Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

General practitioner advice on physical activity: Analyses in a cohort of older primary health care patients (getABI)

<p>Abstract</p> <p>Background</p> <p>Although the benefits of physical activity for health and functioning are recognized to extend throughout life, the physical activity level of most older people is insufficient with respect to current guidelines. The primary health care setting may offer an opportunity to influence and to support older people to become physically active on a regular basis. Currently, there is a lack of data concerning general practitioner (GP) advice on physical activity in Germany. Therefore, the aim of this study was to evaluate the rate and characteristics of older patients receiving advice on physical activity from their GP.</p> <p>Methods</p> <p>This is a cross-sectional study using data collected at 7 years of follow-up of a prospective cohort study (German epidemiological trial on ankle brachial index, getABI). 6,880 unselected patients aged 65 years and above in the primary health care setting in Germany were followed up since October 2001. During the 7-year follow-up telephone interview, 1,937 patients were asked whether their GP had advised them to get regular physical activity within the preceding 12 months. The interview also included questions on socio-demographic and lifestyle variables, medical conditions, and physical activity. Logistic regression analysis (unadjusted and adjusted for all covariables) was used to examine factors associated with receiving advice. Analyses comprised only complete cases with regard to the analysed variables. Results are expressed as odds ratios (ORs) with 95% confidence intervals (95% CI).</p> <p>Results</p> <p>Of the 1,627 analysed patients (median age 77; range 72-93 years; 52.5% women), 534 (32.8%) stated that they had been advised to get regular physical activity. In the adjusted model, those more likely to receive GP advice on physical activity were men (OR [95% CI] 1.34 [1.06-1.70]), patients suffering from pain (1.43 [1.13-1.81]), coronary heart disease and/or myocardial infarction (1.56 [1.21-2.01]), diabetes mellitus (1.79 [1.39-2.30]) or arthritis (1.37 [1.08-1.73]), and patients taking a high (> 5) number of medications (1.41 [1.11-1.80]).</p> <p>Conclusions</p> <p>The study revealed a relatively low rate of older primary health care patients receiving GP advice on physical activity. GPs appeared to focus their advice on patients with chronic medical conditions. However, there are likely to be many more patients who would benefit from advice.</p

Business model innovation and transition to a sustainable food system: A case study in the Lisbon metropolitan area

The food systems’ transition towards a sustainable involves structural changes, namely the emphasis on local production, short supply chains, and the preference for organic products. The shift in the agri-food system is taking place through the creation of entirely new businesses and individual farms moving towards organic production. In both cases, the enterprises use a combination of well-established agricultural knowledge and techniques, new scientific knowledge on productive methods and new technological platforms for commercialization. These mixed sources permit the creation of innovative business models (BMs). They exemplify how traditional industries can absorb/generate innovation at technological and organizational levels, and become part of the new knowledge-based era. The study has three objectives: to analyse the emerging agri-food businesses in the Lisbon Metropolitan Area (LMA); to characterize innovative sustainable BMs within the transition dynamics; to reflect on the challenges that the characteristics of the food system pose for the emergence of these BMs. The study is part of an interdisciplinary project on Spatial Planning for Change (SPLACH). The analysis addresses the food system transition in a specific territory, namely the LMA. The paper presents results of the research conducted, focusing on the case of an organic food initiative, Quinta do Oeste.info:eu-repo/semantics/acceptedVersio

Predicting Future Clinical Changes of MCI Patients Using Longitudinal and Multimodal Biomarkers

Accurate prediction of clinical changes of mild cognitive impairment (MCI) patients, including both qualitative change (i.e., conversion to Alzheimer's disease (AD)) and quantitative change (i.e., cognitive scores) at future time points, is important for early diagnosis of AD and for monitoring the disease progression. In this paper, we propose to predict future clinical changes of MCI patients by using both baseline and longitudinal multimodality data. To do this, we first develop a longitudinal feature selection method to jointly select brain regions across multiple time points for each modality. Specifically, for each time point, we train a sparse linear regression model by using the imaging data and the corresponding clinical scores, with an extra ‘group regularization’ to group the weights corresponding to the same brain region across multiple time points together and to allow for selection of brain regions based on the strength of multiple time points jointly. Then, to further reflect the longitudinal changes on the selected brain regions, we extract a set of longitudinal features from the original baseline and longitudinal data. Finally, we combine all features on the selected brain regions, from different modalities, for prediction by using our previously proposed multi-kernel SVM. We validate our method on 88 ADNI MCI subjects, with both MRI and FDG-PET data and the corresponding clinical scores (i.e., MMSE and ADAS-Cog) at 5 different time points. We first predict the clinical scores (MMSE and ADAS-Cog) at 24-month by using the multimodality data at previous time points, and then predict the conversion of MCI to AD by using the multimodality data at time points which are at least 6-month ahead of the conversion. The results on both sets of experiments show that our proposed method can achieve better performance in predicting future clinical changes of MCI patients than the conventional methods

Use of 16S rRNA Gene Based Clone Libraries to Assess Microbial Communities Potentially Involved in Anaerobic Methane Oxidation in a Mediterranean Cold Seep

