Mapping deuterated methanol toward L1544: I. Deuterium fraction and comparison with modeling

The study of deuteration in pre-stellar cores is important to understand the physical and chemical initial conditions in the process of star formation. In particular, observations toward pre-stellar cores of methanol and deuterated methanol, solely formed on the surface of dust grains, may provide useful insights on surface processes at low temperatures. Here we analyze maps of CO, methanol, formaldehyde and their deuterated isotopologues toward a well-known pre-stellar core. This study allows us to test current gas-dust chemical models. Single-dish observations of CH$_3$OH, CH$_2$DOH, H$_2$CO, H_2\,^{13}CO, HDCO, D$_2$CO and C$^{17}$O toward the prototypical pre-stellar core L1544 were performed at the IRAM 30 m telescope. We analyze their column densities, distributions, and compare these observations with gas-grain chemical models. The maximum deuterium fraction derived for methanol is [CH$_2$DOH]/[CH$_3$OH] $\sim$ 0.08$\pm$0.02, while the measured deuterium fractions of formaldehyde at the dust peak are [HDCO]/[H$_2$CO] $\sim$ 0.03$\pm$0.02, [D$_2$CO]/[H$_2$CO] $\sim$ 0.04$\pm$0.03 and [D$_2$CO]/[HDCO] $\sim$ 1.2$\pm$0.3. Observations differ significantly from the predictions of models, finding discrepancies between a factor of 10 and a factor of 100 in most cases. It is clear though that to efficiently produce methanol on the surface of dust grains, quantum tunneling diffusion of H atoms must be switched on. It also appears that the currently adopted reactive desorption efficiency of methanol is overestimated and/or that abstraction reactions play an important role. More laboratory work is needed to shed light on the chemistry of methanol, an important precursor of complex organic molecules in space.Comment: Accepted for publication in A&

NH_3(1_0-0_0) in the pre-stellar core L1544

Pre-stellar cores represent the initial conditions in the process of star and planet formation, therefore it is important to study their physical and chemical structure. Because of their volatility, nitrogen-bearing molecules are key to study the dense and cold gas present in pre-stellar cores. The NH_3 rotational transition detected with Herschel-HIFI provides a unique combination of sensitivity and spectral resolution to further investigate physical and chemical processes in pre-stellar cores. Here we present the velocity-resolved Herschel-HIFI observations of the ortho-NH_3(1_0-0_0) line at 572 GHz and study the abundance profile of ammonia across the pre-stellar core L1544 to test current theories of its physical and chemical structure. Recently calculated collisional coefficients have been included in our non-LTE radiative transfer code to reproduce Herschel observations. A gas-grain chemical model, including spin-state chemistry and applied to the (static) physical structure of L1544 is also used to infer the abundance profile of ortho-NH_3 . The hyperfine structure of ortho-NH_3(1_0-0_0) is resolved for the first time in space. All the hyperfine components are strongly self-absorbed. The profile can be reproduced if the core is contracting in quasi-equilibrium, consistent with previous work, and if the NH_3 abundance is slightly rising toward the core centre, as deduced from previous interferometric observations of para-NH_3(1,1). The chemical model overestimates the NH_3 abundance at radii between ~ 4000 and 15000 AU by about two orders of magnitude and underestimates the abundance toward the core centre by more than one order of magnitude. Our observations show that chemical models applied to static clouds have problems in reproducing NH_3 observations.Comment: accepted for publication in A&A Letter

The charging of neutral dimethylamine and dimethylamine-sulfuric acid clusters using protonated acetone

