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 data sets 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: Available on GitHub at https://github.com/EricSDavis/mariner and on Bioconducter at https://www.bioconductor.org/packages/release/bioc/html/mariner.html. SUPPLEMENTARY INFORMATION: Supplementary figures are available at Bioinformatics online.

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.

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.

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.

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.

3D chromatin structure in chondrocytes identifies putative osteoarthritis risk genes.

Genome-wide association studies have identified over 100 loci associated with osteoarthritis risk, but the majority of osteoarthritis risk variants are noncoding, making it difficult to identify the impacted genes for further study and therapeutic development. To address this need, we used a multiomic approach and genome editing to identify and functionally characterize potential osteoarthritis risk genes. Computational analysis of genome-wide association studies and ChIP-seq data revealed that chondrocyte regulatory loci are enriched for osteoarthritis risk variants. We constructed a chondrocyte-specific regulatory network by mapping 3D chromatin structure and active enhancers in human chondrocytes. We then intersected these data with our previously collected RNA-seq dataset of chondrocytes responding to fibronectin fragment, a known osteoarthritis trigger. Integration of the 3 genomic datasets with recently reported osteoarthritis genome-wide association study variants revealed a refined set of putative causal osteoarthritis variants and their potential target genes. One of the putative target genes identified was SOCS2, which was connected to a putative causal variant by a 170-kb loop and is differentially regulated in response to fibronectin fragment. CRISPR-Cas9-mediated deletion of SOCS2 in primary human chondrocytes from 3 independent donors led to heightened expression of inflammatory markers after fibronectin fragment treatment. These data suggest that SOCS2 plays a role in resolving inflammation in response to cartilage matrix damage and provides a possible mechanistic explanation for its influence on osteoarthritis risk. In total, we identified 56 unique putative osteoarthritis risk genes for further research and potential therapeutic development.

Survival of patients with small bowel neuroendocrine neoplasms in Auckland, Aotearoa New Zealand.

BACKGROUND: Small intestinal Neuroendocrine Neoplasms (SI-NENs) are the most common primary malignancy of the small bowel. The aim of this study is to define the survival of patients with an SI-NEN in Auckland, Aotearoa New Zealand (AoNZ). METHODS: A retrospective study of all patients diagnosed with a jejunal or ileal SI-NEN in the Auckland region between 2000 and 2012 was performed. The New Zealand NETwork! Registry was searched to identify the study cohort. Retrospective data collection was performed to collect stage, survival and follow up data. RESULTS: One hundred and seven patients were included in the study. The mean age of patients was 62.8 years (SD 11.9). The 5 and 10-year disease-specific survival for all patients was 66.1% (95% CI 56.5-75.7%) and 61.8% (95% CI 51.8-71.8%), respectively. Ten-year disease-specific survival was 100% for stage I and II, 74% (95%CI 61.7-84.4%) for stage III and 33.9% (95%CI 16.9-35.6%) for stage IV SI-NEN. Eleven of 40 (27.5%) patients with stage III disease had recurrence and 3 of 7 (42.8%) patients with stage IV disease had recurrence. In patients with stage IV disease, neither primary resection (HR 2.25, 95% CI 0.92-5.5) nor distant resection (HR 1.72, 95% CI 0.63-4.7) were significantly associated with a disease-specific or overall survival benefit. CONCLUSION: This study demonstrates that stage at SI-NEN diagnosis is associated with survival, but resection of the primary or distant metastases in patients with stage IV disease is not. There was no recurrence in patients with stage I or II disease after complete resection.

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.

Corrigendum: Sexual Interaction in Digital Contexts and Its Implications for Sexual Health: A Conceptual Analysis.

[This corrects the article DOI: 10.3389/fpsyg.2021.769732.].

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.

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.

Sexual Interaction in Digital Contexts and Its Implications for Sexual Health: A Conceptual Analysis.

Based on its prevalence, there is an urgent need to better understand the mechanisms, opportunities and risks of sexual interaction in digital contexts (SIDC) that are related with sexual arousal. While there is a growing body of literature on SIDC, there is also a lack of conceptual clarity and classification. Therefore, based on a conceptual analysis, we propose to distinguish between sexual interaction (1) through, (2) via, and (3) with digital technologies. (1) Sexual interactions through digital technologies are face-to-face sexual interactions that (a) have been started digitally (e.g., people initiating face-to-face sexual encounters through adult dating apps) or (b) are accompanied by digital technology (e.g., couples augmenting their face-to-face sexual encounters through filming themselves during the act and publishing the amateur pornography online). (2) Sexual interactions via digital technology are technology-mediated interpersonal sexual interactions (e.g., via text chat: cybersex; via smartphone: sexting; via webcam: webcam sex/camming). (3) Sexual interactions with digital technology occur when the technology itself has the role of an interaction partner (e.g., sexual interaction with a sex robot or with a media persona in pornography). The three types of SIDC and their respective subtypes are explained and backed up with empirical studies that are grouped according to two major mediators: consent and commerce. Regarding the causes and consequences of the three types of SIDC we suggest a classification that entails biological, psychological, social, economic, and technological factors. Regarding implications of SIDC we suggest to focus on both opportunities and risks for sexual health. The proposed conceptual framework of SIDC is meant to inform future research.

The persuasive power of robot touch. Behavioral and evaluative consequences of non-functional touch from a robot.

The unique physical embodiment of robots enables physical contact between machines and humans. Since interpersonal touch research has demonstrated that touch has several positive behavioral (e.g., reduced stress, better immune functioning) as well as evaluative consequences (e.g., better evaluation of the initiator of touch), the question arises whether touch from a humanoid robot, the body of which is somewhat similar to that of a human, can evoke similar effects. To answer this question, we conducted a between-subjects experiment in the laboratory with n = 48 students who encountered a humanoid robot (Softbank Robotics' NAO) that either did or did not touch their hand in a non-functional manner during a counseling conversation. The analyses of participants' behavior revealed that they mostly reacted by smiling and laughing. Furthermore, participants who were touched by the robot complied significantly more frequently with a request posed by the robot during conversation, and reported better feelings compared to those who were not touched. However, there were no effects of robot touch on subjective evaluations of the robot or on the interaction experience.

Revisiting Human-Agent Communication: The Importance of Joint Co-construction and Understanding Mental States.

The study of human-human communication and the development of computational models for human-agent communication have diverged significantly throughout the last decade. Yet, despite frequently made claims of "super-human performance" in, e.g., speech recognition or image processing, so far, no system is able to lead a half-decent coherent conversation with a human. In this paper, we argue that we must start to re-consider the hallmarks of cooperative communication and the core capabilities that we have developed for it, and which conversational agents need to be equipped with: incremental joint co-construction and mentalizing. We base our argument on a vast body of work on human-human communication and its psychological processes that we reason to be relevant and necessary to take into account when modeling human-agent communication. We contrast those with current conceptualizations of human-agent interaction and formulate suggestions for the development of future systems.

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.

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.