Spatial and topological organization of DNA chains induced by gene co-localization

Transcriptional activity has been shown to relate to the organization of chromosomes in the eukaryotic nucleus and in the bacterial nucleoid. In particular, highly transcribed genes, RNA polymerases and transcription factors gather into discrete spatial foci called transcription factories. However, the mechanisms underlying the formation of these foci and the resulting topological order of the chromosome remain to be elucidated. Here we consider a thermodynamic framework based on a worm-like chain model of chromosomes where sparse designated sites along the DNA are able to interact whenever they are spatially close-by. This is motivated by recurrent evidence that there exists physical interactions between genes that operate together. Three important results come out of this simple framework. First, the resulting formation of transcription foci can be viewed as a micro-phase separation of the interacting sites from the rest of the DNA. In this respect, a thermodynamic analysis suggests transcription factors to be appropriate candidates for mediating the physical interactions between genes. Next, numerical simulations of the polymer reveal a rich variety of phases that are associated with different topological orderings, each providing a way to increase the local concentrations of the interacting sites. Finally, the numerical results show that both one-dimensional clustering and periodic location of the binding sites along the DNA, which have been observed in several organisms, make the spatial co-localization of multiple families of genes particularly efficient.Comment: Figures and Supplementary Material freely available on http://dx.doi.org/10.1371/journal.pcbi.100067

The International Deep Planet Survey I. The frequency of wide-orbit massive planets around A-stars

Breakthrough direct detections of planetary companions orbiting A-type stars confirm the existence of massive planets at relatively large separations, but dedicated surveys are required to estimate the frequency of similar planetary systems. To measure the first estimation of the giant exoplanetary systems frequency at large orbital separation around A-stars, we have conducted a deep-imaging survey of young (8-400 Myr), nearby (19-84 pc) A- and F-stars to search for substellar companions in the 10-300 AU range. The sample of 42 stars combines all A-stars observed in previous AO planet search surveys reported in the literature with new AO observations from VLT/NaCo and Gemini/NIRI. It represents an initial subset of the International Deep Planet Survey (IDPS) sample of stars covering M- to B-stars. The data were obtained with diffraction-limited observations in H- and Ks-band combined with angular differential imaging to suppress the speckle noise of the central stars, resulting in typical 5-sigma detection limits in magnitude difference of 12 mag at 1", 14 mag at 2" and 16 mag at 5" which is sufficient to detect massive planets. A detailed statistical analysis of the survey results is performed using Monte Carlo simulations. Considering the planet detections, we estimate the fraction of A-stars having at least one massive planet (3-14 MJup) in the range 5-320 AU to be inside 5.9-18.8% at 68% confidence, assuming a flat distribution for the mass of the planets. By comparison, the brown dwarf (15-75 MJup) frequency for the sample is 2.0-8.9% at 68% confidence in the range 5-320 AU. Assuming power law distributions for the mass and semimajor axis of the planet population, the AO data are consistent with a declining number of massive planets with increasing orbital radius which is distinct from the rising slope inferred from radial velocity (RV) surveys around evolved A-stars.Comment: 20 pages, 10 figures, 7 tables. Accepted for publication in A&

Cognitive clusters in first-episode psychosis

Impairments in a broad range of cognitive domains have been consistently reported in some individuals with first-episode psychosis (FEP). Cognitive deficits can be observed during the prodromal stage. However, the course of cognitive deficits is still unclear. The aim of this study was to identify cognitive subgroups over time and to compare their sociodemographic, clinical and functional profiles. A total of 114 patients with Schizophrenia Spectrum Disorders were included in the present study. We assessed subjects through psychiatric scales and eight neuropsychological tests at baseline and at two-year follow-up visit. We performed the Partition Around Medoids algorithm with all cognitive variables. Furthermore, we performed a logistic regression to identify the predictors related to the different cognitive clusters at follow-up. Two distinct subgroups were found: the first cluster characterized by cognitive impairment and a second cluster had relatively intact cognition in comparison with norms. Up to 54.7% of patients with cognitive deficits at baseline tended to improve during the first two years of treatment. Patients with intact cognition at follow-up had a higher socioeconomic status, later age of onset, lower negative symptoms and a higher cognitive reserve (CR) at baseline. CR and age of onset were the baseline variables that predicted cognitive impairment. This research allows us to obtain a better understanding of the heterogeneous profile of psychotic disorders. Identifying the characteristics of patients who will present a cognitive impairment could improve early detection and intervention. These results suggest that enhancing CR could contribute to improving the course of the illness. © 2021 Elsevier B.V