Sulfuric acid is generally considered one of the most important substances taking part in atmospheric particle formation. However, in typical atmospheric conditions in the lower troposphere, sulfuric acid and water alone are unable to form particles. It has been suggested that strong bases may stabilize sulfuric acid clusters so that particle formation may occur. More to the point, amines - strong organic bases - have become the subject of interest as possible cause for such stabilization. To probe whether amines play a role in atmospheric nucleation, we need to be able to measure accurately the gas-phase amine vapour concentration. Such measurements often include charging the neutral molecules and molecular clusters in the sample. Since amines are bases, the charging process should introduce a positive charge. This can be achieved by, for example, using chemical ionization with a positively charged reagent with a suitable proton affinity. In our study, we have used quantum chemical methods combined with a cluster dynamics code to study the use of acetone as a reagent ion in chemical ionization and compared the results with measurements performed with a chemical ionization atmospheric pressure interface time-of-flight mass spectrometer (CI-APi-TOF). The computational results indicate that protonated acetone is an effective reagent in chemical ionization. However, in the experiments the reagent ions were not depleted at the predicted dimethylamine concentrations, indicating that either the modelling scheme or the experimental results - or both - contain unidentified sources of error.Peer reviewe

Randomized controlled trials in de-implementation research : a systematic scoping review

Background: Healthcare costs are rising, and a substantial proportion of medical care is of little value. De-implementation of low-value practices is important for improving overall health outcomes and reducing costs. We aimed to identify and synthesize randomized controlled trials (RCTs) on de-implementation interventions and to provide guidance to improve future research. Methods: MEDLINE and Scopus up to May 24, 2021, for individual and cluster RCTs comparing de-implementation interventions to usual care, another intervention, or placebo. We applied independent duplicate assessment of eligibility, study characteristics, outcomes, intervention categories, implementation theories, and risk of bias. Results: Of the 227 eligible trials, 145 (64%) were cluster randomized trials (median 24 clusters; median follow-up time 305 days), and 82 (36%) were individually randomized trials (median follow-up time 274 days). Of the trials, 118 (52%) were published after 2010, 149 (66%) were conducted in a primary care setting, 163 (72%) aimed to reduce the use of drug treatment, 194 (85%) measured the total volume of care, and 64 (28%) low-value care use as outcomes. Of the trials, 48 (21%) described a theoretical basis for the intervention, and 40 (18%) had the study tailored by context-specific factors. Of the de-implementation interventions, 193 (85%) were targeted at physicians, 115 (51%) tested educational sessions, and 152 (67%) multicomponent interventions. Missing data led to high risk of bias in 137 (60%) trials, followed by baseline imbalances in 99 (44%), and deficiencies in allocation concealment in 56 (25%). Conclusions: De-implementation trials were mainly conducted in primary care and typically aimed to reduce low-value drug treatments. Limitations of current de-implementation research may have led to unreliable effect estimates and decreased clinical applicability of studied de-implementation strategies. We identified potential research gaps, including de-implementation in secondary and tertiary care settings, and interventions targeted at other than physicians. Future trials could be improved by favoring simpler intervention designs, better control of potential confounders, larger number of clusters in cluster trials, considering context-specific factors when planning the intervention (tailoring), and using a theoretical basis in intervention design. Registration: OSF Open Science Framework hk4b2.Peer reviewe

Randomized controlled trials in de-implementation research : a systematic scoping review

Background: Healthcare costs are rising, and a substantial proportion of medical care is of little value. De-implementation of low-value practices is important for improving overall health outcomes and reducing costs. We aimed to identify and synthesize randomized controlled trials (RCTs) on de-implementation interventions and to provide guidance to improve future research. Methods: MEDLINE and Scopus up to May 24, 2021, for individual and cluster RCTs comparing de-implementation interventions to usual care, another intervention, or placebo. We applied independent duplicate assessment of eligibility, study characteristics, outcomes, intervention categories, implementation theories, and risk of bias. Results: Of the 227 eligible trials, 145 (64%) were cluster randomized trials (median 24 clusters; median follow-up time 305 days), and 82 (36%) were individually randomized trials (median follow-up time 274 days). Of the trials, 118 (52%) were published after 2010, 149 (66%) were conducted in a primary care setting, 163 (72%) aimed to reduce the use of drug treatment, 194 (85%) measured the total volume of care, and 64 (28%) low-value care use as outcomes. Of the trials, 48 (21%) described a theoretical basis for the intervention, and 40 (18%) had the study tailored by context-specific factors. Of the de-implementation interventions, 193 (85%) were targeted at physicians, 115 (51%) tested educational sessions, and 152 (67%) multicomponent interventions. Missing data led to high risk of bias in 137 (60%) trials, followed by baseline imbalances in 99 (44%), and deficiencies in allocation concealment in 56 (25%). Conclusions: De-implementation trials were mainly conducted in primary care and typically aimed to reduce low-value drug treatments. Limitations of current de-implementation research may have led to unreliable effect estimates and decreased clinical applicability of studied de-implementation strategies. We identified potential research gaps, including de-implementation in secondary and tertiary care settings, and interventions targeted at other than physicians. Future trials could be improved by favoring simpler intervention designs, better control of potential confounders, larger number of clusters in cluster trials, considering context-specific factors when planning the intervention (tailoring), and using a theoretical basis in intervention design. Registration: OSF Open Science Framework hk4b2.Peer reviewe

Multiple formin proteins participate in glioblastoma migration

Background: The prognosis of glioblastoma remains poor, related to its diffuse spread within the brain. There is an ongoing search for molecular regulators of this particularly invasive behavior. One approach is to look for actin regulating proteins that might be targeted by future anti-cancer therapy. The formin family of proteins orchestrates rearrangement of the actin cytoskeleton in multiple cellular processes. Recently, the formin proteins mDia1 and mDia2 were shown to be expressed in glioblastoma in vitro, and their function could be modified by small molecule agonists. This finding implies that the formins could be future therapeutic targets in glioblastoma.Methods: In cell studies, we investigated the changes in expression of the 15 human formins in primary glioblastoma cells and commercially available glioblastoma cell lines during differentiation from spheroids to migrating cells using transcriptomic analysis and qRT-PCR. siRNA mediated knockdown of selected formins was performed to investigate whether their expression affects glioblastoma migration. Using immunohistochemistry, we studied the expression of two formins, FHOD1 and INF2, in tissue samples from 93 IDH-wildtype glioblastomas. Associated clinicopathological parameters and follow-up data were utilized to test whether formin expression correlates with survival or has prognostic value.Results: We found that multiple formins were upregulated during migration. Knockdown of individual formins mDia1, mDia2, FHOD1 and INF2 significantly reduced migration in most studied cell lines. Among the studied formins, knockdown of INF2 generated the greatest reduction in motility in vitro. Using immunohistochemistry, we demonstrated expression of formin proteins FHOD1 and INF2 in glioblastoma tissues. Importantly, we found that moderate/high expression of INF2 was associated with significantly impaired prognosis.Conclusions: Formins FHOD1 and INF2 participate in glioblastoma cell migration. Moderate/high expression of INF2 in glioblastoma tissue is associated with worse outcome. Taken together, our in vitro and tissue studies suggest a pivotal role for INF2 in glioblastoma. When specific inhibiting compounds become available, INF2 could be a target in the search for novel glioblastoma therapies.</div

A machine learning approach based on generative topographic mapping for disruption prevention and avoidance at JET

The need for predictive capabilities greater than 95% with very limited false alarms are demanding requirements for reliable disruption prediction systems in tokamaks such as JET or, in the near future, ITER. The prediction of an upcoming disruption must be provided sufficiently in advance in order to apply effective disruption avoidance or mitigation actions to prevent the machine from being damaged. In this paper, following the typical machine learning workflow, a generative topographic mapping (GTM) of the operational space of JET has been built using a set of disrupted and regularly terminated discharges. In order to build the predictive model, a suitable set of dimensionless, machine-independent, physics-based features have been synthesized, which make use of 1D plasma profile information, rather than simple zero-D time series. The use of such predicting features, together with the power of the GTM in fitting the model to the data, obtains, in an unsupervised way, a 2D map of the multi-dimensional parameter space of JET, where it is possible to identify a boundary separating the region free from disruption from the disruption region. In addition to helping in operational boundaries studies, the GTM map can also be used for disruption prediction exploiting the potential of the developed GTM toolbox to monitor the discharge dynamics. Following the trajectory of a discharge on the map throughout the different regions, an alarm is triggered depending on the disruption risk of these regions. The proposed approach to predict disruptions has been evaluated on a training and an independent test set and achieves very good performance with only one tardive detection and a limited number of false detections. The warning times are suitable for avoidance purposes and, more important, the detections are consistent with physical causes and mechanisms that destabilize the plasma leading to disruptions.Peer reviewe

RF sheath modeling of experimentally observed plasma surface interactions with the JET ITER-Like Antenna

Waves in the Ion Cyclotron Range of Frequencies (ICRF) enhance local Plasma-Surface Interactions (PSI) near the wave launchers and magnetically-connected objects via Radio-Frequency (RF) sheath rectification. ITER will use 20MW of ICRF power over long pulses, questioning the long-term impact of RF-enhanced localized erosion on the lifetime of its Beryllium (Be) wall. Recent dedicated ICRF-heated L-mode discharges documented this process on JET for different types of ICRF antennas. Using visible spectroscopy in JET ICRF-heated L-mode discharges, poloidally-localized regions of enhanced (by similar to 2-4x) Be I and Be II light emission were observed on two outboard limiters magnetically connected to the bottom of the active ITER-Like Antenna (ILA). The observed RF-PSI induced by the ILA was qualitatively comparable to that induced by the JET standard, type-A2 antennas, for similar strap toroidal phasing and connection geometries. The Be II line emission was found more intense when powering the bottom half of the ILA rather than its top half. Conversely, more pronounced SOL density modifications were observed with only top array operation, on field lines connected to the top half of the ILA. So far the near-field modeling of the ILA with antenna code TOPICA (Torino Polytechnic Ion Cyclotron Antenna), using curved antenna model, was partially able to reproduce qualitatively the observed phenomena. A quantitative discrepancy persisted between the observed Be source amplification and the calculated, corresponding increases in E-// field at the magnetically connected locations to the ILA when changing from only top to only bottom half antenna operation. This paper revisits these current drive phased and half-ILA powered cases using for the new simulations flat model of the ILA and more realistic antenna feeding to calculate the E-// field maps with TOPICA code. Further, the Self-consistent Sheaths and Waves for Ion Cyclotron Heating Slow Wave (SSWICH-SW) code, which couples slow wave evanescence with DC Scrape-Off Layer (SOL) biasing, is used to estimate the poloidal distribution of rectified RF-sheath Direct Current (DC) potential V-DC in the private SOL between the ILA poloidal limiters. The approach so far was limited to correlating the observed, enhanced emission regions at the remote limiters to the antenna near-electric fields, as calculated by TOPICA. The present approach includes also a model for the rectification of these near-fields in the private SOL of the ILA. With the improved approach, when comparing only top and only bottom half antenna feeding, we obtained good qualitative correlation between all experimental measurements and the calculated local variations in the E-// field and V-DC potential.Peer reviewe

Current Research into Applications of Tomography for Fusion Diagnostics

Retrieving spatial distribution of plasma emissivity from line integrated measurements on tokamaks presents a challenging task due to ill-posedness of the tomography problem and limited number of the lines of sight. Modern methods of plasma tomography therefore implement a-priori information as well as constraints, in particular some form of penalisation of complexity. In this contribution, the current tomography methods under development (Tikhonov regularisation, Bayesian methods and neural networks) are briefly explained taking into account their potential for integration into the fusion reactor diagnostics. In particular, current development of the Minimum Fisher Regularisation method is exemplified with respect to real-time reconstruction capability, combination with spectral unfolding and other prospective tasks.Peer reviewe