Mariner: explore the Hi-Cs.

MOTIVATION: 3D chromatin structure plays an important role in regulating gene expression and alterations to this structure can result in developmental abnormalities and disease. While genomic approaches like Hi-C and Micro-C can provide valuable insights in 3D chromatin architecture, the resulting datasets are extremely large and difficult to manipulate. RESULTS: Here, we present mariner, a rapid and memory efficient tool to extract, aggregate, and plot data from Hi-C matrices within the R/Bioconductor environment. Mariner simplifies the process of querying and extracting contacts from multiple Hi-C files using a parallel and block-processing approach. Modular functions allow complete workflow customization for advanced users, yet all-in-one functions are available for running the most common types of analyses. Finally, tight integration with existing Bioconductor infrastructure enables complete analysis and visualization of Hi-C data in R. AVAILABILITY AND IMPLEMENTATION: Available on GitHub at https://github.com/EricSDavis/mariner and on Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/mariner.html.

Plotgardener: cultivating precise multi-panel figures in R.

MOTIVATION: The R programming language is one of the most widely used programming languages for transforming raw genomic datasets into meaningful biological conclusions through analysis and visualization, which has been largely facilitated by infrastructure and tools developed by the Bioconductor project. However, existing plotting packages rely on relative positioning and sizing of plots, which is often sufficient for exploratory analysis but is poorly suited for the creation of publication-quality multi-panel images inherent to scientific manuscript preparation. RESULTS: We present plotgardener, a coordinate-based genomic data visualization package that offers a new paradigm for multi-plot figure generation in R. Plotgardener allows precise, programmatic control over the placement, esthetics and arrangements of plots while maximizing user experience through fast and memory-efficient data access, support for a wide variety of data and file types, and tight integration with the Bioconductor environment. Plotgardener also allows precise placement and sizing of ggplot2 plots, making it an invaluable tool for R users and data scientists from virtually any discipline. AVAILABILITY AND IMPLEMENTATION: Package: https://bioconductor.org/packages/plotgardener, Code: https://github.com/PhanstielLab/plotgardener, Documentation: https://phanstiellab.github.io/plotgardener/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Peripheral inflammatory biomarkers define biotypes of bipolar depression.

We identified biologically relevant moderators of response to tumor necrosis factor (TNF)-α inhibitor, infliximab, among 60 individuals with bipolar depression. Data were derived from a 12-week, randomized, placebo-controlled clinical trial secondarily evaluating the efficacy of infliximab on a measure of anhedonia (i.e., Snaith-Hamilton Pleasure Scale). Three inflammatory biotypes were derived from peripheral cytokine measurements using an iterative, machine learning-based approach. Infliximab-randomized participants classified as biotype 3 exhibited lower baseline concentrations of pro- and anti-inflammatory cytokines and soluble TNF receptor-1 and reported greater pro-hedonic improvements, relative to those classified as biotype 1 or 2. Pretreatment biotypes also moderated changes in neuroinflammatory substrates relevant to infliximab's hypothesized mechanism of action. Neuronal origin-enriched extracellular vesicle (NEV) protein concentrations were reduced to two factors using principal axis factoring: phosphorylated nuclear factorκB (p-NFκB), Fas-associated death domain (p-FADD), and IκB kinase (p-IKKα/ß) and TNF receptor-1 (TNFR1) comprised factor "NEV1," whereas phosphorylated insulin receptor substrate-1 (p-IRS1), p38 mitogen-activated protein kinase (p-p38), and c-Jun N-terminal kinase (p-JNK) constituted "NEV2". Among infliximab-randomized subjects classified as biotype 3, NEV1 scores were decreased at weeks 2 and 6 and increased at week 12, relative to baseline, and NEV2 scores increased over time. Decreases in NEV1 scores and increases in NEV2 scores were associated with greater reductions in anhedonic symptoms in our classification and regression tree model (r2 = 0.22, RMSE = 0.08). Our findings provide preliminary evidence supporting the hypothesis that the pro-hedonic effects of infliximab require modulation of multiple TNF-α signaling pathways, including NF-κB, IRS1, and MAPK.

Comprehensive analysis of the ErbB receptor family in pediatric nervous system tumors and rhabdomyosarcoma.

BACKGROUND: There is a paucity of knowledge regarding pediatric biomarkers, including the relevance of ErbB pathway aberrations in pediatric tumors. We investigated the occurrence of ErbB receptor aberrations across different pediatric malignancies, to identify patterns of ErbB dysregulation and define biomarkers suitable for patient enrichment in clinical studies. PROCEDURE: Tissue samples from 297 patients with nervous system tumors and rhabdomyosarcoma were analyzed for immunohistochemical expression or gene amplification of epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2). Exploratory analyses of HER3/HER4 expression, and mRNA expression of ErbB receptors/ligands (NanoString) were performed. Assay validation followed general procedures, with additional validation to address Clinical Laboratory Improvement Amendments (CLIA) requirements. RESULTS: In most tumor types, samples with high ErbB receptor expression were found with heterogeneous distribution. We considered increased/aberrant ErbB pathway activation when greater than or equal to two EGFR/HER2 markers were simultaneously upregulated. ErbB pathway dysregulation was identified in ∼20%-30% of samples for most tumor types (medulloblastoma/primitive neuroectodermal tumors 31.1%, high-grade glioma 27.1%, neuroblastoma 22.7%, rhabdomyosarcoma 23.1%, ependymoma 18.8%), 4.2% of diffuse intrinsic pontine gliomas, and no recurrent or refractory low-grade astrocytomas. In medulloblastoma/primitive neuroectodermal tumors and neuroblastoma, this was attributed mainly to high EGFR polysomy/HER2 amplification, whereas EGFR gene amplification was observed in some high-grade glioma samples. EGFR/HER2 overexpression was most prevalent in ependymoma. CONCLUSIONS: Overexpression and/or amplification of EGFR/HER2 were identified as potential enrichment biomarkers for clinical trials of ErbB-targeted drugs.

Putting the social back into physical distancing: The role of digital connections in a pandemic crisis.

During the COVID-19 pandemic, physical distancing is necessary to reduce the spread of the coronavirus. To compensate for the lack of social encounters, people have been advised to connect with others via digital communication channels. Drawing on a psychological framework combined with assumptions from communication science, we therefore investigated whether technology-mediated communication can actually meet individuals' social needs to foster compliance with distancing measures and whether there are differences between distinct communication channels. Based on an online survey (N = 301) during the first national lockdown in Germany, we found that the impact of audio-visual communication is limited. Instead, the data showed that text-based communication indirectly fostered willingness to adhere to physical distancing through the pathway of increased feelings of social support and life satisfaction. Three follow-up surveys (N = 180) revealed that while feelings of social support increased, people's technology-based communication and willingness to adhere to distancing measures decreased. Our results challenge the assumption that audio-visual communication compensates for lack of physical contact more effectively than text-based communication. This study highlights the potential of text-based communication to increase feelings of social support, which may be particularly important during a pandemic.

Neural Mechanisms for Accepting and Rejecting Artificial Social Partners in the Uncanny Valley.

Artificial agents are becoming prevalent across human life domains. However, the neural mechanisms underlying human responses to these new, artificial social partners remain unclear. The uncanny valley (UV) hypothesis predicts that humans prefer anthropomorphic agents but reject them if they become too humanlike-the so-called UV reaction. Using fMRI, we investigated neural activity when subjects evaluated artificial agents and made decisions about them. Across two experimental tasks, the ventromedial prefrontal cortex (VMPFC) encoded an explicit representation of subjects' UV reactions. Specifically, VMPFC signaled the subjective likability of artificial agents as a nonlinear function of humanlikeness, with selective low likability for highly humanlike agents. In exploratory across-subject analyses, these effects explained individual differences in psychophysical evaluations and preference choices. Functionally connected areas encoded critical inputs for these signals: the temporoparietal junction encoded a linear humanlikeness continuum, whereas nonlinear representations of humanlikeness in dorsomedial prefrontal cortex (DMPFC) and fusiform gyrus emphasized a human-nonhuman distinction. Following principles of multisensory integration, multiplicative combination of these signals reconstructed VMPFC's valuation function. During decision making, separate signals in VMPFC and DMPFC encoded subjects' decision variable for choices involving humans or artificial agents, respectively. A distinct amygdala signal predicted rejection of artificial agents. Our data suggest that human reactions toward artificial agents are governed by a neural mechanism that generates a selective, nonlinear valuation in response to a specific feature combination (humanlikeness in nonhuman agents). Thus, a basic principle known from sensory coding-neural feature selectivity from linear-nonlinear transformation-may also underlie human responses to artificial social partners.SIGNIFICANCE STATEMENT Would you trust a robot to make decisions for you? Autonomous artificial agents are increasingly entering our lives, but how the human brain responds to these new artificial social partners remains unclear. The uncanny valley (UV) hypothesis-an influential psychological framework-captures the observation that human responses to artificial agents are nonlinear: we like increasingly anthropomorphic artificial agents, but feel uncomfortable if they become too humanlike. Here we investigated neural activity when humans evaluated artificial agents and made personal decisions about them. Our findings suggest a novel neurobiological conceptualization of human responses toward artificial agents: the UV reaction-a selective dislike of highly humanlike agents-is based on nonlinear value-coding in ventromedial prefrontal cortex, a key component of the brain's reward system.

Efficacy of adjunctive infliximab vs. placebo in the treatment of anhedonia in bipolar I/II depression.

We investigated the efficacy of tumour necrosis factor (TNF)-α antagonist infliximab on a measure of anhedonia amongst individuals with bipolar I/II depression (ClinicalTrials.gov identifier NCT02363738). Adults (ages 18-65) with bipolar I/II disorder currently experiencing a major depressive episode with a higher probability of inflammatory activity (i.e., meeting one or more of the following inflammatory/metabolic criteria: obesity and dyslipidemia/hypertension, daily cigarette smoking, diabetes mellitus, migraine, inflammatory bowel disease, and/or C-reactive protein level of ⩾5 mg/L) were enrolled in a double-blind, 12-week clinical trial of adjunctive infliximab (5 mg/kg) and saline control, which were administered at weeks 0, 2, and 6. The primary outcome measure for the present secondary analysis was change in the Snaith-Hamilton Pleasure Scale (SHAPS) total score between placebo- and infliximab-treated subjects from baseline to weeks 6 and 12. Plasma concentrations of TNF-α and soluble TNF receptors (sTNFR) 1 and 2 were assessed at weeks 0, 2, 6, and 12. Sixty eligible adults received treatment with infliximab (n=29) or placebo (n=31); 47 subjects completed the study (infliximab: n=21, placebo: n=26). Overall, infliximab-randomized subjects exhibited significantly larger increases in SHAPS total score, denoting greater reductions in anhedonic symptoms, when compared to placebo-randomized subjects (treatment × time interaction effect: χ2=7.15,df=2,p=0.03). Anti-anhedonic efficacy was moderated by baseline plasma levels of TNF-α and sTNFR1, but not by changes in TNF-α or sTNFR1 concentrations. Baseline and changes in sTNFR2 concentrations did not moderate anti-anhedonic efficacy. Infliximab significantly improved a measure of anhedonia relative to placebo in adults with bipolar I/II depression at week 6; intervention efficacy was not sustained 6 weeks after the final infusion.

Age-Related Differences in the Evaluation of a Virtual Health Agent's Appearance and Embodiment in a Health-Related Interaction: Experimental Lab Study.

BACKGROUND: Assistive technologies have become more important owing to the aging population, especially when they foster healthy behaviors. Because of their natural interface, virtual agents are promising assistants for people in need of support. To engage people during an interaction with these technologies, such assistants need to match the users´ needs and preferences, especially with regard to social outcomes. OBJECTIVE: Prior research has already determined the importance of an agent's appearance in a human-agent interaction. As seniors can particularly benefit from the use of virtual agents to maintain their autonomy, it is important to investigate their special needs. However, there are almost no studies focusing on age-related differences with regard to appearance effects. METHODS: A 2×4 between-subjects design was used to investigate the age-related differences of appearance effects in a human-agent interaction. In this study, 46 seniors and 84 students interacted in a health scenario with a virtual agent, whose appearance varied (cartoon-stylized humanoid agent, cartoon-stylized machine-like agent, more realistic humanoid agent, and nonembodied agent [voice only]). After the interaction, participants reported on the evaluation of the agent, usage intention, perceived presence of the agent, bonding toward the agent, and overall evaluation of the interaction. RESULTS: The findings suggested that seniors evaluated the agent more positively (liked the agent more and evaluated it as more realistic, attractive, and sociable) and showed more bonding toward the agent regardless of the appearance than did students. In addition, interaction effects were found. Seniors reported the highest usage intention for the cartoon-stylized humanoid agent, whereas students reported the lowest usage intention for this agent. The same pattern was found for participant bonding with the agent. Seniors showed more bonding when interacting with the cartoon-stylized humanoid agent or voice only agent, whereas students showed the least bonding when interacting with the cartoon-stylized humanoid agent. CONCLUSIONS: In health-related interactions, target group-related differences exist with regard to a virtual assistant's appearance. When elderly individuals are the target group, a humanoid virtual assistant might trigger specific social responses and be evaluated more positively at least in short-term interactions.

N-acetylcysteine for non-paracetamol drug-induced liver injury: a systematic review.

AIMS: N-acetylcysteine (NAC) may be useful in the management of non-paracetamol drug-induced liver injury (DILI). Our objective was to review systematically evidence for the use of NAC as a therapeutic option for non-paracetamol DILI. METHODS: We searched for randomized controlled trials (RCTs) and prospective cohort studies. We searched several bibliographic databases, grey literature sources, conference proceedings and ongoing trials. Our pre-specified primary outcomes were all cause and DILI related mortality, time to normalization of liver biochemistry and adverse events. Secondary outcomes were proportion receiving liver transplant, time to transplantation, transplant-free survival and hospitalization duration. RESULTS: We identified one RCT of NAC vs. placebo in patients with non-paracetamol acute liver failure. There was no difference in the primary outcomes of overall survival at 3 weeks between NAC [70%, 95% confidence interval (CI) = 60%, 81%, n = 81] and placebo (66%, 95% CI = 56%, 77%, n = 92). NAC significantly improved the secondary outcomes of transplant-free survival compared with placebo: 40% NAC (95% CI = 28%, 51%) vs. 27% placebo (95% CI = 18%, 37%). A subgroup analysis according to aetiology found improved transplant-free survival in patients with non-paracetamol DILI, NAC (58%, n = 19) vs. placebo (27%, n = 26), odds ratio (OR) 0.27 (95% CI = 0.076, 0.942). Overall survival was similar, NAC (79%) vs. placebo (65%);, OR 0.50 (95% CI = 0.13, 1.98). CONCLUSION: Current available evidence is limited and does not allow for any firm conclusions to be made regarding the role of NAC in non-paracetamol DILI. We therefore highlight the need for further research in this area.

Mortality from adverse drug reactions in adult medical inpatients at four hospitals in South Africa: a cross-sectional survey.

AIMS: Fatal adverse drug reactions (ADRs) are important causes of death, but data from resource-limited settings are scarce. We determined the proportion of deaths in South African medical inpatients attributable to ADRs, and their preventability, stratified by human immunodeficiency virus (HIV) status. METHODS: We reviewed the folders of all patients who died over a 30 day period in the medical wards of four hospitals. We identified ADR-related deaths (deaths where an ADR was 'possible', 'probable' or 'certain' using WHO-UMC criteria and where the ADR contributed to death). We determined preventability according to previously published criteria. RESULTS: ADRs contributed to the death of 2.9% of medical admissions and 56 of 357 deaths (16%) were ADR-related. Tenofovir, rifampicin and co-trimoxazole were the most commonly implicated drugs. 43% of ADRs were considered preventable. The following factors were independently associated with ADR-related death: HIV-infected patients on antiretroviral therapy (adjusted odds ratio (aOR) 4.4, 95% confidence interval (CI) 1.6, 12), exposure to more than seven drugs (aOR 2.5, 95% CI 1.3, 4.8) and increasing comorbidity score (aOR 1.3, 95% CI 1.1, 1.7). CONCLUSIONS: In our setting, where HIV and tuberculosis are highly prevalent, fatal in-hospital ADRs were more common than reported in high income settings. Most deaths were attributed to drugs used in managing HIV and tuberculosis. A large proportion of the ADRs were preventable, highlighting the need to strengthen systems for health care worker training and support.

Let's Blog About Health! Exploring the Persuasiveness of a Personal HIV Blog Compared to an Institutional HIV Website.

On HIV blogs, people living with HIV share their intimate thoughts and experiences with the world in the form of personal online diaries. While previous research investigated the reasons why patients engage in blogging activities, the effects of such diaries on nondiseased recipients are largely unexplored. Following an experimental design, this study (n = 261) tested whether a one-time exposure to a personal HIV blog has greater persuasive effects on its readers than an institutional HIV website providing the same content. Results showed that although source credibility was perceived as higher when reading the HIV website from an official institution, blog readers had more positive attitudes and a higher self-efficacy toward condom use than website readers. Implications for health message design are discussed.

Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk.

Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. Integrating expression quantitative trait loci (eQTL), 3D chromatin structure, and other genomic approaches with OA GWAS data offers a promising approach to elucidate disease mechanisms; however, comprehensive eQTL maps in OA-relevant tissues and conditions remain scarce. We mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions. We identified thousands of differentially expressed genes, including those associated with differences in sex and age. RNA-seq in chondrocytes from 101 donors across two conditions uncovered 3782 unique eGenes, including 420 that exhibited strong and significant condition-specific effects. Colocalization with OA GWAS signals revealed 13 putative OA risk genes, 10 of which have not been previously identified. Chromatin accessibility and 3D chromatin structure provided insights into the mechanisms and conditional specificity of these variants. Our findings shed light on OA pathogenesis and highlight potential targets for therapeutic development. Highlights: ∘ Comprehensive analysis of sex- and age-related global gene expression in human chondrocytes revealed differences that correlate with osteoarthritis ∘ First response eQTLs in chondrocytes treated with an OA-related stimulus ∘ Deeply sequenced Hi-C in resting and activated chondrocytes helps connect OA risk variants to their putative causal genes ∘ Colocalization analysis reveals 13 (including 10 novel) putative OA risk genes.

Balancing perceptions of targeting: An investigation of political microtargeting transparency through a calculus approach.

Over the last few years, political advertisers have moved with their audiences: to social media platforms. Advertisers on these platforms aim to persuade voters by sending messages tailored to them based on their own data: political microtargeting (PMT). A considerable problem with PMT is that users are often unaware that they are being targeted, while current transparency advances do not seem to suffice in informing users. However, increasing transparency may have consequences on users' privacy perceptions. Thus, the current work investigates whether disclosures, as a measure to increase transparency, increase users' recognition of a microtargeted ad, and subsequently what this means for their perceived benefits, privacy concerns, and their likelihood of engaging in privacy protection behavior, based on the privacy calculus. In a preregistered online one-factorial between-subjects experiment (N = 450) we exposed participants to either an Instagram post containing a currently used disclosure or a more salient disclosure. Our results show that exposure to this disclosure increases recognition of the ad being microtargeted, and that this relates to perceived benefits but not privacy concerns. However, the results show that users' privacy concerns are related to their increased privacy protection behavior. Finally, we found that over four-fifths of our participants who were exposed to the more salient disclosure recalled it correctly.

Explainable AI in medical imaging: An overview for clinical practitioners - Saliency-based XAI approaches.

Since recent achievements of Artificial Intelligence (AI) have proven significant success and promising results throughout many fields of application during the last decade, AI has also become an essential part of medical research. The improving data availability, coupled with advances in high-performance computing and innovative algorithms, has increased AI's potential in various aspects. Because AI rapidly reshapes research and promotes the development of personalized clinical care, alongside its implementation arises an urgent need for a deep understanding of its inner workings, especially in high-stake domains. However, such systems can be highly complex and opaque, limiting the possibility of an immediate understanding of the system's decisions. Regarding the medical field, a high impact is attributed to these decisions as physicians and patients can only fully trust AI systems when reasonably communicating the origin of their results, simultaneously enabling the identification of errors and biases. Explainable AI (XAI), becoming an increasingly important field of research in recent years, promotes the formulation of explainability methods and provides a rationale allowing users to comprehend the results generated by AI systems. In this paper, we investigate the application of XAI in medical imaging, addressing a broad audience, especially healthcare professionals. The content focuses on definitions and taxonomies, standard methods and approaches, advantages, limitations, and examples representing the current state of research regarding XAI in medical imaging. This paper focuses on saliency-based XAI methods, where the explanation can be provided directly on the input data (image) and which naturally are of special importance in medical imaging.

Explainable AI in medical imaging: An overview for clinical practitioners - Beyond saliency-based XAI approaches.

Driven by recent advances in Artificial Intelligence (AI) and Computer Vision (CV), the implementation of AI systems in the medical domain increased correspondingly. This is especially true for the domain of medical imaging, in which the incorporation of AI aids several imaging-based tasks such as classification, segmentation, and registration. Moreover, AI reshapes medical research and contributes to the development of personalized clinical care. Consequently, alongside its extended implementation arises the need for an extensive understanding of AI systems and their inner workings, potentials, and limitations which the field of eXplainable AI (XAI) aims at. Because medical imaging is mainly associated with visual tasks, most explainability approaches incorporate saliency-based XAI methods. In contrast to that, in this article we would like to investigate the full potential of XAI methods in the field of medical imaging by specifically focusing on XAI techniques not relying on saliency, and providing diversified examples. We dedicate our investigation to a broad audience, but particularly healthcare professionals. Moreover, this work aims at establishing a common ground for cross-disciplinary understanding and exchange across disciplines between Deep Learning (DL) builders and healthcare professionals, which is why we aimed for a non-technical overview. Presented XAI methods are divided by a method's output representation into the following categories: Case-based explanations, textual explanations, and auxiliary explanations.

Complex Patterns of Genomic Heterogeneity Identified in 42 Tumor Samples and ctDNA of a Pulmonary Atypical Carcinoid Patient.

Tumor evolution underlies many challenges facing precision oncology, and improving our understanding has the potential to improve clinical care. This study represents a rare opportunity to study tumor heterogeneity and evolution in a patient with an understudied cancer type. A patient with pulmonary atypical carcinoid, a neuroendocrine tumor, metastatic to 90 sites, requested and consented to donate tissues for research. 42 tumor samples collected at rapid autopsy from 14 anatomically distinct sites were analyzed through DNA whole-exome sequencing and RNA sequencing, and five analyzed through linked-read sequencing. Targeted DNA sequencing was completed on two clinical tissue biopsies and one blood plasma sample. Chromosomal alterations and gene variants accumulated over time, and specific chromosomal alterations preceded the single predicted gene driver variant (ARID1A). At the time of autopsy, all sites shared the gain of one copy of Chr 5, loss of one copy of Chr 6 and 21, chromothripsis of one copy of Chr 11, and 39 small variants. Two tumor clones (carrying additional variants) were detected at metastatic sites, and occasionally in different regions of the same organ (e.g., within the pancreas). Circulating tumor DNA (ctDNA) sequencing detected shared tumor variants in the blood plasma and captured marked genomic heterogeneity, including all metastatic clones but few private tumor variants. This study describes genomic tumor evolution and dissemination of a pulmonary atypical carcinoid donated by a single generous patient. It highlights the critical role of chromosomal alterations in tumor initiation and explores the potential of ctDNA analysis to represent genomically heterogeneous disease. Significance: DNA sequencing data from tumor samples and blood plasma from a single patient highlighted the critical early role of chromosomal alterations in atypical carcinoid tumor development. Common tumor variants were readily detected in the blood plasma, unlike emerging tumor variants, which has implications for using ctDNA to capture cancer evolution.

Looking beyond workforce parity: addressing gender inequity in pathology.

While women pathologists have made up over one-third of pathologists in the Australian workforce for over 15 years and at least 50% since 2019, they are under-represented in senior leadership roles, scientific publications, grant recipients, editorial boards, key presentations, and professional awards. This is not unique to pathology and is seen in the broader medical and academic community. Barriers to gender equity and equality in pathology, medicine and academia include gender stereotypes, gender-based discrimination, structural and organisational barriers as well as broader social and cultural barriers. A diverse leadership reflective of the whole professional body and the broader community is important for optimal health outcomes. It is the responsibility and moral duty of individuals and organisations to address any gender disparities, inequities, and inequalities by monitoring, identifying, and acting on gender biases and systemic barriers that hinder appropriate levels of representation by women.

Addressing the identification problem in age-period-cohort analysis: a tutorial on the use of partial least squares and principal components analysis.

In the analysis of trends in health outcomes, an ongoing issue is how to separate and estimate the effects of age, period, and cohort. As these 3 variables are perfectly collinear by definition, regression coefficients in a general linear model are not unique. In this tutorial, we review why identification is a problem, and how this problem may be tackled using partial least squares and principal components regression analyses. Both methods produce regression coefficients that fulfill the same collinearity constraint as the variables age, period, and cohort. We show that, because the constraint imposed by partial least squares and principal components regression is inherent in the mathematical relation among the 3 variables, this leads to more interpretable results. We use one dataset from a Taiwanese health-screening program to illustrate how to use partial least squares regression to analyze the trends in body heights with 3 continuous variables for age, period, and cohort. We then use another dataset of hepatocellular carcinoma mortality rates for Taiwanese men to illustrate how to use partial least squares regression to analyze tables with aggregated data. We use the second dataset to show the relation between the intrinsic estimator, a recently proposed method for the age-period-cohort analysis, and partial least squares regression. We also show that the inclusion of all indicator variables provides a more consistent approach. R code for our analyses is provided in the eAppendix.

How the expertise heuristic accelerates decision-making and credibility judgments in social media by means of effort reduction.

Real-time communication, unlimited distribution of information, and the lack of editorial supervision in social media communication aggravate recipients' credibility evaluations and information selection by what aspects of the source such as expertise have emerged as important anchors for evaluations. It has long been assumed that credibility judgments in social media are specifically guided by heuristics. However, the existing studies merely give indications, for example, based on individuals' self-report but do not test whether important attributes and prerequisites of heuristic decision-making, such as effort reduction, are present. Against this background, the current study (N = 185) analyses by applying a reduced two-alternative choice paradigm whether the relation between the expertise cue and credibility judgments and the choice of information sources is guided by a heuristic, namely the expertise heuristic. Findings indicate that the presence of the expertise cue reduced respondents' task latencies significantly, although participants' decision behavior was not independent from additional information. This is discussed in detail with recourse to theoretical conceptualizations of cognitive heuristics.

The robotic mentalist - On the influences of robots' mentalizing abilities and external manipulative intent on people's credibility attributions.

Robots are used in various social interactions that require them to be perceived as credible agents (e.g., as product recommenders in shopping malls). To be rated credible (i.e., competent, trustworthy, and caring) a robot's mentalizing abilities have shown to be beneficial because they allow a robot to infer users' inner states, thus serving as a prerequisite for understanding their beliefs and attitudes. However, social robots are often deployed by private and thus profit-oriented companies. In such cases where an organization's implied manipulative intent is salient, the effect of robots' mentalizing abilities might be reversed. The reason for this is that mentalizing abilities could pose a persuasive threat to users rather than a feature for better understanding, thereby decreasing credibility attributions. These assumptions were tested in a three (robot's mentalizing abilities) by two (external manipulative intent) between-subjects, pre-registered, laboratory experiment during which participants interacted with a social robot that recommended experience vouchers as potential gifts for participants' target persons. Contrary to our assumptions, inferential statistical results revealed no significant differences in explicit or indirect credibility attributions caused by the experimental manipulation. The external manipulative intent of an organization using the robot caused no differences in participants' behavioral intentions or evaluations of it. Furthermore, only participants' attribution of empathic understanding to the robot varied significantly between the three mentalizing conditions. Our results suggest that people focus more on the robot than on the organization using it, causing potential opportunities for such organizations to hide their economic interests from the users.