Attentional biases in problem and non-problem gamblers

Background: From a cognitive perspective, attentional biases are deemed as factors responsible in the onset and development of gambling disorder. However, knowledge relating to attentional processes in gambling is scarce and studies to date have reported contrasting results. Moreover, no study has ever examined which component and what type of bias are involved in attentional polarization in gambling. Methods: In the present study, 108 Italian participants, equally divided into problem and non-problem gamblers were administered a modified Posner Task, an attentional paradigm in which – through the manipulation of stimuli presentation time – it is possible to measure both initial orienting and maintenance of attention. In addition to the experimental task, participants completed self-report measures involving (i) craving (Gambling Craving Scale), (ii) depression, anxiety and stress (Depression Anxiety Stress Scale) and (iii) emotional dysregulation (Difficulties in Emotion Regulation Scale). Results: Analyses revealed facilitation in detecting gambling-related stimuli at the encoding level in problem gamblers but not in non-problem gamblers. Compared to non-problem gamblers, problem gamblers also reported higher levels of craving, emotional dysregulation, and negative mood states. Furthermore, all measures correlated with the gambling severity. Limitations: The use of indirect measure of attentional bias could be less accurate compared to direct measures. Conclusions: The facilitation in detecting gambling-related stimuli in problem gamblers and the correlation between subjective craving and facilitation bias suggests that attentional polarization could not be due to a conditioning process but that motivational factors such as craving could induce addicted-related seeking-behaviors

Attentional bias in non-problem gamblers, problem gamblers, and abstinent pathological gamblers: an experimental study

Background Attentional biases have been recognized as factors responsible for the maintenance of gambling problems. To date, no study has ever assessed the attentional biases among problem gamblers that have discontinued gambling (e.g., abstinent gamblers in treatment). Methods The sample consisted of 75 participants comprising three groups: non-problem gamblers, problem gamblers, and abstinent pathological gamblers undergoing treatment. The groups were discriminated using South Oaks Gambling Screen scores, with the exception of the abstinent pathological gamblers that already had a DSM-5 diagnosis for gambling disorder. Participants carried out a modified Posner Task for the assessment of attentional bias for gambling stimuli and completed the Depression Anxiety Stress Scale and the Gambling Craving Scale. Results Abstinent pathological gamblers showed an avoidance bias in the maintenance of attention, whereas problem gamblers exhibited a facilitation in detecting gambling stimuli. No biases were detected in non-problem gamblers. The results also demonstrated that compared to the other groups, abstinent pathological gamblers showed high emotional stress and problem gamblers reported a higher level of craving. Limitations The sample size limits the generalizability of results. Conclusions The present study demonstrated that attentional biases affect the maintenance and the discontinuation of gambling activities, and that the subjective feeling of craving for gambling may facilitate problem gamblers’ attention towards gambling stimuli

Mentalizing failures, emotional dysregulation, and cognitive distortions among adolescent problem gamblers

Over the past decade, several studies have investigated the relationship between cognitive distortions and emotion regulation among adolescent gamblers, demonstrating the exacerbating role of alcohol consumption when co-occurring with gambling problems. An important construct, that to date has been largely neglected, is mentalizing (i.e. the ability to refect on one’s own and others’ mental states). The aim of the present study was (for the frst time) to investigate the relative contribution of mentalization, emotional dysregulation, cognitive distortions, and alcohol consumption among adolescent gamblers. A total of 396 students (69.2% females) aged 14–19 years were recruited from secondary schools in Southern Italy. Assessment measures included the South Oaks Gambling Screen Revised for Adolescents (SOGS-RA), the Refective Functioning Questionnaire (RFQ-8), the Diffculties in Emotion Regulation Scale (DERS), the Gambling Related Cognitions Scale (GRCS), and the Alcohol Use Disorders Identifcation Test (AUDIT). Regression analysis showed that, along with male gender, the best predictors of adolescent gambling were scores on two GRCS subscales (i.e., ‘inability to stop gambling’ and ‘interpretative bias’), the RFQ-8’s ‘uncertainty about mental states’ dimension, and the DERS ‘impulse control difculties’ factor, with the overall model explaining more than one-third of the total variance. The results clearly indicated that, along with gambling-related cognitive distortions, uncertainty about mental states, and difculties remaining in control of one’s behavior when experiencing negative emotions contributed signifcantly to problematic gambling among adolescents

Spinal cord atrophy in a primary progressive multiple sclerosis trial: Improved sample size using GBSI

Background: We aimed to evaluate the implications for clinical trial design of the generalised boundary-shift integral (GBSI) for spinal cord atrophy measurement. / Methods: We included 220 primary-progressive multiple sclerosis patients from a phase 2 clinical trial, with baseline and week-48 3DT1-weighted MRI of the brain and spinal cord (1 × 1 × 1 mm3), acquired separately. We obtained segmentation-based cross-sectional spinal cord area (CSA) at C1-2 (from both brain and spinal cord MRI) and C2-5 levels (from spinal cord MRI) using DeepSeg, and, then, we computed corresponding GBSI. / Results: Depending on the spinal cord segment, we included 67.4–98.1% patients for CSA measurements, and 66.9–84.2% for GBSI. Spinal cord atrophy measurements obtained with GBSI had lower measurement variability, than corresponding CSA. Looking at the image noise floor, the lowest median standard deviation of the MRI signal within the cerebrospinal fluid surrounding the spinal cord was found on brain MRI at the C1-2 level. Spinal cord atrophy derived from brain MRI was related to the corresponding measures from dedicated spinal cord MRI, more strongly for GBSI than CSA. Spinal cord atrophy measurements using GBSI, but not CSA, were associated with upper and lower limb motor progression. / Discussion: Notwithstanding the reduced measurement variability, the clinical correlates, and the possibility of using brain acquisitions, spinal cord atrophy using GBSI should remain a secondary outcome measure in MS studies, until further advancements increase the quality of acquisition and reliability of processing

Rarity: Discovering rare cell populations from single-cell imaging data

MOTIVATION: Cell type identification plays an important role in the analysis and interpretation of single-cell data and can be carried out via supervised or unsupervised clustering approaches. Supervised methods are best suited where we can list all cell types and their respective marker genes a priori. While unsupervised clustering algorithms look for groups of cells with similar expression properties. This property permits the identification of both known and unknown cell populations, making unsupervised methods suitable for discovery. Success is dependent on the relative strength of the expression signature of each group as well as the number of cells. Rare cell types therefore present a particular challenge that are magnified when they are defined by differentially expressing a small number of genes. RESULTS: Typical unsupervised approaches fail to identify such rare sub-populations, and these cells tend to be absorbed into more prevalent cell types. In order to balance these competing demands, we have developed a novel statistical framework for unsupervised clustering, named Rarity, that enables the discovery process for rare cell types to be more robust, consistent and interpretable. We achieve this by devising a novel clustering method based on a Bayesian latent variable model in which we assign cells to inferred latent binary on/off expression profiles. This lets us achieve increased sensitivity to rare cell populations while also allowing us to control and interpret potential false positive discoveries. We systematically study the challenges associated with rare cell type identification and demonstrate the utility of Rarity on various IMC data sets. AVAILABILITY: Implementation of Rarity together with examples are available from the Github repository (https://github.com/kasparmartens/rarity). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

T2 lesion location really matters: a 10 year follow-up study in primary progressive multiple sclerosis

Objectives: Prediction of long term clinical outcome in patients with primary progressive multiple sclerosis (PPMS) using imaging has important clinical implications, but remains challenging. We aimed to determine whether spatial location of T2 and T1 brain lesions predicts clinical progression during a 10-year follow-up in PPMS. Methods: Lesion probability maps of the T2 and T1 brain lesions were generated using the baseline scans of 80 patients with PPMS who were clinically assessed at baseline and then after 1, 2, 5 and 10 years. For each patient, the time (in years) taken before bilateral support was required to walk (time to event (TTE)) was used as a measure of progression rate. The probability of each voxel being ‘lesional’ was correlated with TTE, adjusting for age, gender, disease duration, centre and spinal cord cross sectional area, using a multiple linear regression model. To identify the best, independent predictor of progression, a Cox regression model was used. Results: A significant correlation between a shorter TTE and a higher probability of a voxel being lesional on T2 scans was found in the bilateral corticospinal tract and superior longitudinal fasciculus, and in the right inferior fronto-occipital fasciculus (p<0.05). The best predictor of progression rate was the T2 lesion load measured along the right inferior fronto-occipital fasciculus (p=0.016, hazard ratio 1.00652, 95% CI 1.00121 to 1.01186). Conclusion: Our results suggest that the location of T2 brain lesions in the motor and associative tracts is an important contributor to the progression of disability in PPMS, and is independent of spinal cord involvement

Reconfigurable Boolean Logic using Magnetic Single-Electron Transistors

We propose a novel hybrid single-electron device for reprogrammable low-power logic operations, the magnetic single-electron transistor (MSET). The device consists of an aluminium single-electron transistors with a GaMnAs magnetic back-gate. Changing between different logic gate functions is realized by reorienting the magnetic moments of the magnetic layer which induce a voltage shift on the Coulomb blockade oscillations of the MSET. We show that we can arbitrarily reprogram the function of the device from an n-type SET for in-plane magnetization of the GaMnAs layer to p-type SET for out-of-plane magnetization orientation. Moreover, we demonstrate a set of reprogrammable Boolean gates and its logical complement at the single device level. Finally, we propose two sets of reconfigurable binary gates using combinations of two MSETs in a pull-down network

Generalised boundary shift integral for longitudinal assessment of spinal cord atrophy

Spinal cord atrophy measurements obtained from structural magnetic resonance imaging (MRI) are associated with disability in many neurological diseases and serve as in vivo biomarkers of neurodegeneration. Longitudinal spinal cord atrophy rate is commonly determined from the numerical difference between two volumes (based on 3D surface fitting) or two cross-sectional areas (CSA, based on 2D edge detection) obtained at different time-points. Being an indirect measure, atrophy rates are susceptible to variable segmentation errors at the edge of the spinal cord. To overcome those limitations, we developed a new registration-based pipeline that measures atrophy rates directly. We based our approach on the generalised boundary shift integral (GBSI) method, which registers 2 scans and uses a probabilistic XOR mask over the edge of the spinal cord, thereby measuring atrophy more accurately than segmentation-based techniques. Using a large cohort of longitudinal spinal cord images (610 subjects with multiple sclerosis from a multi-centre trial and 52 healthy controls), we demonstrated that GBSI is a sensitive, quantitative and objective measure of longitudinal spinal cord volume change. The GBSI pipeline is repeatable, reproducible, and provides more precise measurements of longitudinal spinal cord atrophy than segmentation-based methods in longitudinal spinal cord atrophy studies

Overview of the Low Complexity Enhancement Video Coding (LCEVC) Standard

The Low Complexity Enhancement Video Coding (LCEVC) specification is a recent standard approved by the ISO/IEC JTC 1/SC 29/WG04 (MPEG) Video Coding. The main goal of LCEVC is to provide a standalone toolset for the enhancement of any other existing codec. It works on top of other coding schemes, resulting in a multi-layer video coding technology, but unlike existing scalable video codecs, adds enhancement layers completely independent from the base video. The LCEVC technology takes as input the decoded video at lower resolution and adds up to two enhancement sub-layers of residuals encoded with specialized low-complexity coding tools, such as simple temporal prediction, frequency transform, quantization, and entropy encoding. This paper provides an overview of the main features of the LCEVC standard: high compression efficiency, low complexity, minimized requirements of memory and processing power

Predictive role of diffusion-weighted MRI in the assessment of response to total neoadjuvant therapy in locally advanced rectal cancer

Objective To investigate the predictive role of diffusion-weighted magnetic resonance imaging (DW-MRI) in the assessment of response to total neoadjuvant therapy (TNT) in patients with locally advanced rectal cancer (LARC). Methods In this single-center retrospective study, patients with LARC who underwent staging MRI and TNT were enrolled. MRI-based staging, tumor volume, and DWI-ADC values were analyzed. Patients were classified as complete responders (pCR) and non-complete responders (non-pCR), according to post-surgical outcome. Pre-treatment ADC values were compared to pathological outcome, post-treatment downstaging, and reduction of tumor volume. The diagnostic accuracy of DWI-ADC in differentiating between pCR and non-pCR groups was calculated with receiver operating characteristic (ROC) analysis. Results A total of 36 patients were evaluated (pCR, n = 20; non-pCR, n = 16). Pre-treatment ADC values were significantly different between the two groups (p = 0.034), while no association was found between pre-TNT tumor volume and pathological response. ADC values showed significant correlations with loco-regional downstaging after therapy (r = -0.537, p = 0.022), and with the reduction of tumor volume (r = -0.480, p = 0.044). ADC values were able to differentiate pCR from non-pCR patients with a sensitivity of 75% and specificity of 70%. Conclusions ADC values on pre-treatment MRI were strongly associated with the outcome in patients with LARC, both in terms of pathological response and in loco-regional downstaging after TNT, suggesting the use of DW-MRI as a potential predictive tool of response to therapy