Social and non-social feedback stimuli lead to comparable levels of reward learning and reward responsiveness in an online probabilistic reward task

Social stimuli seem to be processed more easily and efficiently than non-social stimuli. The current study tested whether social feedback stimuli improve reward learning in a probabilistic reward task (PRT), in which one response option is usually rewarded more often than the other via presentation of non-social reward stimuli. In a pre-registered online study with 305 participants, 75 participants were presented with a non-social feedback stimulus (a star) and information about gains, which is typically used in published PRT studies. Three other groups (with 73–82 participants each) were presented with one of three social feedback stimuli: verbal praise, an attractive happy face, or a “thumbs up”-picture. The data were analysed based on classical signal detection theory, drift diffusion modelling, and Bayesian analyses of null effects. All PRT variants yielded the expected behavioural preference for the more frequently rewarded response. There was no processing advantage of social over non-social feedback stimuli. Bayesian analyses further supported the observation that social feedback stimuli neither increased nor decreased behavioural preferences in the PRT. The current findings suggest that the PRT is a robust experimental paradigm independent of the applied feedback stimuli. They also suggest that the occurrence of a processing advantage for social feedback stimuli is dependent on the experimental task and design.publishedVersio

High survivin expression as a risk factor in patients with anal carcinoma treated with concurrent chemoradiotherapy

Purpose: To investigate the prognostic value of survivin expression in pretreatment specimens from patients with anal cancer treated with concurrent 5-FU and mitomycin C-based chemoradiation (CRT). Material and methods: Immunohistochemical staining for survivin was performed in pretreatment biopsies of 62 patients with anal carcinoma. Survivin expression was correlated with clinical and histopathological characteristics as well as local failure free- (LFFS), distant metastases free- (DMFS), cancer specific- (CSS), and overall survival (OS). Results: Survivin staining intensity was weak in 10%, intermediate in 48% and intense in 42% of the patients. No association between survivin expression and clinicopathologic factors (tumor stage, age and HIV status) could be shown. In univariate analysis, the level of survivin staining was significantly correlated with DMFS (low survivin vs. high survivin: 94% vs. 74%, p=0.04). T-stage, N-stage and the tumor grading were significantly associated with OS and CSS and with DMFS and LFFS, respectively. In multivariate analysis, survivin was confirmed as independent prognostic parameter for DMFS (RR, 0.04; p=0.02) and for OS (RR, 0.27; p=0.04). Conclusion: Our results demonstrated that the level of pretreatment survivin is correlated with the clinical outcome in patients with anal carcinoma treated with concurrent CRT. Further studies are warranted to elucidate the complex role of survivin for the oncologic treatment and to exploit the protein as a therapeutic target in combined modality treatment of anal cancer

Antifungal defense of probiotic Lactobacillus rhamnosus GG is mediated by blocking adhesion and nutrient depletion

Data Availability: All relevant data are available from the Gene Expression Omnibus at the following accession number: GSE97755. Funding: This work was funded by the German Research Council (DFG) Graduation College 685, Dr. Jekyll and Mr. Hyde: A systems approach to the therapy of nosocomial infections caused by Candida albicans: a commensal organism switches to a deadly pathogen/ PTJ (FKZ: 0315409BBMBF), the Dr. Manfred Plempel-foundation, the Dr. Siegried Stettendorf-Foundation, the InfectERA Program (FunComPath; BMBF FKZ 031L0001A), the Integrated Research and Treatment Center for Sepsis Control and Care (CSCC) project CanBac (BMBF, FKZ: 01EO1002), and the German Research Council (DFG) GZ:HE7565/1-1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms

The zip archive contains real images showing macrophages. (ZIP 28979 kb

Improving Automated Hemorrhage Detection in Sparse-view Computed Tomography via Deep Convolutional Neural Network based Artifact Reduction

Purpose: Sparse-view computed tomography (CT) is an effective way to reduce dose by lowering the total number of views acquired, albeit at the expense of image quality, which, in turn, can impact the ability to detect diseases. We explore deep learning-based artifact reduction in sparse-view cranial CT scans and its impact on automated hemorrhage detection. Methods: We trained a U-Net for artefact reduction on simulated sparse-view cranial CT scans from 3000 patients obtained from a public dataset and reconstructed with varying levels of sub-sampling. Additionally, we trained a convolutional neural network on fully sampled CT data from 17,545 patients for automated hemorrhage detection. We evaluated the classification performance using the area under the receiver operator characteristic curves (AUC-ROCs) with corresponding 95% confidence intervals (CIs) and the DeLong test, along with confusion matrices. The performance of the U-Net was compared to an analytical approach based on total variation (TV). Results: The U-Net performed superior compared to unprocessed and TV-processed images with respect to image quality and automated hemorrhage diagnosis. With U-Net post-processing, the number of views can be reduced from 4096 (AUC-ROC: 0.974; 95% CI: 0.972-0.976) views to 512 views (0.973; 0.971-0.975) with minimal decrease in hemorrhage detection (P<.001) and to 256 views (0.967; 0.964-0.969) with a slight performance decrease (P<.001). Conclusion: The results suggest that U-Net based artifact reduction substantially enhances automated hemorrhage detection in sparse-view cranial CTs. Our findings highlight that appropriate post-processing is crucial for optimal image quality and diagnostic accuracy while minimizing radiation dose.Comment: 11 pages, 6 figures, 1 tabl

Ketogenic diet and fasting diet as Nutritional Approaches in Multiple Sclerosis (NAMS): protocol of a randomized controlled study

BACKGROUND: Multiple sclerosis (MS) is the most common inflammatory disease of the central nervous system in young adults that may lead to progressive disability. Since pharmacological treatments may have substantial side effects, there is a need for complementary treatment options such as specific dietary approaches. Ketone bodies that are produced during fasting diets (FDs) and ketogenic diets (KDs) are an alternative and presumably more efficient energy source for the brain. Studies on mice with experimental autoimmune encephalomyelitis showed beneficial effects of KDs and FDs on disease progression, disability, cognition and inflammatory markers. However, clinical evidence on these diets is scarce. In the clinical study protocol presented here, we investigate whether a KD and a FD are superior to a standard diet (SD) in terms of therapeutic effects and disease progression. METHODS: This study is a single-center, randomized, controlled, parallel-group study. One hundred and eleven patients with relapsing-remitting MS with current disease activity and stable immunomodulatory therapy or no disease-modifying therapy will be randomized to one of three 18-month dietary interventions: a KD with a restricted carbohydrate intake of 20-40 g/day; a FD with a 7-day fast every 6 months and 14-h daily intermittent fasting in between; and a fat-modified SD as recommended by the German Nutrition Society. The primary outcome measure is the number of new T2-weighted MRI lesions after 18 months. Secondary endpoints are safety, changes in relapse rate, disability progression, fatigue, depression, cognition, quality of life, changes of gut microbiome as well as markers of inflammation, oxidative stress and autophagy. Safety and feasibility will also be assessed. DISCUSSION: Preclinical data suggest that a KD and a FD may modulate immunity, reduce disease severity and promote remyelination in the mouse model of MS. However, clinical evidence is lacking. This study is the first clinical study investigating the effects of a KD and a FD on disease progression of MS

Auto-completion of Contours in Sketches, Maps and Sparse 2D Images Based on Topological Persistence

We design a new fast algorithm to automatically complete closed contours in a finite point cloud on the plane. The only input can be a scanned map with almost closed curves, a hand-drawn artistic sketch or any sparse dotted image in 2D without any extra parameters. The output is a hierarchy of closed contours that have a long enough life span (persistence) in a sequence of nested neighborhoods of the input points. We prove theoretical guarantees when, for a given noisy sample of a graph in the plane, the output contours geometrically approximate the original contours in the unknown graph

Do all roads lead to Rome? The potential of different approaches to diagnose Aelurostrongylus abstrusus infection in cats

An infection with the cat lungworm, Aelurostrongylus abstrusus, can be subclinical, but it can also cause severe respiratory clinical signs. Larvae excretion, antibody levels, clinical assessment findings of the respiratory system and diagnostic imaging findings were recorded and compared for six cats with experimental aelurostrongylosis. In five cats, patency started 33–47 days post infection (pi), but two cats excreted larvae only in long intervals and low numbers. Positive ELISA results were observed in four cats with patent aelurostrongylosis, starting between five days before and 85 days after onset of patency. One seropositive cat remained copromicroscopically negative. Mild respiratory signs were observed in all cats examined. A computed tomographic (CT) examination of the lungs displayed distinct alterations, even in absence of evident clinical signs or when larvae excretion was low or negative. The thoracic radiograph evaluation correlated with the CT results, but CT was more distinctive. After anthelmintic treatment in the 25th week post infection, pulmonary imaging findings improved back to normal within 6–24 weeks. This study shows that a multifaceted approach, including diagnostic imaging, can provide a clearer diagnosis and monitoring of disease progression. Furthermore, a CT examination provides an alternative to post mortem examination and worm counts in anthelmintic efficacy studies

Improving Image Quality of Sparse-view Lung Cancer CT Images with a Convolutional Neural Network

Purpose: To improve the image quality of sparse-view computed tomography (CT) images with a U-Net for lung cancer detection and to determine the best trade-off between number of views, image quality, and diagnostic confidence. Methods: CT images from 41 subjects (34 with lung cancer, seven healthy) were retrospectively selected (01.2016-12.2018) and forward projected onto 2048-view sinograms. Six corresponding sparse-view CT data subsets at varying levels of undersampling were reconstructed from sinograms using filtered backprojection with 16, 32, 64, 128, 256, and 512 views, respectively. A dual-frame U-Net was trained and evaluated for each subsampling level on 8,658 images from 22 diseased subjects. A representative image per scan was selected from 19 subjects (12 diseased, seven healthy) for a single-blinded reader study. The selected slices, for all levels of subsampling, with and without post-processing by the U-Net model, were presented to three readers. Image quality and diagnostic confidence were ranked using pre-defined scales. Subjective nodule segmentation was evaluated utilizing sensitivity (Se) and Dice Similarity Coefficient (DSC) with 95% confidence intervals (CI). Results: The 64-projection sparse-view images resulted in Se = 0.89 and DSC = 0.81 [0.75,0.86] while their counterparts, post-processed with the U-Net, had improved metrics (Se = 0.94, DSC = 0.85 [0.82,0.87]). Fewer views lead to insufficient quality for diagnostic purposes. For increased views, no substantial discrepancies were noted between the sparse-view and post-processed images. Conclusion: Projection views can be reduced from 2048 to 64 while maintaining image quality and the confidence of the radiologists on a satisfactory level