Search

Trustworthy artificial intelligence (TAI) is trending high on the political agenda. However, what is actually implied when talking about TAI, and why it is so difficult to achieve, remains insufficiently understood by both academic discourse and current AI policy frameworks. This paper offers an analytical scheme with four different dimensions that constitute TAI: a) A user perspective of AI as a quasi-other; b) AI's embedding in a network of actors from programmers to platform gatekeepers; c) The regulatory role of governance in bridging trust insecurities and deciding on AI value trade-offs; and d) The role of narratives and rhetoric in mediating AI and its conflictual governance processes. It is through the analytical scheme that overlooked aspects and missed regulatory demands around TAI are revealed and can be tackled. Conceptually, this work is situated in disciplinary transgression, dictated by the complexity of the phenomenon of TAI. The paper borrows from multiple inspirations such as phenomenology to reveal AI as a quasi-other we (dis-)trust; Science & Technology Studies (STS) to deconstruct AI's social and rhetorical embedding; as well as political science for pinpointing hegemonial conflicts within regulatory bargaining.

Abstract Objective The Mental and Substance Use Disorders Prevalence Study (MDPS) builds upon previous epidemiologic studies to provide estimates of prevalence and treatment rates of mental and substance use disorders among adults aged 18–65 in the U.S. The study background and methods are described. Method The MDPS employed novel techniques such as the inclusion of household, prison, homeless and state psychiatric hospital populations, a semi‐structured clinical interview administered by trained clinical interviewers to assess disorders, the assessment of both past year and lifetime schizophrenia spectrum disorder (SSD) using full Diagnostic and Statistical Manual 5 criteria, as well as other mental and substance use disorders, and video‐based interviewing. Population specific and combined sample weights were developed to estimate nationally representative prevalence and treatment rates. Results Data collection was conducted between October 2020 and October 2022 resulting in 5679 clinical interviews. The statistical weighting and analytic plan are described. Weighted response rates and reasons for non‐response are provided for each study population. Conclusions The MDPS successfully developed and employed novel techniques to estimate the prevalence and treatment rates of mental and substance use disorders in both household and non‐household populations, including some of the most impairing disorders such as SSD.

ABSTRACT While type I conventional dendritic cells (cDC1s) are vital for generating adaptive immunity against intracellular pathogens and tumors, their role in defense against fungal pathogen Cryptococcus neoformans remains unclear. We investigated the role of the cDC1 subset in a fungus-restricting mouse model of cryptococcal infection. The cDC1 subset displayed a unique transcriptional signature with highly upregulated T-cell recruitment, polarization, and activation pathways compared to other DC subsets. Using Batf3−/− mice, which lack the cDC1 population, our results support that Batf3-dependent cDC1s are pivotal for the development of the effective immune response against cryptococcal infection, particularly within the lung and brain. Deficiency in Batf3 cDC1 led to diminished CD4 accumulation and decreased IFNγ production across multiple organs, supporting that cDC1s are a major driver of potent Th1 responses during cryptococcal infection. Consistently, mice lacking Batf3-cDC1 demonstrated markedly diminished fungicidal activity and weaker containment of the fungal pathogen. In conclusion, Batf3-dependent cDC1 can function as a linchpin in mounting Th1 response, ensuring effective fungal control during cryptococcal infection. Harnessing cDC1 pathways may present a promising strategy for interventions against this pathogen.IMPORTANCECryptococcus neoformans causes severe meningoencephalitis, accounting for an estimated 200,000 deaths each year. Central to mounting an effective defense against these infections is T-cell-mediated immunity, which is orchestrated by dendritic cells (DCs). The knowledge about the role of specific DC subsets in shaping anti-cryptococcal immunity is limited. Here, we demonstrate that Batf3 cDC1s are important drivers of protective Th1 CD4 T-cell responses required for clearance of cryptococcal infection. Deficiency of Batf3 cDC1 in the infected mice leads to significantly reduced Th1 response and exacerbated fungal growth to the point where depleting the remaining CD4 T cells no longer affects fungal burden. Unveiling this pivotal role of cDC1 in antifungal defense is likely to be important for the development of vaccines and therapies against life-threatening fungal pathogens.

Abstract In this study, we set out to develop a new social vulnerability index (SVI). In doing so, we suggest some conceptual improvements that can be made to existing methodical approaches to assessing social vulnerability. To make the entanglement of socio-spatial inequalities visible, we are conducting a small-scale study on heterogeneous urban development in the city of Hamburg, Germany. This kind of high-resolution analysis was not previously available, but is increasingly requested by political decision makers. We can thus show hot spots of social vulnerability (SV) in Hamburg, considering the effects of social welfare, education, and age. In doing so, we defined SV as a contextual concept that follows the recent shift in discourse in line with the Intergovernmental Panel on Climate Change’s (IPCC) concepts of risk and vulnerability. Our SVI consists of two subcomponents: sensitivity and coping capacity. Populated areas of Hamburg were identified using satellite information and merged with the social data units of the city. Areas with high SVI are distributed over the entire city, notably in the district of Harburg and the Reiherstieg quarter in Wilhelmsburg near the Elbe, as well as in the densely populated inner city areas of Eimsbüttel and St. Pauli. As a map at a detailed scale, our SVI can be a useful tool to identify areas where the population is most vulnerable to climate-related hazards. We conclude that an enhanced understanding of urban social vulnerability is a prerequisite for urban risk management and urban resilience planning.

To date, the study of hype has become a productive but also eclectic field of research. This introduction provides an overview of the core characteristics of technology hype and distinguishes it from other future-oriented concepts. Further, the authors present promising approaches from various disciplines for studying, critiquing, and dealing with hype. The special issue assembles case studies, methodological and theoretical contributions that analyze tech hypes’ temporality, agency, and institutional dynamics. It provides insights into how hypes are triggered and fostered, but also how they can be deconstructed and anticipated.

To date, the study of hype has become a productive but also eclectic field of research. This introduction provides an overview of the core characteristics of technology hype and distinguishes it from other future-oriented concepts. Further, the authors present promising approaches from various disciplines for studying, critiquing, and dealing with hype. The special issue assembles case studies, methodological and theoretical contributions that analyze tech hypes’ temporality, agency, and institutional dynamics. It provides insights into how hypes are triggered and fostered, but also how they can be deconstructed and anticipated.

Big Tech is trying to water down the AI Act, which is supposed to be finalized before the end of this year. This is yet another chapter in the private sector's influence on governments to turn AI regulation into a toothless self-regulatory framework. The narratives that lobbying power is trying to install follow a well-known pattern. This blog post goes into detail and explains what's at stake.

Abstract “Autonomous weapon systems” (AWS) have been subject to intense discussions for years. Numerous political, academic and legal actors are debating their consequences, with many calling for strict regulation or even a global ban. Surprisingly, it often remains unclear which technologies the term AWS refers to and also in what sense these systems can be characterised as autonomous at all. Despite being feared by many, weapons that are completely self-governing and beyond human control are more of a conceptual possibility than an actual military reality. As will be argued, the conflicting interpretations of AWS are largely the result of the diverse meanings that are constructed in political discourses. These interpretations convert specific understandings of AI into strategic assets and consequently hinder the establishment of common ethical standards and legal regulations. In particular, this article looks at the publicly available military AI strategies and position papers by China and the USA. It analyses how AWS technologies, understood as evoking sociotechnical imaginaries, are politicised to serve particular national interests. The article presents the current theoretical debate, which has sought to find a functional definition of AWS that is sufficiently unambiguous for regulatory or military contexts. Approaching AWS as a phenomenon that is embedded in a particular sociotechnical imaginary, however, flags up the ways in which nation states portray themselves as part of a global AI race, competing over economic, military and geopolitical advantages. Nation states do not just enforce their geopolitical ambitions through a fierce realpolitik rhetoric but also play around with ambiguities in definitions. This especially holds true for China and the USA, since they are regarded and regard themselves as hegemonic antagonists, presenting competing self-conceptions that are apparent in their histories, political doctrines and identities. The way they showcase their AI-driven military prowess indicates an ambivalent rhetoric of legal sobriety, tech-regulation and aggressive national dominance. AWS take on the role of signifiers that are employed to foster political legitimacy or to spark deliberate confusion and deterrence.

Key Points: Question: What is the association between social vulnerability and mental health and substance use disorders and related treatment in the US noninstitutionalized population of adults aged 18 years and older? Findings: In this survey study of 4674 participants from US households, large increases in several mental health and substance use disorders and corresponding decreases in treatment were found in the most socially vulnerable communities. Meaning: The findings suggest that routine measurement of social vulnerability might assist in developing more comprehensive care models that integrate medical and social care for mental health and substance use disorders. This survey study evaluates associations of social vulnerability with mental health disorders and substance use disorders in a noninstitutionalized setting. Importance: Community-level social vulnerability (SV) is associated with physical illness and premature mortality. Its association with mental health (MH) and substance use disorders (SUDs) needs further study. Objective: To study associations of SV with clinical diagnoses of MH disorders, SUDs, and related treatments in the US noninstitutionalized population of adults aged 18 years and older. Design, Setting, and Participants: A survey of adults in a national sample of US households between October 2020 and October 2022. Participants drawn from a multistage, clustered, and stratified area probability sample of US households were included, excluding adults older than 65 years because of the difficulty of differentiating mental disorders from symptoms of dementia. The sample also included adults living in prisons, state psychiatric hospitals, and homeless shelters who were excluded from the sample of US households used in these analyses. Each sample household was sent a letter explaining the study and offering the option to complete the household roster online, by phone, or by email. Of the 12 906 adults selected for clinical interviewing in the household sample, 4674 completed clinical interviews. Main Outcomes and Measures: Main outcomes were Structured Clinical Interview for DSM-5 past-year diagnoses of MH disorders and SUDs and responses to survey questions regarding treatment received. The Social Vulnerability Metric (SVM) and the Area Deprivation Index (ADI) were used to determine SV at the residential zip code level. Results: The analysis involved 4674 participants (2904 [62.13%] female and 1770 [37.87%] male; mean [SD] age, 41.51 [13.41] years). Controlling for measured confounders, the SVM was significantly associated with diagnoses of schizophrenia spectrum disorder (SSD; adjusted odds ratio [aOR], 17.22; 95% CI, 3.05-97.29), opioid use disorder (OUD; aOR, 9.47; 95% CI, 2.30-39.02), stimulant use disorder (aOR, 6.60; 95% CI, 2.01-21.67), bipolar I disorder (aOR, 2.39; 95% CI, 1.19-4.80), posttraumatic stress disorder (aOR, 1.63; 95% CI, 1.06-2.50), and any MH disorder (aOR, 1.44; 95% CI, 1.14-1.83), but not major depressive disorder (MDD), generalized anxiety disorder (GAD), or any SUD. Results were similar for the ADI but generally of lower magnitude (SSD aOR, 11.38; 95% CI, 1.61-80.58; OUD aOR, 2.05; 95% CI, 0.30-14.10; stimulant use disorder aOR, 2.18; 95% CI, 0.52-9.18). Among participants with SSDs, SV was associated with reduced MH treatment (aOR, 0.001; 95% CI, 0.00-0.18) and reduced SUD treatment in participants with OUD or stimulant use disorder (aOR, 0.24; 95% CI, 0.02-2.80). Conclusions and Relevance: In contrast to previous studies using nonclinical symptom-based survey data, we found no association between SV and GAD or MDD. By contrast, there were associations of SV with prevalence of SSD, stimulant use disorder, and OUD with corresponding decreases in treatment. These results suggest that the SVM might assist in developing more comprehensive care models that integrate medical and social care for MH disorders and SUDs. [ABSTRACT FROM AUTHOR]

Mental health issues among Ph.D. students are prevalent and on the rise, with multiple studies showing that Ph.D. students are more likely to experience symptoms of mental health-related issues than the general population. However, the data is still sparse. This study aims to investigate the mental health of 589 Ph.D. students at a public university in Germany using a mixed quantitative and qualitative approach. We administered a web-based self-report questionnaire to gather data on the mental health status, investigated mental illnesses such as depression and anxiety, and potential areas for improvement of the mental health and well-being of Ph.D. students. Our results revealed that one-third of the participants were above the cut-off for depression and that factors such as perceived stress and self-doubt were prominent predictors of the mental health status of Ph.D. students. Additionally, we found job insecurity and low job satisfaction to be predictors of stress and anxiety. Many participants in our study reported working more than full-time while being employed part-time. Importantly, deficient supervision was found to have a negative effect on Ph.D. students' mental health. The study's results are in line with those of earlier investigations of mental health in academia, which likewise reveal significant levels of depression and anxiety among Ph.D. students. Overall, the findings provide a greater knowledge of the underlying reasons and potential interventions required for advancing the mental health problems experienced by Ph.D. students. The results of this research can guide the development of effective strategies to support the mental health of Ph.D. students.

This paper introduces the theoretical concept of perceived resource access security in order to assess the link between natural resource scarcity and interstate conflict. It develops the hypothesis that resource access through international trade is an important determinant for conflict behaviour of states arising from resource concerns, implying a shift in focus away from endowments and towards competition for access. The main analysis is conducted in the form of a unit fixed effects logistic regression covering country-dyads of the period 1962–2010 with military interstate dispute (MID) initiation as dependent variable. The empirical findings consistently demonstrate that a diversified position in resource supply networks mitigates the conflict propensity of states characterized by outside dependence for access to natural resources, and thereby help to determine conditions under which trade reduces conflict. [ABSTRACT FROM AUTHOR]

Telomere length has been hypothesized to be a marker of cumulative exposure to stress, and stress is an established cause of depression and anxiety disorders. The aim of this study was to examine the relationship between depression, anxiety and telomere le

Objective: The Mental and Substance Use Disorders Prevalence Study (MDPS) builds upon previous epidemiologic studies to provide estimates of prevalence and treatment rates of mental and substance use disorders among adults aged 18–65 in the U.S. The study background and methods are described. Method: The MDPS employed novel techniques such as the inclusion of household, prison, homeless and state psychiatric hospital populations, a semi‐structured clinical interview administered by trained clinical interviewers to assess disorders, the assessment of both past year and lifetime schizophrenia spectrum disorder (SSD) using full Diagnostic and Statistical Manual 5 criteria, as well as other mental and substance use disorders, and video‐based interviewing. Population specific and combined sample weights were developed to estimate nationally representative prevalence and treatment rates. Results: Data collection was conducted between October 2020 and October 2022 resulting in 5679 clinical interviews. The statistical weighting and analytic plan are described. Weighted response rates and reasons for non‐response are provided for each study population. Conclusions: The MDPS successfully developed and employed novel techniques to estimate the prevalence and treatment rates of mental and substance use disorders in both household and non‐household populations, including some of the most impairing disorders such as SSD. [ABSTRACT FROM AUTHOR]

For the investigation of protein-ligand interaction patterns, the current accessibility of a wide variety of sampling methods allows quick access to large-scale data. The main example is the intensive use of molecular dynamics simulations applied to crystallographic structures which provide dynamic information on the binding interactions in protein-ligand complexes. Chemical feature interaction based pharmacophore models extracted from these simulations, were recently used with consensus scoring approaches to identify potentially active molecules. While this approach is rapid and can be fully automated for virtual screening, additional relevant information from such simulations is still opaque and so far the full potential has not been entirely exploited. To address these aspects, we developed the hierarchical graph representation of pharmacophore models (HGPM). This single graph representation enables an intuitive observation of numerous pharmacophore models from long MD trajectories and further emphasizes their relationship and feature hierarchy. The resulting interactive depiction provides an easy-to-apprehend tool for the selection of sets of pharmacophores as well as visual support for analysis of pharmacophore feature composition and virtual screening results. Furthermore, the representation can be adapted to include information involving interactions between the same protein and multiple different ligands. Herein, we describe the generation, visualization and use of HGPMs generated from MD simulations of two x-ray crystallographic derived structures of the human glucokinase protein in complex with allosteric activators. The results demonstrate that a large number of pharmacophores and their relationships can be visualized in an interactive, efficient manner, unique binding modes identified and a combination of models derived from long MD simulations can be strategically prioritized for VS campaigns.

Abstract Evidence overwhelmingly suggests that the lymphatics play a critical role in the clearance of cerebrospinal fluid (CSF) from the cranial space. Impairment of CSF outflow into the lymphatics is associated with a number of pathological conditions including spaceflight‐associated neuro‐ocular syndrome (SANS), a problem that limits long‐duration spaceflight. We used near‐infrared fluorescence lymphatic imaging (NIRFLI) to dynamically visualize the deep lymphatic drainage pathways shared by CSF outflow and disrupted during head‐down tilt (HDT), a method used to mimic the cephalad fluid shift that occurs in microgravity. After validating CSF clearance into the lymph nodes of the neck in swine, a pilot study was conducted in human volunteers to evaluate the effect of gravity on the flow of lymph through these deep cervical lymphatics. Injected into the palatine tonsils, ICG was imaged draining into deep jugular lymphatic vessels and subsequent cervical lymph nodes. NIRFLI was performed under HDT, sitting, and supine positions. NIRFLI shows that lymphatic drainage through pathways shared by CSF outflow are dependent upon gravity and are impaired under short‐term HDT. In addition, lymphatic contractile rates were evaluated from NIRFLI following intradermal ICG injections of the lower extremities. Lymphatic contractile activity in the legs was slowed in the gravity neutral, supine position, but increased under the influence of gravity regardless of whether its force direction opposed (sitting) or favored (HDT) lymphatic flow toward the heart. These studies evidence the role of a lymphatic contribution in SANS.