Crossing the Line: Evidence for the Categorization Theory of Spatial Voting

Bølstad and Dinas (2017) propose a model of spatial voting, based on social identity theory, that suggests supporting a candidate/policy on the other side of the ideological spectrum has a disutility that is not accounted for by common spatial models. Unfortunately, the data they use cannot speak directly to whether the disutility arises because individuals perceive their ideology as a social identity. We present the results of an experimental study that measures the norm against crossing the ideological spectrum; tests the cost of doing so, controlling for spatial effects; and demonstrates that this cost increases with the salience and strength of identity norms. By demonstrating the norm mechanism for the disutility of crossing the ideological spectrum, we provide strong support for B&D\u27s model

Smart SU-8 Pillars Implemented in a Microfluidic Bioreactor for Continuous Measurement of Glucose

In this contribution we explore a new and simple approach for immobilizing enzymes like glucose oxidase on SU-8 surfaces to develop a smart substrate integrated in microfluidics. SU-8 is a well known photoresist often used in microfluidic prototyping. Immobilization of enzymes on such substance can open new possibilities in the microfabrication of enzyme biosensors and bioreactors. To demonstrate the consistency of this approach, we describe the design, fabrication and the simple functionalization of a microfluidic bioreactor employing smart SU-8 pillars for continuous amperometric measurement of glucose. The results reveal the possibility of simply binding enzymes on SU-8 surface. Moreover, a significant improvement in the linear response range is observed compared to the previous published amperometric microfluidic glucose sensors

Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry:A network analysis

BACKGROUND: Research into the clustering of symptoms may improve the understanding of the underlying mechanisms that affect survivors' symptom burden. This study applied network analyses in a balanced sample of cancer survivors to 1) explore the clustering of symptoms and 2) assess differences in symptom clustering between cancer types, treatment regimens, and short‐term and long‐term survivors. METHODS: This study used cross‐sectional survey data, collected between 2008 and 2018, from the population‐based Patient Reported Outcomes Following Initial Treatment and Long Term Evaluation of Survivorship registry, which included survivors of 7 cancer types (colorectal cancer, breast cancer, ovarian cancer, thyroid cancer, chronic lymphocytic leukemia, Hodgkin lymphoma, and non‐Hodgkin lymphoma). Regularized partial correlation network analysis was used to explore and visualize the associations between self‐reported symptoms (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire) and the centrality of these symptoms in the network (ie, how strongly a symptom was connected to other symptoms) for the total sample and for subgroups separately. RESULTS: In the total sample (n = 1330), fatigue was the most central symptom in the network with moderate direct relationships with emotional symptoms, cognitive symptoms, appetite loss, dyspnea, and pain. These relationships persisted after adjustments for sociodemographic and clinical characteristics. Connections between fatigue and emotional symptoms, appetite loss, dyspnea, and pain were consistently found across all cancer types (190 for each), treatment regimens, and short‐term and long‐term survivors. CONCLUSIONS: In a heterogenous sample of cancer survivors, fatigue was consistently the most central symptom in all networks. Although longitudinal data are needed to build a case for the causal nature of these symptoms, cancer survivorship rehabilitation programs could focus on fatigue to reduce the overall symptom burden