Results: 4

1.
Figure 4

Figure 4. Simulations assuming independent or coupled pathway competition.. From: Stochastic Competition between Mechanistically Independent Slippage and Death Pathways Determines Cell Fate during Mitotic Arrest.

(A) Cumulative distribution functions of mitotic death (blue) and slippage (green) for four cell lines from experimental measurement. (B) Cumulative survival curves for independent (blue) and coupled (green) pathway competition, averaged over ten sets of simulated data (each consist of 100 single-cell events). The corresponding experimental curve is shown in black.

Hsiao-Chun Huang, et al. PLoS One. 2010;5(12):e15724.
2.
Figure 3

Figure 3. Death kinetics under perturbation of mitotic slippage.. From: Stochastic Competition between Mechanistically Independent Slippage and Death Pathways Determines Cell Fate during Mitotic Arrest.

(A) Probability distributions of time duration from mitotic entry to death for four cell lines treated with Cdc20 siRNA and K5I. Numbers in parentheses indicate number of cells scored. (B) Probability distributions of time duration from mitotic entry to death under K5I plus Lamin A/C siRNA (blue) or Cdc20 siRNA (green). Only cells that died in mitosis were scored for K5I treatment (for HeLa: 90.3%, for MDA: 77.3%, (9)). Only the corresponding percentages of early mitotic death events were scored for Cdc20 siRNA treatment. Numbers in parentheses indicate number of cells scored.

Hsiao-Chun Huang, et al. PLoS One. 2010;5(12):e15724.
3.
Figure 2

Figure 2. Slippage kinetics under perturbation of cell death.. From: Stochastic Competition between Mechanistically Independent Slippage and Death Pathways Determines Cell Fate during Mitotic Arrest.

(A) Probability distributions of time duration from mitotic entry to exit for four cell lines treated with Kinesin-5 inhibitor (K5I) and zVAD-fmk. Numbers in parentheses indicate number of cells scored. (B) Probability distributions of time duration from mitotic entry to exit in A549 cells treated with K5I alone (blue) or K5I plus zVAD-fmk (green). Numbers in parentheses indicate number of cells scored. (C) Probability distributions of time duration from mitotic entry to exit in HeLa cells treated with K5I alone (blue) or K5I plus zVAD-fmk (green). Only cells that exited mitosis were scored for both treatments (for K5I alone: less than 10%; with zVAD-fmk: more than 90%). Numbers in parentheses indicate number of cells scored. (D) Four representative cyclin B1 degradation curves before and after the addition of TRAIL in HeLa cells treated with K5I. Average of whole-cell fluorescent intensity was measured using Region Statistics function in MetaMorph. Degradation rates before and after TRAIL addition were calculated using Linear Regression function in GraphPad Prism 4.

Hsiao-Chun Huang, et al. PLoS One. 2010;5(12):e15724.
4.
Figure 1

Figure 1. Kinetic models explaining intra- and inter-line variations.. From: Stochastic Competition between Mechanistically Independent Slippage and Death Pathways Determines Cell Fate during Mitotic Arrest.

(A) Intra- and inter-line variations under the same drug stimuli. For intra-line variation, non-genetic variations in protein levels or post-translational modifications among individual cells results in different cell fates within a clonal population. For inter-line variation, the average behavior, or overall percentage of cell death/survival, is determined by genetic factors. (B) Models of kinetic competition between death and slippage. For independent pathway competition, mitotic state triggers two independent processes, caspase activation and cyclin B1 proteolysis, each leading to its corresponding state. For coupled pathway competition, mitotic states triggers one signal that is triggering the other, and the two coupled processes compete with their kinetic rates. M: mitosis; D: death; G1: post-slippage G1.

Hsiao-Chun Huang, et al. PLoS One. 2010;5(12):e15724.

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