Optimism Bias in Fans and Sports Reporters.

People are optimistic about their prospects relative to others. However, existing studies can be difficult to interpret because outcomes are not zero-sum. For example, one person avoiding cancer does not necessitate that another person develops cancer. Ideally, optimism bias would be evaluated within a closed formal system to establish with certainty the extent of the bias and the associated environmental factors, such that optimism bias is demonstrated when a population is internally inconsistent. Accordingly, we asked NFL fans to predict how many games teams they liked and disliked would win in the 2015 season. Fans, like ESPN reporters assigned to cover a team, were overly optimistic about their team's prospects. The opposite pattern was found for teams that fans disliked. Optimism may flourish because year-to-year team results are marked by auto-correlation and regression to the group mean (i.e., good teams stay good, but bad teams improve).

Improved Classification of Mammograms Following Idealized Training.

People often make decisions by stochastically retrieving a small set of relevant memories. This limited retrieval implies that human performance can be improved by training on idealized category distributions (Giguère & Love, 2013). Here, we evaluate whether the benefits of idealized training extend to categorization of real-world stimuli, namely classifying mammograms as normal or tumorous. Participants in the idealized condition were trained exclusively on items that, according to a norming study, were relatively unambiguous. Participants in the actual condition were trained on a representative range of items. Despite being exclusively trained on easy items, idealized-condition participants were more accurate than those in the actual condition when tested on a range of item types. However, idealized participants experienced difficulties when test items were very dissimilar from training cases. The benefits of idealization, attributable to reducing noise arising from cognitive limitations in memory retrieval, suggest ways to improve real-world decision making.

Qualification of embryonal carcinoma 2102Ep as a reference for human embryonic stem cell research.

As the number of human embryonic stem cell (hESC) lines increases, so does the need for systematic evaluation of each line's characteristics and potential. Comparisons between lines are complicated by variations in culture conditions, feeders, spontaneous differentiation, and the absence of standardized assays. These difficulties, combined with the inability of most labs to maintain more than a few lines simultaneously, compel the development of reference standards to which hESC lines can be compared. The use of a stable cell line as a reference standard offers many advantages. A line with a relatively unchanging hESC-like gene and protein expression pattern could be a positive control for developing assays. It can be used as a reference for genomics or proteomics studies, especially for normalizing results obtained in separate laboratories. Such a cell line should be widely available without intellectual property restraints, easily cultured without feeders, and resistant to spontaneous changes in phenotype. We propose that the embryonal carcinoma (EC) line 2102Ep meets these requirements. We compared the protein, gene, and microRNA expression of this cell line with those of hESC lines and alternative reference lines such as the EC line NTERA-2 and the karyotypically abnormal hESC line BG01V. The overall expression profiles of all these lines were similar, with exceptions reflecting the germ cell origins of EC. On the basis of global gene and microRNA expression, 2102Ep is somewhat less similar to hESC than the alternatives; however, 2102Ep expresses more hESC-associated microRNAs than NTERA-2 does, and fewer markers of differentiated fates.