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

Distribution of the Octopamine Receptor AmOA1 in the Honey Bee Brain

Octopamine plays an important role in many behaviors in invertebrates. It acts via binding to G protein coupled receptors located on the plasma membrane of responsive cells. Several distinct subtypes of octopamine receptors have been found in invertebrates, yet little is known about the expression pattern of these different receptor subtypes and how each subtype may contribute to different behaviors. One honey bee (Apis mellifera) octopamine receptor, AmOA1, was recently cloned and characterized. Here we continue to characterize the AmOA1 receptor by investigating its distribution in the honey bee brain. We used two independent antibodies produced against two distinct peptides in the carboxyl-terminus to study the distribution of the AmOA1 receptor in the honey bee brain. We found that both anti-AmOA1 antibodies revealed labeling of cell body clusters throughout the brain and within the following brain neuropils: the antennal lobes; the calyces, pedunculus, vertical (alpha, gamma) and medial (beta) lobes of the mushroom body; the optic lobes; the subesophageal ganglion; and the central complex. Double immunofluorescence staining using anti-GABA and anti-AmOA1 receptor antibodies revealed that a population of inhibitory GABAergic local interneurons in the antennal lobes express the AmOA1 receptor in the cell bodies, axons and their endings in the glomeruli. In the mushroom bodies, AmOA1 receptors are expressed in a subpopulation of inhibitory GABAergic feedback neurons that ends in the visual (outer half of basal ring and collar regions) and olfactory (lip and inner basal ring region) calyx neuropils, as well as in the collar and lip zones of the vertical and medial lobes. The data suggest that one effect of octopamine via AmOA1 in the antennal lobe and mushroom body is to modulate inhibitory neurons

Transcriptome Analysis of the Desert Locust Central Nervous System: Production and Annotation of a Schistocerca gregaria EST Database

) displays a fascinating type of phenotypic plasticity, designated as ‘phase polyphenism’. Depending on environmental conditions, one genome can be translated into two highly divergent phenotypes, termed the solitarious and gregarious (swarming) phase. Although many of the underlying molecular events remain elusive, the central nervous system (CNS) is expected to play a crucial role in the phase transition process. Locusts have also proven to be interesting model organisms in a physiological and neurobiological research context. However, molecular studies in locusts are hampered by the fact that genome/transcriptome sequence information available for this branch of insects is still limited. EST information is highly complementary to the existing orthopteran transcriptomic data. Since many novel transcripts encode neuronal signaling and signal transduction components, this paper includes an overview of these sequences. Furthermore, several transcripts being differentially represented in solitarious and gregarious locusts were retrieved from this EST database. The findings highlight the involvement of the CNS in the phase transition process and indicate that this novel annotated database may also add to the emerging knowledge of concomitant neuronal signaling and neuroplasticity events. EST data constitute an important new source of information that will be instrumental in further unraveling the molecular principles of phase polyphenism, in further establishing locusts as valuable research model organisms and in molecular evolutionary and comparative entomology

Digital Self-Management Support Tools in the Care Plan of Patients With Cancer: Review of Randomized Controlled Trials

Background Digital self-management support tools (DSMSTs)—electronic devices or monitoring systems to monitor or improve health status—have become increasingly important in cancer care. Objective The aim of this review is to analyze published randomized clinical trials to assess the effectiveness of DSMSTs on physical and psychosocial symptoms or other supportive care needs in adult patients with cancer. Methods Five databases were searched from January 2013 to January 2020. English or Dutch language randomized controlled trials comparing DSMSTs with no intervention, usual care, alternative interventions, or a combination and including patients aged ≥18 years with pathologically proven cancer in the active treatment or survivorship phases were included. The results were summarized qualitatively. Results A total of 19 publications describing 3 types of DSMSTs were included. Although the content, duration, and frequency of interventions varied considerably across studies, the commonly used elements included an assessment component, tailored symptom self-management support, an information section, a communication section, and a diary. Significant positive effects were observed on quality of life in 6 (out of 10) studies, on anxiety in 1 (out of 5) study and depression in 2 (out of 8) studies, on symptom distress in 5 (out of 7) studies, on physical activity in 4 (out of 6) studies, on dietary behavior in 1 (out of 4) study, and on fatigue in 2 (out of 5) studies. Moreover, significant negative effects were observed on anxiety in 1 (out of 5) study and depression in 1 (out of 8) study. Most interventions were web-based interventions; 2 studies used mobile apps, and 1 study used a game as a DSMST. The overall quality of the studies was found to be good, with 13 out of 19 studies classified as high quality. Conclusions This review suggests that DSMSTs have a beneficial effect on the quality of life. For effects on other patient outcomes (eg, anxiety and depression, symptom distress, physical activity, dietary behavior, and fatigue), the evidence is inconsistent and limited or no effect is suggested. Future research should focus on specific tumor types, study different types of interventions separately, and assess the effects of specific interventions at different stages of disease progression. </jats:sec

Digital Self-Management Support Tools in the Care Plan of Patients With Cancer: Review of Randomized Controlled Trials (Preprint)

BACKGROUND Digital self-management support tools (DSMSTs)—electronic devices or monitoring systems to monitor or improve health status—have become increasingly important in cancer care. OBJECTIVE The aim of this review is to analyze published randomized clinical trials to assess the effectiveness of DSMSTs on physical and psychosocial symptoms or other supportive care needs in adult patients with cancer. METHODS Five databases were searched from January 2013 to January 2020. English or Dutch language randomized controlled trials comparing DSMSTs with no intervention, usual care, alternative interventions, or a combination and including patients aged ≥18 years with pathologically proven cancer in the active treatment or survivorship phases were included. The results were summarized qualitatively. RESULTS A total of 19 publications describing 3 types of DSMSTs were included. Although the content, duration, and frequency of interventions varied considerably across studies, the commonly used elements included an assessment component, tailored symptom self-management support, an information section, a communication section, and a diary. Significant positive effects were observed on quality of life in 6 (out of 10) studies, on anxiety in 1 (out of 5) study and depression in 2 (out of 8) studies, on symptom distress in 5 (out of 7) studies, on physical activity in 4 (out of 6) studies, on dietary behavior in 1 (out of 4) study, and on fatigue in 2 (out of 5) studies. Moreover, significant negative effects were observed on anxiety in 1 (out of 5) study and depression in 1 (out of 8) study. Most interventions were web-based interventions; 2 studies used mobile apps, and 1 study used a game as a DSMST. The overall quality of the studies was found to be good, with 13 out of 19 studies classified as &lt;i&gt;high quality&lt;/i&gt;. CONCLUSIONS This review suggests that DSMSTs have a beneficial effect on the quality of life. For effects on other patient outcomes (eg, anxiety and depression, symptom distress, physical activity, dietary behavior, and fatigue), the evidence is inconsistent and limited or no effect is suggested. Future research should focus on specific tumor types, study different types of interventions separately, and assess the effects of specific interventions at different stages of disease progression. </sec