Causal Mechanisms Research Articles

Leveraging pleiotropy for the improved treatment of psychiatric disorders.

Over 90% of drug candidates fail in clinical trials, while it takes 10-15 years and one billion US dollars to develop a single successful drug. Drug development is more challenging for psychiatric disorders, where disease comorbidity and complex symptom profiles obscure the identification of causal mechanisms for therapeutic intervention. One promising approach for determining more suitable drug candidates in clinical trials is integrating human genetic data into the selection process. Genome-wide association studies have identified thousands of replicable risk loci for psychiatric disorders, and sophisticated statistical tools are increasingly effective at using these data to pinpoint likely causal genes. These studies have also uncovered shared or pleiotropic genetic risk factors underlying comorbid psychiatric disorders. In this article, we argue that leveraging pleiotropic effects will provide opportunities to discover novel drug targets and identify more effective treatments for psychiatric disorders by targeting a common mechanism rather than treating each disease separately.

Exploring perceived relationships between weather, climate and mental health: biometeorological perspectives of healthcare practitioners.

Over the last decade, there has been an increase in research examining the influence of weather and climate in mental health caseloads. Variations in temperature, sunshine hours, cloud cover, precipitation and extreme weather events have been statistically linked to diagnoses and increases in hospital admissions for several mental health conditions. This study aimed to explore whether mental health practitioners perceive there to be a link between mental health and daily, seasonal, or inter-annual shifts in various climate variables in South Africa, and the timing and causal mechanisms thereof. Semi-structured interviews were conducted with 50 practicing healthcare practitioners, and the data was analysed using thematic analysis. The findings of this research show that all 50 participants were aware of the link between weather, climate and mental health, primarily through their awareness of seasonal affective disorder. Of the 50 participants, 38 participants could explain the aetiology of seasonal affective disorder. Participants perceived sunlight and temperature to exert an influence on mental health. All 50 participants perceived exposure to sunlight to exert a positive influence on several mental health conditions. Of the 50 participants, 36 participants perceived increases in temperature to exert an adverse effect on mental health symptomology. A minority of 11 participants perceived precipitation to influence mental health conditions such as seasonal affective disorder, bipolar disorder, and substance abuse disorder. Participants' perceptions of the influence of precipitation on mental health provided a unique potential explanation of this relationship, which, at the time of writing, has not been discussed in formal research.

Monetized Interactions in the Sexual Minorities Network at Daneshjoo Park (Tehran, Iran)

AbstractDaneshjoo Park is located in the center of Tehran and is the first hang-out for modern life in the city, gathering different communities such as students, artists, and various lifestyles. Over the years, it has become the most famous hang-out for LGBTQ communities. Despite its significance and hundreds of visitors per day from different parts of the country, Daneshjoo Park has faced years of neglect. This study, employing grounded theory as a research method and in-depth interview as a gathering data method, investigates the emergence of sex work in the park. Participants, aged 18–40, active or retired sex workers, were selected using theoretical and snowball sampling. The findings highlight that underlying individual circumstances, such as poverty, act as catalysts for creating conditions conducive to engaging in sex work, referred to as “Individual Background Conditions.” These conditions facilitate entry into the social network of sex workers, thereby enabling the manifestation of the phenomenon of sex work within Daneshjoo Park, where individuals are gravitated to engage in sex work. The study identifies “Actualizing Interaction Conditions” as the supportive and reproductive causal mechanism through which the network operates, bringing individuals with these background conditions into the fold. This mechanism has enabled the manifestation of the phenomenon of sex work within Daneshjoo Park. The research also identifies a significant historical shift, termed the “Historical Factor,” indicating a transition in the logic of interaction from traditional forms of interaction to monetary exchanges, which has fundamentally altered the landscape of sex work in the park. Ultimately, the study suggests social empowerment strategies as a response to these findings.

