The use of hybrid cellular automaton models for improving cancer therapy, In Proceedings, Cellular Automata: 6th International Conference on Cellular Automata for Research and Industry, ACRI 2004, Amsterdam, The Netherlands, eds P.M.A. Sloot, B. Chopard, A.G. Hoekstra

The Hybrid Cellular Automata (HCA) modelling framework can be an efficient approach to a number of biological problems, particularly those which involve the integration of multiple spatial and temporal scales. As such, HCA may become a key modelling tool in the development of the so-called intergrative biology. In this paper, we first discuss HCA on a general level and then present results obtained when this approach was implemented in cancer research

A mathematical model of Doxorubicin treatment efficacy on non-Hodgkin’s lymphoma: Investigation of current protocol through theoretical modelling results

Doxorubicin treatment outcomes for non-Hodgkin’s lymphomas (NHL) are mathematically modelled and computationally analyzed. The NHL model includes a tumor structure incorporating mature and immature vessels, vascular structural adaptation and NHL cell-cycle kinetics in addition to Doxorubicin pharmacokinetics (PK) and pharmacodynamics (PD). Simulations provide qualitative estimations of the effect of Doxorubicin on high-grade (HG), intermediate-grade (IG) and low-grade (LG) NHL. Simulation results imply that if the interval between successive drug applications is prolonged beyond a certain point, treatment will be inefficient due to effects caused by heterogeneous blood flow in the system

The stochastic air traffic flow management rerouting problem

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (leaves 42-43).We formulate a model for planning the rerouting of aircraft to alleviate en-route congestion, with system capacity being modeled stochastically. To overcome problems with tractability, we apply a Dantzig-Wolfe decomposition and present an efficient method for solving it. The decomposed formulation is shown to be tractable for real-world problem, and it generates up to a ten percent reduction in cost when compared to an otherwise equivalent deterministic model. We show that even when the decomposed formulation fails to terminate within a reasonable time, a near-optimal solution can still be generated.by Joshua B. Marron.M.Eng

Motility of Colonial Choanoflagellates and the Statistics of Aggregate Random Walkers.

We illuminate the nature of the three-dimensional random walks of microorganisms composed of individual organisms adhered together. Such aggregate random walkers are typified by choanoflagellates, eukaryotes that are the closest living relatives of animals. In the colony-forming species Salpingoeca rosetta we show that the beating of each flagellum is stochastic and uncorrelated with others, and the vectorial sum of the flagellar propulsion manifests as stochastic helical swimming. A quantitative theory for these results is presented and species variability discussed.Work supported by the EPSRC and St. Johns College (JBK), ERC Advanced Investigator Grant 247333 and a Wellcome Trust Senior Investigator Award.This is the final version of the article. It first appeared from American Physical Society via http://dx.doi.org/10.1103/PhysRevLett.116.03810

Joint and individual variation explained (JIVE) for integrated analysis of multiple data types

Research in several fields now requires the analysis of data sets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such data sets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data and provides new directions for the visual exploration of joint and individual structures. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types. Data and software are available at https://genome.unc.edu/jive/Comment: Published in at http://dx.doi.org/10.1214/12-AOAS597 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Transcranial direct current stimulation in neglect rehabilitation after stroke: a systematic review.

Hemispatial neglect is one of the most frequent attention disorders after stroke. The presence of neglect is associated with longer hospital stays, extended rehabilitation periods, and poorer functional recovery. Transcranial direct current stimulation (tDCS) is a new technique with promising results in neglect rehabilitation; therefore, the objective of this systematic review, performed following the PRISMA guidelines, is to evaluate the effectiveness of tDCS on neglect recovery after stroke. The search was done in MEDLINE (PubMed), Web of Science, Scopus, Cochrane Library, and BioMed Central databases. A total of 311 articles were found; only 11 met the inclusion criteria, including 152 post-stroke patients in total. Methodological quality and risk of bias were assessed for all the studies, and methodological characteristics of the studies, sample sizes, methods, main results, and other relevant data were extracted. tDCS intervention ranged from one to twenty sessions distributed in 1 day to 4 weeks, with intensity ranged from 1 to 2 mA. We found moderate evidence for the efficacy of tDCS in the rehabilitation of hemispatial neglect after a stroke, being more effective in combination with other interventions. Nonetheless, the limited number of studies and some studies' design characteristics makes it risky to draw categorical conclusions. Since scientific evidence is still scarce, further research is needed to determine the advantage of this treatment in acute, sub-acute and chronic stroke patients. Future studies should include larger samples, longer follow-ups, and broader neurophysiological assessments, with the final aim of establishing the appropriate use of tDCS as an adjuvant intervention in neurorehabilitation settings.pre-print964 K