Fractal analyses reveal independent complexity and predictability of gait

Locomotion is a natural task that has been assessed for decades and used as a proxy to highlight impairments of various origins. So far, most studies adopted classical linear analyses of spatio-temporal gait parameters. Here, we use more advanced, yet not less practical, non-linear techniques to analyse gait time series of healthy subjects. We aimed at finding more sensitive indexes related to spatio-temporal gait parameters than those previously used, with the hope to better identify abnormal locomotion. We analysed large-scale stride interval time series and mean step width in 34 participants while altering walking direction (forward vs. backward walking) and with or without galvanic vestibular stimulation. The Hurst exponent α and the Minkowski fractal dimension D were computed and interpreted as indexes expressing predictability and complexity of stride interval time series, respectively. These holistic indexes can easily be interpreted in the framework of optimal movement complexity. We show that α and D accurately capture stride interval changes in function of the experimental condition. Walking forward exhibited maximal complexity (D) and hence, adaptability. In contrast, walking backward and/or stimulation of the vestibular system decreased D. Furthermore, walking backward increased predictability (α) through a more stereotyped pattern of the stride interval and galvanic vestibular stimulation reduced predictability. The present study demonstrates the complementary power of the Hurst exponent and the fractal dimension to improve walking classification. Our developments may have immediate applications in rehabilitation, diagnosis, and classification procedures

Visual mate preference evolution during butterfly speciation is linked to neural processing genes

Abstract: Many animal species remain separate not because their individuals fail to produce viable hybrids but because they “choose” not to mate. However, we still know very little of the genetic mechanisms underlying changes in these mate preference behaviours. Heliconius butterflies display bright warning patterns, which they also use to recognize conspecifics. Here, we couple QTL for divergence in visual preference behaviours with population genomic and gene expression analyses of neural tissue (central brain, optic lobes and ommatidia) across development in two sympatric Heliconius species. Within a region containing 200 genes, we identify five genes that are strongly associated with divergent visual preferences. Three of these have previously been implicated in key components of neural signalling (specifically an ionotropic glutamate receptor and two regucalcins), and overall our candidates suggest shifts in behaviour involve changes in visual integration or processing. This would allow preference evolution without altering perception of the wider environment

Inflammation-associated extracellular β-glucuronidase alters cellular responses to the chemical carcinogen benzo[a]pyrene

Neutrophils infiltrate tissues during inflammation, and when activated, they release β-glucuronidase. Since inflammation is associated with carcinogenesis, we investigated how extracellular β-glucuronidase changed the in vitro cellular response to the chemical carcinogen benzo(a)pyrene (B[a]P). For this we exposed human liver (HepG2) and lung (A549) cells to B[a]P in the presence or absence of β-glucuronidase. β-Glucuronidase reduced B[a]P-induced expression of CYP1A1 and CYP1B1 at 6 h after exposure, which did not depend on β-glucuronidase activity, because the inhibitor d-saccharic acid 1,4-lactone monohydrate did not antagonize the effect of β-glucuronidase. On the other hand, the inhibitory effect of β-glucuronidase on CYP expression was dependent on signalling via the insulin-like growth factor receptor (IGF2R, a known receptor for β-glucuronidase), because co-incubation with the IGF2R inhibitor mannose-6-phosphate completely abolished the effect of β-glucuronidase. Extracellular β-glucuronidase also reduced the formation of several B[a]P metabolites and B[a]P–DNA adducts. Interestingly, at 24 h of exposure, β-glucuronidase significantly enhanced CYP expression, probably because β-glucuronidase de-glucuronidated B[a]P metabolites, which continued to trigger the aryl hydrocarbon receptor (Ah receptor) and induced expression of CYP1A1 (in both cell lines) and CYP1B1 (in A549 only). Consequently, significantly higher concentrations of B[a]P metabolites and DNA adducts were found in β-glucuronidase-treated cells at 24 h. DNA adduct levels peaked at 48 h in cells that were exposed to B[a]P and treated with β-glucuronidase. Overall, these data show that β-glucuronidase alters the cellular response to B[a]P and ultimately enhances B[a]P-induced DNA adduct levels

Influence of Input Parameters on Dynamic Orbital Stability of Walking: In-Silico and Experimental Evaluation

Many measures aiming to assess the stability of human motion have been proposed in the literature, but still there is no commonly accepted way to define or quantify locomotor stability. Among these measures, orbital stability analysis via Floquet multipliers is still under debate. Some of the controversies concerning the use of this technique could lie in the absence of a standard implementation. The aim of this study was to analyse the influence of i) experimental measurement noise, ii) variables selected for the construction of the state space, and iii) number of analysed cycles on the outputs of orbital stability applied to walking. The analysis was performed on a 2-dimensional 5-link walking model and on a sample of 10 subjects performing long over-ground walks. Noise resulting from stereophotogrammetric and accelerometric measurement systems was simulated in the in-silico analysis. Maximum Floquet multipliers resulted to be affected by both number of analysed strides and state space composition. The effect of experimental noise was found to be slightly more potentially critical when analysing stereophotogrammetric data then when dealing with acceleration data. Experimental and model results were comparable in terms of overall trend, but a difference was found in the influence of the number of analysed cycles