Loss, gain and choice difficulty in gambling patients: Neural and behavioural processes.

Impaired decision-making is often displayed by individuals suffering from gambling disorder (GD). Since there are a variety of different phenomena influencing decision-making, we focused in this study on the effects of GD on neural and behavioural processes related to loss aversion and choice difficulty. Behavioural responses as well as brain images of 23 patients with GD and 20 controls were recorded while they completed a mixed gambles task, where they had to decide to either accept or reject gambles with different amounts of potential gain and loss. We found no behavioural loss aversion in either group and no group differences regarding loss and gain-related choice behaviour, but there was a weaker relation between choice difficulty and decision time in patients with GD. Similarly, we observed no group differences in processing of losses or gains, but choice difficulty was weaker associated with brain activity in the right anterior insula and anterior cingulate cortex in patients with GD. Our results showed for the first time the effects of GD on neural processes related to choice difficulty. In addition, our findings on choice difficulty give new insights on the psychopathology of GD and on neural processes related to impaired decision-making in GD.

Impact of the Timing of Mechanical Circulatory Support on the Outcomes in Myocardial Infarction-Related Cardiogenic Shock: Subanalysis of the PREPARE CS Registry.

(1) Background: Mechanical circulatory support (MCS) in myocardial infarction-associated cardiogenic shock is subject to debate. This analysis aims to elucidate the impact of MCS's timing on patient outcomes, based on data from the PREPARE CS registry. (2) Methods: The PREPARE CS prospective registry includes patients who experienced cardiogenic shock (SCAI classes C-E) and were subsequently referred for cardiac catheterization. Our present analysis included a subset of this registry, in whom MCS was used and who underwent coronary intervention due to myocardial infarction. Patients were categorized into an Upfront group and a Procedural group, depending on the timing of MCS's introduction in relation to their PCI. The endpoint was in-hospital mortality. (3) Results: In total, 71 patients were included. MCS was begun prior to PCI in 33 (46%) patients (Upfront), whereas 38 (54%) received MCS during or after the initiation of PCI (Procedural). The groups' baseline characteristics and hemodynamic parameters were comparable. The Upfront group had a higher utilization of the Impella® device compared to extracorporeal membrane oxygenation (67% vs. 33%), while the Procedural group exhibited a balanced use of both (50% vs. 50%). Most patients suffered from multi-vessel disease in both groups (82% vs. 84%, respectively; p = 0.99), and most patients required a complex PCI procedure; the latter was more prevalent in the Upfront group (94% vs. 71%, respectively; p = 0.02). Their rates of complete revascularization were comparable (52% vs. 34%, respectively; p = 0.16). Procedural CPR was significantly more frequent in the Procedural group (45% vs. 79%, p < 0.05); however, in-hospital mortality was similar (61% vs. 79%, respectively; p = 0.12). (4) Conclusions: The upfront implantation of MCS in myocardial infarction-associated CS did not provide an in-hospital survival benefit.

DoE-based medium optimization for improved biosurfactant production with Aureobasidium pullulans.

Polyol lipids (a.k.a. liamocins) produced by the polyextremotolerant, yeast-like fungus Aureobasidium pullulans are amphiphilic molecules with high potential to serve as biosurfactants. So far, cultivations of A. pullulans have been performed in media with complex components, which complicates further process optimization due to their undefined composition. In this study, we developed and optimized a minimal medium, focusing on biosurfactant production. Firstly, we replaced yeast extract and peptone in the best-performing polyol lipid production medium to date with a vitamin solution, a trace-element solution, and a nitrogen source. We employed a design of experiments approach with a factor screening using a two-level-factorial design, followed by a central composite design. The polyol lipid titer was increased by 56% to 48 g L-1, and the space-time yield from 0.13 to 0.20 g L-1 h-1 in microtiter plate cultivations. This was followed by a successful transfer to a 1 L bioreactor, reaching a polyol lipid concentration of 41 g L-1. The final minimal medium allows the investigation of alternative carbon sources and the metabolic pathways involved, to pinpoint targets for genetic modifications. The results are discussed in the context of the industrial applicability of this robust and versatile fungus.

The SAFE Model: State Authenticity as a Function of Three Types of Fit.

The SAFE model asserts that state authenticity stems from three types of fit to the environment. Across two studies of university students, we validated instruments measuring self-concept, goal, and social fit as unique predictors of state authenticity. In Study 1 (N = 969), relationships between fit and state authenticity were robust to controlling for conceptually similar and distinct variables. Using experience sampling methodology, Study 2 (N = 269) provided evidence that fit and authenticity co-vary at the state (i.e., within-person) level, controlling for between-person effects. Momentary variation in each fit type predicted greater state authenticity, willingness to return to the situation, and state attachment to one's university. Each fit type was also predicted by distinct contextual features (e.g., location, activity, company). Supporting a theorized link to cognitive fluency, situations eliciting self-concept fit elicited higher working memory capacity and lower emotional burnout. We discuss the implications of fit in educational contexts.

The lay of the land: Associations between environmental features and personality.

OBJECTIVE: Personality traits cluster across countries, regions, cities, and neighborhoods. What drives the formation of these clusters? Ecological theory suggests that physical locations shape humans' patterns of behaviors and psychological characteristics. Based on this theory, we examined whether and how differential land-cover relates to individual personality. METHOD: We followed a preregistered three-pronged analysis approach to investigate the associations between personality (N = 2,690,878) and land-cover across the United States. We used eleven land-cover categories to classify landscapes and tested their association with personality against broad physical and socioeconomic factors. RESULTS: Urban areas were positively associated with openness to experience and negatively associated with conscientiousness. Coastal areas were positively associated with openness to experience and neuroticism but negatively associated with agreeableness and conscientiousness. Cultivated areas were negatively associated with openness. Landscapes at the periphery of human activity, such as shrubs, bare lands, or permanent snows, were not reliably associated with personality traits. CONCLUSIONS: Bivariate correlations, multilevel, and random forest models uncovered robust associations between landscapes and personality traits. These findings align with ecological theory suggesting that an individual's environment contributes to their behaviors, thoughts, and feelings.

The Misinformation Susceptibility Test (MIST): A psychometrically validated measure of news veracity discernment.

Interest in the psychology of misinformation has exploded in recent years. Despite ample research, to date there is no validated framework to measure misinformation susceptibility. Therefore, we introduce Verification done, a nuanced interpretation schema and assessment tool that simultaneously considers Veracity discernment, and its distinct, measurable abilities (real/fake news detection), and biases (distrust/naïvité-negative/positive judgment bias). We then conduct three studies with seven independent samples (Ntotal = 8504) to show how to develop, validate, and apply the Misinformation Susceptibility Test (MIST). In Study 1 (N = 409) we use a neural network language model to generate items, and use three psychometric methods-factor analysis, item response theory, and exploratory graph analysis-to create the MIST-20 (20 items; completion time < 2 minutes), the MIST-16 (16 items; < 2 minutes), and the MIST-8 (8 items; < 1 minute). In Study 2 (N = 7674) we confirm the internal and predictive validity of the MIST in five national quota samples (US, UK), across 2 years, from three different sampling platforms-Respondi, CloudResearch, and Prolific. We also explore the MIST's nomological net and generate age-, region-, and country-specific norm tables. In Study 3 (N = 421) we demonstrate how the MIST-in conjunction with Verification done-can provide novel insights on existing psychological interventions, thereby advancing theory development. Finally, we outline the versatile implementations of the MIST as a screening tool, covariate, and intervention evaluation framework. As all methods are transparently reported and detailed, this work will allow other researchers to create similar scales or adapt them for any population of interest.

Multi-omics for studying and understanding polar life.

Polar ecosystems are experiencing amongst the most rapid rates of regional warming on Earth. Here, we discuss 'omics' approaches to investigate polar biodiversity, including the current state of the art, future perspectives and recommendations. We propose a community road map to generate and more fully exploit multi-omics data from polar organisms. These data are needed for the comprehensive evaluation of polar biodiversity and to reveal how life evolved and adapted to permanently cold environments with extreme seasonality. We argue that concerted action is required to mitigate the impact of warming on polar ecosystems via conservation efforts, to sustainably manage these unique habitats and their ecosystem services, and for the sustainable bioprospecting of novel genes and compounds for societal gain.

ecolo-zip: A global, rich and granular characterization of biogeophysical ecology for 1.5 million postal codes.

The inescapable fact that human life is perpetually embedded in a tangible biogeophysical environment - and the consequences that this has for individuals and societies - have long fascinated scholars of all backgrounds. Technological progress and the advent of big data have spurred ever-more precise attempts to quantify our biogeophysical environments. However, many such datasets lack spatial granularity, global coverage, content depth, or accessibility. Here, we introduce ecolo-zip, a novel geospatial dataset that provides a granular-yet-global, parsimonious-yet-rich ecological characterization of over 1.5 million postal codes across 94 countries and regions. Combining two large-scale satellite image resources (ASTER; SRTM, ICC = 0.999) and a customized geospatial sampling model, we provide high-resolution indicators of physical topography (elevation, mountainousness, distance to sea), vegetation (normalized difference vegetation index), and climate (surface temperature). With this resource - featuring methodological details, visualizations, and application suggestions - we hope to contribute towards understanding the multi-faceted interactions between humans and their environments.

MHC class II antigen presentation by intestinal epithelial cells fine-tunes bacteria-reactive CD4 T cell responses.

Although intestinal epithelial cells (IECs) can express major histocompatibility complex class II (MHC II), especially during intestinal inflammation, it remains unclear if antigen presentation by IECs favours pro- or anti-inflammatory CD4+ T cell responses. Using selective gene ablation of MHC II in IECs and IEC organoid cultures, we assessed the impact of MHC II expression by IECs on CD4+ T cell responses and disease outcomes in response to enteric bacterial pathogens. We found that intestinal bacterial infections elicit inflammatory cues that greatly increase expression of MHC II processing and presentation molecules in colonic IECs. Whilst IEC MHC II expression had little impact on disease severity following Citrobacter rodentium or Helicobacter hepaticus infection, using a colonic IEC organoid-CD4+ T cell co-culture system, we demonstrate that IECs can activate antigen-specific CD4+ T cells in an MHC II-dependent manner, modulating both regulatory and effector Th cell subsets. Furthermore, we assessed adoptively transferred H. hepaticus-specific CD4+ T cells during intestinal inflammation in vivo and report that IEC MHC II expression dampens pro-inflammatory effector Th cells. Our findings indicate that IECs can function as non-conventional antigen presenting cells and that IEC MHC II expression fine-tunes local effector CD4+ T cell responses during intestinal inflammation.

Openness buffers the impact of Belief in Conspiracy Theories on COVID-19 vaccine hesitancy: Evidence from a large, representative Italian sample.

As COVID-19 continues to incur enormous personal and societal costs, widespread vaccination against the virus remains the most effective strategy to end the pandemic. However, vaccine hesitancy is rampant and has been steadily rising for decades. Seeking to remedy this, personality psychologists have begun to explore psychological drivers of vaccine hesitancy, including the Big Five. Openness to Experience presents itself as a vexing case as previous attempts to study its association with vaccine hesitancy have yielded mixed findings. In this preregistered study, we hypothesise that the impact of Openness to Experience on Vaccine Hesitancy depends on its interplay with other factors, namely conspiracy beliefs. To test this, we apply logistic regressions, simple slopes analyses, and propensity score matching to a nationally representative sample of 2500 Italian citizens, collected in May 2021. Contrary to our original hypothesis (i.e., Openness will have a positive association with Vaccine Hesitancy at high - and a negative at low - levels of Conspiracy Beliefs) we find that high Openness diminishes the impact of Belief in Conspiracy Theories on Vaccine Hesitancy. Consistent with previous research, we propose that Openness serves as a buffer against extreme positions by allowing individuals to be exposed to a greater diversity of information.

Greed communication predicts the approval and reach of US senators' tweets.

Social media are at the forefront of modern political campaigning. They allow politicians to communicate directly with constituents and constituents to endorse politicians' messages and share them with their networks. Analyzing every tweet of all US senators holding office from 2013 to 2021 (861,104 tweets from 140 senators), we identify a psycholinguistic factor, greed communication, that robustly predicts increased approval (favorites) and reach (retweets). These effects persist when tested against diverse established psycholinguistic predictors of political content dissemination on social media and various other psycholinguistic variables. We further find that greed communication in the tweets of Democratic senators is associated with greater approval and retweeting compared to greed communication in the tweets of Republican senators, especially when those tweets also mention political outgroups.

Dissection of a Giant Coronary Aneurysm.

Supplemental material is available for this article.

Let the algorithm speak: How to use neural networks for automatic item generation in psychological scale development.

Measurement is at the heart of scientific research. As many-perhaps most-psychological constructs cannot be directly observed, there is a steady demand for reliable self-report scales to assess latent constructs. However, scale development is a tedious process that requires researchers to produce good items in large quantities. In this tutorial, we introduce, explain, and apply the Psychometric Item Generator (PIG), an open-source, free-to-use, self-sufficient natural language processing algorithm that produces large-scale, human-like, customized text output within a few mouse clicks. The PIG is based on the GPT-2, a powerful generative language model, and runs on Google Colaboratory-an interactive virtual notebook environment that executes code on state-of-the-art virtual machines at no cost. Across two demonstrations and a preregistered five-pronged empirical validation with two Canadian samples (NSample 1 = 501, NSample 2 = 773), we show that the PIG is equally well-suited to generate large pools of face-valid items for novel constructs (i.e., wanderlust) and create parsimonious short scales of existing constructs (i.e., Big Five personality traits) that yield strong performances when tested in the wild and benchmarked against current gold standards for assessment. The PIG does not require any prior coding skills or access to computational resources and can easily be tailored to any desired context by simply switching out short linguistic prompts in a single line of code. In short, we present an effective, novel machine learning solution to an old psychological challenge. As such, the PIG will not require you to learn a new language-but instead, speak yours. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Spatial analysis for psychologists: How to use individual-level data for research at the geographically aggregated level.

Psychologists have become increasingly interested in the geographical organization of psychological phenomena. Such studies typically seek to identify geographical variation in psychological characteristics and examine the causes and consequences of that variation. Geo-psychological research offers unique advantages, such as a wide variety of easily obtainable behavioral outcomes. However, studies at the geographically aggregate level also come with unique challenges that require psychologists to work with unfamiliar data formats, sources, measures, and statistical problems. The present article aims to present psychologists with a methodological roadmap that equips them with basic analytical techniques for geographical analysis. Across five sections, we provide a step-by-step tutorial and walk readers through a full geo-psychological research project. We provide guidance for (a) choosing an appropriate geographical level and aggregating individual data, (b) spatializing data and mapping geographical distributions, (c) creating and managing spatial weights matrices, (d) assessing geographical clustering and identifying distributional patterns, and (e) regressing spatial data using spatial regression models. Throughout the tutorial, we alternate between explanatory sections that feature in-depth background information and hands-on sections that use real data to demonstrate the practical implementation of each step in R. The full R code and all data used in this demonstration are available from the OSF project page accompanying this article. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Regional personality differences predict variation in early COVID-19 infections and mobility patterns indicative of social distancing.

The early stages of the COVID-19 pandemic revealed stark regional variation in the spread of the virus. While previous research has highlighted the impact of regional differences in sociodemographic and economic factors, we argue that regional differences in social and compliance behaviors-the very behaviors through which the virus is transmitted-are critical drivers of the spread of COVID-19, particularly in the early stages of the pandemic. Combining self-reported personality data that capture individual differences in these behaviors (3.5 million people) with COVID-19 prevalence and mortality rates as well as behavioral mobility observations (29 million people) in the United States and Germany, we show that regional personality differences can help explain the early transmission of COVID-19; this is true even after controlling for a wide array of important sociodemographic, economic, and pandemic-related factors. We use specification curve analyses to test the effects of regional personality in a robust and unbiased way. The results indicate that in the early stages of COVID-19, Openness to experience acted as a risk factor, while Neuroticism acted as a protective factor. The findings also highlight the complexity of the pandemic by showing that the effects of regional personality can differ (a) across countries (Extraversion), (b) over time (Openness), and (c) from those previously observed at the individual level (Agreeableness and Conscientiousness). Taken together, our findings support the importance of regional personality differences in the early spread of COVID-19, but they also caution against oversimplified answers to phenomena as complex as a global pandemic. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Registered report: Social face evaluation: ethnicity-specific differences in the judgement of trustworthiness of faces and facial parts.

Social face evaluation is a common and consequential element of everyday life based on the judgement of trustworthiness. However, the particular facial regions that guide such trustworthiness judgements are largely unknown. It is also unclear whether different facial regions are consistently utilized to guide judgments for different ethnic groups, and whether previous exposure to specific ethnicities in one's social environment has an influence on trustworthiness judgements made from faces or facial regions. This registered report addressed these questions through a global online survey study that recruited Asian, Black, Latino, and White raters (N = 4580). Raters were shown full faces and specific parts of the face for an ethnically diverse, sex-balanced set of 32 targets and rated targets' trustworthiness. Multilevel modelling showed that in forming trustworthiness judgements, raters relied most strongly on the eyes (with no substantial information loss vis-à-vis full faces). Corroborating ingroup-outgroup effects, raters rated faces and facial parts of targets with whom they shared their ethnicity, sex, or eye color as significantly more trustworthy. Exposure to ethnic groups in raters' social environment predicted trustworthiness ratings of other ethnic groups in nuanced ways. That is, raters from the ambient ethnic majority provided slightly higher trustworthiness ratings for stimuli of their own ethnicity compared to minority ethnicities. In contrast, raters from an ambient ethnic minority (e.g., immigrants) provided substantially lower trustworthiness ratings for stimuli of the ethnic majority. Taken together, the current study provides a new window into the psychological processes underlying social face evaluation and its cultural generalizability. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 7 January 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.6084/m9.figshare.18319244 .

Proteomic Analysis of Adenovirus 5 by UHPLC-MS/MS: Development of a Robust and Reproducible Sample Preparation Workflow.

Adenoviruses (AdVs) have recently become widely used therapeutic vectors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. AdVs are large, nonenveloped viruses with an icosahedral capsid formed from several proteins that encloses double-stranded DNA. These proteins are the main components and key players in initial stages of infection by the virus particles, so their heterogeneity and content must be evaluated to ensure product and process consistency. Peptide mapping can provide detailed information on these proteins, e.g., their amino acid sequences and post-translational modifications (PTMs), which is crucial for the development and optimization of the manufacturing processes. However, sample preparation remains the main bottleneck for successful proteomic analysis of the viral proteins (VPs) of AdVs due to their low concentrations and vast stoichiometric ranges. To address this problem, we have developed a fast and efficient protocol for preparing samples for proteomic analysis of VPs of AdV5 that requires no cleaning step prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The approach enabled identification of 92% of amino acids in AdV5 VPs on average and quantification of 53 PTMs in a single LC-MS/MS experiment using trypsin protease. The data obtained demonstrate the method's potential utility for supporting the development of novel AdV-based gene therapy products (GTPs).

The many geographical layers of culture.

Uchiyama et al. present a dual inheritance framework for conceptualizing how behavioural genetics and cultural evolution interact and affect heritability. We posit that to achieve a holistic and nuanced representation of the cultural environment and evolution against which genetic effects should be evaluated, it is imperative to consider the multiple geographic cultural layers impacting individuals and genetic heritability.