Quasi-periodic X-ray eruptions years after a nearby tidal disruption event.

Quasi-periodic eruptions (QPEs) are luminous bursts of soft X-rays from the nuclei of galaxies, repeating on timescales of hours to weeks1-5. The mechanism behind these rare systems is uncertain, but most theories involve accretion disks around supermassive black holes (SMBHs) undergoing instabilities6-8 or interacting with a stellar object in a close orbit9-11. It has been suggested that this disk could be created when the SMBH disrupts a passing star8,11, implying that many QPEs should be preceded by observable tidal disruption events (TDEs). Two known QPE sources show long-term decays in quiescent luminosity consistent with TDEs4,12 and two observed TDEs have exhibited X-ray flares consistent with individual eruptions13,14. TDEs and QPEs also occur preferentially in similar galaxies15. However, no confirmed repeating QPEs have been associated with a spectroscopically confirmed TDE or an optical TDE observed at peak brightness. Here we report the detection of nine X-ray QPEs with a mean recurrence time of approximately 48 h from AT2019qiz, a nearby and extensively studied optically selected TDE16. We detect and model the X-ray, ultraviolet (UV) and optical emission from the accretion disk and show that an orbiting body colliding with this disk provides a plausible explanation for the QPEs.

X-ray quasi-periodic eruptions from two previously quiescent galaxies.

Quasi-periodic eruptions (QPEs) are very-high-amplitude bursts of X-ray radiation recurring every few hours and originating near the central supermassive black holes of galactic nuclei1,2. It is currently unknown what triggers these events, how long they last and how they are connected to the physical properties of the inner accretion flows. Previously, only two such sources were known, found either serendipitously or in archival data1,2, with emission lines in their optical spectra classifying their nuclei as hosting an actively accreting supermassive black hole3,4. Here we report observations of QPEs in two further galaxies, obtained with a blind and systematic search of half of the X-ray sky. The optical spectra of these galaxies show no signature of black hole activity, indicating that a pre-existing accretion flow that is typical of active galactic nuclei is not required to trigger these events. Indeed, the periods, amplitudes and profiles of the QPEs reported here are inconsistent with current models that invoke radiation-pressure-driven instabilities in the accretion disk5-9. Instead, QPEs might be driven by an orbiting compact object. Furthermore, their observed properties require the mass of the secondary object to be much smaller than that of the main body10, and future X-ray observations may constrain possible changes in their period owing to orbital evolution. This model could make QPEs a viable candidate for the electromagnetic counterparts of so-called extreme-mass-ratio inspirals11-13, with considerable implications for multi-messenger astrophysics and cosmology14,15.

Optimal mechanical interactions direct multicellular network formation on elastic substrates.

Cells self-organize into functional, ordered structures during tissue morphogenesis, a process that is evocative of colloidal self-assembly into engineered soft materials. Understanding how intercellular mechanical interactions may drive the formation of ordered and functional multicellular structures is important in developmental biology and tissue engineering. Here, by combining an agent-based model for contractile cells on elastic substrates with endothelial cell culture experiments, we show that substrate deformation-mediated mechanical interactions between cells can cluster and align them into branched networks. Motivated by the structure and function of vasculogenic networks, we predict how measures of network connectivity like percolation probability and fractal dimension as well as local morphological features including junctions, branches, and rings depend on cell contractility and density and on substrate elastic properties including stiffness and compressibility. We predict and confirm with experiments that cell network formation is substrate stiffness dependent, being optimal at intermediate stiffness. We also show the agreement between experimental data and predicted cell cluster types by mapping a combined phase diagram in cell density substrate stiffness. Overall, we show that long-range, mechanical interactions provide an optimal and general strategy for multicellular self-organization, leading to more robust and efficient realizations of space-spanning networks than through just local intercellular interactions.

Neural crest cells as a source of microevolutionary variation.

Vertebrates have some of the most complex and diverse features in animals, from varied craniofacial morphologies to colorful pigmentation patterns and elaborate social behaviors. All of these traits have their developmental origins in a multipotent embryonic lineage of neural crest cells. This "fourth germ layer" is a vertebrate innovation and the source of a wide range of adult cell types. While others have discussed the role of neural crest cells in human disease and animal domestication, less is known about their role in contributing to adaptive changes in wild populations. Here, we review how variation in the development of neural crest cells and their derivatives generates considerable phenotypic diversity in nature. We focus on the broad span of traits under natural and sexual selection whose variation may originate in the neural crest, with emphasis on behavioral factors such as intraspecies communication that are often overlooked. In all, we encourage the integration of evolutionary ecology with developmental biology and molecular genetics to gain a more complete understanding of the role of this single cell type in trait covariation, evolutionary trajectories, and vertebrate diversity.

Practical causal mediation analysis: extending nonparametric estimators to accommodate multiple mediators and multiple intermediate confounders.

Mediation analysis is appealing for its ability to improve understanding of the mechanistic drivers of causal effects, but real-world data complexities challenge its successful implementation, including (i) the existence of post-exposure variables that also affect mediators and outcomes (thus, confounding the mediator-outcome relationship), that may also be (ii) multivariate, and (iii) the existence of multivariate mediators. All three challenges are present in the mediation analysis we consider here, where our goal is to estimate the indirect effects of receiving a Section 8 housing voucher as a young child on the risk of developing a psychiatric mood disorder in adolescence that operate through mediators related to neighborhood poverty, the school environment, and instability of the neighborhood and school environments, considered together and separately. Interventional direct and indirect effects (IDE/IIE) accommodate post-exposure variables that confound the mediator-outcome relationship, but currently, no readily implementable nonparametric estimator for IDE/IIE exists that allows for both multivariate mediators and multivariate post-exposure intermediate confounders. The absence of such an IDE/IIE estimator that can easily accommodate both multivariate mediators and post-exposure confounders represents a significant limitation for real-world analyses, because when considering each mediator subgroup separately, the remaining mediator subgroups (or a subset of them) become post-exposure intermediate confounders. We address this gap by extending a recently developed nonparametric estimator for the IDE/IIE to allow for easy incorporation of multivariate mediators and multivariate post-exposure confounders simultaneously. We apply the proposed estimation approach to our analysis, including walking through a strategy to account for other, possibly co-occurring intermediate variables when considering each mediator subgroup separately.

The corona contracts in a black-hole transient.

The geometry of the accretion flow around stellar-mass black holes can change on timescales of days to months1-3. When a black hole emerges from quiescence (that is, it 'turns on' after accreting material from its companion) it has a very hard (high-energy) X-ray spectrum produced by a hot corona4,5 positioned above its accretion disk, and then transitions to a soft (lower-energy) spectrum dominated by emission from the geometrically thin accretion disk, which extends to the innermost stable circular orbit6,7. Much debate persists over how this transition occurs and whether it is driven largely by a reduction in the truncation radius of the disk8,9 or by a reduction in the spatial extent of the corona10,11. Observations of X-ray reverberation lags in supermassive black-hole systems12,13 suggest that the corona is compact and that the disk extends nearly to the central black hole14,15. Observations of stellar-mass black holes, however, reveal equivalent (mass-scaled) reverberation lags that are much larger16, leading to the suggestion that the accretion disk in the hard-X-ray state of stellar-mass black holes is truncated at a few hundreds of gravitational radii from the black hole17,18. Here we report X-ray observations of the black-hole transient MAXI J1820+07019,20. We find that the reverberation time lags between the continuum-emitting corona and the irradiated accretion disk are 6 to 20 times shorter than previously seen. The timescale of the reverberation lags shortens by an order of magnitude over a period of weeks, whereas the shape of the broadened iron K emission line remains remarkably constant. This suggests a reduction in the spatial extent of the corona, rather than a change in the inner edge of the accretion disk.

Longitudinal MRI of the developing ferret brain reveals regional variations in timing and rate of growth.

Normative ferret brain development was characterized using magnetic resonance imaging. Brain growth was longitudinally monitored in 10 ferrets (equal numbers of males and females) from postnatal day 8 (P8) through P38 in 6-d increments. Template T2-weighted images were constructed at each age, and these were manually segmented into 12 to 14 brain regions. A logistic growth model was used to fit data from whole brain volumes and 8 of the individual regions in both males and females. More protracted growth was found in males, which results in larger brains; however, sex differences were not apparent when results were corrected for body weight. Additionally, surface models of the developing cortical plate were registered to one another using the anatomically-constrained Multimodal Surface Matching algorithm. This, in turn, enabled local logistic growth parameters to be mapped across the cortical surface. A close similarity was observed between surface area expansion timing and previous reports of the transverse neurogenic gradient in ferrets. Regional variation in the extent of surface area expansion and the maximum expansion rate was also revealed. This characterization of normative brain growth over the period of cerebral cortex folding may serve as a reference for ferret studies of brain development.

Pivekimab sunirine (IMGN632), a novel CD123-targeting antibody-drug conjugate, in relapsed or refractory acute myeloid leukaemia: a phase 1/2 study.

BACKGROUND: Pivekimab sunirine (IMGN632) is a first-in-class antibody-drug conjugate comprising a high-affinity CD123 antibody, cleavable linker, and novel indolinobenzodiazepine pseudodimer payload. CD123 is overexpressed in several haematological malignancies, including acute myeloid leukaemia. We present clinical data on pivekimab sunirine in relapsed or refractory acute myeloid leukaemia. METHODS: This first-in-human, phase 1/2 dose-escalation and dose-expansion study enrolled participants aged 18 years or older at nine hospitals in France, Italy, Spain, and the USA with CD123+ haematological malignancies (Eastern Cooperative Oncology Group performance status of 0-1); participants reported here were in a cohort of participants with acute myeloid leukaemia who were refractory to or had relapsed on one or more previous treatments for acute myeloid leukaemia. The 3 + 3 dose-escalation phase evaluated two dosing schedules: schedule A (once every 3 weeks, on day 1 of a 3-week cycle) and fractionated schedule B (days 1, 4, and 8 of a 3-week cycle). The dose-expansion phase evaluated two cohorts: one cohort given 0·045 mg/kg of bodyweight (schedule A) and one cohort given 0·090 mg/kg of bodyweight (schedule A). The primary endpoints were the maximum tolerated dose and the recommended phase 2 dose. Antileukaemia activity (overall response and a composite complete remission assessment) was a secondary endpoint. The study is ongoing and registered with ClinicalTrials.gov, NCT03386513. FINDINGS: Between Dec 29, 2017, and May 27, 2020, 91 participants were enrolled (schedule A, n=68; schedule B, n=23). 30 (44%) of schedule A participants were female and 38 (56%) were male; 60 (88%) were White, six (9%) were Black or African American, and two (3%) were other races. Pivekimab sunirine at doses of 0·015 mg/kg to 0·450 mg/kg in schedule A was administered in six escalating doses with no maximum tolerated dose defined; three dose-limiting toxicities were observed (reversible veno-occlusive disease; 0·180 mg/kg, n=1 and 0·450 mg/kg, n=1; and neutropenia; 0·300 mg/kg, n=1). Schedule B was not pursued further on the basis of comparative safety and antileukaemia findings with schedule A. The recommended phase 2 dose was selected as 0·045 mg/kg once every 3 weeks. At the recommended phase 2 dose (n=29), the most common grade 3 or worse treatment-related adverse events were febrile neutropenia (three [10%]), infusion-related reactions (two [7%]), and anaemia (two [7%]). Treatment-related serious adverse events occurring in 5% or more of participants treated at the recommended phase 2 dose were febrile neutropenia (two [7%]) and infusion-related reactions (two [7%]). Among 68 participants who received schedule A, one death (1%) was considered to be treatment-related (cause unknown; 0·300 mg/kg cohort). At the recommended phase 2 dose, the overall response rate was 21% (95% CI 8-40; six of 29) and the composite complete remission rate was 17% (95% CI 6-36; five of 29). INTERPRETATION: Pivekimab sunirine showed single-agent activity across multiple doses, with a recommended phase 2 dose of 0·045 mg/kg once every 3 weeks. These findings led to a phase 1b/2 study of pivekimab sunirine plus azacitidine and venetoclax in patients with CD123-positive acute myeloid leukaemia. FUNDING: ImmunoGen.

Epigenetics and the evolution of form: Experimental manipulation of a chromatin modification causes species-specific changes to the craniofacial skeleton.

A central question in biology is the molecular origins of phenotypic diversity. While genetic changes are key to the genotype-phenotype relationship, alterations to chromatin structure and the physical packaging of histone proteins may also be important drivers of vertebrate divergence. We investigate the impact of such an epigenetic mechanism, histone acetylation, within a textbook example of an adaptive radiation. Cichlids of Lake Malawi have adapted diverse craniofacial structures, and here we investigate how histone acetylation influences morphological variation in these fishes. Specifically, we assessed the effect of inhibiting histone deacetylation using the drug trichostatin A (TSA) on developing facial structures. We examined this during three critical developmental windows in two cichlid species with alternate adult morphologies. Exposure to TSA during neural crest cell (NCC) migration and as postmigratory NCCs proliferate in the pharyngeal arches resulted in significant changes in lateral and ventral shape in Maylandia, but not in Tropheops. This included an overall shortening of the head, widening of the lower jaw, and steeper craniofacial profile, all of which are paedomorphic morphologies. In contrast, treatment with TSA during early chondrogenesis did not result in significant morphological changes in either species. Together, these data suggest a sensitivity to epigenetic alterations that are both time- and species-dependent. We find that morphologies are due to nonautonomous or potentially indirect effects on NCC development, including in part a global developmental delay. Our research bolsters the understanding that proper histone acetylation is essential for early craniofacial development and identifies a species-specific robustness to developmental change. Overall, this study demonstrates how epigenetic regulation may play an important role in both generating and buffering morphological variation.

Learning Optimal Dynamic Treatment Regimes from Longitudinal Data.

Studies often report estimates of the average treatment effect (ATE). While the ATE summarizes the effect of a treatment on average, it does not provide any information about the effect of treatment within any individual. A treatment strategy that uses an individual's information to tailor treatment to maximize benefit is known as an optimal dynamic treatment rule (ODTR). Treatment, however, is typically not limited to a single point in time; consequently, learning an optimal rule for a time-varying treatment may involve not just learning the extent to which the comparative treatments' benefits vary across the characteristics of individuals, but also learning the extent to which the comparative treatments' benefits vary as relevant circumstances evolve within an individual. The goal of this paper is to provide a tutorial for estimating ODTR from longitudinal observational and clinical trial data for applied researchers. We describe an approach that uses a doubly-robust unbiased transformation of the conditional average treatment effect. We then learn a time-varying ODTR for when to increase buprenorphine-naloxone (BUP-NX) dose to minimize return-to-regular-opioid-use among patients with opioid use disorder. Our analysis highlights the utility of ODTRs in the context of sequential decision making: the learned ODTR outperforms a clinically defined strategy.

Is nicotine vaping associated with subsequent initiation of cannabis or other substances from adolescence into young adulthood?

Prior studies estimating longitudinal associations between nicotine vaping and subsequent initiation of cannabis and other substances (e.g., cocaine, heroin) have been limited by short follow-up periods, convenience sampling, and possibly inadequate confounding control. We sought to address some of these gaps using the nationally representative Population Assessment of Tobacco and Health Study (PATH) to estimate longitudinal associations between nicotine vaping and the initiation of cannabis or other substances among adolescents transitioning to adulthood from2013 to 2019, adjusting for treatment-confounder feedback. Estimands like the longitudinal average treatment effect were not identified because of extensive practical positivity violations. Therefore, we estimated longitudinal incremental propensity score effects, which were identified. We found that reduced odds of nicotine vaping were associated with decreased risks of cannabis or other substance initiation; these associations strengthened over time. For example, by the final wave (2018-19), cannabis and other substance initiation risks were 6.2 (95%CI:4.6-7.7) and 1.8 (95%CI:0.4-3.2) percentage points lower when odds of nicotine vaping were reduced to be 90% lower in all preceding waves (2013-14 to 2016-18), as compared with observed risks. Strategies to lower nicotine vaping prevalence during this period may have resulted in fewer young people initiating cannabis and other substances.

The role of prescription opioid and cannabis supply policies on opioid overdose deaths.

Mandatory prescription drug monitoring programs and cannabis legalization have been hypothesized to reduce overdose deaths. We examined associations between prescription monitoring programs with access mandates ("must-query PDMPs"), legalization of medical and recreational cannabis supply, and opioid overdose deaths in United States counties in 2013-2020. Using data on overdose deaths from the National Vital Statistics System, we fit Bayesian spatiotemporal models to estimate risk differences and 95% credible intervals (CrI) in county-level opioid overdose deaths associated with enactment of these state policies. Must-query PDMPs were independently associated with on average 0.8 (95% CrI: 0.5, 1.0) additional opioid-involved overdose deaths per 100,000 person-years. Legal cannabis supply was not independently associated with opioid overdose deaths in this time period. Must-query PDMPs enacted in the presence of legal (medical or recreational) cannabis supply were associated with 0.7 (95% CrI: 0.4, 0.9) more opioid-involved deaths, relative to must-query PDMPs without any legal cannabis supply. In a time when overdoses are driven mostly by non-prescribed opioids, stricter opioid prescribing policies and more expansive cannabis legalization were not associated with reduced overdose death rates.

Nonparametric causal mediation analysis for stochastic interventional (in)direct effects.

Causal mediation analysis has historically been limited in two important ways: (i) a focus has traditionally been placed on binary exposures and static interventions and (ii) direct and indirect effect decompositions have been pursued that are only identifiable in the absence of intermediate confounders affected by exposure. We present a theoretical study of an (in)direct effect decomposition of the population intervention effect, defined by stochastic interventions jointly applied to the exposure and mediators. In contrast to existing proposals, our causal effects can be evaluated regardless of whether an exposure is categorical or continuous and remain well-defined even in the presence of intermediate confounders affected by exposure. Our (in)direct effects are identifiable without a restrictive assumption on cross-world counterfactual independencies, allowing for substantive conclusions drawn from them to be validated in randomized controlled trials. Beyond the novel effects introduced, we provide a careful study of nonparametric efficiency theory relevant for the construction of flexible, multiply robust estimators of our (in)direct effects, while avoiding undue restrictions induced by assuming parametric models of nuisance parameter functionals. To complement our nonparametric estimation strategy, we introduce inferential techniques for constructing confidence intervals and hypothesis tests, and discuss open-source software, the $\texttt{medshift}$$\texttt{R}$ package, implementing the proposed methodology. Application of our (in)direct effects and their nonparametric estimators is illustrated using data from a comparative effectiveness trial examining the direct and indirect effects of pharmacological therapeutics on relapse to opioid use disorder.

Studying Continuous, Time-varying, and/or Complex Exposures Using Longitudinal Modified Treatment Policies.

This tutorial discusses a methodology for causal inference using longitudinal modified treatment policies. This method facilitates the mathematical formalization, identification, and estimation of many novel parameters and mathematically generalizes many commonly used parameters, such as the average treatment effect. Longitudinal modified treatment policies apply to a wide variety of exposures, including binary, multivariate, and continuous, and can accommodate time-varying treatments and confounders, competing risks, loss to follow-up, as well as survival, binary, or continuous outcomes. Longitudinal modified treatment policies can be seen as an extension of static and dynamic interventions to involve the natural value of treatment and, like dynamic interventions, can be used to define alternative estimands with a positivity assumption that is more likely to be satisfied than estimands corresponding to static interventions. This tutorial aims to illustrate several practical uses of the longitudinal modified treatment policy methodology, including describing different estimation strategies and their corresponding advantages and disadvantages. We provide numerous examples of types of research questions that can be answered using longitudinal modified treatment policies. We go into more depth with one of these examples, specifically, estimating the effect of delaying intubation on critically ill COVID-19 patients' mortality. We demonstrate the use of the open-source R package lmtp to estimate the effects, and we provide code on https://github.com/kathoffman/lmtp-tutorial.

Overcoming Data Gaps in Life Course Epidemiology by Matching Across Cohorts.

Life course epidemiology is hampered by the absence of large studies with exposures and outcomes measured at different life stages in the same individuals. We describe when the effect of an exposure ( A ) on an outcome ( Y ) in a target population is identifiable in a combined ("synthetic") cohort created by pooling an early-life cohort including measures of A with a late-life cohort including measures of Y . We enumerate causal assumptions needed for unbiased effect estimation in the synthetic cohort and illustrate by simulating target populations under four causal models. From each target population, we randomly sampled early- and late-life cohorts and created a synthetic cohort by matching individuals from the two cohorts based on mediators and confounders. We estimated the effect of A on Y in the synthetic cohort, varying matching variables, the match ratio, and the strength of association between matching variables and A . Finally, we compared bias in the synthetic cohort estimates when matching variables did not d-separate A and Y to the bias expected in the original cohort. When the set of matching variables includes all variables d-connecting exposure and outcome (i.e., variables blocking all backdoor and front-door pathways), the synthetic cohort yields unbiased effect estimates. Even when matching variables did not fully account for confounders, the synthetic cohort estimate was sometimes less biased than comparable estimates in the original cohort. Methods based on merging cohorts may hasten the evaluation of early- and mid-life determinants of late-life health but rely on available measures of both confounders and mediators.

The Combined Relationship of Prescription Drug Monitoring Program Enactment and Medical Cannabis Laws with Chronic Pain-Related Healthcare Visits.

BACKGROUND: U.S. state electronic prescription drug monitoring programs (PDMPs) are associated with reduced opioid dispensing among people with chronic pain and may impact use of other chronic pain treatments. In states with medical cannabis laws (MCLs), patients can use cannabis for chronic pain management, reducing their need for chronic-pain related treatment visits and moderating effects of PDMP laws. OBJECTIVE: Given high rates of chronic pain among Medicaid enrollees, we examined associations between PDMP enactment in the presence or absence of MCL on chronic pain-related outpatient and emergency department (ED) visits. DESIGN: We created annual cohorts of Medicaid enrollees with chronic pain diagnoses using national Medicaid claims data from 2002-2013 and 2016. Negative binomial hurdle models produced adjusted odds ratios (aOR) for the likelihood of any chronic pain-related outpatient or ED visit and incident rate ratios (IRR) for the rate of visits among patients with ≥ 1 visit. PARTICIPANTS: Medicaid enrollees aged 18-64 years with chronic pain (N = 4,878,462). MAIN MEASURES: A 3-level state-year variable with the following categories: 1) no PDMP, 2) PDMP enactment in the absence of MCL, or 3) PDMP enactment in the presence of MCL. Healthcare codes for chronic pain-related outpatient and ED visits each year. KEY RESULTS: The sample was primarily female (67.2%), non-Hispanic White (51.2%), and ages 40-55 years (37.2%). Compared to no-PDMP states, PDMP enactment in the absence of MCL was not associated with chronic pain-related outpatient visits but PDMP enactment in the presence of MCL was associated with lower odds of chronic pain-related outpatient visits (aOR = 0.81, 95% CI:0.71-0.92). PDMP enactment was not associated with ED visits, irrespective of MCL. CONCLUSIONS: During a period of PDMP and MCL expansion, our findings suggest treatment shifts for persons with chronic pain away from outpatient settings, potentially related to increased use of cannabis for chronic pain management.

Independent and joint contributions of physical disability and chronic pain to incident opioid use disorder and opioid overdose among Medicaid patients.

BACKGROUND: Chronic pain has been extensively explored as a risk factor for opioid misuse, resulting in increased focus on opioid prescribing practices for individuals with such conditions. Physical disability sometimes co-occurs with chronic pain but may also represent an independent risk factor for opioid misuse. However, previous research has not disentangled whether disability contributes to risk independent of chronic pain. METHODS: Here, we estimate the independent and joint adjusted associations between having a physical disability and co-occurring chronic pain condition at time of Medicaid enrollment on subsequent 18-month risk of incident opioid use disorder (OUD) and non-fatal, unintentional opioid overdose among non-elderly, adult Medicaid beneficiaries (2016-2019). RESULTS: We find robust evidence that having a physical disability approximately doubles the risk of incident OUD or opioid overdose, and physical disability co-occurring with chronic pain increases the risks approximately sixfold as compared to having neither chronic pain nor disability. In absolute numbers, those with neither a physical disability nor chronic pain condition have a 1.8% adjusted risk of incident OUD over 18 months of follow-up, those with physical disability alone have an 2.9% incident risk, those with chronic pain alone have a 3.6% incident risk, and those with co-occurring physical disability and chronic pain have a 11.1% incident risk. CONCLUSIONS: These findings suggest that those with a physical disability should receive increased attention from the medical and healthcare communities to reduce their risk of opioid misuse and attendant negative outcomes.

Using instrumental variables to address unmeasured confounding in causal mediation analysis.

Mediation analysis is a strategy for understanding the mechanisms by which interventions affect later outcomes. However, unobserved confounding concerns may be compounded in mediation analyses, as there may be unobserved exposure-outcome, exposure-mediator, and mediator-outcome confounders. Instrumental variables (IVs) are a popular identification strategy in the presence of unobserved confounding. However, in contrast to the rich literature on the use of IV methods to identify and estimate a total effect of a non-randomized exposure, there has been almost no research into using IV as an identification strategy to identify mediational indirect effects. In response, we define and nonparametrically identify novel estimands-double complier interventional direct and indirect effects-when 2, possibly related, IVs are available, one for the exposure and another for the mediator. We propose nonparametric, robust, efficient estimators for these effects and apply them to a housing voucher experiment.

Genicular Artery Embolization for Treatment of Symptomatic Knee Osteoarthritis - Two Year Outcome Data.

PURPOSE: To report the 24-month outcomes and subgroup analysis evaluating the safety and effectiveness of the genicular artery embolization (GAE) for the treatment of symptomatic knee osteoarthritis (OA). MATERIALS AND METHODS: Forty participants with symptomatic moderate to severe knee OA from a single-center, single-arm prospective trial of GAE were included in this study. Abnormal genicular artery neovascularity was identified at the subject's focal knee pain with digital subtraction angiography and cone-beam computed tomography. Embolization was performed with 100-µm microspheres. The primary end point was treatment effectiveness as measured by sustained improvement in OA symptoms at 24 months, quantified using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Treatment success was defined as ≥50% decrease in WOMAC relative to baseline. Clinical outcomes were assessed with mean age of 66.0 ± 8.1 years and BMI of 30.1 ± 6.2 kg/m2. RESULTS: Two of the forty (5.0%) patients were lost to follow up. Overall, 18 of 38 (47.4%) patients demonstrated ≥50% reduction in WOMAC at 24 months. In the subset of patients with initial clinical success at 12 months, 18 of 25 (72.0%) reported sustained clinical success at 24 months. Seven of 25 (28.0%) had symptom recurrence between 12 and 24 months and were determined to be clinical failures. All treatment-related adverse events occurred within 12 months following GAE, without additional events after 12 months. CONCLUSION: GAE is effective in achieving sustained symptom relief related to moderate to severe knee OA for up to 24 months with an acceptable safety profile.

Adverse childhood experiences among black sexually minoritized men and Black transgender women in Chicago.

BACKGROUND: Adverse childhood experiences (ACE) are important predictors of mental health outcomes in adulthood. However, commonly used ACE measures such as the Behavioural Risk Factor Surveillance System (BRFSS) have not been validated among Black sexually minoritized men (SMM) nor transgender women (TW), whom are known to have higher rates of ACE and poorer mental health outcomes. Assessing the psychometric properties of the measure is important for health equity research, as measurements that are not valid for some populations will render uninterpretable results. METHODS: Data are drawn from the Neighborhoods and Networks (N2) study, a longitudinal cohort of Black SMM and TW living in Southern Chicago. We conducted confirmatory factor analysis, correlation analysis and a two-parameter Item Response Theory (IRT) on the BRFSS ACE measure, an 11-item measure with 8 domains of ACE. RESULTS: One hundred forty seven participants (85% cisgender male) completed the BRFSS ACE measurement in the N2 study with age ranges from 16-34. The cohort were from a low socioeconomic background: about 40% of the cohort were housing insecure and made than $10,000 or less annually. They also have a high number of ACEs; 34% had endorsed 4 or more ACE domains. The three-factor structure fit the BRFSS ACE measure best; the measurement consisted of three subscales: of "Household Dysfunction", "Emotional / Physical", and "Sexual Abuse" (CFI = 0.975, TLI = 0.967, and RMSEA = 0.051). When the 8 domains of ACE were summed to one score, the total score was is correlated with depressive symptoms and anxiety scores, establishing concurrent validity. Item Response Theory model indicated that the "parental separation" domain had a low discrimination (slope) parameter, suggesting that this domain does not distinguish well between those with and without high ACE. CONCLUSIONS: The BRFFS ACE measure had adequate reliability, a well-replicated structure and some moderate evidence of concurrent validity among Black SMM and TW. The parental separation domain does not discriminate between those with high and low ACE experiences in this population. With changing population demographics and trends in marriage, further examination of this item beyond the current study is warranted to improve health equity research for all.