs.372662, at 22q11.21. The deduced amplicon is derived from a complex region of chromosome 22 that harbors low-copy repeats (LCRs). The amplicon contains 18 genes as likely targets for gene amplification. This study illustrates that large-scale expression microarray analysis in combination with genome databases is sufficient for deducing target genes associated with amplicons and stresses the importance of investigating probe set design before engaging in validation studies.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it