Rodent ultrasonic vocalizations (USVs) are ethologically critical social signals. Rats emit 22 kHz USVs and 50 kHz USVs, respectively, in conjunction with negative and positive affective states. Little is known about what controls emotional reactivity to these social signals. Using male SpragueDawley rats, we examined unconditional and conditional freezing behavior in response to the following auditory stimuli: three 22 kHz USVs, a discontinuous tone whose frequency and on-off pattern matched one of the USVs, a continuous tone with the same or lower frequencies, a 4 kHz discontinuous tone with an on-off pattern matched to one of the USVs, and a 50 kHz USV. There were no differences among these stimuli in terms of the unconditional elicitation of freezing behavior. Thus, the stimuli were equally neutral before conditioning. During differential fear conditioning, one of these stimuli (the CS + ) always co-terminated with a footshock unconditional stimulus (US) and another stimulus (the CS − ) was explicitly unpaired with the US. There were no significant differences among these cues in CS + -elicited freezing behavior. Thus, the stimuli were equally salient or effective as cues in supporting fear conditioning. When the CS + was a 22 kHz USV or a similar stimulus, rats discriminated based on the principal frequency and/or the temporal pattern of the stimulus. However, when these same stimuli served as the CS − , discrimination failed due to generalization from the CS + . Thus, the stimuli differed markedly in the specificity of conditioning. This strikingly asymmetrical stimulus generalization is a novel bias in discrimination.

Context The essential omega-3 fatty acids (ω-3 FAs) eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) exhibit vital biological roles and are critical for cardiovascular and neurologic health. Compared with the general population, football athletes may be at an increased risk of cardiovascular disease. Further, those same athletes are also exposed to repetitive head impacts, which may lead to long-term neurologic deficits. Both diets high in ω-3 FAs and supplementation with ω-3 FAs have been reported to reduce the risk of cardiovascular disease, and early evidence suggests a potential neuroprotective effect of supplementation. Objective To determine the (1) erythrocyte content of DHA and EPA, as measured by the Omega-3 Index, expressed as a percentage of total fatty acids, in National Collegiate Athletic Association Division I football athletes and (2) distribution across the Omega-3 Index risk zones established for cardiovascular disease: high risk, <4%; intermediate risk, 4% to 8%; and low risk, >8%. Design Cross-sectional descriptive study. Setting Multicenter trial. Patients or Other Participants Deidentified data including complete erythrocyte fatty acid profile from the 2017–2018 season, age at time of testing, height, weight, and ethnicity were collected from 404 athletes. Main Outcome Measure(s) Omega-3 Index. Results About 34% of athletes (n = 138) had an Omega-3 Index considered high risk (<4%), and 66% (n = 266) had a risk considered intermediate (4%–8%). None had a low-risk Omega-3 Index. Conclusions The Omega-3 Index is a simple, minimally invasive test of ω-3 FA status. Our data indicate that football athletes may be deficient in the ω-3 FAs DHA and EPA. The fact that no athlete had an Omega-3 Index associated with low risk suggests football athletes may be at increased risk for cardiovascular disease in later life.

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A: Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays. K : Computerized Tomography (CT) and Computed Radiography (CR); Plasma diagnostics -interferometry, spectroscopy and imaging 1Corresponding author. 2See the author list of Overview of the JET preparation for Deuterium-Tritium Operation by E. Joffrin et al. in Nucl.

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