HIV/Pre-Exposure Prophylaxis Knowledge and Acceptability of Rapid HIV Testing Among Transgender Adolescents in a Multidisciplinary Gender Clinic.

Purpose: The objectives of this study were to assess the knowledge of HIV and pre-exposure prophylaxis (PrEP) in transgender adolescents and young adults (AYAs) and to test the acceptability of rapid HIV testing among transgender adolescents in a multidisciplinary gender clinic. Methods: Participants enrolled on the same day as their mental health or medical appointment in a multidisciplinary gender clinic. They completed survey questions regarding HIV and PrEP knowledge and were also offered an optional same-day, rapid, fourth-generation HIV test. Participants who had an HIV test answered additional questions about their testing experience. Results: We enrolled 61 participants; just over half (n=31) were assigned female at birth. Less than a third (n=20, 32.8%) scored 80% or above regarding HIV knowledge. Nearly half of the participants (n=29, 47.5%) were not interested in PrEP. Forty-one percent of participants chose to have a rapid HIV test; all were "satisfied" with the testing experience. There were no positive HIV results. Conclusions: Transgender AYAs have gaps in their understanding of HIV acquisition and transmission. Rapid HIV testing in the setting of gender care is well received by those who desire testing and may be a way to increase knowledge of transgender AYA HIV status.

Strength and resilience of developing brain circuits predict adolescent emotional and stress responses during the COVID-19 pandemic.

The COVID-19 pandemic has had profound but incompletely understood adverse effects on youth. To elucidate the role of brain circuits in how adolescents responded to the pandemic's stressors, we investigated their prepandemic organization as a predictor of mental/emotional health in the first ~15 months of the pandemic. We analyzed resting-state networks from n = 2,641 adolescents [median age (interquartile range) = 144.0 (13.0) months, 47.7% females] in the Adolescent Brain Cognitive Development study, and longitudinal assessments of mental health, stress, sadness, and positive affect, collected every 2 to 3 months from May 2020 to May 2021. Topological resilience and/or network strength predicted overall mental health, stress and sadness (but not positive affect), at multiple time points, but primarily in December 2020 and May 2021. Higher resilience of the salience network predicted better mental health in December 2020 (ß = 0.19, 95% CI = [0.06, 0.31], P = 0.01). Lower connectivity of left salience, reward, limbic, and prefrontal cortex and its thalamic, striatal, amygdala connections, predicted higher stress (ß = -0.46 to -0.20, CI = [-0.72, -0.07], P < 0.03). Lower bilateral robustness (higher fragility) and/or connectivity of these networks predicted higher sadness in December 2020 and May 2021 (ß = -0.514 to -0.19, CI = [-0.81, -0.05], P < 0.04). These findings suggest that the organization of brain circuits may have played a critical role in adolescent stress and mental/emotional health during the pandemic.

Community detection in the human connectome: Method types, differences and their impact on inference.

Community structure is a fundamental topological characteristic of optimally organized brain networks. Currently, there is no clear standard or systematic approach for selecting the most appropriate community detection method. Furthermore, the impact of method choice on the accuracy and robustness of estimated communities (and network modularity), as well as method-dependent relationships between network communities and cognitive and other individual measures, are not well understood. This study analyzed large datasets of real brain networks (estimated from resting-state fMRI from n $$ n $$ = 5251 pre/early adolescents in the adolescent brain cognitive development [ABCD] study), and n $$ n $$ = 5338 synthetic networks with heterogeneous, data-inspired topologies, with the goal to investigate and compare three classes of community detection methods: (i) modularity maximization-based (Newman and Louvain), (ii) probabilistic (Bayesian inference within the framework of stochastic block modeling (SBM)), and (iii) geometric (based on graph Ricci flow). Extensive comparisons between methods and their individual accuracy (relative to the ground truth in synthetic networks), and reliability (when applied to multiple fMRI runs from the same brains) suggest that the underlying brain network topology plays a critical role in the accuracy, reliability and agreement of community detection methods. Consistent method (dis)similarities, and their correlations with topological properties, were estimated across fMRI runs. Based on synthetic graphs, most methods performed similarly and had comparable high accuracy only in some topological regimes, specifically those corresponding to developed connectomes with at least quasi-optimal community organization. In contrast, in densely and/or weakly connected networks with difficult to detect communities, the methods yielded highly dissimilar results, with Bayesian inference within SBM having significantly higher accuracy compared to all others. Associations between method-specific modularity and demographic, anthropometric, physiological and cognitive parameters showed mostly method invariance but some method dependence as well. Although method sensitivity to different levels of community structure may in part explain method-dependent associations between modularity estimates and parameters of interest, method dependence also highlights potential issues of reliability and reproducibility. These findings suggest that a probabilistic approach, such as Bayesian inference in the framework of SBM, may provide consistently reliable estimates of community structure across network topologies. In addition, to maximize robustness of biological inferences, identified network communities and their cognitive, behavioral and other correlates should be confirmed with multiple reliable detection methods.