Oceanic eddy‑induced modifications to air–sea heat and CO2 fluxes in the Brazil‑Malvinas Confluence

Sea surface temperature (SST) anomalies caused by a warm core eddy (WCE) in the Southwestern Atlantic Ocean (SWA) rendered a crucial influence on modifying the marine atmospheric boundary layer (MABL). During the first cruise to support the Antarctic Modeling and Observation System (ATMOS) project, a WCE that was shed from the Brazil Current was sampled. Apart from traditional meteorological measurements, we used the Eddy Covariance method to directly measure the ocean–atmosphere sensible heat, latent heat, momentum, and carbon dioxide ( CO2) fluxes. The mechanisms of pressure adjustment and vertical mixing that can make the MABL unstable were both identified. The WCE also acted to increase the surface winds and heat fluxes from the ocean to the atmosphere. Oceanic regions at middle and high latitudes are expected to absorb atmospheric CO2, and are thereby considered as sinks, due to their cold waters. Instead, the presence of this WCE in midlatitudes, surrounded by predominantly cold waters, caused the ocean to locally act as a CO2 source. The contribution to the atmosphere was estimated as 0.3 ± 0.04 mmol m− 2 day− 1, averaged over the sampling period. The CO2 transfer velocity coefficient (K) was determined using a quadratic fit and showed an adequate representation of ocean–atmosphere fluxes. The ocean–atmosphere CO2, momentum, and heat fluxes were each closely correlated with the SST. The increase of SST inside the WCE clearly resulted in larger magnitudes of all of the ocean–atmosphere fluxes studied here. This study adds to our understanding of how oceanic mesoscale structures, such as this WCE, affect the overlying atmosphere

Cognitive clusters in first-episode psychosis

Impairments in a broad range of cognitive domains have been consistently reported in some individuals with first-episode psychosis (FEP). Cognitive deficits can be observed during the prodromal stage. However, the course of cognitive deficits is still unclear. The aim of this study was to identify cognitive subgroups over time and to compare their sociodemographic, clinical and functional profiles. A total of 114 patients with Schizophrenia Spectrum Disorders were included in the present study. We assessed subjects through psychiatric scales and eight neuropsychological tests at baseline and at two-year follow-up visit. We performed the Partition Around Medoids algorithm with all cognitive variables. Furthermore, we performed a logistic regression to identify the predictors related to the different cognitive clusters at follow-up. Two distinct subgroups were found: the first cluster characterized by cognitive impairment and a second cluster had relatively intact cognition in comparison with norms. Up to 54.7% of patients with cognitive deficits at baseline tended to improve during the first two years of treatment. Patients with intact cognition at follow-up had a higher socioeconomic status, later age of onset, lower negative symptoms and a higher cognitive reserve (CR) at baseline. CR and age of onset were the baseline variables that predicted cognitive impairment. This research allows us to obtain a better understanding of the heterogeneous profile of psychotic disorders. Identifying the characteristics of patients who will present a cognitive impairment could improve early detection and intervention. These results suggest that enhancing CR could contribute to improving the course of the illness

VAMOS: a Pathfinder for the HAWC Gamma-Ray Observatory

VAMOS was a prototype detector built in 2011 at an altitude of 4100m a.s.l. in the state of Puebla, Mexico. The aim of VAMOS was to finalize the design, construction techniques and data acquisition system of the HAWC observatory. HAWC is an air-shower array currently under construction at the same site of VAMOS with the purpose to study the TeV sky. The VAMOS setup included six water Cherenkov detectors and two different data acquisition systems. It was in operation between October 2011 and May 2012 with an average live time of 30%. Besides the scientific verification purposes, the eight months of data were used to obtain the results presented in this paper: the detector response to the Forbush decrease of March 2012, and the analysis of possible emission, at energies above 30 GeV, for long gamma-ray bursts GRB111016B and GRB120328B.Comment: Accepted for pubblication in Astroparticle Physics Journal (20 pages, 10 figures). Corresponding authors: A.Marinelli and D.Zaboro

Impact of COVID-19 Confinement on Physical Activity and Sedentary Behaviour in Spanish University Students: Role of Gender

[EN] During the COVID-19 pandemic, entire populations were instructed to live in home-confinement to prevent the expansion of the disease. Spain was one of the countries with the strictest conditions, as outdoor physical activity was banned for nearly two months. This study aimed to analyse the changes in physical activity and sedentary behaviours in Spanish university students before and during the confinement by COVID-19 with special focus on gender. We also analysed enjoyment, the tools used and motivation and impediments for doing physical activity. An online questionnaire, which included the International Physical Activity Questionnaire Short Form and certain "ad hoc" questions, was designed. Students were recruited by distributing an invitation through the administrative channels of 16 universities and a total of 13,754 valid surveys were collected. Overall, university students reduced moderate (-29.5%) and vigorous (-18.3%) physical activity during the confinement and increased sedentary time (+52.7%). However, they spent more time on high intensity interval training (HIIT) (+18.2%) and mind-body activities (e.g., yoga) (+80.0%). Adaptation to the confinement, in terms of physical activity, was handled better by women than by men. These results will help design strategies for each gender to promote physical activity and reduce sedentary behaviour during confinement periods.S

The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase

The EU Center of Excellence for Exascale in Solid Earth (ChEESE) develops exascale transition capabilities in the domain of Solid Earth, an area of geophysics rich in computational challenges embracing different approaches to exascale (capability, capacity, and urgent computing). The first implementation phase of the project (ChEESE-1P; 2018¿2022) addressed scientific and technical computational challenges in seismology, tsunami science, volcanology, and magnetohydrodynamics, in order to understand the phenomena, anticipate the impact of natural disasters, and contribute to risk management. The project initiated the optimisation of 10 community flagship codes for the upcoming exascale systems and implemented 12 Pilot Demonstrators that combine the flagship codes with dedicated workflows in order to address the underlying capability and capacity computational challenges. Pilot Demonstrators reaching more mature Technology Readiness Levels (TRLs) were further enabled in operational service environments on critical aspects of geohazards such as long-term and short-term probabilistic hazard assessment, urgent computing, and early warning and probabilistic forecasting. Partnership and service co-design with members of the project Industry and User Board (IUB) leveraged the uptake of results across multiple research institutions, academia, industry, and public governance bodies (e.g. civil protection agencies). This article summarises the implementation strategy and the results from ChEESE-1P, outlining also the underpinning concepts and the roadmap for the on-going second project implementation phase (ChEESE-2P; 2023¿2026).This work has been funded by the European Union Horizon 2020 research and innovation program under the ChEESE project, Grant Agreement No. 823844, by the European High Performance Computing Joint Undertaking (JU), Grant Agreement No 101093038, and by 4 different Partnership for Advanced Computing in Europe (PRACE) projects from calls 20 and 21 for granting ChEESE activities with a total of 170M core hours on different machines: VOHA (ID 2019215114), TSUCAST (ID 2019215169), SEISVIEW (ID 2019215212) and TsuHazAP (ID 2020225386)

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured