Therapeutic Strategies Targeting Pancreatic Islet ß-Cell Proliferation, Regeneration, and Replacement.

Diabetes results from insufficient insulin production by pancreatic islet ß-cells or a loss of ß-cells themselves. Restoration of regulated insulin production is a predominant goal of translational diabetes research. Here, we provide a brief overview of recent advances in the fields of ß-cell proliferation, regeneration, and replacement. The discovery of therapeutic targets and associated small molecules has been enabled by improved understanding of ß-cell development and cell cycle regulation, as well as advanced high-throughput screening methodologies. Important findings in ß-cell transdifferentiation, neogenesis, and stem cell differentiation have nucleated multiple promising therapeutic strategies. In particular, clinical trials are underway using in vitro-generated ß-like cells from human pluripotent stem cells. Significant challenges remain for each of these strategies, but continued support for efforts in these research areas will be critical for the generation of distinct diabetes therapies.

The perception of a familiar face is no more than the sum of its parts.

Why do faces become easier to recognize with repeated exposure? Previous research has suggested that familiarity may induce a qualitative shift in visual processing from an independent analysis of individual facial features to analysis that includes information about the relationships among features (Farah, Wilson, Drain, & Tanaka Psychological Review, 105, 482-498, 1998; Maurer, Grand, & Mondloch Trends in Cognitive Science, 6, 255-260, 2002). We tested this idea by using a "summation-at-threshold" technique (Gold, Mundy, & Tjan Psychological Science, 23, 427-434, 2012; Nandy & Tjan Journal of Vision, 8, 3.1-20, 2008), in which an observer's ability to recognize each individual facial feature shown independently is used to predict their ability to recognize all of the features shown in combination. We find that, although people are better overall at recognizing familiar as opposed to unfamiliar faces, their ability to integrate information across features is similar for unfamiliar and highly familiar faces and is well predicted by their ability to recognize each of the facial features shown in isolation. These results are consistent with the idea that familiarity has a quantitative effect on the efficiency with which information is extracted from individual features, rather than a qualitative effect on the process by which features are combined.

The efficiency of dynamic and static facial expression recognition.

Unlike frozen snapshots of facial expressions that we often see in photographs, natural facial expressions are dynamic events that unfold in a particular fashion over time. But how important are the temporal properties of expressions for our ability to reliably extract information about a person's emotional state? We addressed this question experimentally by gauging human performance in recognizing facial expressions with varying temporal properties relative to that of a statistically optimal ("ideal") observer. We found that people recognized emotions just as efficiently when viewing them as naturally evolving dynamic events, temporally reversed events, temporally randomized events, or single images frozen in time. Our results suggest that the dynamic properties of human facial movements may play a surprisingly small role in people's ability to infer the emotional states of others from their facial expressions.