scholarly journals A Two-Stage Mutation Stochastic Model of Carcinogenesis Driven by a Two Level Random Environment

2020 ◽  
Vol 5 (6) ◽  
pp. 1392-1408 ◽  
Author(s):  
V. S. S. Yadavalli ◽  
S. Udayabaskaran ◽  
C. T. Dora Pravina ◽  
S. Sreelakshmi
Keyword(s):  
Stochastic Model ◽  
Random Environment ◽  
Normal Cell ◽  
Malignant Cell ◽  
Intermediate Cell ◽  
Malignant Cells ◽  
Two Stage ◽  
Normal Cells ◽  
The Mean ◽  
Intermediate Cells

In this paper, we present a two-stage stochastic model of carcinogenesis in a two level random environment. The random environment switches between two levels, say, 1 and 2 alternately. When the environment is in level 1, a normal cell either divides into two normal cells or dies; and an intermediate cell divides into two intermediate cells or dies. When the environment is in level 2, a normal cell either divides into two intermediate cells or divides into one normal cell and one intermediate cell or divides into two normal cells or dies; and an intermediate cell either divides into two malignant cells or divides into one intermediate cell and one malignant cell or divides into two intermediate cells or dies. It is assumed that, once a malignant cell is produced, it generates a malignant tumor with probability 1. We obtain the mean numbers of normal, intermediate and malignant cells.

scholarly journals A Two-Stage Mutation Stochastic Model of Carcinogenesis Driven by a Three Level Environmental Process

2020 ◽  
Vol 5 (6) ◽  
pp. 1468-1487
Author(s):  
V. S. S. Yadavalli ◽  
S. Udayabaskaran ◽  
C. T. Dora Pravina ◽  
S. Sreelakshmi
Keyword(s):  
Random Environment ◽  
Normal Cell ◽  
Malignant Cell ◽  
Intermediate Cell ◽  
Malignant Cells ◽  
Level 3 ◽  
Environmental Process ◽  
The Mean ◽  
Intermediate Cells ◽  
Level 2

A two-mutation model of carcinogenesis which evolves under the influence of three level random environment on the production process is formulated and analyzed. A random environment occupies one of the levels 1, 2 and 3 at any time t according to a Markov process. When the environment is in level 1, a normal cell either divides into two normal cells or dies; and an intermediate cell divides into two intermediate cells or dies. When the environment is in level 2, a normal cell either divides into one normal cell and one intermediate cell or dies and an intermediate cell either divides into one intermediate cell and one malignant cell or dies. When the environment is in level 3, a normal cell either divides into two intermediate cells or dies and an intermediate cell either divides into two malignant cells or dies. It is assumed that, once a malignant cell is produced, it generates a malignant tumor with probability 1. We obtain the mean numbers of normal, intermediate and malignant cells at any time t.

scholarly journals The anticancer agent PB-100, selectively active on malignant cells, inhibits multiplication of sixteen malignant cell lines, even multidrug resistant

2000 ◽  
Vol 23 (1) ◽  
pp. 29-33 ◽  
Author(s):  
Mirko Beljanski
Keyword(s):  
Cancer Cells ◽  
Tumor Cells ◽  
Cell Lines ◽  
Plant Extract ◽  
Normal Cell ◽  
Anticancer Agent ◽  
Malignant Cell ◽  
Multidrug Resistant ◽  
Cell Multiplication ◽  
Malignant Cells

The plant-derived anticancer agent PB-100 selectively destroys cancer cells, even when multidrug resistant; yet, it does not inhibit normal (non-malignant) cell multiplication. Testing of PB-100 on sixteen malignant cell lines, several multidrug resistant, as well as on five normal cell lines, confirmed our previous results. Flavopereirine and dihydroflavopereirine, the active principles of PB-100, were chemically synthesized and displayed the same selectivity for tumor cells as the purified plant extract, being active at even lower concentrations.

The global dynamics of stochastic Holling type II predator-prey models with non constant mortality rate

Filomat ◽  
2017 ◽  
Vol 31 (18) ◽  
pp. 5811-5825
Author(s):  
Xinhong Zhang
Keyword(s):  
Mortality Rate ◽  
Stochastic Model ◽  
Sufficient Conditions ◽  
Positive Periodic Solution ◽  
Global Dynamics ◽  
Type Ii ◽  
Predator Prey ◽  
Persistence In The Mean ◽  
The Mean ◽  
Predator Prey Models

In this paper we study the global dynamics of stochastic predator-prey models with non constant mortality rate and Holling type II response. Concretely, we establish sufficient conditions for the extinction and persistence in the mean of autonomous stochastic model and obtain a critical value between them. Then by constructing appropriate Lyapunov functions, we prove that there is a nontrivial positive periodic solution to the non-autonomous stochastic model. Finally, numerical examples are introduced to illustrate the results developed.

scholarly journals Coculture with hiPS-derived intestinal cells enhanced human hepatocyte functions in a pneumatic-pressure-driven two-organ microphysiological system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marie Shinohara ◽  
Hiroshi Arakawa ◽  
Yuuichi Oda ◽  
Nobuaki Shiraki ◽  
Shinji Sugiura ◽  
...  
Keyword(s):  
Normal Cell ◽  
Human Hepatocytes ◽  
New Drugs ◽  
Intestinal Cells ◽  
Specific Gene ◽  
Gene Expressions ◽  
Normal Cells ◽  
Pneumatic Pressure ◽  
Pressure Driven

