21 research outputs found
A mathematical model for assessing KRAS mutation effect on monoclonal antibody treatment of colorectal cancer
No full textThe most challenging task in colorectal cancer research nowadays is to understand the development of acquired resistance to anti-EGFR drugs. The key reason for this problem is the KRAS mutations produced after the treatment with monoclonal antibodies (mAb). KRAS screening tests done before the start of the treatment are not very sensitive to identify minute quantity of the mutated cells, which can produce resistance to the therapy after the beginning of the treatment. Here we present a mathematical model for the analysis of KRAS mutations behavior in colorectal cancer with respect to mAb treatments. To evaluate the drug performance we have developed equations for two types of tumors cells, i.e. KRAS mutated and KRAS wildtype. Both tumor cell populations were treated with a combination of mAb and chemotherapy drugs. It was observed that even the minimal initial concentration of KRAS mutation before the treatment has the ability to make the tumor refractory to the treatment. Patient’s immune responses are specifically taken into considerations and it is found that, in case of KRAS mutations, the immune strength does not affect medication efficacy. Finally, Cetuximab (mAb) and Irinotecan (chemotherapy) drugs are analyzed as firstline treatment of colorectal cancer with few KRAS mutated cells. Results show that this combined treatment is only effective for patients with high immune strengths and it should not be recommended as first-line therapy for patients with moderate immune strengths or weak immune systems because of a potential risk of relapse, with KRAS mutant cells acquired resistance involved with them
Mathematical modeling of drug resistance due to KRAS mutation in colorectal cancer
No full textThe most challenging task in colorectal cancer research nowadays is to understand the development of acquired resistance to anti-EGFR drugs. The key reason for this problem is the KRAS mutations appearance after the treatment with monoclonal antibodies (moAb). Here we present a mathematical model for the analysis of KRAS mutations behavior in colorectal cancer with respect to moAb treatments. To evaluate the drug performance we have developed equations for two types of tumors cells, KRAS mutated and KRAS wild-type. Both tumor cell populations were treated with a combination of moAb and chemotherapy drugs. It was observed that even the minimal initial concentration of KRAS mutation before the treatment has the ability to make the tumor refractory to the treatment. Minor population of KRAS mutations has strong influence on large number of wild-type cells as well rendering them resistant to chemotherapy. Patient׳s immune responses are specifically taken into considerations and it is found that, in case of KRAS mutations, the immune strength does not affect medication efficacy. Finally, cetuximab (moAb) and irinotecan (chemotherapy) drugs are analyzed as first-line treatment of colorectal cancer with few KRAS mutated cells. Results show that this combined treatment could be only effective for patients with high immune strengths and it should not be recommended as first-line therapy for patients with moderate immune strengths or weak immune systems because of a potential risk of relapse, with KRAS mutant cells acquired resistance involved with them
Effect of confinement on the decay of vortex ring
No full textThe effect of confinement on the decay of vortex ring is studied computationally using Lattice Boltzmann Method. An Initial vortex ring, introduced inside a wall bounded cubical domain, is let to evolve and its decay is noted in terms of maximum vorticity at the core and the total kinetic energy inside the domain. The study shows distinct regimes of decay in all cases of confinement ratios(ratio of vortex ring diameter to length of the cubical domain)
An Analytical Criterion for Centrifugal Instability in Non-Axisymmetric Vortices
