Quasar outflow energetics from broad absorption line variability

Quasar outflows have long been recognized as potential contributors to the co-evolution between supermassive black holes (SMBHs) and their host galaxies. The role of outflows in AGN feedback processes can be better understood by placing observational constraints on wind locations and kinetic energies. We utilize broad absorption line (BAL) variability to investigate the properties of a sample of 71 BAL quasars with P$\thinspace$V broad absorption. The presence of P$\thinspace$V BALs indicates that other BALs like C$\thinspace$IV are saturated, such that variability in those lines favours clouds crossing the line of sight. We use these constraints with measurements of BAL variability to estimate outflow locations and energetics. Our data set consists of multiple-epoch spectra from the Sloan Digital Sky Survey and MDM Observatory. We detect significant (4$\sigma$) BAL variations from 10 quasars in our sample over rest frame time-scales between < 0.2-3.8 yr. Our derived distances for the 10 variable outflows are nominally < 1-10 pc from the SMBH using the transverse-motion scenario, and < 100-1000 pc from the central source using ionization-change considerations. These distances, in combination with the estimated high outflow column densities (i.e. $N_{\textrm{H}}$ > 10$^{22}$ cm$^{-2}$), yield outflow kinetic luminosities between ~ 0.001-1 times the bolometric luminosity of the quasar, indicating that many absorber energies within our sample are viable for AGN feedback.Comment: 19 pages, 3 figures, 4 tables, 1 supplementary figure, accepted to MNRA

Shaping public opinion about regional integration: the rhetoric of justification and party cues

The article investigates how justifications used by politicians to explain their positions on policies of regional integration shape public opinion about these policies. I argue that support for a policy position increases when politicians tailor their justifications to the expectations of their audience; and I suggest that this happens even when party cues offer a less effortful way of forming opinions. I test my theoretical expectations in laboratory experiments with diverse samples, which manipulate party cues and justifications for a policy of European integration. I find that citizens use justifications and cues to form opinions. The relative importance of the two factors depends on individual dispositions and political context. In a non-competitive context (study 1), politically invested citizens use cues, while uninvested citizens use justifications. In a competitive context (study 2), the opinions of politically invested citizens are shaped by both factors, while the opinions of uninvested citizens become erratic

The wMelPop strain of Wolbachia interferes with dopamine levels in Aedes aegypti

Wolbachia is an intracellular bacterium that has been stably transinfected into the mosquito vector of dengue, Aedes aegypti. This inherited infection causes a range of metabolic and phenotypic alterations in the mosquito, which might be related to neuronal abnormalities. In order to determine if these alterations were caused by the manipulation of neuroamines by this bacterium, we studied the expression of genes involved in the dopamine biosynthetic pathway and also measured the amount of dopamine in infected and uninfected mosquitoes of different ages. Wolbachia-infected mosquitoes exhibit greater expression of some genes related to the melanization pathway, but not for those directly linked to dopamine production. Although dopamine levels were higher in Wolbachia-positive mosquitoes this was not consistent across all insect ages nor was it related to the previously described Wolbachia induced "bendy" and "shaky" phenotypes

The emergence of the cortisol circadian rhythm in monozygotic and dizygotic twin infants: the twin-pair synchrony

OBJECTIVE: Studies on the influence of genetic factors on the ontogeny of cortisol circadian rhythm in infants are lacking. This study evaluated the influence of twinning and the heritability on the age of emergence of salivary cortisol rhythm. DESIGN AND SUBJECTS: A longitudinal study was performed using salivary samples obtained during morning and night, at 2, 4, 8, 12, 16, 20 and 24 weeks of postnatal life in 34 infants, 10 monozygotic (MZ) and 7 dizygotic (DZ) twin pairs. Salivary cortisol was determined by radioimmunoassay (RIA). Zigosity was verified by DNA analysis of at least 13 short tandem repeat polymorphisms. Difference of the emergence of cortisol circadian rhythm, within each twin pair, the intraclass correlation coefficient and the heritability index (h(2)) were calculated. RESULTS: The mean (± SEM) age of emergence of salivary cortisol circadian rhythm was similar in MZ and DZ (7·8 ± 1·0 vs 7·4 ± 1·3 weeks). Seven pairs showed coincidence of the emergence of cortisol rhythm. Ten pairs were not coincident; among them the within-pair difference of emergence of salivary circadian rhythm was similar in both MZ and DZ groups. The intraclass correlation coefficients were rMZ = 0·60, P = 0·02; and rDZ = 0·65, P = 0·03, respectively. The heritability index (h(2)) was 0·21 (ns). CONCLUSIONS: Salivary circadian rhythm appeared at the same postnatal age in MZ and DZ twin infants. Although several physiological aspects might be involved, the heritability index, obtained in the present study, suggests less genetic than environmental impact on the age of the onset of the cortisol circadian rhythm. Our data also indicated that each twin-pair show synchrony because they probably shared prenatal and postnatal environmental synchronizers

Aerosol Mixing State: Measurements, Modeling, and Impacts

Atmospheric aerosols are complex mixtures of different chemical species, and individual particles exist in many different shapes and morphologies. Together, these characteristics contribute to the aerosol mixing state. This review provides an overview of measurement techniques to probe aerosol mixing state, discusses how aerosol mixing state is represented in atmospheric models at different scales, and synthesizes our knowledge of aerosol mixing state’s impact on climate‐relevant properties, such as cloud condensation and ice nucleating particle concentrations, and aerosol optical properties. We present these findings within a framework that defines aerosol mixing state along with appropriate mixing state metrics to quantify it. Future research directions are identified, with a focus on the need for integrating mixing state measurements and modeling.Key PointsWe define aerosol mixing state and connect it to the physicochemical properties of aerosol particlesWe discuss existing measurements and models to understand chemical and physicochemical mixing stateWe explain the connection between aerosol mixing state and climate‐relevant aerosol propertiesPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150540/1/rog20184_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150540/2/rog20184.pd

Toward an integrative understanding of social behavior: new models and new opportunities.

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur

Microguards and micromessengers of the genome

The regulation of gene expression is of fundamental importance to maintain organismal function and integrity and requires a multifaceted and highly ordered sequence of events. The cyclic nature of gene expression is known as ‘transcription dynamics’. Disruption or perturbation of these dynamics can result in significant fitness costs arising from genome instability, accelerated ageing and disease. We review recent research that supports the idea that an important new role for small RNAs, particularly microRNAs (miRNAs), is in protecting the genome against short-term transcriptional fluctuations, in a process we term ‘microguarding’. An additional emerging role for miRNAs is as ‘micromessengers’—through alteration of gene expression in target cells to which they are trafficked within microvesicles. We describe the scant but emerging evidence that miRNAs can be moved between different cells, individuals and even species, to exert biologically significant responses. With these two new roles, miRNAs have the potential to protect against deleterious gene expression variation from perturbation and to themselves perturb the expression of genes in target cells. These interactions between cells will frequently be subject to conflicts of interest when they occur between unrelated cells that lack a coincidence of fitness interests. Hence, there is the potential for miRNAs to represent both a means to resolve conflicts of interest, as well as instigate them. We conclude by exploring this conflict hypothesis, by describing some of the initial evidence consistent with it and proposing new ideas for future research into this exciting topic

Comparative susceptibility of mosquito populations in North Queensland, Australia to oral infection with dengue virus.

Dengue is the most prevalent arthropod-borne virus, with at least 40% of the world's population at risk of infection each year. In Australia, dengue is not endemic, but viremic travelers trigger outbreaks involving hundreds of cases. We compared the susceptibility of Aedes aegypti mosquitoes from two geographically isolated populations to two strains of dengue virus serotype 2. We found, interestingly, that mosquitoes from a city with no history of dengue were more susceptible to virus than mosquitoes from an outbreak-prone region, particularly with respect to one dengue strain. These findings suggest recent evolution of population-based differences in vector competence or different historical origins. Future genomic comparisons of these populations could reveal the genetic basis of vector competence and the relative role of selection and stochastic processes in shaping their differences. Lastly, we show the novel finding of a correlation between midgut dengue titer and titer in tissues colonized after dissemination

Can standardized patients replace physicians as OSCE examiners?

BACKGROUND: To reduce inter-rater variability in evaluations and the demand on physician time, standardized patients (SP) are being used as examiners in OSCEs. There is concern that SP have insufficient training to provide valid evaluation of student competence and/or provide feedback on clinical skills. It is also unknown if SP ratings predict student competence in other areas. The objectives of this study were: to examine student attitudes towards SP examiners; to compare SP and physician evaluations of competence; and to compare predictive validity of these scores, using performance on the multiple choice questions examination (MCQE) as the outcome variable. METHODS: This was a cross-sectional study of third-year medical students undergoing an OSCE during the Internal Medicine clerkship rotation. Fifty-two students rotated through 8 stations (6 physician, 2 SP examiners). Statistical tests used were Pearson's correlation coefficient, two-sample t-test, effect size calculation, and multiple linear regression. RESULTS: Most students reported that SP stations were less stressful, that SP were as good as physicians in giving feedback, and that SP were sufficiently trained to judge clinical skills. SP scored students higher than physicians (mean 90.4% +/- 8.9 vs. 82.2% +/- 3.7, d = 1.5, p < 0.001) and there was a weak correlation between the SP and physician scores (coefficient 0.4, p = 0.003). Physician scores were predictive of summative MCQE scores (regression coefficient = 0.88 [0.15, 1.61], P = 0.019) but there was no relationship between SP scores and summative MCQE scores (regression coefficient = -0.23, P = 0.133). CONCLUSION: These results suggest that SP examiners are acceptable to medical students, SP rate students higher than physicians and, unlike physician scores, SP scores are not related to other measures of competence

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models