Sub MeV Particles Detection and Identification in the MUNU detector ((1)ISN, IN2P3/CNRS-UJF, Grenoble, France, (2)Institut de Physique, Neuch\^atel, Switzerland, (3) INFN, Padova Italy, (4) Physik-Institut, Z\"{u}rich, Switzerland)

We report on the performance of a 1 m$^{3}$ TPC filled with CF$_{4}$ at 3 bar, immersed in liquid scintillator and viewed by photomultipliers. Particle detection, event identification and localization achieved by measuring both the current signal and the scintillation light are presented. Particular features of $\alpha$ particle detection are also discussed. Finally, the ${54}$Mn photopeak, reconstructed from the Compton scattering and recoil angle is shown.Comment: Latex, 19 pages, 20 figure

Model for eukaryotic tail-anchored protein binding based on the structure of Get3

The Get3 ATPase directs the delivery of tail-anchored (TA) proteins to the endoplasmic reticulum (ER). TA-proteins are characterized by having a single transmembrane helix (TM) at their extreme C terminus and include many essential proteins, such as SNAREs, apoptosis factors, and protein translocation components. These proteins cannot follow the SRP-dependent co-translational pathway that typifies most integral membrane proteins; instead, post-translationally, these proteins are recognized and bound by Get3 then delivered to the ER in the ATP dependent Get pathway. To elucidate a molecular mechanism for TA protein binding by Get3 we have determined three crystal structures in apo and ADP forms from Saccharomyces cerevisae (ScGet3-apo) and Aspergillus fumigatus (AfGet3-apo and AfGet3-ADP). Using structural information, we generated mutants to confirm important interfaces and essential residues. These results point to a model of how Get3 couples ATP hydrolysis to the binding and release of TA-proteins

Consideration of the bioavailability of metal/metalloid species in freshwaters: experiences regarding the implementation of biotic ligand model-based approaches in risk assessment frameworks

After the scientific development of Biotic Ligand Models (BLMs) in recent decades these models are now considered suitable for implementation in regulatory risk assessment of metals in freshwater bodies. The approach has been developed over several years and has been described in many peer-reviewed publications. The original complex BLMs have been applied in prospective risk assessment reports for metals and metal compounds and are also recommended as suitable concepts for the evaluation of monitoring data in the context of the European Water Framework Directive. Currently, several user-friendly BLM-based bioavailability software tools are available for assessing the aquatic toxicity of a limited number of metals (mainly copper, nickel, and zinc). These tools need only a basic set of water parameters as input (e.g., pH, hardness, dissolved organic matter and dissolved metal concentration). Such tools seem appropriate to foster the implementation in routine water quality assessments. This work aims to review the existing bioavailability-based regulatory approaches and the application of available BLM-based bioavailability tools for this purpose. Advantages and possible drawbacks of these tools (e.g., feasibility, boundaries of validity) are discussed, and recommendations for further implementation are given

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool

STOFFENMANAGER® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER® and ART are based on a modified multiplicative model where an exposure base level (mg m−3) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m−3) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER® and ART. A literature review showed that the models have been validated only at the ‘operational analysis’ level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson’s correlations (r is <0.6) for both STOFFENMANAGER® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.Peer reviewe

Distinct alterations in probabilistic reversal learning across at-risk mental state, first episode psychosis and persistent schizophrenia

We used a probabilistic reversal learning task to examine prediction error-driven belief updating in three clinical groups with psychosis or psychosis-like symptoms. Study 1 compared people with at-risk mental state and first episode psychosis (FEP) to matched controls. Study 2 compared people diagnosed with treatment-resistant schizophrenia (TRS) to matched controls. The design replicated our previous work showing ketamine-related perturbations in how meta-level confidence maintained behavioural policy. We applied the same computational modelling analysis here, in order to compare the pharmacological model to three groups at different stages of psychosis. Accuracy was reduced in FEP, reflecting increased tendencies to shift strategy following probabilistic errors. The TRS group also showed a greater tendency to shift choice strategies though accuracy levels were not significantly reduced. Applying the previously-used computational modelling approach, we observed that only the TRS group showed altered confidence-based modulation of responding, previously observed under ketamine administration. Overall, our behavioural findings demonstrated resemblance between clinical groups (FEP and TRS) and ketamine in terms of a reduction in stabilisation of responding in a noisy environment. The computational analysis suggested that TRS, but not FEP, replicates ketamine effects but we consider the computational findings preliminary given limitations in performance of the model

