Activation of kinase phosphorylation by heat-shift and mild heat-shock

Most cells activate intracellular signalling to recover from heat damage. An increase of temperature, known as HS (heat shock), induces two major signalling events: the transcriptional induction of HSPs (heat-shock proteins) and the activation of the MAPK (mitogen-activated protein kinase) cascade. We performed the present study to examine the effects of HS, induced by different experimental conditions, on various kinases [ERK (extracellular-signal-regulated kinase), JNK (c-Jun N-terminal kinase), p38, Akt, AMPK (AMP-activated protein kinase) and PKC (protein kinase C)]. We investigated by Western blot analysis the phosphorylation of MAPK as a measure of cellular responsiveness to heat shift (37°C) and mild HS (40°C) in different cell lines. The results of the study indicate that every cell line responded to heat shift, and to a greater extent to HS, increasing ERK and JNK phosphorylation, whereas variable effects on activation or inhibition of PKC, AMPK, Akt and p38 were observed. Besides the implications of intracellular signalling activated by heat variations, these data may be of technical relevance, indicating possible sources of error due to different experimental temperature conditions

Analysis of offsite Emergency Planning Zones (EPZ) for the Rocky Flats Plant

This project plan for Phase II summarizes the design of a project to complete analysis of offsite Emergency Planning Zones (EPZ) for the Rocky Flats Plant. Federal, state, and local governments develop emergency plans for facilities that may affect the public in the event of an accidental release of nuclear or hazardous materials. One of the purposes of these plans is to identify EPZs where actions might be necessary to protect public health. Public protective actions include sheltering, evacuation, and relocation. Agencies use EPZs to develop response plans and to determine needed resources. The State of Colorado, with support from the US Department of Energy (DOE) and Rocky Flats contractors, has developed emergency plans and EPZs for the Rocky Flats Plant periodically beginning in 1980. In Phase II, Interim Emergency Planning Zones Analysis, Maximum Credible Accident'' we will utilize the current Rocky Flats maximum credible accident (MCA), existing dispersion methodologies, and upgraded dosimetry methodologies to update the radiological EPZs. Additionally, we will develop recommendations for EPZs for nonradiological hazardous materials releases and evaluate potential surface water releases from the facility. This project will allow EG G Rocky Flats to meet current commitments to the state of Colorado and make steady, tangible improvements in our understanding of risk to offsite populations during potential emergencies at the Rocky Flats Plant. 8 refs., 5 figs., 4 tabs

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance:A Case Study in Lung Cancer Patient Preferences

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. Methods: A total of 307 patients with non–small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen’s weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Results: Most respondents (&gt;65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P &lt; 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P &lt; 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53–0.55). Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability. Most respondents found the DCE and SW tasks very easy or easy to understand and answer. A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.</p

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance:A Case Study in Lung Cancer Patient Preferences

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. Methods: A total of 307 patients with non–small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen’s weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Results: Most respondents (&gt;65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P &lt; 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P &lt; 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53–0.55). Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability. Most respondents found the DCE and SW tasks very easy or easy to understand and answer. A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.</p

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance:A Case Study in Lung Cancer Patient Preferences

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. Methods: A total of 307 patients with non–small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen’s weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Results: Most respondents (&gt;65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P &lt; 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P &lt; 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53–0.55). Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability. Most respondents found the DCE and SW tasks very easy or easy to understand and answer. A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.</p

A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

The factor structure of the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen distinct populations

There is considerable evidence that self-criticism plays a major role in the vulnerability to and recovery from psychopathology. Methods to measure this process, and its change over time, are therefore important for research in psychopathology and well-being. This study examined the factor structure of a widely used measure, the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen nonclinical samples (N = 7510) from twelve different countries: Australia (N = 319), Canada (N = 383), Switzerland (N = 230), Israel (N = 476), Italy (N = 389), Japan (N = 264), the Netherlands (N = 360), Portugal (N = 764), Slovakia (N = 1326), Taiwan (N = 417), the United Kingdom 1 (N = 1570), the United Kingdom 2 (N = 883), and USA (N = 331). This study used more advanced analyses than prior reports: a bifactor item-response theory model, a two-tier item-response theory model, and a non-parametric item-response theory (Mokken) scale analysis. Although the original three-factor solution for the FSCRS (distinguishing between Inadequate-Self, Hated-Self, and Reassured-Self) had an acceptable fit, two-tier models, with two general factors (Self-criticism and Self-reassurance) demonstrated the best fit across all samples. This study provides preliminary evidence suggesting that this two-factor structure can be used in a range of nonclinical contexts across countries and cultures. Inadequate-Self and Hated-Self might not by distinct factors in nonclinical samples. Future work may benefit from distinguishing between self-correction versus shame-based self-criticism.Peer reviewe

Multiple Group IRT Measurement Invariance Analysis of the Forms of Self-Criticising/Attacking and Self-Reassuring Scale in Thirteen International Samples

The purpose of this study was to examine the measurement invariance of the Forms of Self-Criticising/Attacking & Self-Reassuring Scale (FSCRS) in terms of Item Response Theory differential test functioning in thirteen distinct samples (N = 7714) from twelve different countries. We assessed differential test functioning for the three FSCRS subscales, Inadequate-Self, Hated-Self and Reassured-Self separately. 32 of the 78 pairwise comparisons between samples for Inadequate-Self, 42 of the 78 pairwise comparisons for Reassured-Self and 54 of the 78 pairwise comparisons for Hated-Self demonstrated no differential test functioning, i.e. measurement invariance. Hated-Self was the most invariant of the three subscales, suggesting that self-hatred is similarly perceived across different cultures. Nonetheless, all three subscales of FSCRS are sensitive to cross-cultural differences. Considering the possible cultural and linguistic differences in the expression of self-criticism and self-reassurance, future analyses of the meanings and connotations of these constructs across the world are necessary in order to develop or tailor a scale which allows cross-cultural comparisons of various treatment outcomes related to self-criticism

How khipus indicated labour contributions in an Andean village: an explanation of colour banding, seriation and ethnocategories

This research was supported by a Global Exploration Grant from the National Geographic Society (GEFNE120-14).New archival and ethnographic evidence reveals that Inka style khipus were used in the Andean community of Santiago de Anchucaya to record contributions to communal labour obligations until the 1940s. Archival testimony from the last khipu specialist in Anchucaya, supplemented by interviews with his grandson, provides the first known expert explanation for how goods, labour obligations, and social groups were indicated on Inka style Andean khipus. This evidence, combined with the analysis of Anchucaya khipus in the Museo Nacional de Arqueología, Antropología y Historia Peruana, furnishes a local model for the relationship between the two most frequent colour patterns (colour banding and seriation) that occur in khipus. In this model, colour banding is associated with individual data whilst seriation is associated with aggregated data. The archival and ethnographic evidence also explains how labour and goods were categorized in uniquely Andean ways as they were represented on khipus.PostprintPeer reviewe