Deep Tectonic Environment Analysis of the Lingshan Conjugate Earthquake within the Qinzhou Fold Belt, South China: Insights Derived from 3D Resistivity Structure Model

The Qinzhou fold belt, situated at the contact zone between the Yangtze and Cathaysia blocks in South China, was affected by the 1936 Lingshan M6¾ earthquake and the 1958 Lingshan M5¾ earthquake, both of which occurred within the conjugate structure. Understanding the deep seismogenic setting and causal mechanism of the Lingshan conjugate earthquake is of great significance for assessing the seismic disaster risk in the region. In this study, we utilized 237 magnetotelluric datasets and employed three-dimensional electromagnetic inversion to characterize the deep-seated three-dimensional resistivity structure of the Qinzhou fold belt and the Lingshan seismic zone. The results reveal that: (1) The NE-trending faults within the Qinzhou fold belt and adjacent areas are classified as trans-crustal faults. The faults exhibit crust-mantle ductile shear zones in their deeper sections, which are essential in governing regional tectonic deformation and seismic activity; (2) The electrical structure of the Qinzhou fold belt is in line with the tectonic characteristics of a composite orogenic belt, having experienced several phases of tectonic modification. The southeastern region is being influenced by mantle-derived magmatic activities originating from the Leiqiong area over a significant distance; (3) In the Lingshan seismic zone, the NE-trending Fangcheng-Lingshan fault is a trans-crustal fault and the NW-trending Zhaixu fault is an intra-crustal fault. The electrical structure pattern “two low, one high” in the zone has a significant impact on the deep tectonic framework of the area and influences the deformation behavior of shallow faults; and (4) The seismogenic structure of the 1936 Lingshan M6¾ earthquake was the Fangcheng-Lingshan fault. The earthquake’s genesis was influenced by the coupling effect of tectonic stress and deep thermal dynamics. The seismogenic structure of the 1958 Lingshan M5¾ earthquake was the Zhaixu fault. The earthquake’s genesis was influenced by tectonic stress and static stress triggering from the 1936 Lingshan M6¾ earthquake. The conjugate rupture mode in the Lingshan seismic zone is influenced by various factors, including differences in physical properties, rheology of deep materials, and the scale and depth of fault development.

Understanding migration power in international studies

Abstract Where and how does power operate in the governance of international migration? Migrants and refugees are increasingly used for strategic purposes in international politics, but scholarship on this matter has yet to engage thoroughly with the central International Relations concept of power. This article draws on the thinking of Michael Barnett and Raymond Duvall to propose a well-rounded picture of the multiple forms of power in, through or against migration that are mobilized by states and other international actors. We thus conceptualize migration power across two relational dimensions: the nature of the social relations between the actors involved (interactive or constitutive) and the specificity of such relations (direct or diffuse). This leads us to distinguish between four complementary types of migration power—compulsory, institutional, structural and productive—and to identify the main causal mechanisms through which they operate. We argue that power in international migration governance is diffuse, wielded by a wide range of actors, unevenly spread across its different dimensions, and yet, deeply asymmetrical in its distribution along intersecting axes: namely global North vs South, as well as state vs non-state. Beyond academia, the recognition of this complexity can encourage more reflexivity in policy-making and more sensitivity among practitioners.

Gaming the Industrial Revolution. Participatory design with historical data for classroom learning

Industrial Re:evolution is an educational game developed by a collaborative team of educators, historians, game designers, and developers. The game allows students to hypothesise about the underlying causal mechanisms of the Industrial Revolution while managing population and resources across 19 discrete regions in England and Wales from 1600 to 1851. The game was developed through a series of participatory workshops, which led to a gameplay concept based on a comprehensive model of the Industrial Revolution, centred on key theoretical frameworks. Through role-playing, problem solving, and in-class discussions, students are encouraged to explore various factors that contribute to the Industrial Revolution and their interdependencies. It helps them develop a deeper understanding of the intricate relationships between different causal factors, improving their ability to explain and analyse complex historical events, and promoting quantitative skills. The game is an open-ended historical simulation based on state-of-the-art research, providing students with the opportunity to interact with real historical data. To enhance classroom implementation, the game is provided with structured activities, lesson plans, student booklets, and multimedia materials, while an online platform will eventually offer a community for educators to share best practices. This study describes the design choices and development of the game.

