The translational neural circuitry of anxiety

Anxiety is an adaptive response that promotes harm avoidance, but at the same time excessive anxiety constitutes the most common psychiatric complaint. Moreover, current treatments for anxiety—both psychological and pharmacological—hover at around 50% recovery rates. Improving treatment outcomes is nevertheless difficult, in part because contemporary interventions were developed without an understanding of the underlying neurobiological mechanisms that they modulate. Recent advances in experimental models of anxiety in humans, such as threat of unpredictable shock, have, however, enabled us to start translating the wealth of mechanistic animal work on defensive behaviour into humans. In this article, we discuss the distinction between fear and anxiety, before reviewing translational research on the neural circuitry of anxiety in animal models and how it relates to human neuroimaging studies across both healthy and clinical populations. We highlight the roles of subcortical regions (and their subunits) such as the bed nucleus of the stria terminalis, the amgydala, and the hippocampus, as well as their connectivity to cortical regions such as dorsal medial and lateral prefrontal/cingulate cortex and insula in maintaining anxiety responding. We discuss how this circuitry might be modulated by current treatments before finally highlighting areas for future research that might ultimately improve treatment outcomes for this common and debilitating transdiagnostic symptom

Ultra-bright gamma-ray emission and dense positron production from two laser-driven colliding foils

Matter can be transferred into energy and the opposite transformation is also possible by use of high-power lasers. A laser pulse in plasma can convert its energy into γ-rays and then e −e + pairs via the multi-photon Breit-Wheeler process. Production of dense positrons at GeV energies is very challenging since extremely high laser intensity ∼ 1024 Wcm−2 is required. Here we propose an all-optical scheme for ultra-bright γ-ray emission and dense positron production with lasers at intensity of 1022−23 Wcm−2 . By irradiating two colliding elliptically-polarized lasers onto two diamondlike carbon foils, electrons in the focal region of one foil are rapidly accelerated by the laser radiation pressure and interact with the other intense laser pulse which penetrates through the second foil due to relativistically induced foil transparency. This symmetric configuration enables efficient Compton back-scattering and results in ultra-bright γ-photon emission with brightness of ∼ 1025 photons/s/mm2 /mrad2 /0.1%BW at 15 MeV and intensity of 5×1023 Wcm−2 . Our first three-dimensional simulation with quantum-electrodynamics incorporated shows that a GeV positron beam with density of 2.5×1022 cm−3 and flux of 1.6×1010/shot is achieved. Collective effects of the pair plasma may be also triggered, offering a window on investigating laboratory astrophysics at PW laser facilities

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Transport coefficients of a relativistic plasma

In this work, a self-consistent transport theory for a relativistic plasma is developed. Using the notation of Braginskii [S. I. Braginskii, in Reviews of Plasma Physics, ed. M. A. Leontovich (1965), Vol. 1, p.174], we provide semi-analytical forms of the electrical resistivity, thermoelectric and thermal conductivity tensors for a Lorentzian plasma in a magnetic field. This treatment is then generalized to plasmas with arbitrary atomic number by numerically solving the linearized Boltzmann equation. The corresponding transport coefficients are fitted by rational functions in order to make them suitable for use in radiation-hydrodynamic simulations and transport calculations. Within the confines of linear transport theory and on the assumption that the plasma is optically thin, our results are valid for temperatures up to a few MeV. By contrast, classical transport theory begins to incur significant errors above kBT ~ 10 keV, e.g., the parallel thermal conductivity is suppressed by 15% at kBT = 20 keV due to relativistic effect

The development and psychometric properties of a self-report Catastrophising Questionnaire

Catastrophizing is a cognitive process that can be defined as predicting the worst possible outcome. It has been shown to be related to psychiatric diagnoses such as depression and anxiety, yet there are no self-report questionnaires specifically measuring it outside the context of pain research. Here, we therefore develop a novel, comprehensive self-report measure of general catastrophizing. We performed five online studies (total n = 734), in which we created and refined a Catastrophizing Questionnaire, and used a factor analytic approach to understand its underlying structure. We also assessed convergent and discriminant validity, and analysed test–retest reliability. Furthermore, we tested the ability of Catastrophizing Questionnaire scores to predict relevant clinical variables over and above other questionnaires. Finally, we also developed a four-item short version of this questionnaire. We found that our questionnaire is best fit by a single underlying factor, and shows convergent and discriminant validity. Exploratory factor analyses indicated that catastrophizing is independent from other related constructs, including anxiety and worry. Moreover, we demonstrate incremental validity for this questionnaire in predicting diagnostic and medication status. Finally, we demonstrate that our Catastrophizing Questionnaire has good test–retest reliability (intraclass correlation coefficient = 0.77, p < 0.001). Critically, we can now, for the first time, obtain detailed self-report data on catastrophizing

The development and psychometric properties of a self-report Catastrophising Questionnaire

Catastrophising is a cognitive process that can be defined as predicting the worst possible outcome. It has been shown to be related to psychiatric diagnoses such as depression and anxiety, yet there are no self-report questionnaires specifically measuring it outside the context of pain research. Here, we therefore develop a novel, comprehensive self-report measure of general catastrophising. We performed five online studies (total n=734), in which we created and refined a Catastrophising Questionnaire, and used a factor analytic approach to understand its underlying structure. We also assessed convergent and discriminant validity, and analysed test-retest reliability. Furthermore, we tested the ability of Catastrophising Questionnaire scores to predict relevant clinical variables over and above other questionnaires. Finally, we also developed a four-item short version of this questionnaire. We found that our questionnaire is best fit by a single underlying factor, and shows convergent and discriminant validity. Exploratory factor analyses indicated that catastrophising is independent from other related constructs, including anxiety and worry. Moreover, we demonstrate incremental validity for this questionnaire in predicting diagnostic and medication status. Finally, we demonstrate that our Catastrophising Questionnaire has good test-retest reliability (Intra-Class-Correlation Coefficient=0.77, p<.001). Critically, we can now, for the first time, obtain detailed self-report data on catastrophising