scholarly journals Are Adaptive Chemotherapy Schedules Robust? A Three-Strategy Stochastic Evolutionary Game Theory Model

Cancers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2880
Author(s):  
Rajvir Dua ◽  
Yongqian Ma ◽  
Paul K. Newton
Keyword(s):  
Drug Interactions ◽  
Process Model ◽  
Evolutionary Game ◽  
Response To Treatment ◽  
Cell Populations ◽  
Large Patient ◽  
Competitive Release ◽  
Closed Treatment ◽  
Wide Range ◽  
Finite Cell

We investigate the robustness of adaptive chemotherapy schedules over repeated cycles and a wide range of tumor sizes. Using a non-stationary stochastic three-component fitness-dependent Moran process model (to track frequencies), we quantify the variance of the response to treatment associated with multidrug adaptive schedules that are designed to mitigate chemotherapeutic resistance in an idealized (well-mixed) setting. The finite cell (N tumor cells) stochastic process consists of populations of chemosensitive cells, chemoresistant cells to drug 1, and chemoresistant cells to drug 2, and the drug interactions can be synergistic, additive, or antagonistic. Tumor growth rates in this model are proportional to the average fitness of the tumor as measured by the three populations of cancer cells compared to a background microenvironment average value. An adaptive chemoschedule is determined by using the N→∞ limit of the finite-cell process (i.e., the adjusted replicator equations) which is constructed by finding closed treatment response loops (which we call evolutionary cycles) in the three component phase-space. The schedules that give rise to these cycles are designed to manage chemoresistance by avoiding competitive release of the resistant cell populations. To address the question of how these cycles perform in practice over large patient populations with tumors across a range of sizes, we consider the variances associated with the approximate stochastic cycles for finite N, repeating the idealized adaptive schedule over multiple periods. For finite cell populations, the distributions remain approximately multi-Gaussian in the principal component coordinates through the first three cycles, with variances increasing exponentially with each cycle. As the number of cycles increases, the multi-Gaussian nature of the distribution breaks down due to the fact that one of the three sub-populations typically saturates the tumor (competitive release) resulting in treatment failure. This suggests that to design an effective and repeatable adaptive chemoschedule in practice will require a highly accurate tumor model and accurate measurements of the sub-population frequencies or the errors will quickly (exponentially) degrade its effectiveness, particularly when the drug interactions are synergistic. Possible ways to extend the efficacy of the stochastic cycles in light of the computational simulations are discussed.

scholarly journals Are adaptive chemotherapy schedules robust? A three-strategy stochastic evolutionary game theory model

2021 ◽  
Author(s):  
Rajvir Dua ◽  
Yongqian Ma ◽  
Paul K. Newton
Keyword(s):  
Drug Interactions ◽  
Evolutionary Game ◽  
Principal Component ◽  
Response To Treatment ◽  
Cell Populations ◽  
Large Patient ◽  
Competitive Release ◽  
Closed Treatment ◽  
Wide Range ◽  
Finite Cell

We investigate the robustness of adaptive chemotherapy schedules over repeated cycles and a wide range of tumor sizes. We introduce a non-stationary stochastic three-component fitness-dependent Moran process to quantify the variance of the response to treatment associated with multidrug adaptive schedules that are designed to mitigate chemotherapeutic resistance in an idealized (well-mixed) setting. The finite cell (N tumor cells) stochastic process consists of populations of chemosensitive cells, chemoresistant cells to drug 1, and chemoresistant cells to drug 2, and the drug interactions can be synergistic, additive, or antagonistic. First, the adaptive chemoschedule is determined by using the N → ∞ limit of the finite-cell process (i.e. the adjusted replicator equations) which is constructed by finding closed treatment response loops (which we call evolutionary cycles) in the three component phase-space. The schedules that give rise to these cycles are designed to manage chemoresistance by avoiding competitive release of the resistant cell populations. To address the question of how these cycles are likely to perform in practice over large patient populations with tumors across a range of sizes, we then consider the statistical variances associated with the approximate stochastic cycles for finite N, repeating the idealized adaptive schedule over multiple periods. For finite cell populations, the error distributions remain approximately multi-Gaussian in the principal component coordinates through the first three cycles, with variances increasing exponentially with each cycle. As the number of cycles increases, the multi-Gaussian nature of the distribution breaks down due to the fact that one of the three subpopulations typically saturates the tumor (competitive release) resulting in treatment failure. This suggests that to design an effective and repeatable adaptive chemoschedule in practice will require a highly accurate tumor model and accurate measurements of the subpopulation frequencies or the errors will quickly (exponentially) degrade its effectiveness, particularly when the drug interactions are synergistic. Possible ways to extend the efficacy of the stochastic cycles in light of the computational simulations are discussed.

scholarly journals The role of synergy and antagonism in designing multidrug adaptive chemotherapy schedules

2020 ◽  
Author(s):  
P.K. Newton ◽  
Y. Ma
Keyword(s):  
Tumor Cell ◽  
Drug Interactions ◽  
Cell Population ◽  
Tumor Recurrence ◽  
Fitness Landscape ◽  
Evolutionary Game ◽  
Cell Populations ◽  
Sensitive Cell ◽  
Stable States ◽  
Competitive Release

Chemotherapeutic resistance via the mechanism of competitive release of resistant tumor cell subpopulations is a major problem associated with cancer treatments and one of the main causes of tumor recurrence. Often, chemoresistance is mitigated by using multidrug schedules (two or more combination therapies) that can act synergistically, additively, or antagonistically on the heterogeneous population of cells as they evolve. In this paper, we develop a three-component evolutionary game theory model to design two-drug adaptive schedules (timing and dose levels associated with C1(t) and C2(t)) that mitigate chemoresistance and delay tumor recurrence in an evolving collection of tumor cells with two resistant subpopulations: R1 (sensitive to drug 1, resistant to drug 2), and R2 (sensitive to drug 2, resistant to drug 1). A key parameter, e, takes us from synergistic (e > 0), to additive (e = 0), to antagonistic (e < 0) drug interactions. In addition to the two resistant populations, the model includes a population of chemosensitive cells, S that have higher baseline fitness but are not resistant to either drug. Using the nonlinear replicator dynamical system with a payoff matrix of Prisoner’s Dilemma (PD) type (enforcing a cost to resistance), we investigate the nonlinear dynamics of the three-component system (S, R1, R2), along with an additional tumor growth model whose growth rate is a function of the fitness landscape of the tumor cell populations. We show that antagonistic drug interactions generally result in slower rates of adaptation of the resistant cells than synergistic ones, making them more effective in combating the evolution of resistance. We then design closed loops in the three-component phase space by shaping the fitness landscape of the cell populations (i.e. altering the evolutionary stable states of the game) using appropriately designed time-dependent schedules (adaptive therapy), altering the dosages and timing of the two drugs using information gleaned from constant dosing schedules. We show that the bifurcations associated with the evolutionary stable states are transcritical, and we detail a typical antagonistic bifurcation that takes place between the sensitive cell population S and the R1 population, and a synergistic bifurcation that takes place between the sensitive cell population S and the R2 population for fixed values of C1 and C2. These bifurcations help us further understand why antagonistic interactions are more effective at controlling competitive release of the resistant population than synergistic interactions in the context of an evolving tumor.

Development and Validation of a New Scoring Tool to Evaluate the Clinical Evolution of Adult Patients with Nonsegmental Vitiligo

Dermatology ◽  
2021 ◽  
pp. 1-9
Author(s):  
María Luisa Peralta-Pedrero ◽  
Denisse Herrera-Bringas ◽  
Karla Samantha Torres-González ◽  
Martha Alejandra Morales-Sánchez ◽  
Fermín Jurado Santa-Cruz ◽  
...  
Keyword(s):  
Body Surface ◽  
Task Force ◽  
Intraclass Correlation ◽  
The Body ◽  
Response To Treatment ◽  
Similar Response ◽  
Clinical Evolution ◽  
Wide Range ◽  
Patient Reported ◽  
Extreme Groups

<b><i>Background:</i></b> Vitiligo has an unpredictable course and a variable response to treatment. Furthermore, the improvement of some vitiligo lesions cannot be considered a guarantee of a similar response to the other lesions. Instruments for patient-reported outcome measures (PROM) can be an alternative to measure complex constructions such as clinical evolution. <b><i>Objective:</i></b> The aim of this study was to validate a PROM that allows to measure the clinical evolution of patients with nonsegmental vitiligo in a simple but standardized way that serves to gather information for a better understanding of the disease. <b><i>Methods:</i></b> The instrument was created through expert consensus and patient participation. For the validation study, a prospective cohort design was performed. The body surface area affected was measured with the Vitiligo Extension Score (VES), the extension, the stage, and the spread by the evaluation of the Vitiligo European Task Force assessment (VETFa). Reliability was determined with test-retest, construct validity through hypothesis testing, discriminative capacity with extreme groups, and response capacity by comparing initial and final measurements. <b><i>Results:</i></b> Eighteen semi-structured interviews and 7 cognitive interviews were conducted, and 4 dermatologists were consulted. The instrument Clinical Evolution-Vitiligo (CV-6) was answered by 119 patients with a minimum of primary schooling. A wide range was observed in the affected body surface; incident and prevalent cases were included. The average time to answer the CV-6 was 3.08 ± 0.58 min. In the test-retest (<i>n</i> = 53), an intraclass correlation coefficient was obtained: 0.896 (95% CI 0.82–0.94; <i>p</i> &#x3c; 0.001). In extreme groups, the mean score was 2 (2–3) and 5 (4–6); <i>p</i> &#x3c; 0.001. The initial CV-6 score was different from the final one and the change was verified with VES and VETFa (<i>p</i> &#x3c; 0.05, <i>n</i> = 92). <b><i>Conclusions:</i></b> The CV-6 instrument allows patient collaboration, it is simple and brief, and it makes it easier for the doctor to focus attention on injuries that present changes at the time of medical consultation.

