Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Frequency-Domain/Image-Domain Deep Network for Magnetic Resonance Image Reconstruction

Decreasing magnetic resonance (MR) image acquisition times can potentially make MR examinations more accessible. Compressed sensing (CS)-based image reconstruction methods decrease MR acquisition time by reconstructing high-quality images from data that were originally sampled at rates inferior to the Nyquist-Shannon sampling theorem. Deep-learning methods have been used to solve the CS MR reconstruction problem. These proposed methods are able to quickly reconstruct images in a single pass using an appropriately trained network. A variety of different network architectures (e.g., U-nets and Residual U-nets) have been proposed to tackle the CS reconstruction problem. A drawback of these architectures is that they typically only work on image domain data. For undersampled data, the images computed by applying the inverse Fast Fourier Transform (iFFT) are aliased. In this work we propose a hybrid architecture, termed W-net, that works both in the k-space (or frequency-domain) and the image (or spatial) domains. Our network is composed of a complex-valued residual U-net in the k-space domain, an iFFT operation, and a real-valued Unet in the image domain. Our experiments demonstrated, using MR raw k-space data, that the proposed hybrid approach can potentially improve CS reconstruction compared to deep-learning networks that operate only in the image domain. In this study we compare our method with four previously published deep neural networks and examine their ability to reconstruct images that are subsequently used to generate regional volume estimates. Our technique was ranked second in the quantitative analysis, but qualitative analysis indicated that our reconstruction performed the best in hard to reconstruct regions, such as the cerebellum. All images reconstructed with our method were successfully post-processed, and showed good volumetry agreement compared with the fully sampled reconstruction measures.
Deep Imitative Models for Flexible Inference, Planning, and Control

Imitation Learning (IL) is an appealing approach to learn desirable autonomous behavior. However, directing IL to achieve arbitrary goals is difficult. In contrast, planning-based algorithms use dynamics models and reward functions to achieve goals. Yet, reward functions that evoke desirable behavior are often difficult to specify. In this paper, we propose Imitative Models to combine the benefits of IL and goal-directed planning. Imitative Models are probabilistic predictive models of desirable behavior able to plan interpretable expert-like trajectories to achieve specified goals. We derive families of flexible goal objectives, including constrained goal regions, unconstrained goal sets, and energy-based goals. We show that our method can use these objectives to successfully direct behavior. Our method substantially outperforms six IL approaches and a planning-based approach in a dynamic simulated autonomous driving task, and is efficiently learned from expert demonstrations without online data collection. We also show our approach is robust to poorly specified goals, such as goals on the wrong side of the road.
Cell-autonomous requirement of TDP-43, an ALS/FTD signature protein, for oligodendrocyte survival and myelination

Significance TDP-43 is the defining pathological hallmark protein for two overlapping adult-onset neurodegenerative diseases, amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). TDP-43 proteinopathies are also found in other major neurodegenerative diseases, such as Alzheimer’s disease, further highlighting the pivotal role of TDP-43 in the nervous system. Curiously, TDP-43 aggregates are also found in oligodendrocytes, which provide myelination and metabolic support for the neurons. Here, we show that TDP-43 is indispensable, in a cell-autonomous manner, for the proper functioning of mature oligodendrocytes, in particular, myelination and cell survival. Specifically, TDP-43 depletion leads to RIPK1-mediated necroptosis of mature oligodendrocytes and down-regulation of myelin proteins that are essential for myelination but exerts no apparent toxicity on motor neurons. TDP-43 aggregates in neurons and glia are the defining pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), raising the possibility of glial damage in the disease pathogenesis. However, the normal physiological functions of TDP-43 in glia are largely unknown. To address how TDP-43 may be required for oligodendroglial functions we selectively deleted TDP-43 in mature oligodendrocytes in mice. Although mice with TDP-43 deleted in oligodendrocytes are born in an expected Mendelian ratio, they develop progressive neurological phenotypes leading to early lethality accompanied by a progressive reduction in myelination. The progressive myelin reduction is likely due to a combination of the cell-autonomous RIPK1-mediated necroptosis of mature oligodendrocytes and the TDP-43–dependent reduction in the expression of myelin genes. Strikingly, enhanced proliferation of NG2-positive oligodendrocyte precursor cells within the white matter, but not the gray matter, was able to replenish the loss of mature oligodendrocytes, indicating an intrinsic regeneration difference between the gray and white matter oligodendrocytes. By contrast, there was no loss of spinal cord motor neurons and no sign of denervation at the neuromuscular synapses. Taken together, our data demonstrate that TDP-43 is indispensable for oligodendrocyte survival and myelination, and loss of TDP-43 in oligodendrocytes exerts no apparent toxicity on motor neurons.
Recurrent and De Novo Autoimmune Hepatitis

Clinical indications for liver transplantation (LT) in patients with autoimmune hepatitis (AIH) are identical to those of patients with other chronic liver diseases that end in acute or semiacute liver failure, decompensated cirrhosis, or hepatocellular carcinoma. Recurrent disease after LT has been reported in 10%‐50% of patients with AIH, and the frequency of detection is influenced in part by the use of protocol or clinically indicated liver biopsy. De novo AIH connotes the development of AIH in patients transplanted for liver diseases other than AIH, and it has been reported in 5%‐10% of pediatric and 1%‐2% of adult recipients. Recurrent disease can negatively impact on graft and patient survival, and retransplantation has been required in 8%‐23%. De novo AIH is within the spectrum of graft dysfunction that includes plasma cell–rich rejection, and it can also progress to cirrhosis and graft failure. Treatment for recurrent or de novo disease is based on the conventional regimens for AIH, and corticosteroid therapy alone or combined with azathioprine is standard. Better control of disease activity prior to LT has been associated with less recurrence, and maintenance corticosteroid treatment after LT can reduce its frequency. In conclusion, recurrent AIH is far more frequent than de novo AIH. Both may have negative impacts on graft and patient survival, and early detection and treatment are key objectives. Future investigations must codify the diagnostic criteria for each graft dysfunction, seek diagnostic biomarkers, and evaluate treatments that improve outcomes without increasing the risk of pre‐ and post‐LT infections.
Localization of Left Ventricular Lead Electrodes in Relation to Myocardial Scar in Patients Undergoing Cardiac Resynchronization Therapy

Background The efficacy of cardiac resynchronization therapy may be reduced in the event of pacing within myocardial fibrosis. We aimed to develop a method to determine the anatomical relationships between the left ventricular (LV) lead and myocardial fibrosis. Methods and Results In consecutive patients indicated for cardiac resynchronization therapy, cardiovascular magnetic resonance imaging with late gadolinium enhancement assessment was performed before implantation. After implantation, an injected computed tomography scanner (CT scan) was performed. The 2 imaging techniques were fused to assess the LV lead position relative to myocardial scar. A total of 68 patients were included. Myocardial scar was found in 29 (43%) and was localized in lateral segments in 14 (21%). Scar was significantly associated with male sex, ischemic cardiomyopathy, a Selvester score adapted to left bundle branch block (LBBB Selvester), and Selvester criteria for localizing lateral fibrosis (V2 S/S′ ratio). Image fusion was feasible in all patients. Position within myocardial scar was confirmed for 6 electrodes in 3 patients. Prolonged QRS duration during LV pacing ≥139% predicted electrode positioning within scar tissue (sensitivity, 83%; specificity, 91%; P=0.002). Conclusions In cardiac resynchronization therapy patients, fusion between preimplantation cardiovascular magnetic resonance and a postimplantation injected computed tomography scan is a feasible technique. Prolongation of the QRS duration during LV pacing predicts pacing within myocardial scar. Accurate location of LV lead pacing electrodes on the epicardial surface relative to myocardial scar, either by imaging or ECG analyses, may help improve cardiac resynchronization therapy response in selected patients.
Chronoamperometric Observation and Analysis of Electrocatalytic Ability of Single Pd Nanoparticle for Hydrogen Peroxide Reduction Reaction

The current generated by the collision of a single nanoparticle (NP) of palladium (Pd) on a gold (Au) ultramicroelectrode (UME) surface was observed using an electrocatalytic amplification method. The hydrogen peroxide reduction reaction was used for the electrocatalytic reaction because the hydrogen peroxide reduction reaction has no gas-phase product, which would induce rapid signal decay. The electrocatalytic current resulting from a single Pd nanoparticle on the Au UME shows a staircase response with accompanying slow current decay. The applying potential and concentration of hydrogen peroxide were optimized for clear distinction of signal. The height of the current step and signal frequency were analyzed and compared with the theoretical expectation. The analysis of the electrocatalytic activity of single Pd NPs provides insight toward their future application.
Asymmetries of the visual system and their influence on visual performance and oculomotor dynamics

Our representation of the visual field is not homogenous. There are differences in resolution not only between the fovea and regions eccentric to it, but also between the nasal and temporal hemiretinae, that can be traced to asymmetric distributions of photoreceptors and ganglion cells. We review evidence for differences in visual and attentional processing and oculomotor behaviour that can be traced to asymmetries of the visual system, mainly emphasising nasal‐temporal asymmetries. Asymmetries in the visual system manifest in various measures, in basic psychophysical tests of visual performance, attentional processing, choice behaviour, saccadic peak velocity, and latencies. Nasal‐temporal asymmetries on saccadic latency seem primarily to occur for express saccades. Neural asymmetries between the upper and lower hemifields are strong and cause corresponding differences in performance between the hemifields. There are interesting individual differences in asymmetric processing which seem to be related to the strength of eye dominance. These neurophysiological asymmetries and the corresponding asymmetries in visual performance and oculomotor behaviour can strongly influence experimental results in vision and must be considered during experimental design and the interpretation of results.
Prevalence and Risk Factors for Augmented Renal Clearance in a Population of Critically Ill Patients

Background: Critically ill patients show a high, albeit variable, prevalence of augmented renal clearance (ARC). This condition has relevant consequences on the elimination of hydrophilic drugs. Knowledge of risk factors for ARC helps in the early identification of ARC. The aims of this study were evaluation of (1) risk factors for ARC and (2) the prevalence of ARC in critically ill patients over a period of 1 year. Methods: A retrospective cohort study was performed for all consecutive patients admitted to our intensive care unit (ICU). Augmented renal clearance was defined by a creatinine clearance ≥130 mL/min/1.73 m2. “Patient with ARC” was defined as a patient with a median of creatinine clearance ≥130 mL/min/1.73 m2 over the period of admission. Four variables were tested, Simplified Acute Physiology Score II (SAPS II), male gender, age, and trauma as cause for ICU admission. An analysis (patient based and clearance based) was performed with logistic regression. Results: Of 475 patients, 446 were included in this study, contributing to 454 ICU admissions and 5586 8-hour creatinine clearance (8h-CLCR). Overall, the prevalence of patients with ARC was 24.9% (n = 113). In a subset of patients with normal serum creatinine levels, the prevalence was 43.0% (n = 104). Of the set of all 8h-CLCR measurements, 25.4% (1418) showed ARC. In the patient-based analysis, the adjusted odds ratio was: 2.0 (confidence interval [CI]:1.1-3.7; P < .05), 0.93 (CI: 0.91-0.94; P < .01), 2.7 (CI: 1.4-5.3; P < .01), and 0.98 (CI: 0.96 -1.01; P = .15), respectively, for trauma, age, male sex, and SAPS II. In the clearance-based analysis, the adjusted odds ratio were 1.7 (CI: 1.4-1.9; P < .01), 0.94 (CI: 0.932-0.942; P < .01), and 2.9 (CI: 2.4-3.4; P < .01), respectively, for trauma, age, and male sex. Conclusions: Trauma, young age, and male sex were independent risk factors for ARC. This condition occurs in a considerable proportion of critical care patients, which was particularly prevalent in patients without evidence of renal dysfunction.
UMONS Submission for WMT18 Multimodal Translation Task

This paper describes the UMONS solution for the Multimodal Machine Translation Task presented at the third conference on machine translation (WMT18). We explore a novel architecture, called deepGRU, based on recent findings in the related task of Neural Image Captioning (NIC). The models presented in the following sections lead to the best METEOR translation score for both constrained (English, image) -> German and (English, image) -> French sub-tasks.
Protein Tyrosine Phosphatases: Regulators of CD4 T Cells in Inflammatory Bowel Disease

Protein tyrosine phosphatases (PTPs) play a critical role in co-ordinating the signaling networks that maintain lymphocyte homeostasis and direct lymphocyte activation. By dephosphorylating tyrosine residues, PTPs have been shown to modulate enzyme activity and both mediate and disrupt protein-protein interactions. Through these molecular mechanisms, PTPs ultimately impact lymphocyte responses to environmental cues such as inflammatory cytokines and chemokines, as well as antigenic stimulation. Mouse models of acute and chronic intestinal inflammation have been shown to be exacerbated in the absence of PTPs such as PTPN2 and PTPN22. This increase in disease severity is due in part to hyper-activation of lymphocytes in the absence of PTP activity. In accordance, human PTPs have been linked to intestinal inflammation. Genome wide association studies (GWAS) identified several PTPs within risk loci for inflammatory bowel disease (IBD). Therapeutically targeting PTP substrates and their associated signaling pathways, such as those implicated in CD4+ T cell responses, has demonstrated clinical efficacy. The current review focuses on the role of PTPs in controlling CD4+ T cell activity in the intestinal mucosa and how disruption of PTP activity in CD4+ T cells can contribute to intestinal inflammation.
Feature Map Filtering: Improving Visual Place Recognition with Convolutional Calibration

Convolutional Neural Networks (CNNs) have recently been shown to excel at performing visual place recognition under changing appearance and viewpoint. Previously, place recognition has been improved by intelligently selecting relevant spatial keypoints within a convolutional layer and also by selecting the optimal layer to use. Rather than extracting features out of a particular layer, or a particular set of spatial keypoints within a layer, we propose the extraction of features using a subset of the channel dimensionality within a layer. Each feature map learns to encode a different set of weights that activate for different visual features within the set of training images. We propose a method of calibrating a CNN-based visual place recognition system, which selects the subset of feature maps that best encodes the visual features that are consistent between two different appearances of the same location. Using just 50 calibration images, all collected at the beginning of the current environment, we demonstrate a significant and consistent recognition improvement across multiple layers for two different neural networks. We evaluate our proposal on three datasets with different types of appearance changes - afternoon to morning, winter to summer and night to day. Additionally, the dimensionality reduction approach improves the computational processing speed of the recognition system.
Dystonic Pseudo Foot Drop

The most common presentation of foot dystonia in patients with Parkinson's disease (PD) or dystonia is inversion of the foot accompanied by flexion of the toes, with or without extension of the hallux. Less commonly, foot dystonia may mimic foot drop, as occurs with weakness of the dorsiflexors muscles, resulting in a pseudo foot drop. This has rarely been reported in the literature and has been poorly recognized, often leading to misdiagnosis and unnecessary investigations and treatment. We report 5 patients with dystonic pseudo foot drop, one of them diagnosed with early‐onset PD, 2 with sporadic PD, and 2 with dystonia. Despite the steppage gait, their physical exam revealed normal strength, and no other explanation for a “foot drop” was found. It is important to recognize this phenomenology, which can be a clue to the diagnosis of early‐onset PD, and may be responsive to levodopa in selected patients.
Improving Generalization of Sequence Encoder-Decoder Networks for Inverse Imaging of Cardiac Transmembrane Potential

Deep learning models have shown state-of-the-art performance in many inverse reconstruction problems. However, it is not well understood what properties of the latent representation may improve the generalization ability of the network. Furthermore, limited models have been presented for inverse reconstructions over time sequences. In this paper, we study the generalization ability of a sequence encoder decoder model for solving inverse reconstructions on time sequences. Our central hypothesis is that the generalization ability of the network can be improved by 1) constrained stochasticity and 2) global aggregation of temporal information in the latent space. First, drawing from analytical learning theory, we theoretically show that a stochastic latent space will lead to an improved generalization ability. Second, we consider an LSTM encoder-decoder architecture that compresses a global latent vector from all last-layer units in the LSTM encoder. This model is compared with alternative LSTM encoder-decoder architectures, each in deterministic and stochastic versions. The results demonstrate that the generalization ability of an inverse reconstruction network can be improved by constrained stochasticity combined with global aggregation of temporal information in the latent space.
A New Single-Item Sleep Quality Scale: Results of Psychometric Evaluation in Patients With Chronic Primary Insomnia and Depression.

STUDY OBJECTIVES A single-item sleep quality scale (SQS) was developed as a simple and practical sleep quality assessment and psychometrically evaluated. METHODS SQS measurement characteristics were evaluated using the Pittsburgh Sleep Quality Index (PSQI) and morning questionnaire-insomnia (MQI) according to prespecified analysis plans in separate clinical studies of patients with insomnia and depression. Patients with insomnia (n = 70) received 4 weeks' usual care with an FDA-approved hypnotic agent; patients with depression (n = 651) received 8 weeks' active or experimental therapy. RESULTS Concurrent criterion validity (correlation with measures of a similar construct) was demonstrated by strong (inverse) correlations between the SQS and MQI (week 1 Pearson correlation -.76) and PSQI (week 8 Goodman-Kruskal correlation -.92) sleep quality items in populations with insomnia and depression, respectively. In patients with depression, stronger correlations between the SQS and PSQI core sleep quality components versus other items supported convergent/divergent construct validity (similarity/dissimilarity to related/unrelated measures). Known-groups validity was evidenced by decreasing mean SQS scores across those who sleep normally, those borderline to having sleep problems, and those with problems sleeping. Test-retest reliability (intraclass correlation coefficient) was . 62 during a 4-week period of sleep stability in patients with insomnia and . 74 in stable patients with depression (1 week). Effect sizes (standardized response means) for change from baseline were 1.32 (week 1) and . 67 (week 8) in populations with insomnia and depression, respectively. Mean SQS changes from baseline to week 8 convergently decreased across groups of patients with depression categorized by level of PSQI sleep quality improvement. CONCLUSIONS The SQS possesses favorable measurement characteristics relative to lengthier or more frequently administered sleep questionnaires in patients with insomnia and depression. CLINICAL TRIAL REGISTRATION Registry: ClincalTrials.gov, Title: Treatment of Patients With Major Depressive Disorder With MK0869, Identifier: NCT00034983, URL: https://clinicaltrials.gov/ct2/show/NCT00034983.
OPV Vaccination and Shedding Patterns in Mexican and US Children

Abstract Background As wild poliovirus is eradicated and countries switch from oral poliovirus vaccine (OPV) to inactivated poliovirus vaccine (IPV) per World Health Organization recommendations, preventing circulation of vaccine-derived poliovirus (cVDPV) is a top priority. Currently, the impact of prior poliovirus vaccination on OPV shedding is not fully understood. Methods Stool samples from 2 populations were tested for OPV to assess shedding patterns. 505 samples from 43 US children vaccinated with OPV were collected over 42 days post-vaccination. 1,379 samples from 148 Mexican children vaccinated with OPV were collected over 71 days post-vaccination. Prior vaccination history was recorded for both groups. Results Seventeen (40%) of the US children had never received poliovirus vaccination while the Mexican children had received at least 2 doses of IPV and 116 (78%) had OPV exposure. In total, 84% of US children and 78% of Mexican children shed OPV (P = .44, Fisher exact test), with a mean shedding duration of 17.4 days for US children and 9.3 days for Mexican children (P < .0001, Wilcoxon-Mann Whitney test). Conclusions Prior vaccination did not affect the likelihood of shedding, as the US and Mexico cohorts had similar shedding proportions. However, prior vaccination affected shedding duration as the Mexican children, who were largely OPV exposed and all of whom had at least 2 IPV vaccinations, shed OPV for half as long as the US cohort. Since different countries maintain different poliovirus vaccination schedules, it is likely that duration of shedding of OPV varies in populations around the world.