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

10Kin1day: a bottom-up neuroimaging initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.The 10Kin1day workshop was generously sponsored by the Neuroscience and Cognition program Utrecht (NCU) of the Utrecht University (https://www.uu.nl/en/research/neuroscience-and-cognition-utrecht), the ENIGMA consortium (http://enigma.ini.usc.edu), and personal grants: MvdH: NWOVIDI (452-16-015), MQ Fellowship; SB-C: the Wellcome Trust; Medical Research Council UK; NIHR CLAHRC for Cambridgeshire and Peterborough Foundation National Health Services Trust; Autism Research Trust; LB: New Investigator Award, Canadian Institutes of Health Research; Dara Cannon: Health Research Board (HRB), Ireland (grant code HRA-POR2013-324); SC: Research Grant Council (Hong Kong)-GRF 14101714; Eveline Crone: ERC-2010-StG-263234; UD: DFG, grant FOR2107 DA1151/5-1, DA1151/5-2, SFB-TRR58, Project C09, IZKF, grant Dan3/012/17; SD: MRC-RFA-UFSP-01-2013 (Shared Roots MRC Flagship grant); TF: Marie Curie Programme, International Training Programme, r’Birth; DG: National Science Centre (UMO-2011/02/A/NZ5/00329); BG: National Science Centre (UMO-2011/02/A/NZ5/00329); JH: Western Sydney University Postgraduate Research Award; LH: Science Foundation Ireland, ERC; HH: Research Grant Council (Hong Kong)-GRF 14101714; LJ: Velux Stiftung, grant 369 & UZH University Research Priority Program Dynamics of Healthy Aging; AJ: DFG, grant FOR2107 JA 1890/7-1; KJ: National Science Centre (UMO-2013/09/N/HS6/02634); VK: The Russian Foundation for Basic Research (grant code 15-06-05758 A); TK: DFG, grant FOR2107 KI 588/14-1, DFG, grant FOR2107 KI 588/15-1; AK: DFG, grant FOR2107 KO 4291/4-1, DFG, grant FOR2107 KO 4291/3-1; IL: The Russian Foundation for Basic Research (grant code 15-06-05758 A); EL: Health and Medical Research Fund - 11121271; SiL: NHMRC-ARC Dementia Fellowship 1110414, NHMRC Dementia Research Team Grant 1095127, NHMRC Project Grant 1062319; CL-J: 537-2011, 2014-849; AM: Wellcome Trust Strategic Award (104036/Z/14/Z), MRC Grant MC_PC_17209; CM: Heisenberg-Grant, German Research Foundation, DFG MO 2363/3-2; PM: Foundation for Science and Technology, Portugal - PDE/BDE/113601/2015; KN: National Science Centre (UMO-2011/02/A/NZ5/00329); PN: National Science Centre (UMO-2013/09/N/HS6/02634); JiP: NWO-Veni 451-10-007; PaR: PER and US would like to thank the Schizophrenia Research Institute and the Chief-Investigators of the Australian Schizophrenia Research Bank V. Carr, U. Schall, R. Scott, A. Jablensky, B. Mowry, P. Michie, S. Catts, F. Henskens, and C. Pantelis; AS: National Science Centre (UMO-2011/02/A/NZ5/00329); SS: European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 707730; CS-M: Carlos III Health Institute (PI13/01958), Carlos III Health Institute (PI16/00889), Carlos III Health Institute (CPII16/00048); ES: National Science Centre (UMO-2011/02/A/NZ5/00329); AT: The Russian Foundation for Basic Research (grant code 15-06-05758 A); DT-G: PI14/00918, PI14/00639; Leonardo Tozzi: Marie Curie Programme, International Training Programme, r’Birth; SV: IMPRS Neurocom stipend; TvE: National Center for Research Resources at the National Institutes of Health (grant numbers: NIH 1 U24 RR021992 (Function Biomedical Informatics Research Network), NIH 1 U24 RR025736-01 (Biomedical Informatics Research Network Coordinating Center; http://www.birncommunity.org) and the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to Paul Thompson). NvH: NWO-VIDI (452-11-014); MW: National Science Centre (UMO-2011/02/A/NZ5/00329); Veronica O’Keane: Meath Foundation; AV and AW: CRC Obesity Mechanism (SFB 1052) Project A1 funded by DFG. The funding sources had no role in the study design, data collection, analysis, and interpretation of the data. We further like to thank Joanna Goc, Veronica O’Keane, Devon Shook, and Leonardo Tozzi for their participation and/or support of the 10K project. HCP data was provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University

Changes in the levels of cytokines, chemokines and malaria-specific antibodies in response to Plasmodium falciparum infection in children living in sympatry in Mali

<p>Abstract</p> <p>Background</p> <p>The Fulani are known to be less susceptible to <it>Plasmodium falciparum </it>malaria as reflected by lower parasitaemia and fewer clinical symptoms than other sympatric ethnic groups. So far most studies in these groups have been performed on adults, which is why little is known about these responses in children. This study was designed to provide more information on this gap.</p> <p>Methods</p> <p>Circulating inflammatory factors and antibody levels in children from the Fulani and Dogon ethnic groups were measured. The inflammatory cytokines; interleukin (IL)-1beta, IL-6, IL-8, IL-10, IL-12p70, tumor necrosis factor (TNF) and the chemokines; regulated on activation normal T cell expressed and secreted (RANTES), monokine-induced by IFN-gamma (MIG), monocyte chemotactic protein (MCP)-1 and IFN-gamma-inducible protein (IP)-10 were measured by cytometric bead arrays. The levels of interferon (IFN)-alpha, IFN-gamma and malaria-specific antibodies; immunoglobulin (Ig) G, IgM and IgG subclasses (IgG1-IgG4) were measured by ELISA.</p> <p>Results</p> <p>The results revealed that the Fulani children had higher levels of all tested cytokines compared to the Dogon, in particular IFN-gamma, a cytokine known to be involved in parasite clearance. Out of all the tested chemokines, only MCP-1 was increased in the Fulani compared to the Dogon. When dividing the children into infected and uninfected individuals, infected Dogon had significantly lower levels of RANTES compared to their uninfected peers, and significantly higher levels of MIG and IP-10 as well as MCP-1, although the latter did not reach statistical significance. In contrast, such patterns were not seen in the infected Fulani children and their chemokine levels remained unchanged upon infection compared to uninfected counterparts. Furthermore, the Fulani also had higher titres of malaria-specific IgG and IgM as well as IgG1-3 subclasses compared to the Dogon.</p> <p>Conclusions</p> <p>Taken together, this study demonstrates, in accordance with previous work, that Fulani children mount a stronger inflammatory and antibody response against <it>P. falciparum </it>parasites compared to the Dogon and that these differences are evident already at an early age. The inflammatory responses in the Fulani were not influenced by an active infection which could explain why less clinical symptoms are seen in this group.</p

10Kin1day: a bottom-up neuroimaging initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain

Current commands for high-efficiency torque control of DC shunt motor

The current commands for a high-efficiency torque control of a DC shunt motor are described. In the proposed control method, the effect of a magnetic saturation and an armature reaction are taken into account by representing the coefficients of an electromotive force and a torque as a function of the field current, the armature current and the revolving speed. The current commands at which the loss of the motor drive system becomes a minimum are calculated as an optimal problem. The proposed control technique of a motor is implemented on the microprocessor-based control system. The effect of the consideration of the magnetic saturation and the armature reaction on the produced torque and the minimisation of the loss are discussed analytically and experimentally </p

Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018.

Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

10Kin1day: A Bottom-Up Neuroimaging Initiative.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain