Mattinglybehrens0113

Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.Long term surface soil moisture (SSM) data with stable and consistent quality are critical for global environment and climate change monitoring. L band radiometers onboard the recently launched Soil Moisture Active Passive (SMAP) Mission can provide the state-of-the-art accuracy SSM, while Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and AMSR2 series provide long term observational records of multi-frequency radiometers (C, X, and K bands). This study transfers the merits of SMAP to AMSR-E/2, and develops a global daily SSM dataset (named as NNsm) with stable and consistent quality at a 36 km resolution (2002-2019). The NNsm can reproduce the SMAP SSM accurately, with a global Root Mean Square Error (RMSE) of 0.029 m3/m3. NNsm also compares well with in situ SSM observations, and outperforms AMSR-E/2 standard SSM products from JAXA and LPRM. Ferrostatin1 This global observation-driven dataset spans nearly two decades at present, and is extendable through the ongoing AMSR2 and upcoming AMSR3 missions for long-term studies of climate extremes, trends, and decadal variability.The real-time live fluorescent monitoring of surface AMPA receptors (AMPARs) could open new opportunities for drug discovery and phenotypic screening concerning neuropsychiatric disorders. We have developed FORTIS, a tool based on pH sensitivity capable of detecting subtle changes in surface AMPARs at a neuronal population level. The expression of SEP-GluA1 or pHuji-GluA1 recombinant AMPAR subunits in mammalian neurons cultured in 96-well plates enables surface AMPARs to be monitored with a microplate reader. Thus, FORTIS can register rapid changes in surface AMPARs induced by drugs or genetic modifications without having to rely on conventional electrophysiology or imaging. By combining FORTIS with pharmacological manipulations, basal surface AMPARs, and plasticity-like changes can be monitored. We expect that employing FORTIS to screen for changes in surface AMPARs will accelerate both neuroscience research and drug discovery.Alterations in cortical inter-areal functional connectivity, and aberrant glutamatergic signalling are implicated in the pathophysiology of schizophrenia but the relationship between the two is unclear. We used multimodal imaging to identify areas of convergence between the two systems. Two separate cohorts were examined, comprising 195 participants in total. All participants received resting state functional MRI to characterise functional brain networks and proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate concentrations in the frontal cortex. Study A investigated the relationship between frontal cortex glutamate concentrations and network connectivity in individuals with schizophrenia and healthy controls. Study B also used 1H-MRS, and scanned individuals with schizophrenia and healthy controls before and after a challenge with the glutamatergic modulator riluzole, to investigate the relationship between changes in glutamate concentrations and changes in network connectivity. In both studies the network based statistic was used to probe associations between glutamate and connectivity, and glutamate associated networks were then characterised in terms of their overlap with canonical functional networks. Study A involved 76 individuals with schizophrenia and 82 controls, and identified a functional network negatively associated with glutamate concentrations that was concentrated within the salience network (p  0.4). Frontal cortex glutamate concentrations are associated with inter-areal functional connectivity of a network that localises to the salience network. Changes in network connectivity in response to glutamate modulation show an opposite effect compared to the relationship observed at baseline, which may complicate pharmacological attempts to simultaneously correct glutamatergic and connectivity aberrations.Many modern interactions happen in a digital space, where automated recommendations and homophily can shape the composition of groups interacting together and the knowledge that groups are able to tap into when operating online. Digital interactions are also characterized by different scales, from small interest groups to large online communities. Here, we manipulate the composition of groups based on a large multi-trait profiling space (including demographic, professional, psychological and relational variables) to explore the causal link between group composition and performance as a function of group size. We asked volunteers to search news online under time pressure and measured individual and group performance in forecasting real geo-political events. Our manipulation affected the correlation of forecasts made by people after online searches. Group composition interacted with group size so that composite diversity benefited individual and group performance proportionally to group size. Aggregating opinions of modular crowds composed of small independent groups achieved better forecasts than aggregating a similar number of forecasts from non-modular ones. link2 Finally, we show differences existing among groups in terms of disagreement, speed of convergence to consensus forecasts and within-group variability in performance. The present work sheds light on the mechanisms underlying effective online information gathering in digital environments.The COVID-19 pandemic has been associated with an increase in obsessive-compulsive disorder/symptoms (OCD/OCS). However, knowledge is limited regarding the trajectories of OCS during the pandemic, as well as their predictors and mechanisms (e.g., experiential avoidance, EA). The aim of this study was to describe the trajectories of OCS and the identification of associated factors. We assessed 1207 participants of the general population in March 2020 (t1) and June 2020 (t2). Pre-pandemic data was available from March 2014 for a subsample (n = 519). To define trajectories, we determined OCS status (OCS+/-). We performed a