Turn to the right, turn away from the green?—A nuanced analysis on how a populist radical right party affects environmental policy making in Sweden

AbstractPopulist radical right parties are on the rise all over Europe. Recent literature investigates their effects on environmental policy, however, often applying an overly broad perspective on the policy area and neglecting causal mechanisms. This article addresses both gaps in an in‐depth case study of partisan effects on Swedish environmental policy in the wake of increasing populist radical right influence. A novel data approach deriving party positions and policy output from the hard figures of budget proposals between 2001 and 2023, allows a nuanced analysis of environmental policy and its subsectors (e.g., nature conservation and climate mitigation). In summary, a traditional partisan effect is confirmed as a major explaining factor for environmental policy change, while the effect unfolds through altered coalition formation strategies leading to the exclusion of “green voices.” This brings to the fore interactive environmental policy effects of the populist radical right and center‐right parties in the context of changing party competition constellations more generally.

7939 Impact of genetic background on chronic inflammation in a letrozole-induced mouse model of PCOS

Abstract Disclosure: N. Ujagar: None. G. De Robles: None. L.M. Velez: None. M. Seldin: None. D. Nicholas: None. The etiology behind polycystic ovary syndrome (PCOS) is elusive due to the heterogeneity of its symptoms and varying severity in patients. There are a wide variety of factors associated with PCOS, like hyperinsulinemia, hyperandrogenism, endotoxemia and chronic inflammation that have been implicated as causal factors in the condition. However mechanisms of cause and effect are difficult to establish in human cohorts. Endotoxemia, observed in humans and mouse models of PCOS, is known to trigger chronic inflammation by activating immune cells. Although correlation of chronic inflammation with PCOS has been established, the type of inflammation in PCOS patients has not been defined, in part due to the genetic variance from person to person. Using a systems immunology approach to mimic human genetic diversity, combined with a letrozole-induced PCOS mouse model, we aim to distinguish the types of inflammation present in PCOS. We analyzed the immune cells from lymph nodes and spleens of 21 different strains of PCOS induced and control mice (130 mice in total), and found that based on genetic background the reproductive and metabolic phenotypes differed- similar to how PCOS presents clinically. We were able to categorize each letrozole-induced mouse strain into the sub-phenotypes of PCOS based on the current guidelines for diagnosing PCOS published in 2023 and extensive characterization of each strain. Splenocytes from these control and PCOS mice were activated in vitro to trigger T cell and myeloid cell cytokine secretion, which was measured via luminex. Clustering analysis of these multi-analyte cytokine measurements together with flow cytometry of the immune cells allowed us to identify T-helper 17 (Th17) cells as the prominent immune cell driving inflammation in letrozole-induce mouse model of PCOS independent of genetic background. This systems immunology approach has allowed us to define PCOS associated inflammation and will be the basis for integrating human inflammation in PCOS with mouse models that appropriately recapitulate disease. The discovery of Th17 cells as key inflammatory mediators provide targets for understanding the mechanisms linking chronic inflammation to reproductive and metabolic outcomes in PCOS, and will assist in future development of anti-inflammatory therapies. Presentation: 6/2/2024

7939 Impact of genetic background on chronic inflammation in a letrozole-induced mouse model of PCOS

Abstract Disclosure: N. Ujagar: None. G. De Robles: None. L.M. Velez: None. M. Seldin: None. D. Nicholas: None. The etiology behind polycystic ovary syndrome (PCOS) is elusive due to the heterogeneity of its symptoms and varying severity in patients. There are a wide variety of factors associated with PCOS, like hyperinsulinemia, hyperandrogenism, endotoxemia and chronic inflammation that have been implicated as causal factors in the condition. However mechanisms of cause and effect are difficult to establish in human cohorts. Endotoxemia, observed in humans and mouse models of PCOS, is known to trigger chronic inflammation by activating immune cells. Although correlation of chronic inflammation with PCOS has been established, the type of inflammation in PCOS patients has not been defined, in part due to the genetic variance from person to person. Using a systems immunology approach to mimic human genetic diversity, combined with a letrozole-induced PCOS mouse model, we aim to distinguish the types of inflammation present in PCOS. We analyzed the immune cells from lymph nodes and spleens of 21 different strains of PCOS induced and control mice (130 mice in total), and found that based on genetic background the reproductive and metabolic phenotypes differed- similar to how PCOS presents clinically. We were able to categorize each letrozole-induced mouse strain into the sub-phenotypes of PCOS based on the current guidelines for diagnosing PCOS published in 2023 and extensive characterization of each strain. Splenocytes from these control and PCOS mice were activated in vitro to trigger T cell and myeloid cell cytokine secretion, which was measured via luminex. Clustering analysis of these multi-analyte cytokine measurements together with flow cytometry of the immune cells allowed us to identify T-helper 17 (Th17) cells as the prominent immune cell driving inflammation in letrozole-induce mouse model of PCOS independent of genetic background. This systems immunology approach has allowed us to define PCOS associated inflammation and will be the basis for integrating human inflammation in PCOS with mouse models that appropriately recapitulate disease. The discovery of Th17 cells as key inflammatory mediators provide targets for understanding the mechanisms linking chronic inflammation to reproductive and metabolic outcomes in PCOS, and will assist in future development of anti-inflammatory therapies. Presentation: 6/2/2024

8663 Sex differences in delayed fear incubation in mice

Abstract Disclosure: M. Littlepage-Saunders: None. M. Rusnak: None. M. Tsuda: None. T. Wu: None. Post-traumatic stress disorder (PTSD) has a lifetime prevalence of 1 in 13 people. It is not fully understood why some are more vulnerable to developing PTSD whereas others are more resilient. Among those who develop PTSD, about a quarter have delayed-onset PTSD where onset of symptoms occur at 6 months or later after experiencing a traumatic event. While there is recognition of this type of PTSD, the underlying mechanism is poorly understood. The development of PTSD is more prevalent in women than men. However, previous preclinical and clinical studies have focused mainly on males. Thus, there lacks an understanding of this sex difference. To enhance our understanding of the causal mechanisms, we designed a study with mice to compare the effect of sex on delayed fear incubation. We expected the female mice to show increased fear responses that would suggest more chronic delayed fear incubation than the male mice. To test this, we evaluated distance travelled, freezing, and latency until the first freezing episode in adult male and female C57Bl/6J mice (7-8 weeks of age; n=8/group) using a delayed fear incubation behavioral assay. Animals were placed in a fear conditioning chamber for a 198 s acclimation period and then administered a single 2 s scrambled footshock of 1.5 mA via the metal grid floor. After an additional 60 s, animals were returned to their home cage. At specific time after shock application, animals underwent a fear recall test where the animals were placed back in the shock chamber for a total of 180 s without any additional footshocks and then returned to their home cage. The study was based on a 2X2 factorial design comprising of sex (male vs female) and recall time (1 day and 14 days post shock). The data showed an increasing freezing trend (p=0.08) at d 14 compared to their recall d 1 counterparts. There was no effect of time or sex on distance travelled or latency until the first freezing episode. Interestingly, female mice showed less freezing when compared to the male mice. Ongoing experiments will look more into circuitry-level changes by comparing neuronal activation through cFos expression in different brain regions that are a part of the limbic system and/or have been associated with fear: the amygdala, hippocampus, prefrontal cortex, and paraventricular nucleus. Presentation: 6/2/2024

Does Proportionality Increase Turnout? A Study of Adaptation to Oscillating Electoral Systems

Does proportionality increase turnout? This article studies a national electoral reform in early twentieth-century Argentina that was implemented asymmetrically across districts, creating a natural laboratory in which some districts oscillated between electoral systems across elections. Leveraging this unusual variation in a difference-in-differences design, this article shows that a shift from multi-member plurality rules towards a slightly more proportional system—which removed one-third of the contested seats from the grasp of the dominant party—led to a four percentage point increase in turnout. An investigation into causal mechanisms indicates that more proportional rules, by increasing the odds that smaller parties obtain seats, promoted strategic party entry and intensified electoral competition, both between and within parties. These findings complement existing quasi-experimental results that focus exclusively on elections in European democracies, confirm that parties are able to adapt immediately to changes in electoral rules, and refute the belief that proportionality does not affect turnout in Latin America.