scholarly journals Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5658
Author(s):  
Donát Alpár ◽  
Bálint Egyed ◽  
Csaba Bödör ◽  
Gábor T. Kovács
Keyword(s):  
High Resolution ◽  
Single Cell ◽  
Childhood Leukemia ◽  
Clinical Decision Making ◽  
Cellular Heterogeneity ◽  
Therapeutic Interventions ◽  
Cell Populations ◽  
Pediatric Leukemia ◽  
Single Cell Sequencing ◽  
Wide Range

Single-cell sequencing (SCS) provides high-resolution insight into the genomic, epigenomic, and transcriptomic landscape of oncohematological malignancies including pediatric leukemia, the most common type of childhood cancer. Besides broadening our biological understanding of cellular heterogeneity, sub-clonal architecture, and regulatory network of tumor cell populations, SCS can offer clinically relevant, detailed characterization of distinct compartments affected by leukemia and identify therapeutically exploitable vulnerabilities. In this review, we provide an overview of SCS studies focused on the high-resolution genomic and transcriptomic scrutiny of pediatric leukemia. Our aim is to investigate and summarize how different layers of single-cell omics approaches can expectedly support clinical decision making in the future. Although the clinical management of pediatric leukemia underwent a spectacular improvement during the past decades, resistant disease is a major cause of therapy failure. Currently, only a small proportion of childhood leukemia patients benefit from genomics-driven therapy, as 15–20% of them meet the indication criteria of on-label targeted agents, and their overall response rate falls in a relatively wide range (40–85%). The in-depth scrutiny of various cell populations influencing the development, progression, and treatment resistance of different disease subtypes can potentially uncover a wider range of driver mechanisms for innovative therapeutic interventions.

scholarly journals Business Process Models in the Context of Predictive Process Monitoring

2021 ◽  
Vol 28 (1) ◽  
pp. 39-46
Author(s):  
Florian Spree
Keyword(s):  
Process Monitoring ◽  
Business Process ◽  
Process Model ◽  
Academic Research ◽  
Research Area ◽  
Process Models ◽  
Business Process Model ◽  
Business Process Models ◽  
Wide Range ◽  
Predictive Process

Predictive process monitoring is a subject of growing interest in academic research. As a result, an increased number of papers on this topic have been published. Due to the high complexity in this research area a wide range of different experimental setups and methods have been applied which makes it very difficult to reliably compare research results. This paper's objective is to investigate how business process models and their characteristics are used during experimental setups and how they can contribute to academic research. First, a literature review is conducted to analyze and discuss the awareness of business process models in experimental setups. Secondly, the paper discusses identified research problems and proposes the concept of a web-based business process model metric suite and the idea of ranked metrics. Through a metric suite researchers and practitioners can automatically evaluate business process model characteristics in their future work. Further, a contextualization of metrics by introducing a ranking of characteristics can potentially indicate how the outcome of experimental setups will be. Hence, the paper's work demonstrates the importance of business process models and their characteristics in the context of predictive process monitoring and proposes the concept of a tool approach and ranking to reliably evaluate business process models characteristics.

Maintenance of multiplication rate stability by cell populations in the face of heterogeneity among individual cells

1988 ◽  
Vol 91 (4) ◽  
pp. 571-576 ◽  
Author(s):  
R. Grundel ◽  
H. Rubin
Keyword(s):  
Growth Rates ◽  
Cell Populations ◽  
Multiplication Rate ◽  
Population Growth Rates ◽  
Wide Range ◽  
Constant Multiplication ◽  
Embryo Cells ◽  
The Face ◽  
Nih 3T3 ◽  
Slow Growing

We addressed the question of how a population of cells can maintain a constant multiplication rate given the heterogeneity of its individual members. Using the NIH 3T3 line of mouse embryo cells, comparisons were made of multiplication rates between offspring subclones and the parental clones from which the subclones were derived. Parents at all levels of multiplication rate produced offspring with a wide range of multiplication rates. Offspring from parent cells with the highest growth rates rarely exceeded their parents in rate of multiplication. Offspring from slow-growing parents, however, often exceeded the parents. It is concluded that the multiplication of NIH 3T3 populations represents constant diversification in multiplication rate: heterogeneous parents producing heterogeneous offspring. Population growth rates can remain stable because the fastest-growing parents generally produce offspring that multiply slower than the parents while the slowest parents often produce offspring that multiply faster than the parents.

