Conversational Alignment: A Study of Neural Coherence and Speech Entrainment

Conversational alignment refers to the tendency for communication partners to adjust their verbal and non-verbal behaviors to become more like one another during the course of human interaction. This alignment phenomenon has been observed in neural patterns, specifically in the prefrontal areas of the brain (Holper et al., 2013; Cui et al., 2012; Dommer et al., 2012; Holper et al., 2012; Funane et al., 2011; Jiang et al., 2012); verbal behaviors such acoustic speech features (e.g., Borrie & Liss, 2014; Borrie et al., 2015; Lubold & Pon-Barry, 2014), phonological features (e.g., Babel, 2012; Pardo, 2006), lexical selection (e.g., Brennan & Clark, 1996; Garrod & Anderson, 1989), syntactic structure (e.g., Branigan, Pickering, & Cleland, 2000; Reitter, Moore, & Keller, 2006); and motor behaviors including body posture, facial expressions and breathing rate (e.g., Furuyama, Hayashi, & Mishima, 2005; Louwerse, Dale, Bard, & Jeuniaux, 2012; Richardson, March, & Schmit, 2005; Shockley, Santana, & Fowler, 2003; McFarland, 2001). While conversational alignment in itself, is a largely physical phenomenon, it has been linked to significant functional value, both in the cognitive and social domains. Cognitively, conversational alignment facilitates spoken message comprehension, enabling listeners to share mental models (Garrod & Pickering, 2004) and generate temporal predictions about upcoming aspects of speech. From a social perspective, behavioral alignment has been linked with establishing turn-taking behaviors, and with increased feelings of rapport, empathy, and intimacy between conversational pairs (e.g., Lee et al. 2010; Nind, & Macrae, 2009; Smith, 2008; Bailenson & Yee, 2005; Chartrand & Barg, 1999; Miles, Putman & Street, 1984; Street & Giles, 1982). Benus (2014), for example, observed that individuals who align their speech features are perceived as more socially attractive and likeable, and have interactions that are more successful. These cognitive and social benefits, associated with conversational alignment, have been observed in both linguistic and neural data (e.g., Holper et al., 2012; 2013, Cui et al. 2012; Jiang et al., 2012; Egetemeir et al., 2011; Stephens et al. 2010). The purpose of the current study was to examine conversational alignment as a multi-level communication phenomenon, by examining the relationship between neural and speech behaviors. To assess neural alignment, we used Near-Infrared Spectroscopy (NIRS), a non-invasive neuroimaging technology that detects cortical increases and decreases in the concentration of oxygenated and deoxygenated hemoglobin at multiple measurement sites to determine the rate that oxygen is being released and absorbed (Ferrari & Quaresima, 2012). While still considered a relatively new neural imaging technique, NIRS has been well established as an efficacious and effective data collection approach, particularly appropriate for social interaction research (e.g., Holper et al., 2013; Jiang et al., 2012; Holper et al., 2012; Suda et al., 2010). We utilized hyperscanning, a technique that allows for the quantitation of two simultaneous signals, allowing us to document neural alignment between two individuals (Babiloni & Astolfi, 2012). Recent studies have revealed neural alignment between two persons in cooperative states, including alignment in the right superior frontal cortices and medial prefrontal regions (Cui et al., 2012; Dommer et al., 2012; Funane et al., 2011). This increased prefrontal interbrain alignment has also been observed in other social interactions, including joint attention tasks (Dommer et al., 2012), imitation tasks (Holper et al., 2012), competitive games (Cheng et al., 2015, Duan et al., 2013), teaching-learning interactions (Holper et al., 2013), face- to-face communication (Jiang et al., 2012), mother-child interactions (Hirata et al., 2014), and during cooperative singing tasks (Osaka et al., 2015). Interestingly, Jiang et al. (2012) showed that increased neural alignment only occurred between conversational participants when they were speaking face-to-face, but not when participants had their backs facing one another. The authors speculated that the multi-sensory information, for example motor behaviors such as gestures, was required for neural alignment to occur

Nociceptin receptor antagonist SB 612111 decreases high fat diet binge eating

Binge eating is a dysregulated form of feeding behavior that occurs in multiple eating disorders including binge-eating disorder, the most common eating disorder. Feeding is a complex behavioral program supported through the function of multiple brain regions and influenced by a diverse array of receptor signaling pathways. Previous studies have shown the overexpression of the opioid neuropeptide nociceptin (orphanin FQ, N/OFQ) can induce hyperphagia, but the role of endogenous nociceptin receptor (NOP) in naturally occurring palatability-induced hyperphagia is unknown. In this study we adapted a simple, replicable form of binge eating of high fat food (HFD). We found that male and female C57BL/6J mice provided with daily one-hour access sessions to HFD eat significantly more during this period than those provided with continuous 24 hour access. This form of feeding is rapid and entrained. Chronic intermittent HFD binge eating produced hyperactivity and increased light zone exploration in the open field and light-dark assays respectively. Treatment with the potent and selective NOP antagonist SB 612111 resulted in a significant dose-dependent reduction in binge intake in both male and female mice, and, unlike treatment with the serotonin selective reuptake inhibitor fluoxetine, produced no change in total 24-hour food intake. SB 612111 treatment also significantly decreased non-binge-like acute HFD consumption in male mice. These data are consistent with the hypothesis that high fat binge eating is modulated by NOP signaling and that the NOP system may represent a promising novel receptor to explore for the treatment of binge eating

The extraordinarily bright optical afterglow of GRB 991208 and its host galaxy

Observations of the extraordinarily bright optical afterglow (OA) of GRB 991208 started 2.1 d after the event. The flux decay constant of the OA in the R-band is -2.30 +/- 0.07 up to 5 d, which is very likely due to the jet effect, and after that it is followed by a much steeper decay with constant -3.2 +/- 0.2, the fastest one ever seen in a GRB OA. A negative detection in several all-sky films taken simultaneously to the event implies either a previous additional break prior to 2 d after the occurrence of the GRB (as expected from the jet effect). The existence of a second break might indicate a steepening in the electron spectrum or the superposition of two events. Once the afterglow emission vanished, contribution of a bright underlying SN is found, but the light curve is not sufficiently well sampled to rule out a dust echo explanation. Our determination of z = 0.706 indicates that GRB 991208 is at 3.7 Gpc, implying an isotropic energy release of 1.15 x 10E53 erg which may be relaxed by beaming by a factor > 100. Precise astrometry indicates that the GRB coincides within 0.2" with the host galaxy, thus given support to a massive star origin. The absolute magnitude is M_B = -18.2, well below the knee of the galaxy luminosity function and we derive a star-forming rate of 11.5 +/- 7.1 Mo/yr. The quasi-simultaneous broad-band photometric spectral energy distribution of the afterglow is determined 3.5 day after the burst (Dec 12.0) implying a cooling frequency below the optical band, i.e. supporting a jet model with p = -2.30 as the index of the power-law electron distribution.Comment: Accepted for publication in Astronomy and Astrophysics, 9 pages, 6 figures (Fig. 3 and Fig. 4 have been updated

Muc5ac Expression Protects the Colonic Barrier in Experimental Colitis

Abstract included in the text

Selenium Toxicity to Honey Bee (Apis mellifera L.) Pollinators: Effects on Behaviors and Survival

We know very little about how soil-borne pollutants such as selenium (Se) can impact pollinators, even though Se has contaminated soils and plants in areas where insect pollination can be critical to the functioning of both agricultural and natural ecosystems. Se can be biotransferred throughout the food web, but few studies have examined its effects on the insects that feed on Se-accumulating plants, particularly pollinators. In laboratory bioassays, we used proboscis extension reflex (PER) and taste perception to determine if the presence of Se affected the gustatory response of honey bee (Apis mellifera L., Hymenoptera: Apidae) foragers. Antennae and proboscises were stimulated with both organic (selenomethionine) and inorganic (selenate) forms of Se that commonly occur in Se-accumulating plants. Methionine was also tested. Each compound was dissolved in 1 M sucrose at 5 concentrations, with sucrose alone as a control. Antennal stimulation with selenomethionine and methionine reduced PER at higher concentrations. Selenate did not reduce gustatory behaviors. Two hours after being fed the treatments, bees were tested for sucrose response threshold. Bees fed selenate responded less to sucrose stimulation. Mortality was higher in bees chronically dosed with selenate compared with a single dose. Selenomethionine did not increase mortality except at the highest concentration. Methionine did not significantly impact survival. Our study has shown that bees fed selenate were less responsive to sucrose, which may lead to a reduction in incoming floral resources needed to support coworkers and larvae in the field. If honey bees forage on nectar containing Se (particularly selenate), reductions in population numbers may occur due to direct toxicity. Given that honey bees are willing to consume food resources containing Se and may not avoid Se compounds in the plant tissues on which they are foraging, they may suffer similar adverse effects as seen in other insect guilds

Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.ABCFS: The Australian Breast Cancer Family Registry (ABCFR; 1992-1995) was supported by the Australian NHMRC, the New South Wales Cancer Council, and the Victorian Health Promotion Foundation (Australia), and by grant UM1CA164920 from the USA National Cancer Institute. The Genetic Epidemiology Laboratory at the University of Melbourne has also received generous support from Mr B. Hovey and Dr and Mrs R.W. Brown to whom we are most grateful. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Breast Cancer Susceptibility Variants and Mammographic Density 5 Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. BBCC: This study was funded in part by the ELAN-Program of the University Hospital Erlangen; Katharina Heusinger was funded by the ELAN program of the University Hospital Erlangen. BBCC was supported in part by the ELAN program of the Medical Faculty, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg. EPIC-Norfolk: This study was funded by research programme grant funding from Cancer Research UK and the Medical Research Council with additional support from the Stroke Association, British Heart Foundation, Department of Health, Research into Ageing and Academy of Medical Sciences. MCBCS: This study was supported by Public Health Service Grants P50 CA 116201, R01 CA 128931, R01 CA 128931-S01, R01 CA 122340, CCSG P30 CA15083, from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. MCCS: Melissa C. Southey is a National Health and Medical Research Council Senior Research Fellow and a Victorian Breast Cancer Research Consortium Group Leader. The study was supported by the Cancer Council of Victoria and by the Victorian Breast Cancer Research Consortium. MEC: National Cancer Institute: R37CA054281, R01CA063464, R01CA085265, R25CA090956, R01CA132839. MMHS: This work was supported by grants from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. (R01 CA128931, R01 CA 128931-S01, R01 CA97396, P50 CA116201, and Cancer Center Support Grant P30 CA15083). Breast Cancer Susceptibility Variants and Mammographic Density 6 NBCS: This study has been supported with grants from Norwegian Research Council (#183621/S10 and #175240/S10), The Norwegian Cancer Society (PK80108002, PK60287003), and The Radium Hospital Foundation as well as S-02036 from South Eastern Norway Regional Health Authority. NHS: This study was supported by Public Health Service Grants CA131332, CA087969, CA089393, CA049449, CA98233, CA128931, CA 116201, CA 122340 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. OOA study was supported by CA122822 and X01 HG005954 from the NIH; Breast Cancer Research Fund; Elizabeth C. Crosby Research Award, Gladys E. Davis Endowed Fund, and the Office of the Vice President for Research at the University of Michigan. Genotyping services for the OOA study were provided by the Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096. OFBCR: This work was supported by grant UM1 CA164920 from the USA National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. SASBAC: The SASBAC study was supported by Märit and Hans Rausing’s Initiative against Breast Cancer, National Institutes of Health, Susan Komen Foundation and Agency for Science, Technology and Research of Singapore (A*STAR). Breast Cancer Susceptibility Variants and Mammographic Density 7 SIBS: SIBS was supported by program grant C1287/A10118 and project grants from Cancer Research UK (grant numbers C1287/8459). COGS grant: Collaborative Oncological Gene-environment Study (COGS) that enabled the genotyping for this study. Funding for the BCAC component is provided by grants from the EU FP7 programme (COGS) and from Cancer Research UK. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post- Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAMEON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.This is the author accepted manuscript. The final version is available via American Association for Cancer Research at http://cancerres.aacrjournals.org/content/early/2015/04/10/0008-5472.CAN-14-2012.abstract

Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

The Mars 2020 Perseverance Rover Mast Camera Zoom (Mastcam-Z) Multispectral, Stereoscopic Imaging Investigation

Mastcam-Z is a multispectral, stereoscopic imaging investigation on the Mars 2020 mission’s Perseverance rover. Mastcam-Z consists of a pair of focusable, 4:1 zoomable cameras that provide broadband red/green/blue and narrowband 400-1000 nm color imaging with fields of view from 25.6° × 19.2° (26 mm focal length at 283 μrad/pixel) to 6.2° × 4.6° (110 mm focal length at 67.4 μrad/pixel). The cameras can resolve (≥ 5 pixels) ∼0.7 mm features at 2 m and ∼3.3 cm features at 100 m distance. Mastcam-Z shares significant heritage with the Mastcam instruments on the Mars Science Laboratory Curiosity rover. Each Mastcam-Z camera consists of zoom, focus, and filter wheel mechanisms and a 1648 × 1214 pixel charge-coupled device detector and electronics. The two Mastcam-Z cameras are mounted with a 24.4 cm stereo baseline and 2.3° total toe-in on a camera plate ∼2 m above the surface on the rover’s Remote Sensing Mast, which provides azimuth and elevation actuation. A separate digital electronics assembly inside the rover provides power, data processing and storage, and the interface to the rover computer. Primary and secondary Mastcam-Z calibration targets mounted on the rover top deck enable tactical reflectance calibration. Mastcam-Z multispectral, stereo, and panoramic images will be used to provide detailed morphology, topography, and geologic context along the rover’s traverse; constrain mineralogic, photometric, and physical properties of surface materials; monitor and characterize atmospheric and astronomical phenomena; and document the rover’s sample extraction and caching locations. Mastcam-Z images will also provide key engineering information to support sample selection and other rover driving and tool/instrument operations decisions

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4×10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat