The Optimism Bias: Is It Adaptive In Academic Settings?

2012 ◽  
Vol 22 (3) ◽  
pp. 415-417
Author(s):  
Caryl Ochse
2012 ◽  
Vol 5 (3) ◽  
pp. 25
Author(s):  
MARY ANN MOON
Keyword(s):  

2009 ◽  
Author(s):  
Petra Alfred ◽  
Carita Devilbiss ◽  
Donald Headley ◽  
Valerie Rice ◽  
Conne Bazley ◽  
...  

2006 ◽  
Author(s):  
Kristiana Powers ◽  
Melanie L. Bromley ◽  
Chaz D. Esparza ◽  
James C. Kaufman
Keyword(s):  

2006 ◽  
Author(s):  
Bryce Sullivan ◽  
Jennifer M. Craft ◽  
Jameca W. Falconer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Roko Duplancic ◽  
Darko Kero

AbstractWe describe a novel approach for quantification and colocalization of immunofluorescence (IF) signals of multiple markers on high-resolution panoramic images of serial histological sections utilizing standard staining techniques and readily available software for image processing and analysis. Human gingiva samples stained with primary antibodies against the common leukocyte antigen CD45 and factors related to heparan sulfate glycosaminoglycans (HS GAG) were used. Expression domains and spatial gradients of IF signals were quantified by histograms and 2D plot profiles, respectively. The importance of histomorphometric profiling of tissue samples and IF signal thresholding is elaborated. This approach to quantification of IF staining utilizes pixel (px) counts and comparison of px grey value (GV) or luminance. No cell counting is applied either to determine the cellular content of a given histological section nor the number of cells positive to the primary antibody of interest. There is no selection of multiple Regions-Of-Interest (ROIs) since the entire histological section is quantified. Although the standard IF staining protocol is applied, the data output enables colocalization of multiple markers (up to 30) from a given histological sample. This can serve as an alternative for colocalization of IF staining of multiple primary antibodies based on repeating cycles of staining of the same histological section since those techniques require non standard staining protocols and sophisticated equipment that can be out of reach for small laboratories in academic settings. Combined with the data from ontological bases, this approach to quantification of IF enables creation of in silico virtual disease models.


2021 ◽  
Author(s):  
J. E. C. Adriaense ◽  
V. Šlipogor ◽  
S. Hintze ◽  
L. Marshall ◽  
C. Lamm ◽  
...  

AbstractEmotional contagion is suggested to facilitate group life by enhancing synchronized responses to the environment. Cooperative breeders are an example of a social system that requires such intricate coordination between individuals. Therefore, we studied emotional contagion in common marmosets by means of a judgement bias test. Demonstrators were exposed to an emotion manipulation (i.e., positive, negative, control), and observers perceived only the demonstrator’s behaviour. We predicted that the positive or negative states of the demonstrator would induce matching states in the observer, indicating emotional contagion. All subjects’ emotional states were assessed through behaviour and cognition, the latter by means of a judgement bias test. Behavioural results showed a successful emotion manipulation of demonstrators, with manipulation-congruent expressions (i.e., positive calls in the positive condition, and negative calls and pilo-erect tail in the negative condition). Observers showed no manipulation-congruent expressions, but showed more scratching and arousal after the positive manipulation. Concerning the judgement bias test, we predicted that subjects in a positive state should increase their response to ambiguous cues (i.e., optimism bias), and subjects in a negative state should decrease their response (i.e., pessimism bias). This prediction was not supported as neither demonstrators nor observers showed such bias in either manipulation. Yet, demonstrators showed an increased response to the near-positive cue, and additional analyses showed unexpected responses to the reference cues, as well as a researcher identity effect. We discuss all results combined, including recently raised validation concerns of the judgement bias test, and inherent challenges to empirically studying emotional contagion.


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