Self-alignment of a compact large-area atomic Sagnac interferometer

We report on the realization of a compact atomic Mach-Zehndertype Sagnac interferometer of 13.7 cm length, which covers an area of 19 mm(2) previously reported only for large thermal beam interferometers. According to Sagnac's formula, which holds for both light and atoms, the sensitivity for rotation rates increases linearly with the area enclosed by the interferometer. The use of cold atoms instead of thermal atoms enables miniaturization of Sagnac interferometers without sacrificing large areas. In comparison with thermal beams, slow atoms offer better matching of the initial beam velocity and the velocity with which the matter waves separate. In our case, the area is spanned by a cold atomic beam of 2.79m s(-1), which is split, deflected and combined by driving a Raman transition between the two hyperfine ground states of Rb-87 in three spatially separated light zones. The use of cold atoms requires a precise angular alignment and high wave front quality of the three independent light zones over the cloud envelope. We present a procedure for mutually aligning the beam splitters at the microradian level by making use of the atom interferometer itself in different configurations. With this method, we currently achieve a sensitivity of 6.1 x 10(-7) rad s(-1) Hz(-1/2).DFG/SFB/407EU/NESTEU/FINAQSEU/EuroquasarEU/IQSQUESTMax-Planck-GesellschaftINTERCAN networkUFA-DF

Comparing neural correlates of conditioned inhibition between children with and without anxiety disorders - A preliminary study

Cognitive-behavioral therapy (CBT), a first-line treatment for pediatric anxiety disorders, is based on principles of threat learning and extinction. However, CBT does not work sufficiently for up to 40% of clinically anxious youth. The neural and behavioral correlates of conditioned inhibition might provide promising targets for attempts to improve CBT response. During conditioned inhibition, threat and safety cues appear together, forming a safety compound. Here, we test whether this safety compound elicits a reduced fear response compared to pairing the threat cue with a novel cue (novel compound). The current pilot study compares behavioral, physiological, and neural correlates of conditioned inhibition between children with (n=17, Mage=13.09, SD=3.05) and without (n=18, Mage=14.49, SD=2.38) anxiety disorders. Behavioral and physiological measures did not differ between children with and without anxiety disorders during fear acquisition. During testing, children with anxiety disorders showed overall higher skin conductance response and expected to hear the aversive sound following the novel compound more often than children without anxiety disorders. Children with anxiety disorders showed more activity in the right ventromedial prefrontal cortex (vmPFC) to the safety versus novel compound. Children without anxiety disorders showed the opposite pattern - more right vmPFC activity to the novel versus safety compound (F(1,31)=5.40, p=0.03). No group differences manifested within the amygdala, dorsal anterior cingulate cortex, or hippocampus. These pilot findings suggest a feasible approach for examining conditioned inhibition in pediatric anxiety disorders. If replicated in larger samples, findings may implicate perturbed conditioned inhibition in pediatric anxiety disorders and provide targets for CBT

Obesity and the Risk of Papillary Thyroid Cancer: A Pooled Analysis of Three Case-Control Studies.

Background: There is a correlation between temporal trends of obesity prevalence and papillary thyroid cancer (PTC) incidence in the United States. Obesity is a well-recognized risk factor for many cancers, but there are few studies on the association between obesity and PTC risk. We investigated the association between anthropometric measurements and PTC risk using pooled individual data from three case–control populations. Methods: Height and weight information were obtained from three independent case–control studies, including 1917 patients with PTC (1360 women and 557 men) and 2127 cancer-free controls from the United States, Italy, and Germany. Body mass index (BMI), body fat percentage, and body surface area (BSA) were calculated. An unconditional logistic regression model was used to calculate odds ratios (ORs) and confidence intervals (CIs) with respect to risk of PTC, adjusted by age, sex, race/ethnicity, and study site. Results: In the pooled population, for both men and women, an increased risk of PTC was found to be associated with greater weight, BMI, body fat percentage, and BSA, whereas a reduced risk of PTC was associated with greater height, in the pooled population for both men and women. Compared with normal-weight subjects (BMI 18.5–24.9 kg/m2), the ORs for overweight (BMI 25–29.9 kg/m2) and obese (BMI ‡ 30 kg/m2) subjects were 1.72 [CI 1.48–2.00] and 4.17 [CI 3.41–5.10] respectively. Compared with the lowest quartile of body fat percentage, the ORs for the highest quartile were 3.83 [CI 2.85–5.15] in women and 4.05 [CI 2.67– 6.15] in men. Conclusion: Anthropometric factors, especially BMI and body fat percentage, were significantly associated with increased risk of PTC. Future studies of anthropometric factors and PTC that incorporate intermediate factors, including adiposity and hormone biomarkers, are essential to help clarify potential mechanisms of the relationship

Computational modeling of threat learning reveals links with anxiety and neuroanatomy in humans

Influential theories implicate variations in the mechanisms supporting threat learning in the severity of anxiety symptoms. We use computational models of associative learning in conjunction with structural imaging to explicate links among the mechanisms underlying threat learning, their neuroanatomical substrates, and anxiety severity in humans. We recorded skin-conductance data during a threat-learning task from individuals with and without anxiety disorders (N=251; 8-50 years; 116 females). Reinforcement-learning model variants quantified processes hypothesized to relate to anxiety: threat conditioning, threat generalization, safety learning, and threat extinction. We identified the best-fitting models for these processes and tested associations among latent learning parameters, whole-brain anatomy, and anxiety severity. Results indicate that greater anxiety severity related specifically to slower safety learning and slower extinction of response to safe stimuli. Nucleus accumbens gray-matter volume moderated learning-anxiety associations. Using a modeling approach, we identify computational mechanisms linking threat learning and anxiety severity and their neuroanatomical substrates

Which Fish Should I Eat? Perspectives Influencing Fish Consumption Choices

Background: Diverse perspectives have influenced fish consumption choices

Small RNA analysis in Sindbis virus infected human HEK293 cells

In contrast to the defence mechanism of RNA interference (RNAi) in plants and invertebrates, its role in the innate response to virus infection of mammals is a matter of debate. Since RNAi has a well-established role in controlling infection of the alphavirus Sindbis virus (SINV) in insects, we have used this virus to investigate the role of RNAi in SINV infection of human cells

Neuromonitoring in neonatal critical care part II: extremely premature infants and critically ill neonates

Abstract: Neonatal intensive care has expanded from cardiorespiratory care to a holistic approach emphasizing brain health. To best understand and monitor brain function and physiology in the neonatal intensive care unit (NICU), the most commonly used tools are amplitude-integrated EEG, full multichannel continuous EEG, and near-infrared spectroscopy. Each of these modalities has unique characteristics and functions. While some of these tools have been the subject of expert consensus statements or guidelines, there is no overarching agreement on the optimal approach to neuromonitoring in the NICU. This work reviews current evidence to assist decision making for the best utilization of these neuromonitoring tools to promote neuroprotective care in extremely premature infants and in critically ill neonates. Neuromonitoring approaches in neonatal encephalopathy and neonates with possible seizures are discussed separately in the companion paper. Impact: For extremely premature infants, NIRS monitoring has a potential role in individualized brain-oriented care, and selective use of aEEG and cEEG can assist in seizure detection and prognostication.For critically ill neonates, NIRS can monitor cerebral perfusion, oxygen delivery, and extraction associated with disease processes as well as respiratory and hypodynamic management. Selective use of aEEG and cEEG is important in those with a high risk of seizures and brain injury.Continuous multimodal monitoring as well as monitoring of sleep, sleep–wake cycling, and autonomic nervous system have a promising role in neonatal neurocritical care

A Robust Approach for Multivariate Binary Vectors Clustering and Feature Selection

International audienceGiven a set of binary vectors drawn from a ¯nite multiple Bernoulli mixture model, an important problem is to determine which vectors are outliers and which features are relevant. The goal of this paper is to propose a model for binary vectors clustering that accommo- dates outliers and allows simultaneously the incorporation of a feature selection methodology into the clustering process. We derive an EM al- gorithm to ¯t the proposed model. Through simulation studies and a set of experiments involving handwritten digit recognition and visual scenes categorization, we demonstrate the usefulness and e®ectiveness of our method