Individual Differences in Dopamine Are Associated with Reward Discounting in Clinical Groups But Not in Healthy Adults.

Some people are more willing to make immediate, risky, or costly reward-focused choices than others, which has been hypothesized to be associated with individual differences in dopamine (DA) function. In two studies using PET imaging, one empirical (Study 1: N = 144 males and females across 3 samples) and one meta-analytic (Study 2: N = 307 across 12 samples), we sought to characterize associations between individual differences in DA and time, probability, and physical effort discounting in human adults. Study 1 demonstrated that individual differences in DA D2-like receptors were not associated with time or probability discounting of monetary rewards in healthy humans, and associations with physical effort discounting were inconsistent across adults of different ages. Meta-analytic results for temporal discounting corroborated our empirical finding for minimal effect of DA measures on discounting in healthy individuals but suggested that associations between individual differences in DA and reward discounting depend on clinical features. Addictions were characterized by negative correlations between DA and discounting, but other clinical conditions, such as Parkinson's disease, obesity, and attention-deficit/hyperactivity disorder, were characterized by positive correlations between DA and discounting. Together, the results suggest that trait differences in discounting in healthy adults do not appear to be strongly associated with individual differences in D2-like receptors. The difference in meta-analytic correlation effects between healthy controls and individuals with psychopathology suggests that individual difference findings related to DA and reward discounting in clinical samples may not be reliably generalized to healthy controls, and vice versa.SIGNIFICANCE STATEMENT Decisions to forgo large rewards for smaller ones due to increasing time delays, uncertainty, or physical effort have been linked to differences in dopamine (DA) function, which is disrupted in some forms of psychopathology. It remains unclear whether alterations in DA function associated with psychopathology also extend to explaining associations between DA function and decision making in healthy individuals. We show that individual differences in DA D2 receptor availability are not consistently related to monetary discounting of time, probability, or physical effort in healthy individuals across a broad age range. By contrast, we suggest that psychopathology accounts for observed inconsistencies in the relationship between measures of DA function and reward discounting behavior

Palbociclib plus letrozole as first-line therapy in estrogen receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer with extended follow-up.

PurposeIn the initial PALOMA-2 (NCT01740427) analysis with median follow-up of 23 months, palbociclib plus letrozole significantly prolonged progression-free survival (PFS) in women with estrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC) [hazard ratio (HR) 0.58; P < 0.001]. Herein, we report results overall and by subgroups with extended follow-up.MethodsIn this double-blind, phase 3 study, post-menopausal women with ER+/HER2- ABC who had not received prior systemic therapy for their advanced disease were randomized 2:1 to palbociclib-letrozole or placebo-letrozole. Endpoints include investigator-assessed PFS (primary), safety, and patient-reported outcomes (PROs).ResultsAfter a median follow-up of approximately 38 months, median PFS was 27.6 months for palbociclib-letrozole (n = 444) and 14.5 months for placebo-letrozole (n = 222) (HR 0.563; 1-sided P < 0.0001). All subgroups benefited from palbociclib treatment. The improvement of PFS with palbociclib-letrozole was maintained in the next 2 subsequent lines of therapy and delayed the use of chemotherapy (40.4 vs. 29.9 months for palbociclib-letrozole vs. placebo-letrozole). Safety data were consistent with the known profile. Patients' quality of life was maintained.ConclusionsWith approximately 15 months of additional follow-up, palbociclib plus letrozole continued to demonstrate improved PFS compared with placebo plus letrozole in the overall population and across all patient subgroups, while the safety profile remained favorable and quality of life was maintained. These data confirm that palbociclib-letrozole should be considered the standard of care for first-line therapy in patients with ER+/HER2- ABC, including those with low disease burden or long disease-free interval. Sponsored by Pfizer; ClinicalTrials.gov: NCT01740427

Rotation Curve Fitting Model

One key piece of evidence for dark matter is the flat rotation curve problem: the disagreement between measured galactic rotation curves and their luminous mass. A novel solution to this problem is presented here. A model of relativistic frame effects on Doppler shifts due to the slightly curved frames of an emitting galaxy and the Milky Way is derived. This model predicts observed Doppler shifted spectra (in excess of the luminous mass) based only on the observed luminous matter profile and one free model parameter. Fits to the 175 galaxies reported in the SPARC database of galactic rotation profiles and accurate photometry measurements are compared between this novel model and dark matter and MOND (RAR) models. We find on the SPARC sample of 175 galaxies; that MOND-RAR has an average reduced chisquare of $\chi^2_r = 4.22$ for 175 galaxies fitted, the isothermal dark matter model has $\chi^2_r = 1.90$ for 165 galaxies fitted, and the new model we present has $\chi^2_r = 2.39$ for 172 galaxies fitted. Implications of this model are discussed.Comment: 27 pages, 9 figure

Social cognitive processes explain bias in juror decisions

Jury decisions are among the most consequential social decisions in which bias plays a notable role. While courts take measures to reduce the influence of non-evidentiary factors, jurors may still incorporate biases into their decisions. One common bias, crime-type bias, is the extent to which the perceived strength of a prosecutor&rsquo;s case depends on the severity of the crime. Moral judgment, affect and social cognition have been proposed as core processes underlying this and other biases. Behavioral evidence alone has been insufficient to distinguish these explanations. To identify the mechanism underlying crime-type bias, we collected functional magnetic resonance imaging patterns of brain activation from mock jurors reading criminal scenarios. Brain patterns from crime-type bias were most similar to those associated with social cognition (mentalizing and racial bias) but not affect or moral judgment. Our results support a central role for social cognition in juror decisions and suggest that crime-type bias and cultural bias may arise from similar mechanisms. &nbsp;</p

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets

Cultural antecedents of sustainability and regional economic development - a study of SME ‘Mittelstand’ firms in Baden-Württemberg (Germany)

This paper examines behavioural and regional/geographic cultural antecedents of sustainability in SME contexts. The study identifies prevailing macro-representations of sustainability in the literature and highlights an over-focus on large firms constituting the predominant unit of analysis. Moreover, there is a propensity in the literature to view sustainability primarily in terms of ‘environmental’ – closely linked to a corporate strategic imperative narrative of economic competitiveness and profitability. Overall, this perspective tends to generate accounts which are acultural, apolitical and ahistorical in terms of innovative actions and sustainability practices. In response, using a conceptual framework of moral identity, the paper develops a more micro-foundational insight to sustainability (developing notions of ‘tangible’ and ‘intangible’) and examines regional economic development attitudes at individual owner-manager/managing director level in small-to-medium-sized firms. Methodologically, an inductively framed interview schedule was employed with owner-managers and managing directors (n = 30) of manufacturing SMEs in the Baden-Württemberg region (Germany). The study identified a range of micro-foundational behavioural antecedents operating in the sample companies. In particular, it underlined that many of the SME owner-managers/managing directors expressed views informed by a particular moral identity connected with a perspective rooted in regionally bound, longstanding and ‘expected’ behaviours of trust, fairness, honesty and community responsibility

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed