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Although political violence has been perpetrated on behalf of a wide range of political ideologies, it is unclear whether there are systematic differences between ideologies in the use of violence to pursue a political cause. Prior research on this topic is scarce and mostly restricted to self-reported measures or less extreme forms of political aggression. Moreover, it has generally focused on respondents in Western countries and has been limited to either comparisons of the supporters of left-wing and right-wing causes or examinations of only Islamist extremism. In this research we address these gaps by comparing the use of political violence by left-wing, right-wing, and Islamist extremists in the United States and worldwide using two unique datasets that cover real-world examples of politically motivated, violent behaviors. Across both datasets, we find that radical acts perpetrated by individuals associated with left-wing causes are less likely to be violent. In the United States, we find no difference between the level of violence perpetrated by right-wing and Islamist extremists. However, differences in violence emerge on the global level, with Islamist extremists being more likely than right-wing extremists to engage in more violent acts.

The lowest-energy exciton state in caesium lead halide perovskite nanocrystals is shown to be a bright triplet state, contrary to expectations that lowest-energy excitons should always be dark. A bright future for semiconductors Lead halide perovskite semiconductor nanocrystals are attracting considerable interest as materials for solar cells and light-emitting diodes because of their excellent photophysical properties. But what makes them so special? Excitons are the electronic excitations that are ultimately responsible for the emissive properties of nanostructured semiconductors, and prevailing wisdom is that the lowest-energy excitonic state will be long-lived and hence poorly emitting (or 'dark'). Michael Becker et al . now show that caesium lead halide perovskites disobey this rule: the lowest-energy excitons are instead unusually 'bright', emitting much faster than any other semiconductor nanocrystal. Furthermore, they identify the structural and electronic factors responsible for this anomalous behaviour, providing vital clues for the identification of other semiconducting materials that might behave similarly. Nanostructured semiconductors emit light from electronic states known as excitons 1 . For organic materials, Hund’s rules 2 state that the lowest-energy exciton is a poorly emitting triplet state. For inorganic semiconductors, similar rules 3 predict an analogue of this triplet state known as the ‘dark exciton’ 4 . Because dark excitons release photons slowly, hindering emission from inorganic nanostructures, materials that disobey these rules have been sought. However, despite considerable experimental and theoretical efforts, no inorganic semiconductors have been identified in which the lowest exciton is bright. Here we show that the lowest exciton in caesium lead halide perovskites (CsPbX 3 , with X = Cl, Br or I) involves a highly emissive triplet state. We first use an effective-mass model and group theory to demonstrate the possibility of such a state existing, which can occur when the strong spin–orbit coupling in the conduction band of a perovskite is combined with the Rashba effect 5 , 6 , 7 , 8 , 9 , 10 . We then apply our model to CsPbX 3 nanocrystals 11 , and measure size- and composition-dependent fluorescence at the single-nanocrystal level. The bright triplet character of the lowest exciton explains the anomalous photon-emission rates of these materials, which emit about 20 and 1,000 times faster 12 than any other semiconductor nanocrystal at room 13 , 14 , 15 , 16 and cryogenic 4 temperatures, respectively. The existence of this bright triplet exciton is further confirmed by analysis of the fine structure in low-temperature fluorescence spectra. For semiconductor nanocrystals, which are already used in lighting 17 , lasers 18 and displays 19 , these excitons could lead to materials with brighter emission. More generally, our results provide criteria for identifying other semiconductors that exhibit bright excitons, with potential implications for optoelectronic devices.

An ensemble of emitters can behave very differently from its individual constituents when they interact coherently via a common light field. After excitation of such an ensemble, collective coupling can give rise to a many-body quantum phenomenon that results in short, intense bursts of light—so-called superfluorescence 1 . Because this phenomenon requires a fine balance of interactions between the emitters and their decoupling from the environment, together with close identity of the individual emitters, superfluorescence has thus far been observed only in a limited number of systems, such as certain atomic and molecular gases and a few solid-state systems 2 – 7 . The generation of superfluorescent light in colloidal nanocrystals (which are bright photonic sources practically suited for optoelectronics 8 , 9 ) has been precluded by inhomogeneous emission broadening, low oscillator strength, and fast exciton dephasing. Here we show that caesium lead halide (CsPbX 3 , X = Cl, Br) perovskite nanocrystals 10 – 13 that are self-organized into highly ordered three-dimensional superlattices exhibit key signatures of superfluorescence. These are dynamically red-shifted emission with more than 20-fold accelerated radiative decay, extension of the first-order coherence time by more than a factor of four, photon bunching, and delayed emission pulses with Burnham–Chiao ringing behaviour 14 at high excitation density. These mesoscopically extended coherent states could be used to boost the performance of opto-electronic devices 15 and enable entangled multi-photon quantum light sources 16 , 17 . Cooperative quantum effects in superlattices of quantum dots made of caesium lead halide perovskite give rise to superfluorescence, with the individual emitters interacting coherently to give intense bursts of light.

Mixture regression models are an important method for uncovering unobserved heterogeneity. A fundamental challenge in their application relates to the identification of the appropriate number of segments to retain from the data. Prior research has provided several simulation studies that compare the performance of different segment retention criteria. Although collinearity between the predictor variables is a common phenomenon in regression models, its effect on the performance of these criteria has not been analyzed thus far. We address this gap in research by examining the performance of segment retention criteria in mixture regression models characterized by systematically increased collinearity levels. The results have fundamental implications and provide guidance for using mixture regression models in empirical (marketing) studies.

Patients with gout and cardiovascular disease were assigned to receive febuxostat or allopurinol. At 32 months, there was no significant between-group difference in a composite cardiovascular end point, but all-cause and cardiovascular mortality were higher with febuxostat.

The coronavirus disease 2019 (Covid-19) pandemic, caused by SARS-CoV-2, has resulted in a global testing supply shortage. In response, pooled testing has emerged as a promising strategy that can immediately increase testing capacity. In pooled sample testing, multiple samples are combined (or pooled) together and tested as a single unit. If the pool is positive, the individual samples can then be individually tested to identify the positive case(s). Here, we provide support for the adoption of sample pooling with the point-of-care Cepheid Xpert ® Xpress SARS-CoV-2 molecular assay. Corroborating previous findings, the limit of detection of this assay was comparable to laboratory-developed reverse-transcription quantitative PCR SARS-CoV-2 tests, with observed detection below 100 copies/mL. The Xpert ® Xpress assay detected SARS-CoV-2 after samples with minimum viral loads of 461 copies/mL were pooled in groups of six. Based on these data, we recommend the adoption of pooled testing with the Xpert ® Xpress SARS-CoV-2 assay where warranted based on public health needs. The suggested number of samples per pool, or the pooling depth, is unique for each point-of-care testing site and can be determined by the positive test rates. To statistically determine appropriate pooling depth, we have calculated the pooling efficiency for numerous combinations of pool sizes and test rates. This information is included as a supplemental dataset that we encourage public health authorities to use as a guide to make recommendations that will maximize testing capacity and resource conservation.

Sustained anticipatory anxiety is central to Generalized Anxiety Disorder (GAD). During anticipatory anxiety, phasic threat responding appears to be mediated by the amygdala, while sustained threat responding seems related to the bed nucleus of the stria terminalis (BNST). Although sustained anticipatory anxiety in GAD patients was proposed to be associated with BNST activity alterations, firm evidence is lacking. We aimed to explore temporal characteristics of BNST and amygdala activity during threat anticipation in GAD patients. Nineteen GAD patients and nineteen healthy controls (HC) underwent functional magnetic resonance imaging (fMRI) during a temporally unpredictable threat anticipation paradigm. We defined phasic and a systematic variation of sustained response models for blood oxygen level-dependent responses during threat anticipation, to disentangle temporally dissociable involvement of the BNST and the amygdala. GAD patients relative to HC responded with increased phasic amygdala activity to onset of threat anticipation and with elevated sustained BNST activity that was delayed relative to the onset of threat anticipation. Both the amygdala and the BNST displayed altered responses during threat anticipation in GAD patients, albeit with different time courses. The results for the BNST activation hint towards its role in sustained threat responding, and contribute to a deeper understanding of pathological sustained anticipatory anxiety in GAD.

Acute myeloid leukaemia is a fatal disease for most patients. We have found that ferumoxytol (Feraheme), an FDA-approved iron oxide nanoparticle for iron deficiency treatment, demonstrates an anti-leukaemia effect in vitro and in vivo. Using leukaemia cell lines and primary acute myeloid leukaemia patient samples, we show that low expression of the iron exporter ferroportin results in a susceptibility of these cells via an increase in intracellular iron from ferumoxytol. The reactive oxygen species produced by free ferrous iron lead to increased oxidative stress and cell death. Ferumoxytol treatment results in a significant reduction of disease burden in a murine leukaemia model and patient-derived xenotransplants bearing leukaemia cells with low ferroportin expression. Our findings show how a clinical nanoparticle previously considered largely biologically inert could be rapidly incorporated into clinical trials for patients with leukaemia with low ferroportin levels.Administration of the clinically approved iron oxide nanoparticle drug ferumoxytol in vitro results in an anti-leukaemia effect and in vivo extended overall survival in part due to the low expression of the iron export protein ferroportin.

The authors present a computational framework for false-discovery-rate-controlled metabolite annotation from high-resolution imaging mass spectrometry data. High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry ( https://github.com/alexandrovteam/pySM ). We introduce a metabolite-signal match score and a target–decoy FDR estimate for spatial metabolomics.

Interpersonal violence (IPV) is one of the most frequent causes for the development of posttraumatic stress disorder (PTSD) in women. Trauma-related triggers have been proposed to evoke automatic emotional responses in PTSD. The present functional magnetic resonance study investigated the neural basis of trauma-related picture processing in women with IPV-PTSD (n = 18) relative to healthy controls (n = 18) using a newly standardized trauma-related picture set and a non-emotional vigilance task. We aimed to identify brain activation and connectivity evoked by trauma-related pictures, and associations with PTSD symptom severity. We found hyperactivation during trauma-related vs neutral picture processing in both subcortical [basolateral amygdala (BLA), thalamus, brainstem] and cortical [anterior cingulate cortex (ACC), medial prefrontal cortex (mPFC), insula, occipital cortex] regions in IPV-PTSD. In patients, brain activation in amygdala, ACC, insula, occipital cortex and brainstem correlated positively with symptom severity. Furthermore, connectivity analyses revealed hyperconnectivity between BLA and dorsal ACC/mPFC. Results show symptom severity-dependent brain activation and hyperconnectivity in response to trauma-related pictures in brain regions related to fear and visual processing in women suffering from IPV-PTSD. These brain mechanisms appear to be associated with immediate responses to trauma-related triggers presented in a non-emotional context in this PTSD subgroup.