Short and Long-run Effects of Obesity on Cognitive Skills: Evidence from an English Cohort

This paper investigates the consequences of obesity on individuals’ cognitive ability using data from the British Cohort Study. Specifically, it focuses on the outcomes of two cognitive tests: the B.A.S. (British Ability Scale), taken when cohort members are 10 years old, and a basic (literacy and numeracy) skills test, sit at age 34. The analysis is performed using both the individuals’ BMI (Body Mass Index) and an indicator for the obesity condition as measures of body weight and, for the test taken in adulthood, the impact of past weight status is also evaluated. In order to understand whether the influence of obesity is causal, we employ instrumental variables, using both parents’ BMI as instruments for cohort members’ BMI. Even after controlling for a large set of covariates describing individuals’ family environment, our results show that weight excess has a significant negative causal effect on cognitive skills, both in childhood and in adulthood. Moreover, childhood obesity has a long-run impact on skills at age 34

Quasi-experiments to estimate the economic impact of research infrastructures

The paper discusses the application of the quasi-experiment research design to the empirical evaluation of large-scale research infrastructures' socio-economic benefits. Specifically, after introducing the quasi-experimental methodology, it provides an illustrative example in which a quasi-experiment approach is used to assess the technological procurement spillovers of the Italian Space Agency

Fractal analysis of sampled profiles: Systematic study

A quantitative evaluation of the influence of sampling on the numerical fractal analysis of experimental profiles is of critical importance. Although this aspect has been widely recognized, a systematic analysis of the sampling influence is still lacking. Here we present the results of a systematic analysis of synthetic self-affine profiles in order to clarify the consequences of the application of a poor sampling (up to 1000 points) typical of scanning probe microscopy for the characterization of real interfaces and surfaces. We interpret our results in terms of a deviation and a dispersion of the measured exponent with respect to the "true" one. Both the deviation and the dispersion have always been disregarded in the experimental literature, and this can be very misleading if results obtained from poorly sampled images are presented. We provide reasonable arguments to assess the universality of these effects and propose an empirical method to take them into account. We show that it is possible to correct the deviation of the measured Hurst exponent from the "true" one and give a reasonable estimate of the dispersion error. The last estimate is particularly important in the experimental results since it is an intrinsic error that depends only on the number of sampling points and can easily overwhelm the statistical error. Finally, we test our empirical method calculating the Hurst exponent for the well-known 1 + 1 dimensional directed percolation profiles, with a 512-point sampling

The empirics of regulatory reforms proxied by categorical variables: recent findings and methodological issues

Some regulatory reforms do not change just a specific signal that can be represented by a quantitative continuous variable, such as a tax rate, a price cap, or an emission threshold. The standard theory of reform in applied welfare economics (going back to contributions by e.g. Ramsey, Samuelson and Guesnerie) asks the question: What is the marginal effect on social welfare of changing a policy signal? However, reforms such as privatization, unbundling or liberalization of network industries are often described by ‘packages’ shifting a policy framework. It is increasingly frequent in the empirical evaluation of such reforms to use categorical variables, often in polytomous form, for instance describing unbundling steps (vertical integration, accounting, functional, legal, ownership separation) on a discrete numerical scale, such as those proposed by the OECD and other international bodies. We review recent econometric literature evaluating regulatory reforms using such variables (40 papers) and we discuss some methodological issues arising in this context

Sleep Power Topography in Children with Attention Deficit Hyperactivity Disorder (ADHD).

