Mathematical model of brain tumour with glia-neuron interactions and chemotherapy treatment

Acknowledgements This study was possible by partial financial support from the following Brazilian government agencies: Fundação Araucária, EPSRC-EP/I032606/1 and CNPq, CAPES and Science Without Borders Program Process nos. 17656125, 99999.010583/2013-00 and 245377/2012-3.Peer reviewedPreprin

Synaptic Plasticity and Spike Synchronisation in Neuronal Networks

This work was possible by partial financial support from the following Brazilian government agencies: CNPq (154705/2016-0, 311467/2014-8), CAPES, Fundacao Araucaria, and Sao Paulo Research Foundation (processes FAPESP 2011/19296-1, 2015/07311-7, 2016/16148-5, 2016/23398-8, 2015/50122-0). Research supported by grant 2015/50122-0 Sao Paulo Research Foundation (FAPESP) and DFG-IRTG 1740/2.Peer reviewedPostprin

Fractional dynamics and recurrence analysis in cancer model

In this work, we analyze the effects of fractional derivatives in the chaotic dynamics of a cancer model. We begin by studying the dynamics of a standard model, {\it i.e.}, with integer derivatives. We study the dynamical behavior by means of the bifurcation diagram, Lyapunov exponents, and recurrence quantification analysis (RQA), such as the recurrence rate (RR), the determinism (DET), and the recurrence time entropy (RTE). We find a high correlation coefficient between the Lyapunov exponents and RTE. Our simulations suggest that the tumor growth parameter ($\rho_1$) is associated with a chaotic regime. Our results suggest a high correlation between the largest Lyapunov exponents and RTE. After understanding the dynamics of the model in the standard formulation, we extend our results by considering fractional operators. We fix the parameters in the chaotic regime and investigate the effects of the fractional order. We demonstrate how fractional dynamics can be properly characterized using RQA measures, which offer the advantage of not requiring knowledge of the fractional Jacobian matrix. We find that the chaotic motion is suppressed as $\alpha$ decreases, and the system becomes periodic for $\alpha \lessapprox 0.9966$. We observe limit cycles for $\alpha \in (0.9966,0.899)$ and fixed points for $\alpha<0.899$. The fixed point is determined analytically for the considered parameters. Finally, we discover that these dynamics are separated by an exponential relationship between $\alpha$ and $\rho_1$. Also, the transition depends on a supper transient which obeys the same relationship

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Home-based exercise program in the indeterminate form of Chagas disease (PEDI-CHAGAS study): A study protocol for a randomized clinical trial

BackgroundChagas disease (CD) is a neglected endemic disease with worldwide impact due to migration. Approximately 50–70% of individuals in the chronic phase of CD present the indeterminate form, characterized by parasitological and/or serological evidence of Trypanosoma cruzi infection, but without clinical signs and symptoms. Subclinical abnormalities have been reported in indeterminate form of CD, including pro-inflammatory states and alterations in cardiac function, biomarkers and autonomic modulation. Moreover, individuals with CD are usually impacted on their personal and professional life, making social insertion difficult and impacting their mental health and quality of life (QoL). Physical exercise has been acknowledged as an important strategy to prevent and control numerous chronic-degenerative diseases, but unexplored in individuals with the indeterminate form of CD. The PEDI-CHAGAS study (which stands for “Home-Based Exercise Program in the Indeterminate Form of Chagas Disease” in Portuguese) aims to evaluate the effects of a home-based exercise program on physical and mental health outcomes in individuals with indeterminate form of CD.Methods and designThe PEDI-CHAGAS is a two-arm (exercise and control) phase 3 superiority randomized clinical trial including patients with indeterminate form of CD. The exclusion criteria are &lt;18 years old, evidence of non-Chagasic cardiomyopathy, musculoskeletal or cognitive limitations that preclude the realization of exercise protocol, clinical contraindication for regular exercise, and regular physical exercise (≥1 × per week). Participants will be assessed at baseline, and after three and 6 months of follow-up. The primary outcome will be QoL. Secondary outcomes will include blood pressure, physical fitness components, nutritional status, fatigability, autonomic modulation, cardiac morphology and function, low back pain, depression and anxiety, stress, sleep quality, medication use and adherence, and biochemical, inflammatory and cardiac biomarkers. Participants in the intervention group will undergo a home-based exercise program whilst those in the control group will receive only general information regarding the benefits of physical activity. Both groups will receive the same general nutritional counseling consisting of general orientations about healthy diets.ConclusionThe findings from the present study may support public health intervention strategies to improve physical and mental health parameters to be implemented more effectively in this population.Clinical trial registration[https://ensaiosclinicos.gov.br/rg/RBR-10yxgcr9/], identifier [U1111-1263-0153]