| 1. |
- Nilbert, Mef, et al.
(författare)
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Complex karyotypic anomalies in a bizarre leiomyoma of the uterus.
- 1989
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Ingår i: Genes, Chromosomes and Cancer. - : Wiley. - 1045-2257 .- 1098-2264. ; 1:2, s. 131-134
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Tidskriftsartikel (refereegranskat)abstract
- Cytogenetic investigation of short-term cultures from a bizarre leiomyoma of the uterus, a tumor type not hitherto karyotypically characterized, revealed two abnormal clones with multiple complex rearrangements. Three-fourths of the aberrant cells were hypodiploid with the composite karyotype 38-44, XX,-6,-7,-10,-11,+20,-22, r(1), der(2) (:2p23cen2q13::1q211qter), der(2)t(2;9)(p21;q13), t(5;?)(q35;?), t(5;?),(q35;?), + der(5)t(5;15)(q11;q15), der(8)t(8;11)(q24;q13), t(15;?)(p12;?), der(16)t(12;16)(q13;p13),+r,+mar. The remaining abnormal mitoses were hypotetraploid, with chromosome numbers ranging from 74 to 86. These massively rearranged cells showed the same markers that were found in the hypodiploid clone, but in duplicate, indicating that this clone had arisen through polyploidization of hypodiploid cells. Flow cytometry revealed a DNA index of 1.03.
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| 3. |
- Baldetorp, Bo, et al.
(författare)
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Statistical evaluation of cell kinetic data from DNA flow cytometry (FCM) by the EM algorithm
- 1989
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Ingår i: Cytometry. - : Wiley. - 0196-4763 .- 1097-0320. ; 10:6, s. 695-705
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Tidskriftsartikel (refereegranskat)abstract
- Flow cytometric DNA measurements yield the amount of DNA for each of a large number of cells. A DNA histogram normally consists of a mixture of one or more constellations of G0/G1-, S-, G2/M-phase cells, together with internal standards, debris, background noise, and one or more populations of clumped cells. We have modelled typical DNA histograms as a mixed distribution with Gaussian densities for the G0/G1 and G2/M phases, an S-phase density, assumed to be uniform between the G0/G1 and G2/M peaks, observed with a Gaussian error, and with Gaussian densities for standards of chicken and trout red blood cells. The debris is modelled as a truncated exponential distribution, and we also have included a uniform background noise distribution over the whole observation interval. We have explored a new approach for maximum-likelihood analyses of complex DNA histograms by the application of the EM algorithm. This algorithm was used for four observed DNA histograms of varying complexity. Our results show that the algorithm works very well, and it converges to reasonable values for all parameters. In simulations from the estimated models, we have investigated bias, variance, and correlations of the estimates.
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