This study provides data on the diversities of bacterial and archaeal communities in an active methane seep at the Kazan mud volcano in the deep Eastern Mediterranean sea. Layers of varying depths in the Kazan sediments were investigated in terms of (1) chemical parameters and (2) DNA-based microbial population structures. The latter was accomplished by analyzing the sequences of directly amplified 16S rRNA genes, resulting in the phylogenetic analysis of the prokaryotic communities. Sequences of organisms potentially associated with processes such as anaerobic methane oxidation and sulfate reduction were thus identified. Overall, the sediment layers revealed the presence of sequences of quite diverse bacterial and archaeal communities, which varied considerably with depth. Dominant types revealed in these communities are known as key organisms involved in the following processes: (1) anaerobic methane oxidation and sulfate reduction, (2) sulfide oxidation, and (3) a range of (aerobic) heterotrophic processes. In the communities in the lowest sediment layer sampled (22–34 cm), sulfate-reducing bacteria and archaea of the ANME-2 cluster (likely involved in anaerobic methane oxidation) were prevalent, whereas heterotrophic organisms abounded in the top sediment layer (0–6 cm). Communities in the middle layer (6–22 cm) contained organisms that could be linked to either of the aforementioned processes. We discuss how these phylogeny (sequence)-based findings can support the ongoing molecular work aimed at unraveling both the functioning and the functional diversities of the communities under study

The Role of Stimulus Salience and Attentional Capture Across the Neural Hierarchy in a Stop-Signal Task

Inhibitory motor control is a core function of cognitive control. Evidence from diverse experimental approaches has linked this function to a mostly right-lateralized network of cortical and subcortical areas, wherein a signal from the frontal cortex to the basal ganglia is believed to trigger motor-response cancellation. Recently, however, it has been recognized that in the context of typical motor-control paradigms those processes related to actual response inhibition and those related to the attentional processing of the relevant stimuli are highly interrelated and thus difficult to distinguish. Here, we used fMRI and a modified Stop-signal task to specifically examine the role of perceptual and attentional processes triggered by the different stimuli in such tasks, thus seeking to further distinguish other cognitive processes that may precede or otherwise accompany the implementation of response inhibition. In order to establish which brain areas respond to sensory stimulation differences by rare Stop-stimuli, as well as to the associated attentional capture that these may trigger irrespective of their task-relevance, we compared brain activity evoked by Stop-trials to that evoked by Go-trials in task blocks where Stop-stimuli were to be ignored. In addition, region-of-interest analyses comparing the responses to these task-irrelevant Stop-trials, with those to typical relevant Stop-trials, identified separable activity profiles as a function of the task-relevance of the Stop-signal. While occipital areas were mostly blind to the task-relevance of Stop-stimuli, activity in temporo-parietal areas dissociated between task-irrelevant and task-relevant ones. Activity profiles in frontal areas, in turn, were activated mainly by task-relevant Stop-trials, presumably reflecting a combination of triggered top-down attentional influences and inhibitory motor-control processes

Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer's Disease

The role of structural brain magnetic resonance imaging (MRI) is becoming more and more emphasized in the early diagnostics of Alzheimer's disease (AD). This study aimed to assess the improvement in classification accuracy that can be achieved by combining features from different structural MRI analysis techniques. Automatically estimated MR features used are hippocampal volume, tensor-based morphometry, cortical thickness and a novel technique based on manifold learning. Baseline MRIs acquired from all 834 subjects (231 healthy controls (HC), 238 stable mild cognitive impairment (S-MCI), 167 MCI to AD progressors (P-MCI), 198 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were used for evaluation. We compared the classification accuracy achieved with linear discriminant analysis (LDA) and support vector machines (SVM). The best results achieved with individual features are 90% sensitivity and 84% specificity (HC/AD classification), 64%/66% (S-MCI/P-MCI) and 82%/76% (HC/P-MCI) with the LDA classifier. The combination of all features improved these results to 93% sensitivity and 85% specificity (HC/AD), 67%/69% (S-MCI/P-MCI) and 86%/82% (HC/P-MCI). Compared with previously published results in the ADNI database using individual MR-based features, the presented results show that a comprehensive analysis of MRI images combining multiple features improves classification accuracy and predictive power in detecting early AD. The most stable and reliable classification was achieved when combining all available features

Disrupted lymph node and splenic stroma in mice with induced inflammatory melanomas is associated with impaired recruitment of T and dendritic cells

International audienceMigration of dendritic cells (DC) from the tumor environment to the T cell cortex in tumor-draining lymph nodes (TDLN) is essential for priming naïve T lymphocytes (TL) to tumor antigen (Ag). We used a mouse model of induced melanoma in which similar oncogenic events generate two phenotypically distinct melanomas to study the influence of tumor-associated inflammation on secondary lymphoid organ (SLO) organization. One tumor promotes inflammatory cytokines, leading to mobilization of immature myeloid cells (iMC) to the tumor and SLO; the other does not. We report that inflammatory tumors induced alterations of the stromal cell network of SLO, profoundly altering the distribution of TL and the capacity of skin-derived DC and TL to migrate or home to TDLN. These defects, which did not require tumor invasion, correlated with loss of fibroblastic reticular cells in T cell zones and in impaired production of CCL21. Infiltrating iMC accumulated in the TDLN medulla and the splenic red pulp. We propose that impaired function of the stromal cell network during chronic inflammation induced by some tumors renders spleens non-receptive to TL and TDLN non-receptive to TL and migratory DC, while the entry of iMC into these perturbed SLO is enhanced. This could constitute a mechanism by which inflammatory tumors escape immune control. If our results apply to inflammatory tumors in general, the demonstration that SLO are poorly receptive to CCR7-dependent migration of skin-derived DC and naïve TL may constitute an obstacle for proposed vaccination or adoptive TL therapies of their hosts