hierarchical multinomial logistic regression to investigate predictors of trajectories. Between t1 and t2, 66% of participants had an asymptomatic trajectory (OCS-/OCS-); 18% had a continuously symptomatic trajectory (OCS+/OCS+). Ten percent had a delayed-onset trajectory (OCS-/OCS+), and the recovery trajectory group (OCS+/OCS-) was the smallest group (6%). Higher education reduced the odds of an OCS+/OCS- trajectory. OCS in 2014 was associated with increased odds of showing an OCS+/OCS+ or OCS-/OCS+ trajectory. When EA at t1 and change in EA from t1 to t2 were added to the model, higher EA at t1 was associated with increased odds of scoring above the cut score on one or more of the assessments. A higher decrease in EA from t1 to t2 reduced the probability of showing an OCS+/OCS+ and an OCS-/OCS+ trajectory. While the current data supports a slight increase in OCS during the pandemic, trajectories differed, and EA seems to represent an important predictor for an unfavorable development.Fractional statistics is one of the most intriguing features of topological phases in 2D. In particular, the so-called non-Abelian statistics plays a crucial role towards realizing topological quantum computation. Recently, the study of topological phases has been extended to 3D and it has been proposed that loop-like extensive objects can also carry fractional statistics. In this work, we systematically study the so-called three-loop braiding statistics for 3D interacting fermion systems. link3 Most surprisingly, we discover new types of non-Abelian three-loop braiding statistics that can only be realized in fermionic systems (or equivalently bosonic systems with emergent fermionic particles). On the other hand, due to the correspondence between gauge theories with fermionic particles and classifying fermionic symmetry-protected topological (FSPT) phases with unitary symmetries, our study also gives rise to an alternative way to classify FSPT phases. We further compare the classification results for FSPT phases with arbitrary Abelian unitary total symmetry Gf and find systematical agreement with previous studies.The COVID-19 pandemic and quarantine measures have sparked debate regarding their traumatic nature. This cross-sectional study reports the prevalence rate of probable post-traumatic stress syndrome (PTSD) and associated factors among French university students. A total of 22,883 students completed the online questionnaire. The prevalence rate of probable PTSD, assessed using the PTSD Checklist for DSM-5, was 19.5% [19.0-20.0]. Female (1.32 [1.21-1.45]) or non-binary gender (1.76 [1.35-2.31]), exposure to a non-COVID-19-related traumatic event (3.37 [3.08-3.67]), having lived through quarantine alone (1.22 [1.09-1.37]), poor quality of social ties (2.38 [2.15-2.62]), loss of income (1.20 [1.09-1.31]), poor quality housing (1.90 [1.59-2.26]), low-quality of the information received (1.50 [1.35-1.66]) and a high level of exposure to COVID-19 (from 1.38 [1.24-1.54] to 10.82 [2.33-76.57] depending on the score) were associated with PTSD. Quarantine was considered potentially traumatic by 78.8% of the students with probable PTSD. These findings suggest the pandemic context and lockdown measures could have post-traumatic consequences, stimulating debate on the nosography of PTSD.To clarify the structure of genetic risks for 11 major psychiatric disorders, we calculated, from morbidity risks for disorders in 1st-5th degree relatives controlling for cohabitation effects, in the Swedish population born between 1932 and 1995 (n = 5,830,014), the family genetic risk scores (FGRS) for major depression (MD), anxiety disorders (AD), obsessive-compulsive disorder (OCD), bipolar disorder (BD), schizophrenia (SZ), bulimia (BUL), anorexia nervosa (AN), alcohol use disorder (AUD), drug use disorder (DUD), ADHD, and autism-spectrum disorder (ASD). For all affected individuals, we calculated their mean standardized FGRS for each disorder. The patterns of FGRS were quite similar for MD and AD, and for AUD and DUD, but substantially less similar for BUL and AN, BD and SZ, and ADHD and ASD. While OCD had high levels of FGRS for MD and AD, the overall FGRS profile differed considerably from MD and AD. ADHD FGRS scores were substantially elevated in AUD and DUD. FGRS scores for BD, OCD, AN, ASD, ADHD, and especially SZ were relatively disorder-specific while genetic risk for MD and AD had more generalized effects. The levels of FGRS for BMI, coronary artery disease, and educational attainment across our disorders replicated prior associations found using molecular genetic methods. All diagnostic categories examined had elevated FGRS for many disorders producing, for each condition, an informative FGRS profile. Using a novel method which approximates, from pedigree data, aggregate genetic risk, we have replicated and extended prior insights into the structure of genetic risk factors for key psychiatric illnesses.Fragment-based drug design has introduced a bottom-up process for drug development, with improved sampling of chemical space and increased effectiveness in early drug discovery. Here, we combine the use of pharmacophores, the most general concept of representing drug-target interactions with the theory of protein hotspots, to develop a design protocol for fragment libraries. The SpotXplorer approach compiles small fragment libraries that maximize the coverage of experimentally confirmed binding pharmacophores at the most preferred hotspots. The efficiency of this approach is demonstrated with a pilot library of 96 fragment-sized compounds (SpotXplorer0) that is validated on popular target classes and emerging drug targets. Biochemical screening against a set of GPCRs and proteases retrieves compounds containing an average of 70% of known pharmacophores for these targets. More importantly, SpotXplorer0 screening identifies confirmed hits against recently established challenging targets such as the histone methyltransferase SETD2, the main protease (3CLPro) and the NSP3 macrodomain of SARS-CoV-2.