OBJECTIVE Recent years saw an increasing interest towards sleep microstructure abnormalities in attention-deficit/hyperactivity disorder (ADHD). However, the existing literature on sleep electroencephalographic (EEG) power in ADHD is still controversial, often based on single electrode recordings, and mainly focused on slow wave activity (SWA) during NREM sleep. This study aimed to systematically investigate sleep power topography in all traditional frequency bands, in all sleep stages and across sleep cycles using high-density EEG (HD-EEG). METHOD Thirty drug-naïve children with ADHD (10.5 ± 2.1 years, 21 male) and 23 typically developing (TD) control participants (mean age: 10.2 ± 1.6 years, 13 male) were included in the current analysis. Signal power topography was computed in classical frequency bands during sleep, contrasted between groups and sleep cycles, and correlated with measures of ADHD severity, cognitive functioning and estimated total sleep time. RESULTS Compared to TD subjects, patients with ADHD consistently displayed a widespread increase in low-frequency activity (between 3 and 10 Hz) during NREM sleep, but not during REM sleep and wake before sleep onset. Such a difference involved a wide centro-posterior cluster of channels in the upper SWA range, in Theta, and low-Alpha. Between-group difference was maximal in sleep stage N3 in the first sleep cycle, and positively correlated with average total sleep time. CONCLUSIONS These results support the concept that children with ADHD, compared to TD peers, have a higher sleep pressure and altered sleep homeostasis, which possibly interfere with (and delay) cortical maturation

Revealing emergent magnetic charge in an antiferromagnet with diamond quantum magnetometry

Whirling topological textures play a key role in exotic phases of magnetic materials and are promising for logic and memory applications. In antiferromagnets, these textures exhibit enhanced stability and faster dynamics with respect to their ferromagnetic counterparts, but they are also difficult to study due to their vanishing net magnetic moment. One technique that meets the demand of highly sensitive vectorial magnetic field sensing with negligible backaction is diamond quantum magnetometry. Here we show that an archetypal antiferromagnet—haematite—hosts a rich tapestry of monopolar, dipolar and quadrupolar emergent magnetic charge distributions. The direct read-out of the previously inaccessible vorticity of an antiferromagnetic spin texture provides the crucial connection to its magnetic charge through a duality relation. Our work defines a paradigmatic class of magnetic systems to explore two-dimensional monopolar physics, and highlights the transformative role that diamond quantum magnetometry could play in exploring emergent phenomena in quantum materials

COVID-19 in rheumatic diseases in Italy: first results from the Italian registry of the Italian Society for Rheumatology (CONTROL-19)

OBJECTIVES: Italy was one of the first countries significantly affected by the coronavirus disease 2019 (COVID-19) epidemic. The Italian Society for Rheumatology promptly launched a retrospective and anonymised data collection to monitor COVID-19 in patients with rheumatic and musculoskeletal diseases (RMDs), the CONTROL-19 surveillance database, which is part of the COVID-19 Global Rheumatology Alliance. METHODS: CONTROL-19 includes patients with RMDs and proven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) updated until May 3rd 2020. In this analysis, only molecular diagnoses were included. The data collection covered demographic data, medical history (general and RMD-related), treatments and COVID-19 related features, treatments, and outcome. In this paper, we report the first descriptive data from the CONTROL-19 registry. RESULTS: The population of the first 232 patients (36% males) consisted mainly of elderly patients (mean age 62.2 years), who used corticosteroids (51.7%), and suffered from multi-morbidity (median comorbidities 2). Rheumatoid arthritis was the most frequent disease (34.1%), followed by spondyloarthritis (26.3%), connective tissue disease (21.1%) and vasculitis (11.2%). Most cases had an active disease (69.4%). Clinical presentation of COVID-19 was typical, with systemic symptoms (fever and asthenia) and respiratory symptoms. The overall outcome was severe, with high frequencies of hospitalisation (69.8%), respiratory support oxygen (55.7%), non-invasive ventilation (20.9%) or mechanical ventilation (7.5%), and 19% of deaths. Male patients typically manifested a worse prognosis. Immunomodulatory treatments were not significantly associated with an increased risk of intensive care unit admission/mechanical ventilation/death. CONCLUSIONS: Although the report mainly includes the most severe cases, its temporal and spatial trend supports the validity of the national surveillance system. More complete data are being acquired in order to both test the hypothesis that RMD patients may have a different outcome from that of the general population and determine the safety of immunomodulatory treatments

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon