Assessment of multiple measures of honey bee (Apis mellifera ligustica) and horse (Equus ferus caballus) responding on fixed interval schedules: An individual versus aggregate analysis

We compared different measures of temporal control of two species' responding when reinforced on fixed interval schedules of reinforcement. The measures that were evaluated are: cumulative response curves, response bin tallies, quarter life, index of curvature, post-reinforcement pause, inter-response times, trial duration, and response duration. Honey bee (Apis mellifera ligustica) and horse (Equus ferus caballus) responding was exposed to fixed interval schedules of reinforcement because the former species has not demonstrated evidence of temporally control responding (Grossmann, 1973) while the latter has demonstrated evidence of temporally control responding (Myers and Mesker, 1960); comparing response patterns from temporally controlled versus non-temporally controlled fixed interval performances revealed what measures do, or do not, convincingly operationalize temporal control. To contrast the effectiveness of an individual versus aggregate analyses of these measures of temporal control, both Observation Oriented Modeling and null hypothesis significance testing analysis methods were employed and compared. For most measures and assessments, horses demonstrated consistent evidence of responding coming under temporal control while honey bees demonstrated inconsistent evidence of responding coming under temporal control of the fixed interval schedules

New Paradigm to Analyze Extensive Post-reinforcement or Social Reinforcement Delays in Free-flying Honey Bees (Apis Mellifera)

We have developed a novel paradigm to study and analyze how free-flying honey bees (Apis mellifera) react when presented with varying schedules of post-reinforcement delays of either 0s, 300s, or 600s. We measured inter-visit-interval, response length, inter-response-time, and response rate in addition to monitoring temperature. Honey bees exposed to these large intervals react in multiple patterns compared to groups not encountering delays. Three patterns of inter-visit-intervals were observed, and in most cases, the experimental bees had larger inter-visit-intervals when encountering the post-reinforcement delays. Based on response length, we believe adjunctive responses were observed during the delay intervals. We saw no group differences in inter-response time. Honey bees with larger response rates tended to not finish the experiment while the removal of the delay intervals increased subject response rates for those subjects that completed the trials. Our findings and protocol lead us to consider we have in fact studied social pre-reinforcement delays.Department of Psycholog

Auditory startle response predicts introversion: an individual analysis

We assessed a possible link between the Introversion/Extraversion spectrum and sensori-motor gating and predicted self-reported introverts would have more sensitive sensori-motor gating pathways than extraverts at the individual subject level. 28 subjects self-identified as introverts or extraverts; individuals that self-identified as both introverted and extraverted were classified as ambiverts . Participants\u27orbicularis oculus muscles were electromyographically measured while abrupt auditory stimuli ranging from 50 to 100 decibels were played over headphones. As predicted, introverts exhibited greater electromyographical frequencies and magnitudes of response to stimuli at almost all levels of stimulus intensity. These results indicate introverts tend to be more sensitive, on a physiological level, to incoming stimuli compared to extraverts; this finding counters explanations of introversion as a purely social construct. Interestingly, a further and unpredicted pattern of three distinct groups was also observed. These groups are not organized along the lines of introversion/extraversion and may be linked to the concept of neuroticism

Acoustics and oceanographic observations collected during the QPE Experiment by Research Vessels OR1, OR2 and OR3 in the East China Sea in the Summer of 2009

This document describes data, sensors, and other useful information pertaining to the ONR sponsored QPE field program to quantify, predict and exploit uncertainty in observations and prediction of sound propagation. This experiment was a joint operation between Taiwanese and U.S. researchers to measure and assess uncertainty of predictions of acoustic transmission loss and ambient noise, and to observe the physical oceanography and geology that are necessary to improve their predictability. This work was performed over the continental shelf and slope northeast of Taiwan at two sites: one that was a relatively flat, homogeneous shelf region and a more complex geological site just shoreward of the shelfbreak that was influenced by the proximity of the Kuroshio Current. Environmental moorings and ADCP moorings were deployed and a shipboard SeaSoar vehicle was used to measure environmental spatial structure. In addition, multiple bottom moored receivers and a horizontal hydrophone array were deployed to sample transmission loss from a mobile source and ambient noise. The acoustic sensors, environmental sensors, shipboard resources, and experiment design, and their data, are presented and described in this technical report.Funding was provided by the Office of Naval Research under Contract No. N00014-08-1-076

Party identification and party closeness in comparative perspective

The present analysis uses data from 1974 and 1981 U. S. cross sections, which incorporate a panel, to compare the standard NES measure of party identification (ID) with a measure of partisanship derived from a party closeness question widely employed in cross-national research. Important features of the two scales are examined by transforming the closeness measure into a scale of very close, fairly close, not very close, and no preference corresponding to the seven-point ID scale. The scales are highly correlated and are similar in their reliability. More than 75% of the “independents” in the ID scale choose a party in the closeness version, and over half of these select the “fairly close” category. Respondents do not volunteer that they are independents when that alternative is not stated in the question.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45482/1/11109_2004_Article_BF00990552.pd

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment