Respondents of health survey powered by the innovative NURO app exhibit correlations between exercise frequencies and diet habits, and between stress levels and sleep wellness.

Nurosene's NURO app (nurosene.com) is an innovative smartphone application that gathers and analyzes active self-report metrics from users, empowering them with data-driven health machine intelligence. We present the data collected and analyzed from the initial round of participants who responded to a 12-question survey on their life-style and health status. Exploratory results using a variational autoencoder (VAE) suggested that much of the variability of the 12 dimensional data could be accounted for by two approximately uncorrelated latent variables: one pertaining to stress and sleep, and the other pertaining to exercise and diet. Subsequent modeling of the data using exploratory and confirmatory factor analyses (EFAs and CFAs) found that optimal data fits consisted of four factors, namely exercise, diet, stress, and sleep. Covariance values were high between exercise and diet, and between stress and sleep, but much lower between other pairings of non-identical factors. Both EFAs and CFAs provided extra contexts to and quantified the more preliminary VAE observations. Overall, our results significantly reduce the apparent complexity of the response data. This reduction allows for more efficient future stratification and analyses of participants based on simpler latent variables. Our discovery of novel relationships between stress and sleep, and between exercise and diet suggests the possibility of applying predictive analytics in future efforts.

Rotation of sex combs in Drosophila melanogaster requires precise and coordinated spatio-temporal dynamics from forces generated by epithelial cells.

The morphogenesis of sex combs (SCs), a male trait in many species of fruit flies, is an excellent system in which to study the cell biology, genetics and evolution of a trait. In Drosophila melanogaster, where the incipient SC rotates from horizontal to a vertical position, three signal comb properties have been documented: length, final angle and shape (linearity). During SC rotation, in which many cellular processes are occurring both spatially and temporally, it is difficult to distinguish which processes are crucial for which attributes of the comb. We have used a novel approach combining simulations and experiments to uncover the spatio-temporal dynamics underlying SC rotation. Our results indicate that 1) the final SC shape is primarily controlled by the inhomogeneity of initial cell size in cells close to the immature comb, 2) the final angle is primarily controlled by later cell expansion and 3) a temporal sequence of cell expansion mitigates the malformations generally associated with longer rotated SCs. Overall, our work has linked together the morphological diversity of SCs and the cellular dynamics behind such diversity, thus providing important insights on how evolution may affect SC development via the behaviours of surrounding epithelial cells.

Network models predict that reduced excitatory fluctuations can give rise to hippocampal network hyper-excitability in MeCP2-null mice.

Rett syndrome is a severe pediatric neurological disorder caused by loss of function mutations within the gene encoding methyl CpG-binding protein 2 (MeCP2). Although MeCP2 is expressed near ubiquitously, the primary pathophysiology of Rett syndrome stems from impairments of nervous system function. One alteration within different regions of the MeCP2-deficient brain is the presence of hyper-excitable network responses. In the hippocampus, such responses exist despite there being an overall decrease in spontaneous excitatory drive within the network. In this study, we generated and used mathematical, neuronal network models to resolve this apparent paradox. We did this by taking advantage of previous mathematical modelling insights that indicated that decreased excitatory fluctuations, but not mean excitatory drive, more critically explain observed changes in hippocampal network oscillations from MeCP2-null mouse slices. Importantly, reduced excitatory fluctuations could also bring about hyper-excitable responses in our network models. Therefore, these results indicate that diminished excitatory fluctuations may be responsible for the hyper-excitable state of MeCP2-deficient hippocampal circuitry.

Inhibitory networks of fast-spiking interneurons generate slow population activities due to excitatory fluctuations and network multistability.

Slow population activities (SPAs) exist in the brain and have frequencies below ~5 Hz. Despite SPAs being prominent in several cortical areas and serving many putative functions, their mechanisms are not well understood. We studied a specific type of in vitro GABAergic, inhibition-based SPA exhibited by C57BL/6 murine hippocampus. We used a multipronged approach consisting of experiment, simulation, and mathematical analyses to uncover mechanisms responsible for hippocampal SPAs. Our results show that hippocampal SPAs are an emergent phenomenon in which the "slowness" of the network is due to interactions between synaptic and cellular characteristics of individual fast-spiking, inhibitory interneurons. Our simulations quantify characteristics underlying hippocampal SPAs. In particular, for hippocampal SPAs to occur, we predict that individual fast-spiking interneurons should have frequency-current (f-I) curves that exhibit a suitably sized kink where the slope of the curve decreases more abruptly in the gamma frequency range with increasing current. We also predict that these interneurons should be well connected with one another. Our mathematical analyses show that the combination of synaptic and intrinsic conditions, as predicted by our simulations, promotes network multistability. Population slow timescales occur when excitatory fluctuations drive the network between different stable network firing states. Since many of the parameters we use are extracted from experiments and subsequent measurements of experimental f-I curves of fast-spiking interneurons exhibit characteristics as predicted, we propose that our network models capture a fundamental operating mechanism in biological hippocampal networks.

Inhibition dominates in shaping spontaneous CA3 hippocampal network activities in vitro.

We have assessed the balance of excitation and inhibition in in vitro rodent hippocampal slices exhibiting spontaneous, basal sharp waves (bSPWs). A defining signature of a network exhibiting bSPWs is the rise and fall in local field activities with frequencies ranging from 0.5 to 4.5 Hz. This variation of extracellular local field activities manifests at the intracellular level as postsynaptic potentials (PSPs). In correspondence with the local field bSPWs, we consider "sparse" and "synchronous" parts of bSPWs at the intracellular level. We have used intracellular data of bSPW-associated PSPs together with mathematical extraction techniques to quantify the mean and variance of synaptic conductances that a neuron experiences during bSPW episodes. We find that inhibitory conductances dominate in pyramidal cells and in a putative interneuron, and that inhibitory variances are much greater than excitatory ones during synchronous parts of bSPWs. Specifically, we find that there is at least a twofold increase in inhibitory conductance dominance from "sparse" to "synchronous" bSPW states and that this transition is associated with inhibitory fluctuations of greater than 10% of the change in mean inhibitory conductance. On the basis of our findings, we suggest that such inhibitory fluctuations during transition may be a physiological feature of systems expressing such population activities. In summary, our results provide a quantified basis for understanding the interaction of excitatory and inhibitory neuronal subpopulations in bSPW activities.

A simple model for describing the concentration of 212Pb in the atmosphere.

The implementation of the Comprehensive Test Ban Treaty is resulting in the construction of a world-wide system of 80 monitoring stations that will be able to detect air-borne radioactivity, not only from atomic bombs but also from other anthropogenic and natural sources. A prototype monitoring station has been operating since April 1996 in Vancouver, BC, Canada. This station provides daily reports of natural radioactivity, including 7Be and decay products of 220Rn (thoron). Data for 212Pb concentrations have been analyzed over a 6-month period. The concentration is reduced by rainfall, high wind velocity, and low temperatures and it also depends on the wind direction, but atmospheric inversions appeared to have little impact. We present a relatively simple model, which is easy to use and which offers predictive powers that can be applied to other similar environmental situations.