Hippocampal volume increase in response to aerobic exercise has been consistently observed in animal models. However, the evidence from human studies is equivocal. We undertook a systematic review to identify all controlled trials examining the effect of aerobic exercise on the hippocampal volumes in humans, and applied meta-analytic techniques to determine if aerobic exercise resulted in volumetric increases. We also sought to establish how volume changes differed in relation to unilateral measures of left/right hippocampal volume, and across the lifespan. A systematic search identified 4398 articles, of which 14 were eligible for inclusion in the primary analysis. A random-effects meta-analysis showed no significant effect of aerobic exercise on total hippocampal volume across the 737 participants. However, aerobic exercise had significant positive effects on left hippocampal volume in comparison to control conditions. Post-hoc analyses indicated effects were driven through exercise preventing the volumetric decreases which occur over time. These results provide meta-analytic evidence for exercise-induced volumetric retention in the left hippocampus. Aerobic exercise interventions may be useful for preventing age-related hippocampal deterioration and maintaining neuronal health.
As successful malaria control programmes re-orientate towards elimination, the identification of transmission foci, targeting of attack measures to high-risk areas and management of importation risk become high priorities. When resources are limited and transmission is varying seasonally, approaches that can rapidly prioritize areas for surveillance and control can be valuable, and the most appropriate attack measure for a particular location is likely to differ depending on whether it exports or imports malaria infections.Methods/Results: Here, using the example of Namibia, a method for targeting of interventions using surveillance data, satellite imagery, and mobile phone call records to support elimination planning is described. One year of aggregated movement patterns for over a million people across Namibia are analyzed, and linked with case-based risk maps built on satellite imagery. By combining case-data and movement, the way human population movements connect transmission risk areas is demonstrated. Communities that were strongly connected by relatively higher levels of movement were then identified, and net export and import of travellers and infection risks by region were quantified. These maps can aid the design of targeted interventions to maximally reduce the number of cases exported to other regions while employing appropriate interventions to manage risk in places that import them.
SUMMARY: Pathview is a novel tool set for pathway based data integration and visualization. It maps and renders user data on relevant pathway graphs. Users only need to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps and integrates user data onto the pathway, and renders pathway graphs with the mapped data. Although built as a stand-alone program, Pathview may seamlessly integrate with pathway and functional analysis tools for large-scale and fully automated analysis pipelines. AVAILABILITY: The package is freely available under the GPLv3 licence through Bioconductor and R-Forge. It is available at http://bioconductor.org/packages/release/bioc/html/pathview.html and at http://Pathview.r-forge.r-project.org/. CONTACT: firstname.lastname@example.org.
When a plaid object is presented, the visual system decomposes it into its constituting orientation primitives and integrates them at later processing stages. The present study reveals the time course of this process by applying meta- and paracontrast masking to both simple oriented and plaid gratings. With various stimulus onset asynchronies (SOA) between target gratings and surrounding mask annuli, subjects were asked to identify whether targets were simple gratings collinear to the masks, orthogonal to the masks, plaid, or whether no target was presented. The resulting time courses for each type of stimulus confusion showed that metacontrast peaked when orientation primitives had already begun to be integrated into one object, indicated by a dominance of “no target” responses given to plaid stimuli at SOAs around 70 ms. At SOAs around 10 to 30 ms masking also had a significant impact but acted on separable components, indicated by a dominance of “orthogonal” responses given plaid stimuli. Probability summation of “no target” responses given simple gratings revealed that only at shorter SOAs performance for plaid stimuli could be predicted assuming independent features but not at SOAs of at 50-70 ms. We discuss in how far these results could also be explained by the dynamics of cross-orientation suppression (COS) and how they might relate to the process of feature integration in plaids.
The integrated navigation system with strapdown inertial navigation system (SINS), Beidou (BD) receiver and Doppler velocity log (DVL) can be used in marine applications owing to the fact that the redundant and complementary information from different sensors can markedly improve the system accuracy. However, the existence of multisensor asynchrony will introduce errors into the system. In order to deal with the problem, conventionally the sampling interval is subdivided, which increases the computational complexity. In this paper, an innovative integrated navigation algorithm based on a Cubature Kalman filter (CKF) is proposed correspondingly. A nonlinear system model and observation model for the SINS/BD/DVL integrated system are established to more accurately describe the system. By taking multi-sensor asynchronization into account, a new sampling principle is proposed to make the best use of each sensor’s information. Further, CKF is introduced in this new algorithm to enable the improvement of the filtering accuracy. The performance of this new algorithm has been examined through numerical simulations. The results have shown that the positional error can be effectively reduced with the new integrated navigation algorithm. Compared with the traditional algorithm based on EKF, the accuracy of the SINS/BD/DVL integrated navigation system is improved, making the proposed nonlinear integrated navigation algorithm feasible and efficient.
Human mobility is increasing in its volume, speed and reach, leading to the movement and introduction of pathogens through infected travelers. An understanding of how areas are connected, the strength of these connections and how this translates into disease spread is valuable for planning surveillance and designing control and elimination strategies. While analyses have been undertaken to identify and map connectivity in global air, shipping and migration networks, such analyses have yet to be undertaken on the road networks that carry the vast majority of travellers in low and middle income settings. Here we present methods for identifying road connectivity communities, as well as mapping bridge areas between communities and key linkage routes. We apply these to Africa, and show how many highly-connected communities straddle national borders and when integrating malaria prevalence and population data as an example, the communities change, highlighting regions most strongly connected to areas of high burden. The approaches and results presented provide a flexible tool for supporting the design of disease surveillance and control strategies through mapping areas of high connectivity that form coherent units of intervention and key link routes between communities for targeting surveillance.
The presence of an evaluative audience can alter skilled motor performance through changes in force output. To investigate how this is mediated within the brain, we emulated real-time social monitoring of participants' performance of a fine grip task during functional magnetic resonance neuroimaging. We observed an increase in force output during social evaluation that was accompanied by focal reductions in activity within bilateral inferior parietal cortex. Moreover, deactivation of the left inferior parietal cortex predicted both inter- and intra-individual differences in socially-induced change in grip force. Social evaluation also enhanced activation within the posterior superior temporal sulcus, which conveys visual information about others' actions to the inferior parietal cortex. Interestingly, functional connectivity between these two regions was attenuated by social evaluation. Our data suggest that social evaluation can vary force output through the altered engagement of inferior parietal cortex; a region implicated in sensorimotor integration necessary for object manipulation, and a component of the action-observation network which integrates and facilitates performance of observed actions. Social-evaluative situations may induce high-level representational incoherence between one’s own intentioned action and the perceived intention of others which, by uncoupling the dynamics of sensorimotor facilitation, could ultimately perturbe motor output.
Therapeutic drug monitoring (TDM) typically requires painful blood drawn from patients. We propose a painless and minimally-invasive alternative for TDM using hollow microneedles suitable to extract extremely small volumes (<1 nL) of interstitial fluid to measure drug concentrations. The inner lumen of a microneedle is functionalized to be used as a micro-reactor during sample collection to trap and bind target drug candidates during extraction, without requirements of sample transfer. An optofluidic device is integrated with this microneedle to rapidly quantify drug analytes with high sensitivity using a straightforward absorbance scheme. Vancomycin is currently detected by using volumes ranging between 50-100 μL with a limit of detection (LoD) of 1.35 μM. The proposed microneedle-optofluidic biosensor can detect vancomycin with a sample volume of 0.6 nL and a LoD of <100 nM, validating this painless point of care system with significant potential to reduce healthcare costs and patients suffering.
Mindfulness, a psychological process reflecting attention and awareness to what is happening in the present moment, has been associated with increased well-being and decreased depression and anxiety in both healthy and patient populations. However, little research has explored underlying neural pathways. Recent work suggests that mindfulness (and mindfulness training interventions) may foster neuroplastic changes in cortico-limbic circuits responsible for stress and emotion regulation. Building on this work, we hypothesized that higher levels of dispositional mindfulness would be associated with decreased grey matter volume in the amgydala. In the present study, a self-report measure of dispositional mindfulness and structural MRI images were obtained from 155 healthy community adults. Volumetric analyses showed that higher dispositional mindfulness is associated with decreased grey matter volume in the right amygdala, and exploratory analyses revealed that higher dispositional mindfulness is also associated with decreased grey matter volume in the left caudate. Moreover, secondary analyses indicate that these amygdala and caudate volume associations persist after controlling for relevant demographic and individual difference factors (i.e., age, total grey matter volume, neuroticism, depression). Such volumetric differences may help explain why mindful individuals have reduced stress reactivity, and suggest new candidate structural neurobiological pathways linking mindfulness with mental and physical health outcomes.
Solar energy storage is an emerging technology which can promote the solar energy as the primary source of electricity. Recent development of laser scribed graphene electrodes exhibiting a high electrical conductivity have enabled a green technology platform for supercapacitor-based energy storage, resulting in cost-effective, environment-friendly features, and consequent readiness for on-chip integration. Due to the limitation of the ion-accessible active porous surface area, the energy densities of these supercapacitors are restricted below ~3 × 10(-3) Whcm(-3). In this paper, we demonstrate a new design of biomimetic laser scribed graphene electrodes for solar energy storage, which embraces the structure of Fern leaves characterized by the geometric family of space filling curves of fractals. This new conceptual design removes the limit of the conventional planar supercapacitors by significantly increasing the ratio of active surface area to volume of the new electrodes and reducing the electrolyte ionic path. The attained energy density is thus significantly increased to ~10(-1) Whcm(-3)- more than 30 times higher than that achievable by the planar electrodes with ~95% coulombic efficiency of the solar energy storage. The energy storages with these novel electrodes open the prospects of efficient self-powered and solar-powered wearable, flexible and portable applications.