SARS-CoV-2 transmission patterns in educational settings during the Alpha wave in Reggio-Emilia, Italy

: Different monitoring and control policies have been implemented in schools to minimize the spread of SARS-CoV-2. Transmission in schools has been hard to quantify due to the large proportion of asymptomatic carriers in young individuals. We applied a Bayesian approach to reconstruct the transmission chains between 284 SARS-CoV-2 infections ascertained during 87 school outbreak investigations conducted between March and April 2021 in Italy. Under the policy of reactive quarantines, we found that 42.5% (95%CrI: 29.5-54.3%) of infections among school attendees were caused by school contacts. The mean number of secondary cases infected at school by a positive individual during in-person education was estimated to be 0.33 (95%CrI: 0.23-0.43), with marked heterogeneity across individuals. Specifically, we estimated that only 26.0% (95%CrI: 17.6-34.1%) of students and school personnel who tested positive during in-person education caused at least one secondary infection at school. Positive individuals who attended school for at least 6 days before being isolated or quarantined infected on average 0.49 (95%CrI: 0.14-0.83) secondary cases. Our findings provide quantitative insights on the contribution of school transmission to the spread of SARS-CoV-2 in young individuals. Identifying positive cases within 5 days after exposure to their infector could reduce onward transmission at school by at least 30%

Geology of the Victoria quadrangle (H02), Mercury

Mercury’s quadrangle H02 ‘Victoria’ is located in the planet’s northern hemisphere and lies between latitudes 22.5° N and 65° N, and between longitudes 270° E and 360° E. This quadrangle covers 6.5% of the planet’s surface with a total area of almost 5 million km2. Our 1:3,000,000-scale geologic map of the quadrangle was produced by photo-interpretation of remotely sensed orbital images captured by the MESSENGER spacecraft. Geologic contacts were drawn between 1:300,000 and 1:600,000 mapping scale and constitute the boundaries of intercrater, intermediate and smooth plains units; in addition, three morpho-stratigraphic classes of craters larger than 20 km were mapped. The geologic map reveals that this area is dominated by Intercrater Plains encompassing some almost-coeval, probably younger, Intermediate Plains patches and interrupted to the north-west, north-east and east by the Calorian Northern Smooth Plains. This map represents the first complete geologic survey of the Victoria quadrangle at this scale, and an improvement of the existing 1:5,000,000 Mariner 10-based map, which covers only 36% of the quadrangle

A machine learning pipeline for quantitative phenotype prediction from genotype data

<p>Abstract</p> <p>Background</p> <p>Quantitative phenotypes emerge everywhere in systems biology and biomedicine due to a direct interest for quantitative traits, or to high individual variability that makes hard or impossible to classify samples into distinct categories, often the case with complex common diseases. Machine learning approaches to genotype-phenotype mapping may significantly improve Genome-Wide Association Studies (GWAS) results by explicitly focusing on predictivity and optimal feature selection in a multivariate setting. It is however essential that stringent and well documented Data Analysis Protocols (DAP) are used to control sources of variability and ensure reproducibility of results. We present a genome-to-phenotype pipeline of machine learning modules for quantitative phenotype prediction. The pipeline can be applied for the direct use of whole-genome information in functional studies. As a realistic example, the problem of fitting complex phenotypic traits in heterogeneous stock mice from single nucleotide polymorphims (SNPs) is here considered.</p> <p>Methods</p> <p>The core element in the pipeline is the L1L2 regularization method based on the naïve elastic net. The method gives at the same time a regression model and a dimensionality reduction procedure suitable for correlated features. Model and SNP markers are selected through a DAP originally developed in the MAQC-II collaborative initiative of the U.S. FDA for the identification of clinical biomarkers from microarray data. The L1L2 approach is compared with standard Support Vector Regression (SVR) and with Recursive Jump Monte Carlo Markov Chain (MCMC). Algebraic indicators of stability of partial lists are used for model selection; the final panel of markers is obtained by a procedure at the chromosome scale, termed ’saturation’, to recover SNPs in Linkage Disequilibrium with those selected.</p> <p>Results</p> <p>With respect to both MCMC and SVR, comparable accuracies are obtained by the L1L2 pipeline. Good agreement is also found between SNPs selected by the L1L2 algorithms and candidate loci previously identified by a standard GWAS. The combination of L1L2-based feature selection with a saturation procedure tackles the issue of neglecting highly correlated features that affects many feature selection algorithms.</p> <p>Conclusions</p> <p>The L1L2 pipeline has proven effective in terms of marker selection and prediction accuracy. This study indicates that machine learning techniques may support quantitative phenotype prediction, provided that adequate DAPs are employed to control bias in model selection.</p