What Enables Implementation of Pain Management Interventions in Intensive Care Units and Why: A Realist Evaluation to Refine Program Theory.

To uncover perspectives and refine 12 initial program theories concerning the implementation of pain management interventions in intensive care units. Contexts enabling implementation are delineated, and causal mechanisms within these contexts are described. A realist evaluation approach was employed. Fourteen purposively selected Australian nurses of variant roles were virtually and individually interviewed between July and September 2023. Participants were presented with initial program theory, and their perspectives were collated. Data were analysed using an integrated approach of context (C), mechanism (M), outcome (O) categorisation coding, CMO configurations connecting and pattern matching. Pain management interventions work if perceived to be beneficial, precise, comprehensive and fit for purpose. Nurses should be willing to change attitudes and update knowledge. Unit leaders should nurture the development of nurses' professional identity, access to learning, autonomy and self-determination. Organisations should change the infrastructure, provide resources, mitigate barriers, develop shared mental models, update evidence and institute quality assurance. Adherence to interventions is affected by the outcomes of implementation and intrinsic merits of interventions. In these contexts, confidence is boosted; feelings of empowerment, self-efficacy, reflective motivation, trust, awareness and autonomy are developed; and capacity is built. Furthermore, frustration from the variability of practices is reduced, accountability and ownership are augmented, yielding positive implementation outcomes. Findings have implications on nurses, team leaders and organisations concerned with implementation. The findings provided a fortified understanding of conditions favouring successful implementation of pain management interventions. Actions should be undertaken at an individual, unit and organisation level to ensure successful implementation. RAMESES II Reporting Standards for Realist Evaluations informed presentation of study. Intensive care nurses contributed insights to refine the program theory.

Unraveling the role of hepatitis B virus DNA integration in B-cell lymphomagenesis.

Studies have shown that hepatitis B virus (HBV)-associated B-cell non-Hodgkin lymphoma (NHL) constitutes a unique subgroup with distinct clinical features. It still leaves open the question of whether the integration of HBV DNA into the B-cell genome is a causal mechanism in the development of lymphoma. Using the hybridisation capture-based next generation sequencing and RNA sequencing, we characterised the HBV integration pattern in 45 HBV-associated B-cell NHL tumour tissues. A total of 354 HBV integration sites were identified in 13 (28.9%) samples, indicating the relatively low integration frequency in B-cell NHLs. High plasma HBV DNA loads were not associated with the existence of HBV integration. The insertion sites distributed randomly across all the lymphoma genome without any preferential hotspot neither at the chromosomal level nor at the genetic level. Intriguingly, most HBV integrations were nonclonal in B-cell NHLs, implying that they did not confer a survival advantage. Analysis of the paired diagnosis-relapse samples showed the unstable status of HBV integrations during disease progression. Furthermore, transcriptomic analysis revealed the limited biological impact of HBV integration. Our study provides an unbiased HBV integration map in B-cell NHLs, revealing the insignificant role of HBV DNA integration in B-cell lymphomagenesis.

Sub‐Pixel Displacement Estimation With Deep Learning: Application to Optical Satellite Images Containing Sharp Displacements

AbstractOptical image correlation is a powerful method for remotely constraining ground movement from optical satellite imagery related to natural disasters (e.g., earthquakes, volcanoes, landslides). This approach enables the characterization, and identification of the causal factors and mechanisms underlying such processes. By employing sub‐pixel correlation algorithms, one can obtain highly accurate (m‐to‐cm level) displacement fields at high spatial resolution (dm‐to‐cm) by comparing satellite images acquired before and after a period of movement. However, this method generally assumes a homogeneous translation of all pixels within a given correlation window, which will lead to biased estimates of ground displacement if the real case is not well represented by such a simplification, especially when resolving ground displacements next to sharp gradients in displacement, such as those found in the near‐field of earthquake surface ruptures. In this paper, we present an innovative deep learning method estimating sub‐pixel displacement maps from optical satellite images for the retrieval of ground displacement. From the generation of a realistic simulated database, comprising Landsat‐8 satellite image pairs containing simulated sub‐pixel shifts and sharp discontinuities, we develop a Convolutional Neural Network able to retrieve sub‐pixel displacements. The comparison to state‐of‐the‐art correlation methods shows that our pipeline significantly reduces by 32% the estimation bias around fault ruptures, leading to more accurate characterization of the near‐field strain in surface rupturing earthquakes. Application of our model to the 2019 Ridgecrest earthquake demonstrates the ability of our model to accurately and quickly resolve ground displacement using real satellite images. Code is made available at https://gricad‐gitlab.univ‐grenoble‐alpes.fr/montagtr/cnn4l‐discontinuities.

The Influence of Structural Brain Changes on Cognition in the Context of Healthy Aging: Exploring Mediation Effects Through gBAT-The Graphical Brain Association Tool.

The contribution of age-related structural brain changes to the well-established link between aging and cognitive decline is not fully defined. While both age-related regional brain atrophy and cognitive decline have been extensively studied, the specific mediating role of age-related regional brain atrophy on cognitive functions is unclear. This study introduces an open-source software tool with a graphical user interface that streamlines advanced whole-brain mediation analyses, enabling researchers to systematically explore how the brain acts as a mediator in relationships between various behavioral and health outcomes. The tool is showcased by investigating regional brain volume as a mediator to determine the contribution of age-related brain volume loss toward cognition in healthy aging. We analyzed regional brain volumes and cognitive testing data (Montreal Cognitive Assessment [MoCA]) from a cohort of 131 neurologically healthy adult participants (mean age 50 ± 20.8 years, range 20-79, 73% females) drawn from the Aging Brain Cohort Study at the University of South Carolina. Using our open-source tool developed for evaluating brain-behavior associations across the brain and optimized for exploring mediation effects, we conducted a series of mediation analyses using participant age as the predictor variable, total MoCA and MoCA subtest scores as the outcome variables, and regional brain volume as potential mediators. Age-related atrophy within specific anatomical networks was found to mediate the relationship between age and cognition across multiple cognitive domains. Specifically, atrophy in bilateral frontal, parietal, and occipital areas, along with widespread subcortical regions mediated the effect of age on total MoCA scores. Various MoCA subscores were influenced by age through atrophy in distinct brain regions. These involved prefrontal regions, sensorimotor cortex, and parieto-occipital areas for executive function subscores, prefrontal and temporo-occipital regions, along with the caudate nucleus for attention and concentration subscores, frontal and parieto-occipital areas, alongside connecting subcortical areas such as the optic tract for visuospatial subscores and frontoparietal areas for language subscores. Brain-based mediation analysis offers a causal framework for evaluating the mediating role of brain structure on the relationship between age and cognition and provides a more nuanced understanding of cognitive aging than previously possible. By validating the applicability and effectiveness of this approach and making it openly available to the scientific community, we facilitate the exploration of causal mechanisms between variables mediated by the brain.

Effects of interval treadmill training on spatiotemporal parameters in children with cerebral palsy: A machine learning approach

Quantifying individualized rehabilitation responses and optimizing therapy for each person is challenging. For interventions like treadmill training, there are multiple parameters, such as speed or incline, that can be adjusted throughout sessions. This study evaluates if causal modeling and Bayesian Additive Regression Trees (BART) can be used to accurately track the direct effects of treadmill training on gait. We developed a Directed Acyclic Graph (DAG) to specify the assumed relationship between training input parameters and spatiotemporal outcomes during Short Burst Locomotor Treadmill Training (SBLTT), a therapy designed specifically for children with cerebral palsy (CP). We evaluated outcomes after 24 sessions of SBLTT for simulated datasets of 150 virtual participants and experimental data from four children with CP, ages 4–13 years old. Individual BART models were created from treadmill data of each step. Simulated datasets demonstrated that BART could accurately identify specified responses to training, including strong correlations for step length progression (R2 = 0.73) and plateaus (R2 = 0.87). Model fit was stronger for participants with less step-to-step variability but did not impact model accuracy. For experimental data, participants’ step lengths increased by 26 ± 13 % after 24 sessions. Using BART to control for speed or incline, we found that step length increased for three participants (direct effect: 13.5 ± 4.5 %), while one participant decreased step length (−11.6 %). SBLTT had minimal effects on step length asymmetry and step width. Tools such as BART can leverage step-by-step data collected during training for researchers and clinicians to monitor progression, optimize rehabilitation protocols, and inform the causal mechanisms driving individual responses.

Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells.

Greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage-grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage-grouse nest success. Cattle grazing is often assumed to adversely affect sage-grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage-grouse nest predator predating sage-grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage-grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator-specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage-grouse nests. The primary predators detected at sage-grouse nests were coyotes (Canis latrans) and corvids (Corvidea). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non-invasive method for identifying sage-grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage-grouse recruitment.

Balancing Progress and Protection: The Precautionary Principle in Global Environmental Governance

The precautionary principle is based on the premise that the lack of scientific proof does not justify ignoring potential environmental harm. It advocates for taking precautions to avoid damage rather than dealing with the consequences. Therefore, the precautionary principle is a useful guide when governments need to create policy and regulations in the face of scientific uncertainty. This is especially important with regards to sustainable development as it provides legislators with a framework to enact environmental protections even in the absence of scientific certainty regarding the harm caused by specific industrial activities. Regulators across the world need to strike a balance between the economic benefits of some industrial activity and its social and environmental costs. Imprecise knowledge of health risks, inadequate data, lack of definitive proof, unclear priorities, and public debate all complicate the assessment and regulation of these costs. This article draws attention to the ongoing discussion around particulate matter, specifically around the nature of the exposure-response relationship for different health endpoints, the underlying causal mechanisms of the health impacts caused by different types of particles, and the effects of these impacts on diverse populations. It could lead to different reactions from the judiciary. Due to this uncertainty, those in charge of making decisions about regulations and adjudications about health, well-being, and the environment face governance issues.

Wellbeing public policy needs more theory

Advocacy for ‘wellbeing public policy’ (WPP) requires suitable evidence. Endorsing the ambition to focus policy on wellbeing outcomes, we nevertheless argue that the current evidence base is deficient due to a lack of theory. For the purposes of our analysis, we identify theory narrowly with conceptual clarity and themodelling of causal mechanisms underlying statistical regularities. The prevailing focus on identifying ‘drivers’ of wellbeing and their effect sizes is not well suited for such theorising. We show that this status quo creates potential for conceptual confusion, incorrect aggregation, poor robustness and external validity of policy evaluations, inept interventions, and raises the prospect of a ‘Lucas critique’ in wellbeing economics. We discuss what sort of theory addresses these pitfalls, and where WPP could proceed fruitfully even in the absence of such theory. Ultimately, we call upon wellbeing experts to invest in developing theory as this would improve the basis for WPP and outcomes for those affected by it. Moreover, such theoretical contributions from the field of WPP could spillover to other disciplines, extending the reach and influence of wellbeing research.

The daily experience of hunger in UK females with and without food insecurity

Food insecurity (FI) is associated with increased mortality risk, depression, and obesity in females in high-income countries, but causal mechanisms remain unclear. FI is often assumed to lead to increased levels of hunger. However, quantitative evidence describing daily experiences of hunger in FI is lacking. Our pre-registered study used ecological momentary assessment to capture experiences of hunger in two groups of UK-based females: those experiencing FI (N = 143) and those experiencing food security (FS; N = 149). Participants self-reported hunger hourly (0900-2100) for one week (Monday-Sunday). There was no difference between groups in mean hunger (t(290) = 0.17, p = .866, d = 0.02) nor within-day standard deviation in hunger (t(290) = 1.31, p = .193, d = 0.15). However, both quantities fluctuated more from day to day in the FI group. Compared to the FS group, participants in the FI group had a larger day-to-day variation in mean hunger (t(284) = 2.43, p = .016, d = 0.29) and a larger day-to-day variation in the within-day standard deviation of hunger (t(284) = 2.90, p = .004, d = 0.34). In exploratory analyses, we found that the hunger of the two groups patterned differently across the day. Our findings suggest that experiences of hunger are less stable in those experiencing FI, which may reflect associations between FI and greater uncertainty in food access, higher variability in meal timings or the increased likelihood of chaotic home and work lives.