Optimism bias and its relation to scenario valence, gender, sociality, and insecure attachment.

Optimism bias refers to the tendency to display unjustified high/low expectations of future positive/negative events. This study asked 202 participants to estimate the likelihood of 96 different events. We investigated optimism biases for both oneself and the general population, and how these biases are influenced by gender, valence of the event, sociality of the event, as well as attachment anxiety and attachment avoidance. We found that sociality interacted with gender, with the difference in optimism bias for social vs. alone events being larger among women than among men. Attachment anxiety mainly reduced the optimism bias among men deliberating over future alone situations, while attachment avoidance primarily reduced optimism bias among female respondents deliberating over future social interactions. These results may have implications for the well-being and motivation of differently attached men and women and ultimately inspire psychotherapy interventions

Enhanced sensitivity to optimistic cues is manifested in brain structure: A voxel-based morphometry study

Recent research shows that congruent outcomes are more rapidly (and incongruent less rapidly) detected when individuals receive optimistic rather than pessimistic cues, an effect that was termed optimism robustness. In the current voxel-based morphometry study, we examined whether optimism robustness has a counterpart in brain structure. The participants’ task was to detect two different letters (symbolizing monetary gain or loss) in a visual search matrix. Prior to each onset of the search matrix, two different verbal cues informed our participants about a high probability to gain (optimistic expectancy) or lose (pessimistic expectancy) money. The target presented was either congruent or incongruent with these induced expectancies. Optimism robustness revealed in the participants’ reaction times correlated positively with gray matter volume (GMV) in brain regions involved in selective attention (medial visual association area, intraparietal sulcus), emphasizing the strong intertwinement of optimistic expectancies and attention deployment. In addition, GMV in the primary visual cortex diminished with increasing optimism robustness, in line with the interpretation of optimism robustness arising from a global, context-oriented perception. Future studies should address the malleability of these structural correlates of optimism robustness. Our results may assist in the identification of treatment targets in depression

Predictive modeling of optimism bias using gray matter cortical thickness.

People have been shown to be optimistically biased when their future outcome expectancies are assessed. In fact, we display optimism bias (OB) toward our own success when compared to a rival individual's (personal OB [POB]). Similarly, success expectancies for social groups we like reliably exceed those we mention for a rival group (social OB [SOB]). Recent findings suggest the existence of neural underpinnings for OB. Mostly using structural/functional MRI, these findings rely on voxel-based mass-univariate analyses. While these results remain associative in nature, an open question abides whether MRI information can accurately predict OB. In this study, we hence used predictive modelling to forecast the two OBs. The biases were quantified using a validated soccer paradigm, where personal (self versus rival) and social (in-group versus out-group) forms of OB were extracted at the participant level. Later, using gray matter cortical thickness, we predicted POB and SOB via machine-learning. Our model explained 17% variance (R2 = 0.17) in individual variability for POB (but not SOB). Key predictors involved the rostral-caudal anterior cingulate cortex, pars orbitalis and entorhinal cortex-areas that have been associated with OB before. We need such predictive models on a larger scale, to help us better understand positive psychology and individual well-being

Cellular glycosylation affects Herceptin binding and sensitivity of breast cancer cells to doxorubicin and growth factors

Alterations in protein glycosylation are a key feature of oncogenesis and have been shown to affect cancer cell behaviour perturbing cell adhesion, favouring cell migration and metastasis. This study investigated the effect of N-linked glycosylation on the binding of Herceptin to HER2 protein in breast cancer and on the sensitivity of cancer cells to the chemotherapeutic agent doxorubicin (DXR) and growth factors (EGF and IGF-1). The interaction between Herceptin and recombinant HER2 protein and cancer cell surfaces (on-rate/off-rate) was assessed using a quartz crystal microbalance biosensor revealing an increase in the accessibility of HER2 to Herceptin following deglycosylation of cell membrane proteins (deglycosylated cells Bmax: 6.83 Hz; glycosylated cells Bmax: 7.35 Hz). The sensitivity of cells to DXR and to growth factors was evaluated using an MTT assay. Maintenance of SKBR-3 cells in tunicamycin (an inhibitor of N-linked glycosylation) resulted in an increase in sensitivity to DXR (0.1 µM DXR P<0.001) and a decrease in sensitivity to IGF-1 alone and to IGF-1 supplemented with EGF (P<0.001). This report illustrates the importance of N-linked glycosylation in modulating the response of cancer cells to chemotherapeutic and biological treatments and highlights the potential of glycosylation inhibitors as future combination treatments for breast cancer

Insulin-like growth factor-I receptor activity is essential for Kaposi's sarcoma growth and survival

Kaposi's sarcoma (KS) is a highly vascular tumour and is the most common neoplasm associated with human immunodeficiency virus (HIV-1) infection. Growth factors, in particular vascular endothelial growth factor (VEGF), have been shown to play an important role in its development. The role of insulin-like growth factors (IGFs) in the pathophysiology of different tumours led us to evaluate the role of IGF system in KS. The IGF-I receptors (IGF-IR) were identified by immunohistochemistry in biopsies taken from patients with different AIDS/HIV-related KS stages and on KSIMM cells (an established KS-derived cell line). Insulin-like growth factor-I is a growth factor for KSIMM cells with a maximum increase of 3H-thymidine incorporation of 130±27.6% (P<0.05) similar to that induced by VEGF and with which it is additive (281±13%) (P<0.05). Moreover, specific blockade of the receptor (either by α IR3 antibody or by picropodophyllin, a recently described selective IGF-IR tyrosine phosphorylation inhibitor) induced KSIMM apoptosis, suggesting that IGF-IR agonists (IGF-I and -II) mediate antiapoptotic signals for these cells. We were able to identify an autocrine loop essential for KSIMM cell survival in which IGF-II is the IGF-IR agonist secreted by the cells. In conclusion, IGF-I pathway inhibition is a promising therapeutical approach for KS tumours

Comparing personal and social optimism biases: Magnitude, overlap, modifiability, and links with social identification and expertise

Individuals are more optimistic about their own future than a comparable person’s future (personal optimism bias). In addition, they show overoptimism toward people or social groups they identify with compared with those they do not identify with (social optimism bias). However, commonalities and differences between personal and social forms of optimism bias remain to be addressed. Data from an experiment on anticipated performances in soccer (including 160 participants), revealed (a) comparable magnitudes of personal and social optimism biases, and (b) only partial overlap between personal and social optimism biases. We further found the magnitude of the biases to depend on (c) prior experience in the investigated area. Social optimism bias, however, did not correlate with (d) the extent to which the participants identified with a social in-group. In addition, we demonstrate that (e) despite the availability of objective feedback, both personal and social optimism biases are hard to overcome. Our data further suggest (f) the existence of qualitatively different social optimism biases; biases that can possibly be distinguished by their degree of automaticity or the adoption of a more affective vs. utilitarian stance. Consequently, the present research reveals that the phenomenon of social optimism bias needs further refinement to adequately address its specific sub-components

Data for "Optimism bias and its relation to scenario valence, gender, sociality, and insecure attachment"

This is the data that underlies the research on the submitted article: Optimism bias and its relation to scenario valence, gender, sociality, and insecure attachmen

Asymmetrical update of beliefs about future outcomes is driven by outcome valence and social group membership

People are eager to update their beliefs, such as a perceived risk, if they receive information that is better than expected but are reluctant to do so when the evidence is unfavourable. When estimating the likelihood of future outcomes, this phenomenon of asymmetrical belief update helps generate and maintain personal optimism bias. In this study, we investigated whether asymmetrical belief update also extends to estimating the future of other individuals. Specifically, we prompted respondents to assess the perceived likelihood of three social targets experiencing future positive and negative events: an in-group, a mild out-group and an extreme out-group. We then provided the respondents with feedback about the base rates of those events in the general population and prompted them to re-assess their initial estimates for all social targets. Respondents expected more positive than negative outcomes for the in-group and the mild out-group, but more negative outcomes for the extreme out-group. We also found an asymmetrical update of beliefs contingent on the valence of the future event and the social target. For negative outcomes, respondents updated more following good news than bad news, particularly for the mild out-group. For positive outcomes, respondents equally updated their beliefs following good news and bad news for the in-group and the mild out-group. However, they updated their beliefs significantly more following bad news than good news for the extreme out-group member. Our data thus reveal the strong and robust influence of social stereotypes on future expectancies for others

Predictive modeling of optimism bias using gray matter cortical thickness

Optimism bias (OB) is an expectancy bias, where people expect irrationally good future outcomes for themselves. Predictive modeling for OB would open new opportunities for estimating an overall state of well-being and understanding clinical conditions such as depression. To our knowledge, this is the first study attempting to address OB implementing a dedicated machine-learning based predictive modeling. We calculate people’s OB via a soccer paradigm, where participants rate their comparative chances for a successful outcome against their rival (i.e., personal OB) and a rival team (social OB). Later, using gray matter cortical thickness (CT) in a machine-learning framework, we predict both POB and SOB. Our results reveal a significant brain structure-based predictive model for experimentally assessed POB (Pearson’s r = 0.41, p = 0.007). Strongest predictors include left rostral and caudal ACC, right pars orbitalis and entorhinal cortex, all shown to have a role in OB before. Our confounder analysis suggests that the predictions are predominantly driven by CT measures and are not corrupted by demographic data (e.g., age and sex). There were no predictors recognized for estimating SOB. More of such predictive models on a large-scale data platform are needed, to help us understand positive psychology and individual well-being

Epidermal growth factor, latrophilin, and seven transmembrane domain-containing protein 1 marker, a novel angiogenesis marker

Florentina Serban, Stefan-Alexandru Artene, Ada Maria Georgescu, Stefana Oana Purcaru, Daniela Elise Tache, Oana Alexandru, Anica Dricu Department of Biochemistry, University of Medicine and Pharmacy of Craiova, Craiova, Romania Abstract: Epidermal growth factor, latrophilin, and seven transmembrane domain-containing protein 1 on chromosome 1 (ELTD1), an orphan adhesion G-protein coupled receptor, was reported as a regulator of angiogenesis, also involved in cancer progression and development. More recently, ELTD1 was identified as a potential new tumor marker for high-grade glioma. ELTD1, belongs to the G-protein coupled receptor superfamily that comprises the biggest receptor family in the human genome. Following the discovery of ELTD1 almost a decade ago, only a few research groups have attempted to find its role in normal and tumor cells, important information about this receptor remaining still unknown. The ELTD1 ligand has not currently been identified and intracellular signaling studies have not yet been performed in normal or tumor cells. Although the current published data on ELTD1 function and structure are rather limited, this receptor seems to be very important, not only as biomarker, but also as molecular target in glioblastoma. This review summarizes and discusses the current knowledge on ELTD1 structure, function, and its role in both physiological and tumoral angiogenesis. Keywords: ELTD1, angiogenesis, glioma, biomarke