The potential of Virtual Reality as anxiety management tool: a randomized controlled study in a sample of patients affected by Generalized Anxiety Disorder

Background: Generalized anxiety disorder (GAD) is a psychiatric disorder characterized by a constant and unspecific anxiety that interferes with daily-life activities. Its high prevalence in general population and the severe limitations it causes, point out the necessity to find new efficient strategies to treat it. Together with the cognitive-behavioural treatments, relaxation represents a useful approach for the treatment of GAD, but it has the limitation that it is hard to be learned. To overcome this limitation we propose the use of virtual reality (VR) to facilitate the relaxation process by visually presenting key relaxing images to the subjects. The visual presentation of a virtual calm scenario can facilitate patients' practice and mastery of relaxation, making the experience more vivid and real than the one that most subjects can create using their own imagination and memory, and triggering a broad empowerment process within the experience induced by a high sense of presence. According to these premises, the aim of the present study is to investigate the advantages of using a VR-based relaxation protocol in reducing anxiety in patients affected by GAD. Methods/Design: The trialis based on a randomized controlled study, including three groups of 25 patients each (for a total of 75 patients): (1) the VR group, (2) the non-VR group and (3) the waiting list (WL) group. Patients in the VR group will be taught to relax using a VR relaxing environment and audio-visual mobile narratives; patients in the non-VR group will be taught to relax using the same relaxing narratives proposed to the VR group, but without the VR support, and patients in the WL group will not receive any kind of relaxation training. Psychometric and psychophysiological outcomes will serve as quantitative dependent variables, while subjective reports of participants will be used as qualitative dependent variables. Conclusion: We argue that the use of VR for relaxation represents a promising approach in the treatment of GAD since it enhances the quality of the relaxing experience through the elicitation of the sense of presence. This controlled trial will be able to evaluate the effects of the use of VR in relaxation while preserving the benefits of randomization to reduce bias

Animal models of major depressive disorder and the implications for drug discovery and development

Introduction: Depression is a highly debilitating psychiatric disorder that affects the global population and causes severe disabilities and suicide. Depression pathogenesis remains poorly understood, and the disorder is often treatment-resistant and recurrent, necessitating the development of novel therapies, models and concepts in this field. Areas covered: Animal models are indispensable for translational biological psychiatry, and markedly advance the study of depression. Novel approaches continuously emerge that may help untangle the disorder heterogeneity and unclear categories of disease classification systems. Some of these approaches include widening the spectrum of model species used for translational research, using a broader range of test paradigms, exploring new pathogenic pathways and biomarkers, and focusing more closely on processes beyond neural cells (e.g. glial, inflammatory and metabolic deficits). Expert opinion: Dividing the core symptoms into easily translatable, evolutionarily conserved phenotypes is an effective way to reevaluate current depression modeling. Conceptually novel approaches based on the endophenotype paradigm, cross-species trait genetics and ‘domain interplay concept’, as well as using a wider spectrum of model organisms and target systems will enhance experimental modeling of depression and antidepressant drug discovery. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group

SIMBIO-SYS : Scientific Cameras and Spectrometer for the BepiColombo Mission

The SIMBIO-SYS (Spectrometer and Imaging for MPO BepiColombo Integrated Observatory SYStem) is a complex instrument suite part of the scientific payload of the Mercury Planetary Orbiter for the BepiColombo mission, the last of the cornerstone missions of the European Space Agency (ESA) Horizon + science program. The SIMBIO-SYS instrument will provide all the science imaging capability of the BepiColombo MPO spacecraft. It consists of three channels: the STereo imaging Channel (STC), with a broad spectral band in the 400-950 nm range and medium spatial resolution (at best 58 m/px), that will provide Digital Terrain Model of the entire surface of the planet with an accuracy better than 80 m; the High Resolution Imaging Channel (HRIC), with broad spectral bands in the 400-900 nm range and high spatial resolution (at best 6 m/px), that will provide high-resolution images of about 20% of the surface, and the Visible and near-Infrared Hyperspectral Imaging channel (VIHI), with high spectral resolution (6 nm at finest) in the 400-2000 nm range and spatial resolution reaching 120 m/px, it will provide global coverage at 480 m/px with the spectral information, assuming the first orbit around Mercury with periherm at 480 km from the surface. SIMBIO-SYS will provide high-resolution images, the Digital Terrain Model of the entire surface, and the surface composition using a wide spectral range, as for instance detecting sulphides or material derived by sulphur and carbon oxidation, at resolutions and coverage higher than the MESSENGER mission with a full co-alignment of the three channels. All the data that will be acquired will allow to cover a wide range of scientific objectives, from the surface processes and cartography up to the internal structure, contributing to the libration experiment, and the surface-exosphere interaction. The global 3D and spectral mapping will allow to study the morphology and the composition of any surface feature. In this work, we describe the on-ground calibrations and the results obtained, providing an important overview of the instrument performances. The calibrations have been performed at channel and at system levels, utilizing specific setup in most of the cases realized for SIMBIO-SYS. In the case of the stereo camera (STC), it has been necessary to have a validation of the new stereo concept adopted, based on the push-frame. This work describes also the results of the Near-Earth Commissioning Phase performed few weeks after the Launch (20 October 2018). According to the calibration results and the first commissioning the three channels are working very well.Peer reviewe