AbstractExamining intestine–liver interactions is important for achieving the desired physiological drug absorption and metabolism response in in vitro drug tests. Multi-organ microphysiological systems (MPSs) constitute promising tools for evaluating inter-organ interactions in vitro. For coculture on MPSs, normal cells are challenging to use because they require complex maintenance and careful handling. Herein, we demonstrated the potential of coculturing normal cells on MPSs in the evaluation of intestine–liver interactions. To this end, we cocultured human-induced pluripotent stem cell-derived intestinal cells and fresh human hepatocytes which were isolated from PXB mice with medium circulation in a pneumatic-pressure-driven MPS with pipette-friendly liquid-handling options. The cytochrome activity, albumin production, and liver-specific gene expressions in human hepatocytes freshly isolated from a PXB mouse were significantly upregulated via coculture with hiPS-intestinal cells. Our normal cell coculture shows the effects of the interactions between the intestine and liver that may occur in vivo. This study is the first to demonstrate the coculturing of hiPS-intestinal cells and fresh human hepatocytes on an MPS for examining pure inter-organ interactions. Normal-cell coculture using the multi-organ MPS could be pursued to explore unknown physiological mechanisms of inter-organ interactions in vitro and investigate the physiological response of new drugs.

Distribution of the number of alleles in multigene families

1992 ◽  
Vol 29 (04) ◽  
pp. 759-769
Author(s):  
R. C. Griffiths
Keyword(s):  
Stochastic Model ◽  
Gene Conversion ◽  
Lower Bounds ◽  
Multigene Families ◽  
Expected Number ◽  
Allele Type ◽  
The Mean

The distribution of the number of alleles in samples from r chromosomes is studied. The stochastic model used includes gene conversion within chromosomes and mutation at loci on the chromosomes. A method is described for simulating the distribution of alleles and an algorithm given for computing lower bounds for the mean number of alleles. A formula is derived for the expected number of samples from r chromosomes which contain the allele type of a locus chosen at random.

Pronucleus formation, DNA synthesis and metaphase entry in porcine oocytes following intracytoplasmic injection of murine spermatozoa

Zygote ◽  
2003 ◽  
Vol 11 (3) ◽  
pp. 261-270 ◽  
Author(s):  
Bong-Ki Kim ◽  
Sun Hong Cheon ◽  
Youn Jeong Lee ◽  
Sun Ho Choi ◽  
Xiang Shun Cui ◽  
...  
Keyword(s):  
Dna Synthesis ◽  
Normal Cell ◽  
S Phase ◽  
Normal Male ◽  
Ultrastructural Observation ◽  
Intracytoplasmic Injection ◽  
Paternal Factors ◽  
The Mean ◽  
Species Specific ◽  
Mean Time

The onset of pronucleus formation and DNA synthesis in porcine oocytes following the injection of porcine or murine sperm was determined in order to obtain insights into species-specific paternal factors that contribute to fertilisation. Similar frequencies of oocytes with female pronuclei were observed after injection with porcine sperm or with murine sperm. In contrast, male pronuclei formed 8-9 h following the injection of porcine sperm, and 6-8 h following the injection of murine sperm. After pronucleus formation maternally derived microtubules were assembled and appeared to move both male and female pronuclei to the oocyte centre. A few porcine oocytes entered metaphase 22 h after the injection of murine sperm, but normal cell division was not observed. The mean time of onset of S-phase in male pronuclei was 9.7 h following porcine sperm injection and 7.4 h following mouse sperm injection. Ultrastructural observation revealed that male pronuclei derived from murine sperm in porcine oocytes are morphologically similar to normal male pronuclei in porcine zygotes. These results suggest that species-specific paternal factors influence the onset of pronucleus formation and DNA synthesis. However, normal nuclear cytoplasmic interactions were observed in porcine S-phase oocytes following murine sperm injection.

A stochastic model for polymer degradation

1972 ◽  
Vol 9 (1) ◽  
pp. 43-53 ◽  
Author(s):  
S. K. Srinivasan ◽  
K. M. Mehata
Keyword(s):  
Stochastic Model ◽  
General Model ◽  
Polymer Degradation ◽  
Mean Square ◽  
Product Density ◽  
The Mean ◽  
Number Of Segments

The stochastic model for breaking of molecular segments proposed by Bithell is analysed and some results relating to the distribution of the number of fragments are obtained by using a slightly more general model which allows multiple ruptures. The product density technique is employed to derive the mean and mean square number of segments at any time t and the number of segments with length greater than y at time of production.

A Two-Stage Combination Model for Wind Power Forecasting

2015 ◽  
Vol 737 ◽  
pp. 9-13
Author(s):  
Jun Zhang ◽  
Yuan Hao Wang ◽  
Ying Yi Li ◽  
Feng Guo
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Wind Farm ◽  
General Trend ◽  
Two Stage ◽  
Combination Model ◽  
Second Stage ◽  
Combination Forecasting ◽  
The Mean ◽  
Power Sequence

With the wind farm data from the southeast coast this paper builds a two-stage combination forecasting model of output power based on data preprocessing which include filling up missing data and pre-decomposition. The first stage is a composite prediction of decomposed power sequence in which a time series and optimized BP neural network predict the general trend and the correlation of various factors respectively. The second stage is BP neural network with its input is the results of first stage. The effectiveness and accuracy of the two-stage combination model are verified by comparing the mean square error of the combination model and other models.

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