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J Los

Publications and source records attributed to J Los.

16 recordsLinked to original sources
PubMed2006

Dissociative ion-pair formation in collisions of fast potassium atoms with benzene and fluorobenzene.

Using a crossed molecular-beam technique, electron transfer is studied in collisions of fast potassium atoms with benzene and fluorobenzene molecules. The negative fragment ions formed in the collision region are extracted by a pulsed voltage, and their masses and energy release distributions analyzed by a time-of-flight (TOF) method. The dominant fragment from C6H5F is F-. The phenyl ring fragments CH- and C2H- are also observed but with lower intensities. In the case of C6H6 the dominant anionic specie is C2H-. The kinetic-energy release distributions of the various fragments are derived from the width and shapes of the TOF peaks in the spectrum.

Journal Article↗
PubMed2000

Linear and nonlinear measures predict swimming in the leech

Stimulation of a trigger interneuron of an isolated nerve cord preparation of the medicinal leech, Hirudo medicinalis, sometimes leads to swimming; sometimes it does not. We investigate signals transmitted in the ventral cord of the leech after stimulation and seek quantitative measures that would make it possible to distinguish signals that predict swimming from those that do not. We find that a number of linear as well as nonlinear measures provide statistically significant distinctions between the two kinds of signals. The linear measures are the time dependence of (i) the standard deviation and (ii) the autocorrelation function at a small time delay. The nonlinear measures are (i) a measure of nonlinear predictability and (ii) the time dependence of a measure of the size of the embedded signal trajectory. Calculations using surrogate data suggest that the differences between the two classes of signals are dynamical as well as statistical.

Journal Article↗
PubMed1997

Prognostic implications of different cell cycle analysis models of flow cytometric DNA histograms of 1,301 breast cancer patients: results from the Multicenter Morphometric Mammary Carcinoma Project (MMMCP).

Conflicting prognostic results with regard to DNA flow cytometric cell cycle variables have been reported for breast cancer patients. An important reason for this may be related to differences in the interpretation of DNA histograms. Several computer programs based on different cell cycle fitting models are available resulting in significant variations in percent S-phase and other cell cycle variables. Our present study evaluated the prognostic value of percent S-phase cells obtained using 5 different cell cycle analysis models. Flow cytometric DNA histograms obtained from 1,301 fresh frozen breast cancer samples were interpreted with 5 different cell cycle analysis models using a commercially available computer program. Model 1 used the zero order S-phase calculation and "sliced nuclei" debris correction, model 2 added fixed G2/M- to G0/G1-phase ratio, and model 3 added correction for aggregates. Model 4 applied the first-order S-phase calculation and sliced debris correction. Model 5 fixed the coefficients of variation CVs of the G0/G1- and G2/M-phases in addition to applying the sliced nuclei debris correction and zero order S-phase calculation. The different models yielded clearly different prognostic results. The average percent S-phase cells of the aggregate correction model (model 3) provided the best prognostic value in all cases for overall survival (OS) as well as disease-free survival (DFS) (OS: p < 0.0001; DFS: p < 0.0001), in lymph node-positive cases (OS: p < 0.0001; DFS: p = 0.004) and in DNA-diploid subgroups (OS: p = 0.004; DFS: p = 0.001). For the lymph node negative and DNA-non-diploid subgroups, the percent S-phase of the second cell cycle reached slightly better prognostic significance than the average percent S-phase cells. In multivariate analysis, the average percent S-phase of the aggregate correction model had the best additional prognostic value to tumor size and lymph node status. In conclusion, different cell cycle analysis models yield clearly different prognostic results for invasive breast cancer patients. The most important prognostic percent S-phase variable was the average percent S-phase cells when aggregate correction was included in cell cycle analysis.

Adult↗
PubMed1997

Prognostic value of DNA ploidy using flow cytometry in 1301 breast cancer patients: results of the prospective Multicenter Morphometric Mammary Carcinoma Project.

The literature on breast cancer reports conflicting prognostic results with respect to DNA ploidy of flow cytometric DNA histograms. This might result from different DNA ploidy classification methods. Our study evaluated the prognostic power of DNA ploidy, using different classification methods, in a large prospective group (n = 1301) of breast cancer patients. Flow cytometric DNA histograms obtained from fresh frozen material were interpreted with use of a commercially available computer program. On the basis of the number of stemlines and the DNA Index, we classified the DNA ploidy by different methods. In all of the cases, the classification method "DNA diploid versus DNA nondiploid" provided the best prognostic significance for overall survival (OS) (Mantel-Cox (MC) = 5.4, P = .02; relative risk (RR) = 1.3, P = .05) and for disease-free survival (DFS) (MC = 11.8, P = .0006; RR = 1.3, P < .05). This was also true for the OS of the lymph node-positive (but not the lymph node-negative) subgroup (MC = 4.1, P = .04; RR = 1.3, P = .05). In subgroups classified on the basis of tumor size, DNA ploidy showed prognostic significance for DFS only in the subgroup of tumors smaller than 2 cm and larger than 5 cm. In multivariate analysis, DNA ploidy showed no additional prognostic power to lymph node status and tumor size. The classification "DNA diploid versus DNA nondiploid" was mostly consistent with respect to prognostic power for OS and DFS, especially in small or lymph node-positive tumors. The RR of DNA nondiploid patients was only marginally higher, however, so large study groups are required to reach statistical significance. This could partly explain the disagreements in the literature. Therefore, DNA ploidy seems to be of little clinical importance in breast cancer patients, compared with other prognostic parameters.

Adult↗
PubMed1989

The Multicenter Morphometric Mammary Carcinoma Project (MMMCP). A nationwide prospective study on reproducibility and prognostic power of routine quantitative assessments in The Netherlands.

The Multicenter Morphometric Mammary Carcinoma Project (MMMCP) has been set up to investigate prospectively the prognostic value and reproducibility of routine assessments of the morphometric Multivariate Prognostic Index (MPI) and other quantitative parameters in comparison with classical prognosticators and steroid receptors in breast cancer patients. In this project, 34 hospitals participate, divided over six geographically different regions. Of each patient entering in the study, multiple clinical and classical pathological parameters (including tumor size and lymph node status) as well as several quantitative parameters such as mean nuclear area, DNA index and mitotic activity index will be evaluated. Of all patients, the MPI will be assessed with tumour size, lymph node status and mitotic activity index. The quantitative assessments are performed in all consecutive breast cancers which enter the participating pathology laboratories, and all measurements are controlled in Amsterdam. The patient intake time will be from January 1, 1988 until January 1, 1990. It is expected that 3000 patients will enter in this study. Follow up data will be gathered up to 10 years. However, two to five years after the initiation of the Project, a first evaluation of the reproducibility and prognostic significance of routine MPI and other assessments in breast cancer patients will be possible. A detailed description of this project is given.

Breast Neoplasms↗