The short-term effects of sedentary behaviour on cerebral hemodynamics and cognitive performance in older adults: a cross-over design on the potential impact of mental and/or physical activity.

BACKGROUND: Sedentary behaviour might be a potential risk factor for cognitive decline. However, the short-term effects of sedentary behaviour on (cerebro) vascular and cognitive performance in older people are unknown. METHODS: We used a cross-over design with 22 older adults (78 years, 9 females) to assess the short-term hemodynamic and cognitive effects of three hours uninterrupted sitting and explored if these effects can be counteracted with regular (every 30 min) two-minute walking breaks. In addition, we investigated if low versus high mental activity during the three hours of sitting modified these effects. Before and after each condition, alertness, executive functioning, and working memory were assessed with the Test of Attentional Performance battery. Additionally, cerebral blood flow velocity (Transcranial Doppler) and blood pressure (Finapres) were measured in rest, and during sit-to-stand and CO2 challenges to assess baroreflex sensitivity, cerebral autoregulation, and cerebral vasomotor reactivity. RESULTS: No short-term differences were observed in cognitive performance, cerebral blood flow velocity, baroreflex sensitivity, cerebral autoregulation, or cerebral vasomotor reactivity across time, or between conditions. Blood pressure and cerebrovascular resistance increased over time (8.6 mmHg (5.0;12.1), p < 0.001), and 0.23 in resistance (0.01;0.45), p = 0.04). However, these effects were not mitigated by mental activity or by short walking breaks to interrupt sitting. CONCLUSIONS: In older individuals, three hours of sitting did not influence cognitive performance or cerebral perfusion. However, the sitting period increased blood pressure and cerebrovascular resistance, which are known to negatively impact brain health in the long-term. Importantly, we found that these effects in older individuals cannot be mitigated by higher mental activity and/or regular walking breaks. TRIAL REGISTRATION: Clinical trial registration URL: https://www.toetsingonline.nl/. Unique identifier: NL64309.091.17. Date of registration: 06-02-2018

Statistical challenges in the development and evaluation of marker-based clinical tests

Exciting new technologies for assessing markers in human specimens are now available to evaluate unprecedented types and numbers of variations in DNA, RNA, proteins, or biological structures such as chromosomes. These markers, whether viewed individually, or collectively as a 'signature', have the potential to be useful for disease risk assessment, screening, early detection, prognosis, therapy selection, and monitoring for therapy effectiveness or disease recurrence. Successful translation from basic research findings to clinically useful test requires basic, translational, and regulatory sciences and a collaborative effort among individuals with varied types of expertise including laboratory scientists, technology developers, clinicians, statisticians, and bioinformaticians. The focus of this commentary is the many statistical challenges in translational marker research, specifically in the development and validation of marker-based tests that have clinical utility for therapeutic decision-making

Epidemics on contact networks: a general stochastic approach

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our systematic framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible (SIS) and susceptible-infectious-removed (SIR) dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.Comment: Main document: 16 pages, 7 figures. Electronic Supplementary Material (included): 6 pages, 1 tabl

Complementarity of Spike- and Rate-Based Dynamics of Neural Systems

Relationships between spiking-neuron and rate-based approaches to the dynamics of neural assemblies are explored by analyzing a model system that can be treated by both methods, with the rate-based method further averaged over multiple neurons to give a neural-field approach. The system consists of a chain of neurons, each with simple spiking dynamics that has a known rate-based equivalent. The neurons are linked by propagating activity that is described in terms of a spatial interaction strength with temporal delays that reflect distances between neurons; feedback via a separate delay loop is also included because such loops also exist in real brains. These interactions are described using a spatiotemporal coupling function that can carry either spikes or rates to provide coupling between neurons. Numerical simulation of corresponding spike- and rate-based methods with these compatible couplings then allows direct comparison between the dynamics arising from these approaches. The rate-based dynamics can reproduce two different forms of oscillation that are present in the spike-based model: spiking rates of individual neurons and network-induced modulations of spiking rate that occur if network interactions are sufficiently strong. Depending on conditions either mode of oscillation can dominate the spike-based dynamics and in some situations, particularly when the ratio of the frequencies of these two modes is integer or half-integer, the two can both be present and interact with each other

Novel Role of Y1 Receptors in the Coordinated Regulation of Bone and Energy Homeostasis

The importance of neuropeptide Y (NPY) and Y2 receptors in the regulation of bone and energy homeostasis has recently been demonstrated. However, the contributions of the other Y recep- tors are less clear. Here we show that Y1 receptors are expressed on osteoblastic cells. Moreover, bone and adipose tissue mass are elevated in Y1/ mice with a generalized increase in bone formation on cortical and cancellous surfaces. Importantly, the inhibitory effects of NPY on bone marrow stromal cells in vitro are absent in cells derived from Y1/ mice, indicating a direct action of NPY on bone cells via this Y receptor. Interestingly, in contrast to Y2 receptor or germ line Y1 receptor deletion, con- ditional deletion of hypothalamic Y1 receptors in adult mice did not alter bone homeostasis, food intake, or adiposity. Further- more, deletion of both Y1 and Y2 receptors did not produce additive effects in bone or adiposity. Thus Y1 receptor pathways act powerfully to inhibit bone production and adiposity by non- hypothalamic pathways, with potentially direct effects on bone tissue through a single pathway with Y2 receptors

Fast flowing populations are not well mixed

In evolutionary dynamics, well-mixed populations are almost always associated with all-to-all interactions; mathematical models are based on complete graphs. In most cases, these models do not predict fixation probabilities in groups of individuals mixed by flows. We propose an analytical description in the fast-flow limit. This approach is valid for processes with global and local selection, and accurately predicts the suppression of selection as competition becomes more local. It provides a modelling tool for biological or social systems with individuals in motion.Comment: 19 pages, 8 figure

A modified sequence capture approach allowing standard and methylation analyses of the same enriched genomic DNA sample

Background: Bread wheat has a large complex genome that makes whole genome resequencing costly. Therefore, genome complexity reduction techniques such as sequence capture make re-sequencing cost effective. With a high-quality draft wheat genome now available it is possible to design capture probe sets and to use them to accurately genotype and anchor SNPs to the genome. Furthermore, in addition to genetic variation, epigenetic variation provides a source of natural variation contributing to changes in gene expression and phenotype that can be profiled at the base pair level using sequence capture coupled with bisulphite treatment. Here, we present a new 12 Mbp wheat capture probe set, that allows both the profiling of genotype and methylation from the same DNA sample. Furthermore, we present a method, based on Agilent SureSelect Methyl-Seq, that will use a single capture assay as a starting point to allow both DNA sequencing and methyl-seq. Results: Our method uses a single capture assay that is sequentially split and used for both DNA sequencing and methyl-seq. The resultant genotype and epi-type data is highly comparable in terms of coverage and SNP/methylation site identification to that generated from separate captures for DNA sequencing and methyl-seq. Furthermore, by defining SNP frequencies in a diverse landrace from the Watkins collection we highlight the importance of having genotype data to prevent false positive methylation calls. Finally, we present the design of a new 12 Mbp wheat capture and demonstrate its successful application to re-sequence wheat. Conclusions: We present a cost-effective method for performing both DNA sequencing and methyl-seq from a single capture reaction thus reducing reagent costs, sample preparation time and DNA requirements for these complementary analyses

Brain Rhythms Reveal a Hierarchical Network Organization

Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or “virtual brains”, whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs) and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic), in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states display lower complexity than virtual brains modeling normal neural function. We finally discuss the implications of our results for the neurobiology of health and disease