Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks

Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in experimental data being the overrepresentation of bidirectional connections among pyramidal cells. Using numerical and analytical methods, we investigated the effects of partially symmetric connectivity on dynamics in networks of rate units. We considered the two dynamical regimes exhibited by random neural networks: the weak-coupling regime, where the firing activity decays to a single fixed point unless the network is stimulated, and the strong-coupling or chaotic regime, characterized by internally generated fluctuating firing rates. In the weak-coupling regime, we computed analytically for an arbitrary degree of symmetry the auto-correlation of network activity in presence of external noise. In the chaotic regime, we performed simulations to determine the timescale of the intrinsic fluctuations. In both cases, symmetry increases the characteristic asymptotic decay time of the autocorrelation function and therefore slows down the dynamics in the network.Comment: 17 pages, 7 figure

Hemoglobin spectra affect measurement of tissue oxygen saturation

Tissue oxygen saturation (StO2) is a valuable clinical parameter e.g. for intensive care applications or monitoring during surgery. Studies showed that near-infrared spectroscopy (NIRS) based tissue oximeters of different brands give systematically different readings of StO2. Usually these readings are linearly correlated and therefore StO2 readings from one instrument can easily be converted to those of another instrument. However, it is interesting to understand why there is this difference. One reason may be that different brands employ different spectra of hemoglobin. The aim here was to investigate how these different absorption spectra of hemoglobin affect the StO2 readings. Therefore, we performed changes in StO2 in a phantom experiment with real human hemoglobin at three different concentrations (26.5, 45 and 70 μM): desaturation by yeast consuming the oxygen and re-saturation by bubbling oxygen gas. The partial pressure of O2 in the liquid changed from at least 10 kPa to ~0 kPa and ISS OxiplexTS, a frequency-domain NIRS instrument, was used to monitor changes of StO2. When we employed two different absorption spectra for hemoglobin, StO2 values were comparable in the normal physiological range. However, particularly at high and low StO2 values, a difference of >6% between these two spectra were noticed. Such a difference of >6% is substantial and relevant for medical applications. This may partly explain why different brands of NIRS instruments provide different StO2 readings. The hemoglobin spectra are therefore a factor to be considered for future developments and applications of NIRS oximeters

In Vitro Comparisons of Near-Infrared Spectroscopy Oximeters: Impact of Slow Changes in Scattering of Liquid Phantoms

Several cerebral oximeters based on near-infrared spectroscopy (NIRS) are commercially available that determine tissue oxygen saturation (StO). One problem is an inconsistency of StO readings between different brands of instruments. Liquid blood phantoms mimicking optical properties of the neonatal head enable quantitative device comparisons. However, occasionally, the reduced scattering coefficient (μ') of these phantoms decreases over time. AIM To investigate whether this decrease in μ' affects the validity of comparison of these devices. StO was measured by several NIRS oximeters simultaneously on a phantom, which exhibited a particularly strong decrease in μ'. We found that a decrease in μ' by ≤16% from baseline led to deviations in StO of ≤3%

Absorption spectra of early stool from preterm infants need to be considered in abdominal NIRS oximetry

Necrotizing enterocolitis (NEC) is the most common gastrointestinal emergency of the preterm infant. Low abdominal tissue oxygen saturation (StO2) measured by near-infrared spectroscopy (NIRS) oximetry may be an early sign of NEC relevant for treating or even preventing NEC. However, current commercial NIRS oximeters provide inaccurate StO2 readings because they neglect stool as an abdominal absorber. To tackle this problem, we determined the optical properties of faeces of preterm infants to enable a correct abdominal StO2 measurement. In 25 preterm born infants (median age 31 0/7 ± 2 1/7 weeks, weight 1478 ± 511 g), we measured their first five stool probes with a VIS/NIR spectrometer and calculated the optical properties using the Inverse Adding Doubling (IAD) method. We obtained two absorption spectra representing meconium and transitional stool. Probabilistic cluster analysis correctly classified 96 out of 107 stool probes. The faeces spectra need to be considered to enable correct abdominal StO2 measurements with NIRS oximetry

INTEGRATION OF COMPLEMENTARY BIOMARKERS IN PATIENTS WITH FIRST EPISODE PSYCHOSIS: RESEARCH PROTOCOL OF A PROSPECTIVE FOLLOW UP STUDY

In this project, we recruited a sample of 150 patients with first episode of psychosis with schizophrenia features (FEP) and 100 healthy controls. We assessed the differences between these two groups, as well as the changes between the acute phase of illness and subsequent remission among patients over 18-month longitudinal follow-up. The assessments were divided into four work packages (WP): WP1- psychopathological status, neurocognitive functioning and emotional recognition; WP2- stress response measured by saliva cortisol during a stress paradigm; cerebral blood perfusion in the resting state (with single photon emission computed tomography (SPECT) and during activation paradigm (with Transcranial Ultrasonography Doppler (TCD); WP3-post mortem analysis in histologically prepared human cortical tissue of post mortem samples of subjects with schizophrenia in the region that synaptic alteration was suggested by WP1 and WP2; WP4- pharmacogenetic analysis (single gene polymorphisms and genome wide association study (GWAS). We expect that the analysis of these data will identify a set of markers that differentiate healthy controls from patients with FEP, and serve as an additional diagnostic tool in the first episode of psychosis, and prediction tool which can be then used to help tailoring individualized treatment options. In this paper, we describe the project protocol including aims and methods and provide a brief description of planned post mortem studies and pharmacogenetic analysis

Socioeconomic differences in food habits among 6- to 9-year-old children from 23 countries-WHO European Childhood Obesity Surveillance Initiative (COSI 2015/2017)

Background: Socioeconomic differences in children's food habits are a key public health concern. In order to inform policy makers, cross-country surveillance studies of dietary patterns across socioeconomic groups are required. The purpose of this study was to examine associations between socioeconomic status (SES) and children's food habits. Methods: The study was based on nationally representative data from children aged 6-9 years (n = 129,164) in 23 countries in the World Health Organization (WHO) European Region. Multivariate multilevel analyses were used to explore associations between children's food habits (consumption of fruit, vegetables, and sugar-containing soft drinks) and parental education, perceived family wealth and parental employment status. Results: Overall, the present study suggests that unhealthy food habits are associated with lower SES, particularly as assessed by parental education and family perceived wealth, but not parental employment status. We found cross-national and regional variation in associations between SES and food habits and differences in the extent to which the respective indicators of SES were related to children's diet. Conclusion: Socioeconomic differences in children's food habits exist in the majority of European and Asian countries examined in this study. The results are of relevance when addressing strategies, policy actions, and interventions targeting social inequalities in children's diets.The authors gratefully acknowledge support from a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. Data collection in the countries was made possible through funding from Albania: WHO through the Joint Programme on Children, Food Security and Nutrition “Reducing Malnutrition in Children,” funded by the Millennium Development Goals Achievement Fund, and the Institute of Public Health; Bulgaria: Ministry of Health, National Center of Public Health and Analyses, WHO Regional Office for Europe; Croatia: Ministry of Health, Croatian Institute of Public Health and WHO Regional Office for Europe; Czechia: Ministry of Health of the Czech Republic, grant nr. AZV MZČR 17-31670 A and MZČ–VO EÚ 00023761; Denmark: Danish Ministry of Health; Georgia: WHO; Ireland: Health Service Executive; Italy: Ministry of Health and Italian National Institute of Health; Kazakhstan: Ministry of Health of the Republic of Kazakhstan and WHO Country Office; Kyrgyzstan: World Health Organization; Latvia: Ministry of Health, Centre for Disease Prevention and Control; Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and WHO; Malta: Ministry of Health; Montenegro: WHO and Institute of Public Health of Montenegro; Norway: Ministry of Health and Norwegian Institute of Public Health; Poland: National Health Programme, Ministry of Health; Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates and the kind technical support from the Center for Studies and Research on Social Dynamics and Health (CEIDSS); Romania: Ministry of Health; Russian Federation: WHO; San Marino: Health Ministry, Educational Ministry; Serbia: This study was supported by the World Health Organization (Ref. File 2015-540940); Spain: Spanish Agency for Food Safety and Nutrition (AESAN); Tajikistan: WHO Country Office in Tajikistan and Ministry of Health and Social Protection; Turkmenistan: WHO Country Office in Turkmenistan and Ministry of Health; Turkey: Turkish Ministry of Health and World Bank. The CO-CREATE project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 774210.info:eu-repo/semantics/publishedVersio

Urban and rural differences in frequency of fruit, vegetable, and soft drink consumption among 6–9‐year‐old children from 19 countries from the WHO European region

In order to address the paucity of evidence on the association between childhood eating habits and urbanization, this cross-sectional study describes urban–rural differences in frequency of fruit, vegetable, and soft drink consumption in 123,100 children aged 6–9 years from 19 countries participating in the fourth round (2015-2017) of the WHO European Childhood Obesity Surveillance Initiative (COSI). Children's parents/caregivers completed food-frequency questionnaires. A multivariate multilevel logistic regression analysis was performed and revealed wide variability among countries and within macroregions for all indicators. The percentage of children attending rural schools ranged from 3% in Turkey to 70% in Turkmenistan. The prevalence of less healthy eating habits was high, with between 30–80% and 30–90% children not eating fruit or vegetables daily, respectively, and up to 45% consuming soft drinks on >3 days a week. For less than one third of the countries, children attending rural schools had higher odds (OR-range: 1.1–2.1) for not eating fruit or vegetables daily or consuming soft drinks >3 days a week compared to children attending urban schools. For the remainder of the countries no significant associations were observed. Both population-based interventions and policy strategies are necessary to improve access to healthy foods and increase healthy eating behaviors among children.The authors gratefully acknowledge support from a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. Data collection in the countries was made possible through funding from Albania: WHO through the Joint Programme on Children, Food Security and Nutrition “Reducing Malnutrition in Children,” funded by the Millennium Development Goals Achievement Fund, and the Institute of Public Health; Austria: Federal Ministry of Social Affairs, Health, Care and Consumer Protection, Republic of Austria; Bulgaria: Ministry of Health, National Center of Public Health and Analyses, WHO Regional Office for Europe; Croatia: Ministry of Health, Croatian Institute of Public Health and WHO Regional Office for Europe; Ministry of Health of the Czech Republic, grant nr. AZV MZČR 17-31670 A and MZČR–RVO EÚ 00023761; Denmark: Danish Ministry of Health; Estonia: Ministry of Social Affairs, Ministry of Education and Research (IUT 42-2), WHO Country Office, and National Institute for Health Development; Georgia: WHO; Ireland: Health Service Executive; Italy: Ministry of Health and Italian National Institute of Health; Kazakhstan: Ministry of Health of the Republic of Kazakhstan and WHO Country Office; Kyrgyzstan: World Health Organization; Latvia: Ministry of Health, Centre for Disease Prevention and Control; Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and WHO; Malta: Ministry of Health; Montenegro: WHO and Institute of Public Health of Montenegro; North Macedonia: COSI in North Macedonia is funded by the Government of North Macedonia through National Annual Program of Public Health and implemented by the Institute of Public Health and Centers of Public Health in the country. WHO country office provides support for training and data management; Norway: Ministry of Health and Norwegian Institute of Public Health; Poland: National Health Programme, Ministry of Health; Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates and the kind technical support from the Center for Studies and Research on Social Dynamics and Health (CEIDSS); Romania: Ministry of Health; Serbia: This study was supported by the World Health Organization (Ref. File 2015-540940); Slovakia: Biennial Collaborative Agreement between WHO Regional Office for Europe and Ministry of Health SR; Spain: Spanish Agency for Food Safety and Nutrition (AESAN); Tajikistan: WHO Country Office in Tajikistan and Ministry of Health and Social Protection; Turkmenistan: WHO Country Office in Turkmenistan and Ministry of Health; Turkey: Turkish Ministry of Health and World Bank.info:eu-repo/semantics/publishedVersio

Socioeconomic disparities in physical activity, sedentary behavior and sleep patterns among 6- to 9-year-old children from 24 countries in the WHO European region

Physical activity, sedentary behavior, and sleep are important predictors of children's health. This paper aimed to investigate socioeconomic disparities in physical activity, sedentary behavior, and sleep across the WHO European region. This cross-sectional study used data on 124,700 children aged 6 to 9 years from 24 countries participating in the WHO European Childhood Obesity Surveillance Initiative between 2015 and 2017. Socioeconomic status (SES) was measured through parental education, parental employment status, and family perceived wealth. Overall, results showed different patterns in socioeconomic disparities in children's movement behaviors across countries. In general, high SES children were more likely to use motorized transportation. Low SES children were less likely to participate in sports clubs and more likely to have more than 2 h/day of screen time. Children with low parental education had a 2.24 [95% CI 1.94-2.58] times higher risk of practising sports for less than 2 h/week. In the pooled analysis, SES was not significantly related to active play. The relationship between SES and sleep varied by the SES indicator used. Importantly, results showed that low SES is not always associated with a higher prevalence of "less healthy" behaviors. There is a great diversity in SES patterns across countries which supports the need for country-specific, targeted public health interventions.The authors gratefully acknowledge support from a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. Data collection in the countries was made possible through funding from: Croatia: Ministry of Health, Croatian Institute of Public Health and WHO Regional Office for Europe. Albania: World Health Organization (WHO) Country Office Albania and the WHO Regional Office for Europe. Bulgaria: WHO Regional Office for Europe. Czech Republic: Ministry of Health of the Czech Republic, grant nr. AZV MZČR 17-31670 A and MZČR–RVO EÚ 00023761. Denmark: The Danish Ministry of Health. France: Santé publique France, the French Agency for Public Health. Georgia: WHO. Ireland: Health Service Executive. Italy: Italian Ministry of Health; Italian National Institute of Health (Istituto Superiore di Sanità). Kazakhstan: the Ministry of Health of the Republic of Kazakhstan within the scientific and technical program. Kyrgyzstan: World Health Organization. Latvia: Centre for Disease Prevention and Control, Ministry of Health, Latvia. Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and WHO. Malta: Ministry of Health. Montenegro: WHO and Institute of Public Health of Montenegro. Poland: National Health Programme, Ministry of Health. Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates and the kind technical support from the Center for Studies and Research on Social Dynamics and Health (CEIDSS). Romania: Ministry of Health. Russian Federation: WHO. San Marino: Health Ministry. Spain: the Spanish Agency for Food Safety & Nutrition. Tajikistan: WHO Country Office in Tajikistan and Ministry of Health and Social Protection; Turkmenistan: WHO Country Office in Turkmenistan and Ministry of Health. Turkey: Turkish Ministry of Health and World Bank. Austria: Federal Ministry of Labor, Social Affairs, Health and Consumer Protection of Austria.info:eu-repo/semantics/publishedVersio

Parental Perceptions of Children’s Weight Status in 22 Countries: The WHO European Childhood Obesity Surveillance Initiative: COSI 2015/2017

Introduction: Parents can act as important agents of change and support for healthy childhood growth and development. Studies have found that parents may not be able to accurately perceive their child’s weight status. The purpose of this study was to measure parental perceptions of their child’s weight status and to identify predictors of potential parental misperceptions. Methods: We used data from the World Health Organization (WHO) European Childhood Obesity Surveillance Initiative and 22 countries. Parents were asked to identify their perceptions of their children’s weight status as “underweight,” “normal weight,” “a little overweight,” or “extremely overweight.” We categorized children’s (6–9 years; n = 124,296) body mass index (BMI) as BMI-for-age Z-scores based on the 2007 WHO-recommended growth references. For each country included in the analysis and pooled estimates (country level), we calculated the distribution of children according to the WHO weight status classification, distribution by parental perception of child’s weight status, percentages of accurate, overestimating, or underestimating perceptions, misclassification levels, and predictors of parental misperceptions using a multilevel logistic regression analysis that included only children with overweight (including obesity). Statistical analyses were performed using Stata version 15 1. Results: Overall, 64.1% of parents categorized their child’s weight status accurately relative to the WHO growth charts. However, parents were more likely to underestimate their child’s weight if the child had overweight (82.3%) or obesity (93.8%). Parents were more likely to underestimate their child’s weight if the child was male (adjusted OR [adjOR]: 1.41; 95% confidence intervals [CI]: 1.28–1.55); the parent had a lower educational level (adjOR: 1.41; 95% CI: 1.26–1.57); the father was asked rather than the mother (adjOR: 1.14; 95% CI: 0.98–1.33); and the family lived in a rural area (adjOR: 1.10; 95% CI: 0.99–1.24). Overall, parents’ BMI was not strongly associated with the underestimation of children’s weight status, but there was a stronger association in some countries. Discussion/Conclusion: Our study supplements the current literature on factors that influence parental perceptions of their child’s weight status. Public health interventions aimed at promoting healthy childhood growth and development should consider parents’ knowledge and perceptions, as well as the sociocultural contexts in which children and families live.The authors gratefully acknowledge support from a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. Data collection in the countries was made possible through funding by: Albania: World Health Organization through the Joint Programme on Children, Food Security and Nutrition “Reducing Malnutrition in Children,” funded by the Millennium Development Goals Achievement Fund, and the Institute of Public Health; Bulgaria: Ministry of Health, National Center of Public Health and Analyses, World Health Organization Regional Office for Europe; Croatia: Ministry of Health, Croatian Institute of Public Health and World Health Organization Regional Office for Europe; Czechia: Grants AZV MZČR 17-31670 A and MZČR – RVO EÚ 00023761; Denmark: Danish Ministry of Health; France: French Public Health Agency; Georgia: World Health Organization; Ireland: Health Service Executive; Italy: Ministry of Health; Istituto Superiore di sanità (National Institute of Health); Kazakhstan: Ministry of Health of the Republic of Kazakhstan and World Health Organization Country Office; Latvia: n/a; Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and World Health Organization; Malta: Ministry of Health; Montenegro: World Health Organization and Institute of Public Health of Montenegro; Poland: National Health Programme, Ministry of Health; Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates and the kind technical support of Center for Studies and Research on Social Dynamics and Health (CEIDSS); Romania: Ministry of Health; Russia (Moscow): n/a; San Marino: Health Ministry; Educational Ministry; Social Security Institute; the Health Authority; Spain: Spanish Agency for Food Safety and Nutrition (AESAN); Tajikistan: World Health Organization Country Office in Tajikistan and Ministry of Health and Social Protection; and Turkmenistan: World Health Organization Country Office in Turkmenistan and Ministry of Health. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated.info:eu-repo/semantics/publishedVersio