GaN atomic electric fields from a segmented STEM detector: Experiment and simulation.

Atomic electric fields in a thin GaN sample are measured with the centre-of-mass approach in 4D-scanning transmission electron microscopy (4D-STEM) using a 12-segmented STEM detector in a Spectra 300 microscope. The electric fields, charge density and potential are compared to simulations and an experimental measurement using a pixelated 4D-STEM detector. The segmented detector benefits from a high recording speed, which enables measurements at low radiation doses. However, there is measurement uncertainty due to the limited number of segments analysed in this study.

Detecting Prolonged Stress in Real Life Using Wearable Biosensors and Ecological Momentary Assessments: Naturalistic Experimental Study.

BACKGROUND: Increasing efforts toward the prevention of stress-related mental disorders have created a need for unobtrusive real-life monitoring of stress-related symptoms. Wearable devices have emerged as a possible solution to aid in this process, but their use in real-life stress detection has not been systematically investigated. OBJECTIVE: We aimed to determine the utility of ecological momentary assessments (EMA) and physiological arousal measured through wearable devices in detecting ecologically relevant stress states. METHODS: Using EMA combined with wearable biosensors for ecological physiological assessments (EPA), we investigated the impact of an ecological stressor (ie, a high-stakes examination week) on physiological arousal and affect compared to a control week without examinations in first-year medical and biomedical science students (51/83, 61.4% female). We first used generalized linear mixed-effects models with maximal fitting approaches to investigate the impact of examination periods on subjective stress exposure, mood, and physiological arousal. We then used machine learning models to investigate whether we could use EMA, wearable biosensors, or the combination of both to classify momentary data (ie, beeps) as belonging to examination or control weeks. We tested both individualized models using a leave-one-beep-out approach and group-based models using a leave-one-subject-out approach. RESULTS: During stressful high-stakes examination (versus control) weeks, participants reported increased negative affect and decreased positive affect. Intriguingly, physiological arousal decreased on average during the examination week. Time-resolved analyses revealed peaks in physiological arousal associated with both momentary self-reported stress exposure and self-reported positive affect. Mediation models revealed that the decreased physiological arousal in the examination week was mediated by lower positive affect during the same period. We then used machine learning to show that while individualized EMA outperformed EPA in its ability to classify beeps as originating from examinations or from control weeks (1603/4793, 33.45% and 1648/4565, 36.11% error rates, respectively), a combination of EMA and EPA yields optimal classification (1363/4565, 29.87% error rate). Finally, when comparing individualized models to group-based models, we found that the individualized models significantly outperformed the group-based models across all 3 inputs (EMA, EPA, and the combination). CONCLUSIONS: This study underscores the potential of wearable biosensors for stress-related mental health monitoring. However, it emphasizes the necessity of psychological context in interpreting physiological arousal captured by these devices, as arousal can be related to both positive and negative contexts. Moreover, our findings support a personalized approach in which momentary stress is optimally detected when referenced against an individual's own data.

A deletion containing a CTCF-element in intron 8 of the Bbs7 gene is partially responsible for juvenile obesity in the Berlin Fat Mouse.

The Berlin Fat Mouse Inbred (BFMI) line is a model for juvenile obesity. Previous studies on crosses between BFMI and C57Bl/6N (B6N) have identified a recessive defect causing juvenile obesity on chromosome 3 (jObes1). Bbs7 was identified as the most likely candidate gene for the observed effect. Comparative sequence analysis showed a 1578 bp deletion in intron 8 of Bbs7 in BFMI mice. A CTCF-element is located inside this deletion. To investigate the functional effect of this deletion, it was introduced into B6N mice using CRISPR/Cas9. Two mice containing the target deletion were obtained (B6N Bbs7emI8∆1 and Bbs7emI8∆2) and were subsequently mated to BFMI and B6N to generate two families suitable for complementation. Inherited alleles were determined and body composition was measured by quantitative magnetic resonance. Evidence for a partial complementation (13.1-15.1%) of the jObes1 allele by the CRISPR/Cas9 modified B6N Bbs7emI8∆1 and Bbs7emI8∆2 alleles was found. Mice carrying the complementation alleles had a 23-27% higher fat-to-lean ratio compared to animals which have a B6N allele (P(Bbs7emI8∆1) = 4.25 × 10-7; P(Bbs7emI8∆2) = 3.17 × 10-5). Consistent with previous findings, the recessive effect of the BFMI allele was also seen for the B6N Bbs7emI8∆1 and Bbs7emI8∆2 alleles. However, the effect size of the B6N Bbs7emI8∆1 and Bbs7emI8∆2 alleles was smaller than the BFMI allele, and thus showed only a partial complementation. Findings suggest additional variants near Bbs7 in addition to or interacting with the deletion in intron 8.

Identification of four novel QTL linked to the metabolic syndrome in the Berlin Fat Mouse.

BACKGROUND: The Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and the metabolic syndrome. This study aimed to identify genetic variants associated with impaired glucose metabolism using the obese lines BFMI861-S1 and BFMI861-S2, which are genetically closely related, but differ in several traits. BFMI861-S1 is insulin resistant and stores ectopic fat in the liver, whereas BFMI861-S2 is insulin sensitive. METHODS: In generation 10, 397 males of an advanced intercross line (AIL) BFMI861-S1 × BFMI861-S2 were challenged with a high-fat, high-carbohydrate diet and phenotyped over 25 weeks. QTL-analysis was performed after selective genotyping of 200 mice using the GigaMUGA Genotyping Array. Additional 197 males were genotyped for 7 top SNPs in QTL regions. For the prioritization of positional candidate genes whole genome sequencing and gene expression data of the parental lines were used. RESULTS: Overlapping QTL for gonadal adipose tissue weight and blood glucose concentration were detected on chromosome (Chr) 3 (95.8-100.1 Mb), and for gonadal adipose tissue weight, liver weight, and blood glucose concentration on Chr 17 (9.5-26.1 Mb). Causal modeling suggested for Chr 3-QTL direct effects on adipose tissue weight, but indirect effects on blood glucose concentration. Direct effects on adipose tissue weight, liver weight, and blood glucose concentration were suggested for Chr 17-QTL. Prioritized positional candidate genes for the identified QTL were Notch2 and Fmo5 (Chr 3) and Plg and Acat2 (Chr 17). Two additional QTL were detected for gonadal adipose tissue weight on Chr 15 (67.9-74.6 Mb) and for body weight on Chr 16 (3.9-21.4 Mb). CONCLUSIONS: QTL mapping together with a detailed prioritization approach allowed us to identify candidate genes associated with traits of the metabolic syndrome. In addition, we provided evidence for direct and indirect genetic effects on blood glucose concentration in the insulin-resistant mouse line BFMI861-S1.

Self-regulation of stress-related large-scale brain network balance using real-time fMRI neurofeedback.

It has recently been shown that acute stress affects the allocation of neural resources between large-scale brain networks, and the balance between the executive control network and the salience network in particular. Maladaptation of this dynamic resource reallocation process is thought to play a major role in stress-related psychopathology, suggesting that stress resilience may be determined by the retained ability to adaptively reallocate neural resources between these two networks. Actively training this ability could hence be a potentially promising way to increase resilience in individuals at risk for developing stress-related symptomatology. Using real-time functional Magnetic Resonance Imaging, the current study investigated whether individuals can learn to self-regulate stress-related large-scale network balance. Participants were engaged in a bidirectional and implicit real-time fMRI neurofeedback paradigm in which they were intermittently provided with a visual representation of the difference signal between the average activation of the salience and executive control networks, and tasked with attempting to self-regulate this signal. Our results show that, given feedback about their performance over three training sessions, participants were able to (1) learn strategies to differentially control the balance between SN and ECN activation on demand, as well as (2) successfully transfer this newly learned skill to a situation where they (a) did not receive any feedback anymore, and (b) were exposed to an acute stressor in form of the prospect of a mild electric stimulation. The current study hence constitutes an important first successful demonstration of neurofeedback training based on stress-related large-scale network balance - a novel approach that has the potential to train control over the central response to stressors in real-life and could build the foundation for future clinical interventions that aim at increasing resilience.

The BOLD response in primary motor cortex and supplementary motor area during kinesthetic motor imagery based graded fMRI neurofeedback.

There is increasing interest in exploring the use of functional MRI neurofeedback (fMRI-NF) as a therapeutic technique for a range of neurological conditions such as stroke and Parkinson's disease (PD). One main therapeutic potential of fMRI-NF is to enhance volitional control of damaged or dysfunctional neural nodes and networks via a closed-loop feedback model using mental imagery as the catalyst of self-regulation. The choice of target node/network and direction of regulation (increase or decrease activity) are central design considerations in fMRI-NF studies. Whilst it remains unclear whether the primary motor cortex (M1) can be activated during motor imagery, the supplementary motor area (SMA) has been robustly activated during motor imagery. Such differences in the regulation potential between primary and supplementary motor cortex are important because these areas can be differentially affected by a stroke or PD, and the choice of fMRI-NF target and grade of self-regulation of activity likely have substantial influence on the clinical effects and cost effectiveness of NF-based interventions. In this study we therefore investigated firstly whether healthy subjects would be able to achieve self-regulation of the hand-representation areas of M1 and the SMA using fMRI-NF training. There was a significant decrease in M1 neural activity during fMRI-NF, whereas SMA neural activity was increased, albeit not with the predicated graded effect. This study has important implications for fMRI-NF protocols that employ motor imagery to modulate activity in specific target regions of the brain and to determine how they may be tailored for neurorehabilitation.

The potential of MR-Encephalography for BCI/Neurofeedback applications with high temporal resolution.

Real-time functional magnetic resonance imaging (rt-fMRI) enables the update of various brain-activity measures during an ongoing experiment as soon as a new brain volume is acquired. However, the recorded Blood-oxygen-level dependent (BOLD) signal also contains physiological artifacts such as breathing and heartbeat, which potentially cause misleading false positive effects especially problematic in brain-computer interface (BCI) and neurofeedback (NF) setups. The low temporal resolution of echo planar imaging (EPI) sequences (which is in the range of seconds) prevents a proper separation of these artifacts from the BOLD signal. MR-Encephalography (MREG) has been shown to provide the high temporal resolution required to unalias and correct for physiological fluctuations and leads to increased specificity and sensitivity for mapping task-based activation and functional connectivity as well as for detecting dynamic changes in connectivity over time. By comparing a simultaneous multislice echo planar imaging (SMS-EPI) sequence and an MREG sequence using the same nominal spatial resolution in an offline analysis for three different experimental fMRI paradigms (perception of house and face stimuli, motor imagery, Stroop task), the potential of this novel technique for future BCI and NF applications was investigated. First, adapted general linear model pre-whitening which accounts for the high temporal resolution in MREG was implemented to calculate proper statistical results and be able to compare these with the SMS-EPI sequence. Furthermore, the respiration- and cardiac pulsation-related signals were successfully separated from the MREG signal using independent component analysis which were then included as regressors for a GLM analysis. Only the MREG sequence allowed to clearly separate cardiac pulsation and respiration components from the signal time course. It could be shown that these components highly correlate with the recorded respiration and cardiac pulsation signals using a respiratory belt and fingertip pulse plethysmograph. Temporal signal-to-noise ratios of SMS-EPI and MREG were comparable. Functional connectivity analysis using partial correlation showed a reduced standard error in MREG compared to SMS-EPI. Also, direct time course comparisons by down-sampling the MREG signal to the SMS-EPI temporal resolution showed lower variance in MREG. In general, we show that the higher temporal resolution is beneficial for fMRI time course modeling and this aspect can be exploited in offline application but also, is especially attractive, for real-time BCI and NF applications.

Active head motion reduction in magnetic resonance imaging using tactile feedback.

Head motion is a common problem in clinical as well as empirical (functional) magnetic resonance imaging applications, as it can lead to severe artefacts that reduce image quality. The scanned individuals themselves, however, are often not aware of their head motion. The current study explored whether providing subjects with this information using tactile feedback would reduce their head motion and consequently improve image quality. In a single session that included six runs, 24 participants performed three different cognitive tasks: (a) passive viewing, (b) mental imagery, and (c) speeded responses. These tasks occurred in two different conditions: (a) with a strip of medical tape applied from one side of the magnetic resonance head coil, via the participant's forehead, to the other side, and (b) without the medical tape being applied. Results revealed that application of medical tape to the forehead of subjects to provide tactile feedback significantly reduced both translational as well as rotational head motion. While this effect did not differ between the three cognitive tasks, there was a negative quadratic relationship between head motion with and without feedback. That is, the more head motion a subject produced without feedback, the stronger the motion reduction given the feedback. In conclusion, the here tested method provides a simple and cost-efficient way to reduce subjects' head motion, and might be especially beneficial when extensive head motion is expected a priori.

Ultrathin Au-Alloy Nanowires at the Liquid-Liquid Interface.

Ultrathin bimetallic nanowires are of importance and interest for applications in electronic devices such as sensors and heterogeneous catalysts. In this work, we have designed a new, highly reproducible and generalized wet chemical method to synthesize uniform and monodispersed Au-based alloy (AuCu, AuPd, and AuPt) nanowires with tunable composition using microwave-assisted reduction at the liquid-liquid interface. These ultrathin alloy nanowires are below 4 nm in diameter and about 2 µm long. Detailed microstructural characterization shows that the wires have an face centred cubic (FCC) crystal structure, and they have low-energy twin-boundary and stacking-fault defects along the growth direction. The wires exhibit remarkable thermal and mechanical stability that is critical for important applications. The alloy wires exhibit excellent electrocatalytic activity for methanol oxidation in an alkaline medium.

Interaction between numbers and size during visual search.

The current study investigates an interaction between numbers and physical size (i.e. size congruity) in visual search. In three experiments, participants had to detect a physically large (or small) target item among physically small (or large) distractors in a search task comprising single-digit numbers. The relative numerical size of the digits was varied, such that the target item was either among the numerically large or small numbers in the search display and the relation between numerical and physical size was either congruent or incongruent. Perceptual differences of the stimuli were controlled by a condition in which participants had to search for a differently coloured target item with the same physical size and by the usage of LCD-style numbers that were matched in visual similarity by shape transformations. The results of all three experiments consistently revealed that detecting a physically large target item is significantly faster when the numerical size of the target item is large as well (congruent), compared to when it is small (incongruent). This novel finding of a size congruity effect in visual search demonstrates an interaction between numerical and physical size in an experimental setting beyond typically used binary comparison tasks, and provides important new evidence for the notion of shared cognitive codes for numbers and sensorimotor magnitudes. Theoretical consequences for recent models on attention, magnitude representation and their interactions are discussed.

Nanoscopic Insights into InGaN/GaN Core-Shell Nanorods: Structure, Composition, and Luminescence.

Nitride-based three-dimensional core-shell nanorods (NRs) are promising candidates for the achievement of highly efficient optoelectronic devices. For a detailed understanding of the complex core-shell layer structure of InGaN/GaN NRs, a systematic determination and correlation of the structural, compositional, and optical properties on a nanometer-scale is essential. In particular, the combination of low-temperature cathodoluminescence (CL) spectroscopy directly performed in a scanning transmission electron microscope (STEM), and quantitative high-angle annular dark field imaging enables a comprehensive study of the nanoscopic attributes of the individual shell layers. The investigated InGaN/GaN core-shell NRs, which were grown by metal-organic vapor-phase epitaxy using selective-area growth exhibit an exceptionally low density of extended defects. Using highly spatially resolved CL mapping of single NRs performed in cross-section, we give a direct insight into the optical properties of the individual core-shell layers. Most interesting, we observe a red shift of the InGaN single quantum well from 410 to 471 nm along the nonpolar side wall. Quantitative STEM analysis of the active region reveals an increasing thickness of the single quantum well (SQW) from 6 to 13 nm, accompanied by a slight increase of the indium concentration along the nonpolar side wall from 11% to 13%. Both effects, the increased quantum-well thickness and the higher indium incorporation, are responsible for the observed energetic shift of the InGaN SQW luminescence. Furthermore, compositional mappings of the InGaN quantum well reveal the formation of locally indium rich regions with several nanometers in size, leading to potential fluctuations in the InGaN SQW energy landscape. This is directly evidenced by nanometer-scale resolved CL mappings that show strong localization effects of the excitonic SQW emission.

Different brains process numbers differently: structural bases of individual differences in spatial and nonspatial number representations.

A dominant hypothesis on how the brain processes numerical size proposes a spatial representation of numbers as positions on a "mental number line." An alternative hypothesis considers numbers as elements of a generalized representation of sensorimotor-related magnitude, which is not obligatorily spatial. Here we show that individuals' relative use of spatial and nonspatial representations has a cerebral counterpart in the structural organization of the posterior parietal cortex. Interindividual variability in the linkage between numbers and spatial responses (faster left responses to small numbers and right responses to large numbers; spatial-numerical association of response codes effect) correlated with variations in gray matter volume around the right precuneus. Conversely, differences in the disposition to link numbers to force production (faster soft responses to small numbers and hard responses to large numbers) were related to gray matter volume in the left angular gyrus. This finding suggests that numerical cognition relies on multiple mental representations of analogue magnitude using different neural implementations that are linked to individual traits.

Conventional transmission electron microscopy imaging beyond the diffraction and information limits.

There are mainly two complementary imaging modes in transmission electron microscopy (TEM): Conventional TEM (CTEM) and scanning TEM (STEM). In the CTEM mode the specimen is illuminated with a plane electron wave, and the direct image formed by the objective lens is recorded in the image plane. STEM is based on scanning the specimen surface with a focused electron beam and collecting scattered electrons with an extended disk or ring-shaped detector. Here we show that combination of CTEM imaging with STEM illumination generally allows extending the point resolution of CTEM imaging beyond the diffraction limit. This new imaging mode improves imaging characteristics, is more robust against chromatic aberration, exhibits direct structural imaging with superior precision, visualizes light elements with excellent contrast, and even allows us to overcome the conventional information limit of a microscope.

Influence of static atomic displacements on composition quantification of AlGaN/GaN heterostructures from HAADF-STEM images.

In an earlier publication Rosenauer et al. introduced a method for determination of composition in AlGaN/GaN heterostructures from high-angle annular dark field (HAADF) images. Static atomic displacements (SADs) were neglected during simulation of reference data because of the similar covalent radii of Al and Ga. However, SADs have been shown (Grillo et al.) to influence the intensity in HAADF images and therefore could be the reason for an observed slight discrepancy between measured and nominal concentrations. In the present study parameters of the Stillinger-Weber potential were varied in order to fit computed elastic constants, lattice parameters and bonding energies to experimental ones. A reference data set of HAADF images was simulated, in which the new parameterization was used to account for SADs. Two reference samples containing AlGaN layers with different Al concentrations were investigated and Al concentrations in the layers determined based on the new data set. We found that these concentrations were in good agreement with nominal concentrations as well as concentrations determined using alternative techniques such as strain state analysis and energy dispersive X-ray spectroscopy.

Expyriment: a Python library for cognitive and neuroscientific experiments.

Expyriment is an open-source and platform-independent lightweight Python library for designing and conducting timing-critical behavioral and neuroimaging experiments. The major goal is to provide a well-structured Python library for script-based experiment development, with a high priority being the readability of the resulting program code. Expyriment has been tested extensively under Linux and Windows and is an all-in-one solution, as it handles stimulus presentation, the recording of input/output events, communication with other devices, and the collection and preprocessing of data. Furthermore, it offers a hierarchical design structure, which allows for an intuitive transition from the experimental design to a running program. It is therefore also suited for students, as well as for experimental psychologists and neuroscientists with little programming experience.

Atom counting based on Voronoi averaged STEM intensities using a crosstalk correction scheme.

If quantitative scanning transmission electron microscopy is used for very precise thickness measurements with atomic resolution, it is commonly referred to as ¼atom counting«. Due to scattering and the finite probe extent the signal recorded in one atomic column is dependent not only on its own height but also on the height of its neighbours. Especially for thicker specimens this crosstalk effect can have significant impact on the measured intensity. If it is not appropriately accounted for in the evaluation, it can result in a deterioration of accuracy that impedes the possibility of actual atom counting. However, as the number of possible neighbour configurations can be excessively large, a comprehensive consideration of all in the evaluation reference is neigh impossible. This work proposes a method that allows for the a-posteriori reduction of crosstalk during the evaluation by algebraic means. Based on a parametric model, which is described in detail in the article, the crosstalk is expressed by an invertible matrix. Applying the inverted matrix to the measurement yields crosstalk corrected intensity values with very little computational effort. These can subsequently be evaluated by direct comparison to simple reference data. The working principle of the method is presented on the example of crystalline gold. The crosstalk parametrisation is found by fitting a model to sets of specifically created multislice simulations. The parameters are given for both aberration corrected and uncorrected STEM. Subsequently the abilities and potential of the technique are assessed in simulative studies on multiple model systems including gold nanoparticles. Overall a significant and robust improvement of the attainable precision can be demonstrated making the proposed method a promising tool for reference-based atom counting.

Polymyositis with cytochrome C oxidase negative fibers--a pathological and clinical challenge.

Polymyositis (PM) with cytochrome C oxidase negative fibers also referred to as PM with mitochondrial pathology (PM-Mito) is characterized by the symptoms of inclusion body myositis (IBM) and by the myopathological findings of PM except for an increase of muscle fibers with insufficient mitochondrial cytochrome C oxidase activity. Few PM-Mito cases are published; mitochondrial ultrastructure has not been studied in these patients. We report 2 PM-Mito patients with later onset than usually seen in IBM and poor responsiveness to glucocorticoids. Electron microscopy of muscle fibers showed irregular mitochondrial ultrastructure. Sjögren syndrome related antinuclear antibodies (Anti-Ro and Anti-La) were found in one of the two patients but the typical clinical symptoms of Sjögren syndrome such as xerostomia and keratoconjunctivitis were absent in this patient. Taken together, our observations, viewed in conjunction with the current literature, suggest that PM-Mito is an underdiagnosed disease with a multifactorial pathogenesis that should be elucidated in further studies. We want to encourage clinicians and pathologists to consider the possibility of PM-Mito in patients with atypical PM or sIBM.

A sensorimotor perspective on numerical cognition.

Numbers are present in every part of modern society and the human capacity to use numbers is unparalleled in other species. Understanding the mental and neural representations supporting this capacity is of central interest to cognitive psychology, neuroscience, and education. Embodied numerical cognition theory suggests that beyond the seemingly abstract symbols used to refer to numbers, their underlying meaning is deeply grounded in sensorimotor experiences, and that our specific understanding of numerical information is shaped by actions related to our fingers, egocentric space, and experiences with magnitudes in everyday life. We propose a sensorimotor perspective on numerical cognition in which number comprehension and numerical proficiency emerge from grounding three distinct numerical core concepts: magnitude, ordinality, and cardinality.

Study protocol for a randomised controlled trial investigating the effects of Mindfulness Based Stress Reduction on stress regulation and associated neurocognitive mechanisms in stressed university students: the MindRest study.

BACKGROUND: Stress-related disorders are a growing public health concern. While stress is a natural and adaptive process, chronic exposure to stressors can lead to dysregulation and take a cumulative toll on physical and mental well-being. One approach to coping with stress and building resilience is through Mindfulness-Based Stress Reduction (MBSR). By understanding the neural mechanisms of MBSR, we can gain insight into how it reduces stress and what drives individual differences in treatment outcomes. This study aims to establish the clinical effects of MBSR on stress regulation in a population that is susceptible to develop stress-related disorders (i.e., university students with mild to high self-reported stress), to assess the role of large-scale brain networks in stress regulation changes induced by MBSR, and to identify who may benefit most from MBSR. METHODS: This study is a longitudinal two-arm randomised, wait-list controlled trial to investigate the effects of MBSR on a preselected, Dutch university student population with elevated stress levels. Clinical symptoms are measured at baseline, post-treatment, and three months after training. Our primary clinical symptom is perceived stress, with additional measures of depressive and anxiety symptoms, alcohol use, stress resilience, positive mental health, and stress reactivity in daily life. We investigate the effects of MBSR on stress regulation in terms of behaviour, self-report measures, physiology, and brain activity. Repetitive negative thinking, cognitive reactivity, emotional allowance, mindfulness skills, and self-compassion will be tested as potential mediating factors for the clinical effects of MBSR. Childhood trauma, personality traits and baseline brain activity patterns will be tested as potential moderators of the clinical outcomes. DISCUSSION: This study aims to provide valuable insights into the effectiveness of MBSR in reducing stress-related symptoms in a susceptible student population and crucially, to investigate its effects on stress regulation, and to identify who may benefit most from the intervention. TRIAL REGISTRATION: Registered on September 15, 2022, at clinicaltrials.gov, NCT05541263 .