High-speed 4-dimensional scanning transmission electron microscopy using compressive sensing techniques.

Here we show that compressive sensing allows 4-dimensional (4-D) STEM data to be obtained and accurately reconstructed with both high-speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4-D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal-to-noise ratio in the recovered phase using 0.3% of the total data. Lay abstract: Four-dimensional scanning transmission electron microscopy (4-D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2-dimensional signal is acquired at each 2-D probe location, equating to a 4-D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4-D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100-1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4-D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10-100 times. The acquired data is then processed to fill-in or inpaint the missing data, taking advantage of the inherently low-complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4-D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4-D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100-300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

The Potential of Subsampling and Inpainting for Fast Low-Dose Cryo FIB-SEM Imaging.

Traditional image acquisition for cryo focused ion-beam scanning electron microscopy (FIB-SEM) tomography often sees thousands of images being captured over a period of many hours, with immense data sets being produced. When imaging beam sensitive materials, these images are often compromised by additional constraints related to beam damage and the devitrification of the material during imaging, which renders data acquisition both costly and unreliable. Subsampling and inpainting are proposed as solutions for both of these aspects, allowing fast and low-dose imaging to take place in the Focused ion-beam scanning electron microscopy FIB-SEM without an appreciable loss in image quality. In this work, experimental data are presented which validate subsampling and inpainting as a useful tool for convenient and reliable data acquisition in a FIB-SEM, with new methods of handling three-dimensional data being employed in the context of dictionary learning and inpainting algorithms using a newly developed microscope control software and data recovery algorithm.

Model-based and model-free mechanisms in methamphetamine use disorder.

People with methamphetamine use disorder (MUD) struggle to shift their behaviour from methamphetamine-orientated habits to goal-oriented choices. The model-based/model-free framework is well suited to understand this difficulty by unpacking the computational mechanisms that support experienced-based (model-free) and goal-directed (model-based) choices. We aimed to examine whether 1) participants with MUD differed from controls on behavioural proxies and/or computational mechanisms of model-based/model-free choices; 2) model-based/model-free decision-making correlated with MUD symptoms; and 3) model-based/model-free deficits improved over six weeks in the group with MUD. Participants with MUD and controls with similar age, IQ and socioeconomic status completed the Two-Step Task at treatment commencement (MUD n = 30, Controls n = 31) and six weeks later (MUD n = 23, Controls n = 26). We examined behavioural proxies of model-based/model-free decisions using mixed logistic regression, and their underlying mechanisms using computational modelling. At a behavioural level, participants with MUD were more likely to switch their choices following rewarded actions, although this pattern improved at follow up. At a computational level, groups were similar in their use of model-based mechanisms, but participants with MUD were less likely to apply model-free mechanisms and less likely to repeat rewarded actions. We did not find evidence that individual differences in model-based or model-free parameters were associated with greater severity of methamphetamine dependence, nor did we find that group differences in computational parameters changed between baseline and follow-up assessment. Decision-making challenges in people with MUD are likely related to difficulties in pursuing choices previously associated with positive outcomes.

Disability-Related Costs of Children with Disabilities in the Philippines.

The assessment of disability-related costs among children remains a largely under-researched subject with related questions rarely included in surveys. This paper addresses this issue through a unique mixed methods study conducted in the Philippines combining a nationally representative survey and in-depth interviews with families and health professionals. To quantify the extra costs associated with disabilities, the research used the standard of living approach, whereby expenditure levels of families with children with and without disabilities were compared in relation to different measures of living standards. The results find consistent evidence of high extra costs among households that have children with disabilities and point to health expenses as the leading source. Using an asset index as the indicator of living standards, a child with a disability is estimated to require between 40% and 80% extra expenditure to reach the same living standard of other children. However, the size of extra costs is substantially higher when the measure of the standard of living relies on a broader set of deprivations. In such cases, higher estimates of extra costs are likely to be the result of the lack of an inclusive environment. Critically, this points to the need to provide not only financial support but also inclusive services, especially in health and education.

Proof-of-concept trial of Goal Management Training+ to improve executive functions and treatment outcomes in methamphetamine use disorder.

BACKGROUND: Deficits in executive function are common in methamphetamine use disorder (MUD), likely contributing to difficulties in sustained treatment success. Cognitive remediation interventions are designed to treat such deficits but have not been adapted to the needs of people with MUD. This study presents a proof-of-concept trial to evaluate a new cognitive remediation program for MUD, Goal Management Training+ (GMT+). METHODS: This was a cluster-randomised crossover trial comparing GMT+ with a psychoeducation-based control (Brain Health Workshop; BHW). GMT+ is a therapist-administered group-based cognitive remediation for executive dysfunction comprising four 90-minute weekly sessions and daily journal activities. BHW is a lifestyle psychoeducation program matched to GMT+ for therapist involvement, format, and duration. Participants (n = 36; GMT n = 17; BHW n = 19) were recruited from therapeutic communities in Victoria, Australia. Primary outcomes included intervention acceptability, feasibility, and improvements in self-reported executive function. Secondary outcomes included cognitive tests of executive function, severity of methamphetamine dependence, craving, and quality of life. We performed mixed linear modelling and calculated Hedges' g effect sizes. RESULTS: GMT+ participant ratings and program retention indicated high acceptability. There was no difference between GMT+ and BHW on self-reported executive function (g = 0.06). Cognitive tasks suggested benefits of GMT+ on information gathering (g = 0.88) and delay-discounting (g = 0.80). Severity of methamphetamine dependence decreased more in GMT+ (g = 1.47). CONCLUSIONS: GMT+ was well-accepted but did not improve self-reported executive functioning. Secondary outcomes suggested GMT+ was beneficial for objective cognitive performance and severity of dependence.

Towards real-time STEM simulations through targeted subsampling strategies.

Scanning transmission electron microscopy images can be complex to interpret on the atomic scale as the contrast is sensitive to multiple factors such as sample thickness, composition, defects and aberrations. Simulations are commonly used to validate or interpret real experimental images, but they come at a cost of either long computation times or specialist hardware such as graphics processing units. Recent works in compressive sensing for experimental STEM images have shown that it is possible to significantly reduce the amount of acquired signal and still recover the full image without significant loss of image quality, and therefore it is proposed here that similar methods can be applied to STEM simulations. In this paper, we demonstrate a method that can significantly increase the efficiency of STEM simulations through a targeted sampling strategy, along with a new approach to independently subsample each frozen phonon layer. We show the effectiveness of this method by simulating a SrTiO3 grain boundary and monolayer 2H-MoS2 containing a sulphur vacancy using the abTEM software. We also show how this method is not limited to only traditional multislice methods, but also increases the speed of the PRISM simulation method. Furthermore, we discuss the possibility for STEM simulations to seed the acquisition of real data, to potentially lead the way to self-driving (correcting) STEM.

Computational mechanisms underpinning greater exploratory behaviour in excess weight relative to healthy weight adolescents.

Obesity in adolescence is associated with cognitive changes that lead to difficulties in shifting unhealthy habits in favour of alternative healthy behaviours, similar to addictive behaviours. An outstanding question is whether this shift in goal-directed behaviour is driven by over-exploitation or over-exploration of rewarding outcomes. Here, we addressed this question by comparing explore/exploit behaviour on the Iowa Gambling Task in 43 adolescents with excess weight against 38 adolescents with healthy weight. We computationally modelled both exploitation behaviour (e.g., reinforcement sensitivity and inverse decay parameters), and explorative behaviour (e.g., maximum directed exploration value). We found that overall, adolescents with excess weight displayed more behavioural exploration than their healthy-weight counterparts - specifically, demonstrating greater overall switching behaviour. Computational models revealed that this behaviour was driven by a higher maximum directed exploration value in the excess-weight group (U = 520.00, p = .005, BF10 = 5.11). Importantly, however, we found substantial evidence that groups did not differ in reinforcement sensitivity (U = 867.00, p = .641, BF10 = 0.30). Overall, our study demonstrates a preference for exploratory behaviour in adolescents with excess weight, independent of sensitivity to reward. This pattern could potentially underpin an intrinsic desire to explore energy-dense unhealthy foods - an as-yet untapped mechanism that could be targeted in future treatments of obesity in adolescents.

A Novel Lepidoptera bioassay analysed using a reduced GUTS model.

Lepidopteran species can be both pests and also beneficial pollinators for agricultural crops. However, despite these important roles, the effects of pesticides on this diverse taxa are relatively understudied. To facilitate the assessment of pesticides and other chemical hazards on this taxa, we present a novel bioassay capable of testing chemical sensitivity to lepidopteran larvae through dietary exposure. We used Mamestra brassicae caterpillars as a model lepidopteran and tested their sensitivity for the organophosphate insecticide chlorpyrifos. We exposed larvae to an artificial diet spiked with chlorpyrifos and monitored survival over time, as well as weight change over a 96-hour exposure period. To test the repeatability and reliability of the developed bioassay, the experiment was repeated three times. The survival in time data collected enabled analysis with the General Unified Threshold of Survival (GUTS) model, recently recognized by EFSA as a ready-to-use tool for regulatory purposes. The GUTS modelling was used to derive a set of relevant toxicokinetic and toxicodynamic parameters relating to the larval response to exposure over time. We found that across the three repeats studies there was no more than a threefold difference in LC50 values (13.1, 18.7 and 8.1 mg/Kg) at 48 h and fourfold difference at 96 h, highlighting the repeatability of the bioassay. We also highlighted the potential of the method to observe sub-lethal effects such as changes in weight. Finally, we discuss the applications of this new bioassay method to chemical risk assessments and its potential for use in other scenarios, such as mixture or pulsed exposure testing.

Modelling the effects of the pyrethroid insecticide cypermethrin on the life cycle of the soil dwelling annelid Enchytraeus crypticus, an original experimental design to calibrate a DEB-TKTD model.

The Dynamic Energy Budget theory (DEB) enables ecotoxicologists to model the effects of chemical stressors on organism life cycles through the coupling of toxicokinetic-toxicodynamic (TK-TD) models. While good progress has been made in the application of DEB-TKTD models for aquatic organisms, applications for soil fauna are scarce, due to the lack of dedicated experimental designs suitable for collecting the required time series effect data. Enchytraeids (Annelida: Clitellata) are model organisms in soil ecology and ecotoxicology. They are recognised as indicators of biological activity in soil, and chemical stress in terrestrial ecosystems. Despite this, the application of DEB-TKTD models to investigate the impact of chemicals has not yet been tested on this family. Here we assessed the impact of the pyrethroid insecticide cypermethrin on the life cycle of Enchytraeus crypticus. We developed an original experimental design to collect the data required for the calibration of a DEB-TKTD model for this species. E. crypticus presented a slow initial growth phase that has been successfully simulated with the addition of a size-dependent food limitation for juveniles in the DEB model. The DEB-TKTD model simulations successfully agreed with the data for all endpoints and treatments over time. The highlighted physiological mode of action (pMoA) for cypermethrin was an increase of the growth energy cost. The threshold for effects on survival was estimated at 73.14 mg kg- 1, and the threshold for effects on energy budget (i.e., sublethal effects) at 19.21 mg kg- 1. This study demonstrates that DEB-TKTD models can be successfully applied to E. crypticus as a representative soil species, and may improve the ecological risk assessment for terrestrial ecosystems, and our mechanistic understanding of chemical effects on non-target species.

The genome sequence of the red compost earthworm, Lumbricus rubellus (Hoffmeister, 1843).

We present a genome assembly from an individual Lumbricus rubellus (the red compost earthworm; Annelida; Clitellata; Haplotaxida; Lumbricidae). The genome sequence is 787.5 megabases in span. Most of the assembly is scaffolded into 18 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 15.81 kilobases in length. Gene annotation of this assembly on Ensembl identified 33,426 protein coding genes.

SIM-STEM Lab: Incorporating Compressed Sensing Theory for Fast STEM Simulation.

Recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future.

Protocol for a cluster randomised crossover pilot trial of Goal Management Training+ (GMT+) for methamphetamine use disorder.

Background: Methamphetamine use disorder (MUD) is associated with executive dysfunctions, which are linked with poorer treatment outcomes. However, current treatments for MUD do not directly address cognition. We recently modified Goal Management Training (now Goal Management Training+; GMT+), a group-based intervention originally designed to improve executive functions after brain injury, to enhance suitability for MUD. Here, we describe the rationale and design of a trial which aims to determine the acceptability and feasibility of GMT+ during residential rehabilitation for MUD, and its impact on executive functions and clinical outcomes. Methods: We used a cluster randomised crossover design: participants are randomised at the cluster level to receive either GMT+ or psychoeducation-control (Brain Health Workshop; BHW). GMT+ is delivered in four 90-min weekly sessions and includes a between-session journal with 10-min daily activities. The program targets attention, impulse control, goal-setting, and decision-making. BHW is a health-oriented intervention that delivers information about the brain and promotes healthy exercise, diet, and sleep. It is matched to GMT+ on program format, length, and time with therapists. We will recruit forty-eight participants with MUD from residential treatment services. Our primary outcomes are acceptability, feasibility, and self-reported executive functioning. Secondary outcomes include craving, quality of life and cognitive performance. Outcome assessments are performed at baseline, post-interventions, 4-week follow-up, and 12-week follow-up. Conclusions: This study will provide GMT+ feasibility and acceptability data and will indicate initial efficacy on executive functions and clinical outcomes in residential treatment for MUD. Information from this pilot trial will inform a powered RCT.

How to analyse and account for interactions in mixture toxicity with toxicokinetic-toxicodynamic models.

The assessment of chemical mixture toxicity is one of the major challenges in ecotoxicology. Chemicals can interact, leading to more or less effects than expected, commonly named synergism and antagonism respectively. The classic ad hoc approach for the assessment of mixture effects is based on dose-response curves at a single time point, and is limited to identifying a mixture interaction but cannot provide predictions for untested exposure durations, nor for scenarios where exposure varies in time. We here propose a new approach using toxicokinetic-toxicodynamic modelling: The General Unified Threshold model of Survival (GUTS) framework, recently extended for mixture toxicity assessment. We designed a dedicated mechanistic interaction module coupled with the GUTS mixture model to i) identify interactions, ii) test hypotheses to identify which chemical is likely responsible for the interaction, and finally iii) simulate and predict the effect of synergistic and antagonistic mixtures. We tested the modelling approach experimentally with two species (Enchytraeus crypticus and Mamestra brassicae) exposed to different potentially synergistic mixtures (composed of: prochloraz, imidacloprid, cypermethrin, azoxystrobin, chlorothalonil, and chlorpyrifos). Furthermore, we also tested the model with previously published experimental data on two other species (Bombus terrestris and Daphnia magna) exposed to pesticide mixtures (clothianidin, propiconazole, dimethoate, imidacloprid and thiacloprid) found to be synergistic or antagonistic with the classic approach. The results showed an accurate simulation of synergistic and antagonistic effects for the different tested species and mixtures. This modelling approach can identify interactions accounting for the entire time of exposure, and not only at one time point as in the classic approach, and provides predictions of the mixture effect for untested mixture exposure scenarios, including those with time-variable mixture composition.

Development of Goal Management Training+ for Methamphetamine Use Disorder Through Collaborative Design.

Background: Methamphetamine use disorder (MUD) is associated with executive dysfunctions, which are linked with poorer treatment outcomes including earlier drop out and relapse. However, current treatments for MUD do not address executive functions. Goal Management Training (GMT) is an evidence-based cognitive remediation program for executive dysfunction, although required modifications to enhance its relevance and application within addiction treatment settings. This study aimed to (1) tailor GMT to the key cognitive deficits and typical treatment duration of MUD; (2) explore consumers' (people with MUD) engagement with the revised program; (3) implement a prototype of the program with consumers; and (4) present the manualized standard administration to clinical service providers. Methods: We followed the Medical Research Council Complex Interventions Framework and employed an evidence- and person-based intervention development process. We used a four-phased approach and collaborated with neuropsychology experts, design researchers in healthcare, consumers with MUD, and clinical service providers. Each aim was addressed in a separate study phase; including content refinement and review with neuropsychology experts (phase 1), intervention design and collaboration with consumers (phase 2), prototype development and review with consumers (phase 3), and final program modifications and review with clinical stakeholders (phase 4). Results: Findings from phase 1 indicated support for targeting four cognitive processes (attention, impulse control, goal setting, and decision-making). Key feedback included the need to help habitualize cognitive strategies and to guide consumers in applying these strategies in emotionally salient situations. Findings from phases 2 and 3 indicated consumer support for the program strategies and materials but highlighted the need to further enhance the personal relevance of specific content and journal activities. Findings from phase 4 provided clinicians support for the revised program but indicated an opportunity to minimize unintended effects. We present the intervention materials for the final revised program, Goal Management Training+ (GMT+), in line with TIDieR guidelines. Conclusions: GMT+ targets key cognitive processes and is sensitive to the clinical needs of people with MUD. Our intervention development process was important for informing the active ingredients and materials for GMT+, and indicated initial consumer and provider acceptability prior to conducting a clinical trial.

Computational models of exploration and exploitation characterise onset and efficacy of treatment in methamphetamine use disorder.

People with Methamphetamine Use Disorder (PwMUD) spend substantial time and resources on substance use, which hinders their ability to explore alternate reinforcers. Gold-standard behavioural treatments attempt to remedy this by encouraging action towards non-drug reinforcers, but substance use often persists. We aimed to unravel the mechanistic drivers of this behaviour by applying a computational model of explore/exploit behaviour to decision-making data (Iowa Gambling Task) from 106 PwMUD and 48 controls. We then examined the longitudinal link between explore/exploit mechanisms and changes in methamphetamine use 6 weeks later. Exploitation parameters included reinforcement sensitivity and inverse decay (i.e., number of past outcomes used to guide choices). Exploration parameters included maximum directed exploration value (i.e., value of trying novel actions). The Timeline Follow Back measured changes in methamphetamine use. Compared to controls, PwMUD showed deficits in exploitative decision-making, characterised by reduced reinforcement sensitivity, U = 3065, p = 0.009, and less use of previous choice outcomes, U = 3062, p = 0.010. This was accompanied by a behavioural pattern of frequent shifting between choices, which appeared consistent with random exploration. Furthermore, PwMUD with greater reductions of methamphetamine use at 6 weeks had increased directed exploration (ß = 0.22, p = 0.045); greater use of past choice outcomes (ß = -0.39, p = 0.002) and greater choice consistency (ß = -0.39, p = 0.002). Therefore, limited computational exploitation and increased behavioural exploration characterise PwMUD's presentation to treatment, while increased directed exploration, use of past choice outcomes and choice consistency predict greater reductions of methamphetamine use.

A Fullerene-Platinum Complex for Direct Functional Patterning of Single Metal Atom-Embedded Carbon Nanostructures.

The development of patterning materials ("resists") at the nanoscale involves two distinct trends: one is toward high sensitivity and resolution for miniaturization, the other aims at functionalization of the resists to realize bottom-up construction of distinct nanoarchitectures. Patterning of carbon nanostructures, a seemingly ideal application for organic functional resists, has been highly reliant on complicated pattern transfer processes because of a lack of patternable precursors. Herein, we present a fullerene-metal coordination complex as a fabrication material for direct functional patterning of sub-10 nm metal-containing carbon structures. The attachment of one platinum atom per fullerene molecule not only leads to significant improvement of sensitivity and resolution but also enables stable atomic dispersion of the platinum ions within the carbon matrix, which may gain fundamentally new interest in functional patterning of hierarchical carbon nanostructures.

MiR-423-5p prevents MALAT1-mediated proliferation and metastasis in prostate cancer.

BACKGROUND: The long non-coding RNA (lncRNA), MALAT1, plays a key role in the development of different cancers, and its expression is associated with worse prognosis in patients. However, its mechanism of action and its regulation are not well known in prostate cancer (PCa). A general mechanism of action of lncRNAs is their interaction with other epigenetic regulators including microRNAs (miRNAs). METHODS: Using lentiviral stable miRNA transfection together with cell biology functional assays and gene expression/target analysis, we investigated the interaction between MALAT1 and miR-423-5p, defined as a target with in silico prediction analysis, in PCa. RESULTS: Through bioinformatic analysis of data available from TCGA, we have found that MALAT1 expression correlates with high Gleason grade, metastasis occurrence, and reduced survival in PCa patients. These findings were validated on a TMA of PCa showing a significant correlation between MALAT1 expression with both stage and grading. We report that, in PCa cells, MALAT1 expression and activity is regulated by miR-423-5p that binds MALAT1, downregulates its expression and inhibits its activity in promoting proliferation, migration, and invasion. Using NanoString analysis, we unraveled downstream cell pathways that were affected by miR-423-5p expression and MALAT1 downregulation and identified several alterations in genes that are involved in metastatic response and angiogenic pathways. In addition, we showed that the overexpression of miR-423-5p increases survival and decreases metastases formation in a xenograft mouse model. CONCLUSIONS: We provide evidence on the role of MALAT1 in PCa tumorigenesis and progression. Also, we identify a direct interaction between miR-423-5p and MALAT1, which results in the suppression of MALAT1 action in PCa.