No full textNon-axisymmetric vortices are ubiquitous in nature; examples include polar vortices in planets, the giant red spot in Jupiter, tornadoes and cyclones on Earth, mesoscale eddies in the ocean. Turbulent flows are furthermore known to be dominated by small- and large-scale vortex structures. Owing to the wide range of applications, knowledge of conditions under which a given vortex becomes unstable is beneficial. Here, the centrifugal instability of two-dimensional, non-axisymmetric vortices in the presence of an axial flow and a background rotation is studied using the local stability approach. The local stability approach, based on geometric optics and similar in formulation to the rapid distortion theory \cite{bib:godeferd2001}, considers the evolution of shortwavelength perturbations along streamlines in the base flow. This approach, developed by Lifschitz Hameiri \cite{bib:lifschitz1991}, is particularly useful for base flows for which a global stability analysis is computationally expensive. A sufficient criterion for centrifugal instability in an axisymmetric vortex with and is first derived by analytically solving the local stability equations for wave vectors that are periodic upon evolution around a closed streamline. This criterion is then heuristically extended to non-axisymmetric vortices and written in terms of integral quantities on a streamline. The criterion is then shown to be accurate in describing centrifugal instability over a reasonably large range of parameters that specify Stuart vortices and Taylor-Green vortices
Hybrid Modeling of Cancer Drug Resistance Mechanisms
No full textCancer is a multi-scale disease and its overwhelming complexity depends upon the multiple
interwind events occurring at both molecular and cellular levels, making it very difficult
for therapeutic advancements in cancer research. The resistance to cancer drugs is a
significant challenge faced by scientists nowadays. The roots of the problem reside not
only at the molecular level, due to multiple type of mutations in a single tumor, but also
at the cellular level of drug interactions with the tumor. Tumor heterogeneity is the term
used by oncologists for the involvement of multiple mutations in the development of a
tumor at the sub-cellular level. The mechanisms for tumor heterogeneity are rigorously
being explored as a reason for drug resistance in cancer patients. It is important to observe
cell interactions not only at intra-tumoral level, but it is also essential to study the drug
and tumor cell interactions at cellular level to have a complete picture of the mechanisms
underlying drug resistance.
The multi-scale nature of cancer drug resistance problem require modeling approaches
that can capture all the multiple sub-cellular and cellular interaction factors with respect to
dierent scales for time and space. Hybrid modeling offers a way to integrate both discrete
and continuous dynamics to overcome this challenge. This research work is focused on the
development of hybrid models to understand the drug resistance behaviors in colorectal
and lung cancers. The common thing about the two types of cancer is that they both have
dierent mutations at epidermal growth factor receptors (EGFRs) and they are normally
treated with anti-EGFR drugs, to which they develop resistances with the passage of time.
The acquiring of resistance is the sign of relapse in both kind of tumors.
The most challenging task in colorectal cancer research nowadays is to understand the
development of acquired resistance to anti-EGFR drugs. The key reason for this problem is
the KRAS mutations appearance after the treatment with monoclonal antibodies (moAb).
A hybrid model is proposed for the analysis of KRAS mutations behavior in colorectal
cancer with respect to moAb treatments. The colorectal tumor hybrid model is represented
as a single state automata, which shows tumor progression and evolution by means of
mathematical equations for tumor sub-populations, immune system components and drugs
for the treatment. The drug introduction is managed as a discrete step in this model.
To evaluate the drug performance on a tumor, equations for two types of tumors cells
are developed, i.e KRAS mutated and KRAS wild-type. Both tumor cell populations
were treated with a combination of moAb and chemotherapy drugs. It is observed that
even a minimal initial concentration of KRAS mutated cells before the treatment has the ability to make the tumor refractory to the treatment. Moreover, a small population of
KRAS mutated cells has a strong influence on a large number of wild-type cells by making
them resistant to chemotherapy. Patient's immune responses are specifically taken into
considerations and it is found that, in case of KRAS mutations, the immune strength does
not affect medication efficacy. Finally, cetuximab (moAb) and irinotecan (chemotherapy)
drugs are analyzed as first-line treatment of colorectal cancer with few KRAS mutated
cells. Results show that this combined treatment could be only effective for patients with
high immune strengths and it should not be recommended as first-line therapy for patients
with moderate immune strengths or weak immune systems because of a potential risk of
relapse, with KRAS mutant cells acquired resistance involved with them.
Lung cancer is more complicated then colorectal cancer because of acquiring of multiple
resistances to anti-EGFR drugs. The appearance of EGFR T790M and KRAS mutations
makes tumor resistant to a geftinib and AZD9291 drugs, respectively. The hybrid model for
lung cancer consists of two non-resistant and resistant states of tumor. The non-resistant
state is treated with geftinib drug until resistance to this drug makes tumor regrowth
leading towards the resistant state. The resistant state is treated with AZD9291 drug for
recovery. In this model the complete resistant state due to KRAS mutations is ignored
because of the unavailability of parameter information and patient data. Each tumor state
is evaluated by mathematical differential equations for tumor growth and progression. The
tumor model consists of four tumor sub-population equations depending upon the type
of mutations. The drug administration in this model is also managed as a discrete step
for exact scheduling and dosages. The parameter values for the model are obtained by
experiments performed in the laboratory. The experimental data is only available for
the tumor progression along with the geftinib drug. The model is then fine tuned for
obtaining the exact tumor growth patterns as observed in clinic, only for the geftinib
drug. The growth rate for EGFR T790M tumor sub-population is changed to obtain the
same tumor progression patterns as observed in real patients. The growth rate of mutations
largely depends upon the immune system strength and by manipulating the growth rates
for different tumor populations, it is possible to capture the factor of immune strength of
the patient. The fine tuned model is then used to analyze the effect of AZD9291 drug
on geftinib resistant state of the tumor. It is observed that AZD9291 could be the best
candidate for the treatment of the EGFR T790M tumor sub-population.
Hybrid modeling helps to understand the tumor drug resistance along with tumor
progression due to multiple mutations, in a more realistic way and it also provides a way
for personalized therapy by managing the drug administration in a strict pattern that
avoid the growth of resistant sub-populations as well as target other populations at the
same time. The only key to avoid relapse in cancer is the personalized therapy and the
proposed hybrid models promises to do that
Formal Analysis of Oscillatory Behaviors in Biological Regulatory Networks: An Alternative Approach
No full textAbstractIn the realm of system biology, the study of regulatory networks leads biologists to the development of increasingly large, detailed and complex models. These complex models, replicating the dynamics of cell processes, are then analyzed using different approaches to obtain predictions. Genetic oscillations play a main role in the activity of signal transduction by maintaining the cascade of internal biochemical reactions with the extracellular environment. Molecular alterations in the performance of such behavioral rhythms can lead to severe pathological problems, e.g. cancer. Different formal approaches have been proposed to analyze Biological Regulatory Networks (BRNs) Such approaches mainly involve the use of non-functional and Binary Decision Diagrams (BDDs) based model checkers for the analysis of irregular structured BRNs, and dense time concept for the modeling of BRNs. Computational Tree Logic (CTL) based analysis of BRNs is not suitable for identifying cyclic (oscillatory) behaviors in irregular structures and the use of Linear Temporal Logic (LTL) for the analysis of multistability is not viable. Morover, the reachability problem becomes undecidable in case of dense time modeling. In order to address these issues, we use delays and Minsky machines to observe the oscillatory behavior and to overcome the limitation of LTL for the analysis of multistable states. To demonstrate our approach, we consider two different case studies: Pseudomonas aeruginosa and P53-Mdm2 feedback loop
Methodological consequences of weak embodied cognition and shared intentionality
No full textEmbodied approaches to cognition have been empirically successful both in developmental psychology and robotics. Shared intentionality has been similarly productive in developmental and comparative psychology. However, embodiment and shared intentionality both have a rich philosophical history. As a consequence, researchers who aim to benefit from the methodological advances of these literature must navigate through a variety of different usages, many of which rest on potentially contentious philosophies regarding the nature of mind. We attempt to identify renditions of embodiment and shared intentionality that can motivate research while making relatively modest assumptions. As we will see, such readings already exist in the embodied cognition literature. We find most uses of shared intentionality, however, to be unnecessarily strong theses that inevitably tie a researcher to contentious frameworks. We suggest a usage-based explication of shared intentionality that is far weaker, and may motivate research in the absence of such assumptions.Peer reviewedFinal article publishedShared IntentionalityEmbodimentDevelopmental RoboticsSituated CognitionSynthetic ModellingSocial cognitio