Landscape structure affects the prevalence and distribution of a tick-borne zoonotic pathogen

Background Landscape structure can affect pathogen prevalence and persistence with consequences for human and animal health. Few studies have examined how reservoir host species traits may interact with landscape structure to alter pathogen communities and dynamics. Using a landscape of islands and mainland sites we investigated how natural landscape fragmentation affects the prevalence and persistence of the zoonotic tick-borne pathogen complex Borrelia burgdorferi(sensu lato), which causes Lyme borreliosis. We hypothesized that the prevalence of B. burgdorferi (s.l.) would be lower on islands compared to the mainland and B. afzelii, a small mammal specialist genospecies, would be more affected by isolation than bird-associated B. garinii and B. valaisiana and the generalist B. burgdorferi (sensu stricto). Methods Questing (host-seeking) nymphal I. Ricinus ticks (n = 6567) were collected from 12 island and 6 mainland sites in 2011, 2013 and 2015 and tested for B. burgdorferi(s.l.). Deer abundance was estimated using dung transects. Results The prevalence of B. burgdorferi (s.l.) was significantly higher on the mainland (2.5%, 47/1891) compared to island sites (0.9%, 44/4673) (P &lt; 0.01). While all four genospecies of B. burgdorferi (s.l.) were detected on the mainland, bird-associated species B. garinii and B. valaisiana and the generalist genospecies B. burgdorferi(s.s.) predominated on islands. Conclusion We found that landscape structure influenced the prevalence of a zoonotic pathogen, with a lower prevalence detected among island sites compared to the mainland. This was mainly due to the significantly lower prevalence of small mammal-associated B. afzelii. Deer abundance was not related to pathogen prevalence, suggesting that the structure and dynamics of the reservoir host community underpins the observed prevalence patterns, with the higher mobility of bird hosts compared to small mammal hosts leading to a relative predominance of the bird-associated genospecies B. garinii and generalist genospecies B. burgdorferi (s.s.) on islands. In contrast, the lower prevalence of B. afzelii on islands may be due to small mammal populations there exhibiting lower densities, less immigration and stronger population fluctuations. This study suggests that landscape fragmentation can influence the prevalence of a zoonotic pathogen, dependent on the biology of the reservoir host

Neural correlates of a single-session massage treatment

The current study investigated the immediate neurophysiological effects of different types of massage in healthy adults using functional magnetic resonance imaging (fMRI). Much attention has been given to the default mode network, a set of brain regions showing greater activity in the resting state. These regions (i.e. insula, posterior and anterior cingulate, inferior parietal and medial prefrontal cortices) have been postulated to be involved in the neural correlates of consciousness, specifically in arousal and awareness. We posit that massage would modulate these same regions given the benefits and pleasant affective properties of touch. To this end, healthy participants were randomly assigned to one of four conditions: 1. Swedish massage, 2. reflexology, 3. massage with an object or 4. a resting control condition. The right foot was massaged while each participant performed a cognitive association task in the scanner. We found that the Swedish massage treatment activated the subgenual anterior and retrosplenial/posterior cingulate cortices. This increased blood oxygen level dependent (BOLD) signal was maintained only in the former brain region during performance of the cognitive task. Interestingly, the reflexology massage condition selectively affected the retrosplenial/posterior cingulate in the resting state, whereas massage with the object augmented the BOLD response in this region during the cognitive task performance. These findings should have implications for better understanding how alternative treatments might affect resting state neural activity and could ultimately be important for devising new targets in the management of mood disorders