scholarly journals Effect of various abiotic stressors on some biochemical indices of Lepidium sativum plants

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Omar N. Al-Sammarraie ◽  
Khalid Y. Alsharafa ◽  
Muhamad O. Al-limoun ◽  
Khaled M. Khleifat ◽  
Sameeh A. Al-Sarayreh ◽  
...  
Keyword(s):  
Specific Activity ◽  
Morphological Changes ◽  
Early Response ◽  
Response To Treatment ◽  
Lepidium Sativum ◽  
Short Term ◽  
Drought Treatment ◽  
Protein Levels ◽  
Short Term Exposure ◽  
Wide Range

AbstractIn this study, the regulation of ascorbate peroxidase (APX) specific activity, anthocyanin, carotenoid, hydrogen peroxide, lipid peroxidation, and protein levels in cress leaves in response to different abiotic stresses were investigated. The total APX specific activity was significantly elevated after 9 days of drought treatment, short-term (2 h) exposure to 10, 100 and 370 µE of light, long-term exposure (at least 6 days) to 100 mM NaCl versus the specific APX activity in the controls. Furthermore, a significant change in total APX activity was detected in response to treatment with different temperatures; this change was an early response to 4 °C and 30 °C for a maximum of 4 h, while short-term exposure to 35 °C did not change total APX activity. The results of the present study revealed that plants have a wide range of mechanisms to cope with different stresses that possibly involve morphological changes. The results indicated that Lepidium sativum plants launch common protective pathways only under drought, salinity and high light stresses, while other protective mechanisms/strategies could be responsible for increasing the plants tolerance towards temperature and low light. Future studies will investigate changes in the photosynthetic quantum yield and specific target metabolites, proteins, and nonenzymatic antioxidants.

scholarly journals Effects of social network diversity in the disablement process: a comparison of causal inference methods and an outcome-wide approach to the Indonesian Family Life Surveys, 2007–2015

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Julia Schröders ◽  
Fatwa Sari Tetra Dewi ◽  
Maria Nilsson ◽  
Mark Nichter ◽  
Miguel San Sebastian
Keyword(s):  
Older Adults ◽  
Social Network ◽  
Health Outcomes ◽  
Health Effects ◽  
Family Life ◽  
Process Model ◽  
Healthy Aging ◽  
Men And Women ◽  
Disablement Process ◽  
Wide Range

Abstract Background Social networks (SN) have been proven to be instrumental for healthy aging and function as important safety nets, particular for older adults in low and middle-income countries (LMICs). Despite the importance of interpreting health outcomes in terms of SN, in many LMICs – including Indonesia – epidemiological studies and policy responses on the health effects of SN for aging populations are still uncommon. Using outcome-wide multi-method approaches to longitudinal panel data, this study aims to outline more clearly the role of SN diversity in the aging process in Indonesia. We explore whether and to what degree there is an association of SN diversity with adult health outcomes and investigate potential gender differences, heterogeneous treatment effects, and effect gradients along disablement processes. Methods Data came from the fourth and fifth waves of the Indonesian Family Life Survey fielded in 2007–08 and 2014–15. The analytic sample consisted of 3060 adults aged 50+ years. The primary exposure variable was the diversity of respondents’ SN at baseline. This was measured through a social network index (SNI), conjoining information about household size together with a range of social ties with whom respondents had active contact across six different types of role relationships. Guided by the disablement process model, a battery of 19 outcomes (8 pathologies, 5 impairments, 4 functional limitations, 2 disabilities) were included into analyses. Evidence for causal effects of SN diversity on health was evaluated using outcome-wide multivariable regression adjustment (RA), propensity score matching (PSM), and instrumental variable (IV) analyses. Results At baseline, 60% of respondents had a low SNI. Results from the RA and PSM models showed greatest concordance and that among women a diverse SN was positively associated with pulmonary outcomes and upper and lower body functions. Both men and women with a high SNI reported less limitations in performing activities of daily living (ADL) and instrumental ADL (IADL) tasks. A high SNI was negatively associated with C-reactive protein levels in women. The IV analyses yielded positive associations with cognitive functions for both men and women. Conclusions Diverse SN confer a wide range of strong and heterogeneous long-term health effects, particularly for older women. In settings with limited formal welfare protection, intervening in the SN of older adults and safeguarding their access to diverse networks can be an investment in population health, with manifold implications for health and public policy.

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