Repositioning the Catalytic Triad Aspartic Acid of Haloalkane Dehalogenase: Effects on Stability, Kinetics, and Structure

Haloalkane dehalogenase (DhlA) catalyzes the hydrolysis of haloalkanes via an alkyl-enzyme intermediate. The covalent intermediate, which is formed by nucleophilic substitution with Asp124, is hydrolyzed by a water molecule that is activated by His289. The role of Asp260, which is the third member of the catalytic triad, was studied by site-directed mutagenesis. Mutation of Asp260 to asparagine resulted in a catalytically inactive D260N mutant, which demonstrates that the triad acid Asp260 is essential for dehalogenase activity. Furthermore, Asp260 has an important structural role, since the D260N enzyme accumulated mainly in inclusion bodies during expression, and neither substrate nor product could bind in the active-site cavity. Activity for brominated substrates was restored to D260N by replacing Asn148 with an aspartic or glutamic acid. Both double mutants D260N+N148D and D260N+N148E had a 10-fold reduced kcat and 40-fold higher Km values for 1,2-dibromoethane compared to the wild-type enzyme. Pre-steady-state kinetic analysis of the D260N+N148E double mutant showed that the decrease in kcat was mainly caused by a 220-fold reduction of the rate of carbon-bromine bond cleavage and a 10-fold decrease in the rate of hydrolysis of the alkyl-enzyme intermediate. On the other hand, bromide was released 12-fold faster and via a different pathway than in the wild-type enzyme. Molecular modeling of the mutant showed that Glu148 indeed could take over the interaction with His289 and that there was a change in charge distribution in the tunnel region that connects the active site with the solvent. On the basis of primary structure similarity between DhlA and other α/β-hydrolase fold dehalogenases, we propose that a conserved acidic residue at the equivalent position of Asn148 in DhlA is the third catalytic triad residue in the latter enzymes.

The coordination of cell growth during fission yeast mating requires Ras1-GTP hydrolysis

The spatial and temporal control of polarity is fundamental to the survival of all organisms. Cells define their polarity using highly conserved mechanisms that frequently rely upon the action of small GTPases, such as Ras and Cdc42. Schizosaccharomyces pombe is an ideal system with which to study the control of cell polarity since it grows from defined tips using Cdc42-mediated actin remodeling. Here we have investigated the importance of Ras1-GTPase activity for the coordination of polarized cell growth during fission yeast mating. Following pheromone stimulation, Ras1 regulates both a MAPK cascade and the activity of Cdc42 to enable uni-directional cell growth towards a potential mating partner. Like all GTPases, when bound to GTP, Ras1 adopts an active conformation returning to an inactive state upon GTP-hydrolysis, a process accelerated through interaction with negative regulators such as GAPs. Here we show that, at low levels of pheromone stimulation, loss of negative regulation of Ras1 increases signal transduction via the MAPK cascade. However, at the higher concentrations observed during mating, hyperactive Ras1 mutations promote cell death. We demonstrate that these cells die due to their failure to coordinate active Cdc42 into a single growth zone resulting in disorganized actin deposition and unsustainable elongation from multiple tips. These results provide a striking demonstration that the deactivation stage of Ras signaling is fundamentally important in modulating cell polarity

GTP-dependent structural rearrangement of the eRF1:eRF3 complex and eRF3 sequence motifs essential for PABP binding

Translation termination in eukaryotes is governed by the concerted action of eRF1 and eRF3 factors. eRF1 recognizes the stop codon in the A site of the ribosome and promotes nascent peptide chain release, and the GTPase eRF3 facilitates this peptide release via its interaction with eRF1. In addition to its role in termination, eRF3 is involved in normal and nonsense-mediated mRNA decay through its association with cytoplasmic poly(A)-binding protein (PABP) via PAM2-1 and PAM2-2 motifs in the N-terminal domain of eRF3. We have studied complex formation between full-length eRF3 and its ligands (GDP, GTP, eRF1 and PABP) using isothermal titration calorimetry, demonstrating formation of the eRF1:eRF3:PABP:GTP complex. Analysis of the temperature dependence of eRF3 interactions with G nucleotides reveals major structural rearrangements accompanying formation of the eRF1:eRF3:GTP complex. This is in contrast to eRF1:eRF3:GDP complex formation, where no such rearrangements were detected. Thus, our results agree with the established active role of GTP in promoting translation termination. Through point mutagenesis of PAM2-1 and PAM2-2 motifs in eRF3, we demonstrate that PAM2-2, but not PAM2-1 is indispensible for eRF3:PABP complex formation

X-ray Structures of the Signal Recognition Particle Receptor Reveal Targeting Cycle Intermediates

The signal recognition particle (SRP) and its conjugate receptor (SR) mediate cotranslational targeting of a subclass of proteins destined for secretion to the endoplasmic reticulum membrane in eukaryotes or to the plasma membrane in prokaryotes. Conserved active site residues in the GTPase domains of both SRP and SR mediate discrete conformational changes during formation and dissociation of the SRP·SR complex. Here, we describe structures of the prokaryotic SR, FtsY, as an apo protein and in two different complexes with a non-hydrolysable GTP analog (GMPPNP). These structures reveal intermediate conformations of FtsY containing GMPPNP and explain how the conserved active site residues position the nucleotide into a non-catalytic conformation. The basis for the lower specificity of binding of nucleotide in FtsY prior to heterodimerization with the SRP conjugate Ffh is also shown. We propose that these structural changes represent discrete conformational states assumed by FtsY during targeting complex formation and dissociation

G Protein Activation without a GEF in the Plant Kingdom

Animal heterotrimeric G proteins are activated by guanine nucleotide exchange factors (GEF), typically seven transmembrane receptors that trigger GDP release and subsequent GTP binding. In contrast, the Arabidopsis thaliana G protein (AtGPA1) rapidly activates itself without a GEF and is instead regulated by a seven transmembrane Regulator of G protein Signaling (7TM-RGS) protein that promotes GTP hydrolysis to reset the inactive (GDP-bound) state. It is not known if this unusual activation is a major and constraining part of the evolutionary history of G signaling in eukaryotes. In particular, it is not known if this is an ancestral form or if this mechanism is maintained, and therefore constrained, within the plant kingdom. To determine if this mode of signal regulation is conserved throughout the plant kingdom, we analyzed available plant genomes for G protein signaling components, and we purified individually the plant components encoded in an informative set of plant genomes in order to determine their activation properties in vitro. While the subunits of the heterotrimeric G protein complex are encoded in vascular plant genomes, the 7TM-RGS genes were lost in all investigated grasses. Despite the absence of a Gα-inactivating protein in grasses, all vascular plant Gα proteins examined rapidly released GDP without a receptor and slowly hydrolyzed GTP, indicating that these Gα are self-activating. We showed further that a single amino acid substitution found naturally in grass Gα proteins reduced the Gα-RGS interaction, and this amino acid substitution occurred before the loss of the RGS gene in the grass lineage. Like grasses, non-vascular plants also appear to lack RGS proteins. However, unlike grasses, one representative non-vascular plant Gα showed rapid GTP hydrolysis, likely compensating for the loss of the RGS gene. Our findings, the loss of a regulatory gene and the retention of the “self-activating” trait, indicate the existence of divergent Gα regulatory mechanisms in the plant kingdom. In the grasses, purifying selection on the regulatory gene was lost after the physical decoupling of the RGS protein and its cognate Gα partner. More broadly these findings show extreme divergence in Gα activation and regulation that played a critical role in the evolution of G protein signaling pathways