Psychological Distress and Suicidality Among Transgender Young Adults in the United States.

PURPOSE: Transgender young adults (TYA) are burdened by adverse mental health outcomes. Guided by intersectionality and minority stress frameworks, we compared prevalence of psychological distress and suicidality among TYA of different social identities to inform future interventions. METHODS: In this secondary data analysis of 12,738 TYA, ages 18-25 years, from the 2015 United States Transgender Survey, we developed multivariable regression models examining associations between social identities and psychological distress and suicidality, adjusting for relevant covariates. Self-reported identities were used as proxies for minority stress resulting from structural oppressions related to gender binarism, transmisogyny, heterosexism, and racism. RESULTS: Overall, 53% met criteria for serious psychological distress, and 66% reported suicidal ideation. Statistically higher odds of serious psychological distress and suicidal ideation and plan were found for TYA assigned male compared to assigned female at birth (adjusted odds ratios [aORs] = 1.14-1.50). Nonbinary TYA assigned male at birth also had lower odds of all outcomes compared to all other TYA (aORs = 0.6-0.7). Compared to White TYA, Latiné/x TYA were more likely to experience serious psychological distress (aOR = 1.19, 95% confidence interval: 1.02, 1.39) and multiracial TYA were more likely to report suicide plan(s) and attempt(s) (aORs = 1.25-1.30). Finally, compared to heterosexual TYA, bisexual/pansexual TYA were more likely to report suicide plan(s) (aOR = 1.28, 95% confidence intervals: 1.04, 1.52), and all sexual minority TYA were more likely to report serious psychological distress and suicidal ideation (aORs = 1.31-2.00). DISCUSSION: Results highlight complex associations between intersectional minority stress and mental health outcomes among TYA. Associations between identities and mental health morbidity highlight an urgent need for targeted mental health interventions.

Contrast-Enhanced Ultrasound of the Chest in Children and Adolescents: A Pilot Study for Assessment of Added Diagnostic Value.

OBJECTIVES: To determine the added diagnostic value of contrast-enhanced ultrasound (CEUS) in pediatric chest abnormalities by comparing interpretation of CEUS studies and confidence level to conventional US studies. METHODS: CEUS studies in patients with a variety of clinically suspected chest abnormalities performed between 2016 and 2020 were reviewed and compared to same-day conventional US studies. Examinations were independently interpreted by 4 radiologists blinded to clinical and other imaging data. Rater confidence was classified as low, moderate, or high. Diagnostic accuracy was determined by comparing image interpretation to patient outcome as the ground truth. Interobserver agreement was also assessed. RESULTS: Sixteen patients (10 male) with 18 CEUS studies were included. Median rater agreement with ground truth was significantly higher for CEUS (100%) than conventional US (50%; P = .004). Median rater confidence was high (3.0) for CEUS, and low-moderate (1.5) for conventional US (P < .001). CEUS sensitivity (54.6-81.8%) and specificity (63.4-100.0%) were greater than conventional US (45.5-72.7% and 12.5-63.5%, respectively). CEUS false positives (0-4) and false negatives (2-5) were fewer than conventional US (4-7 and 3-6, respectively). Except for one rater pair where agreement was substantial (κ = .78, P < .01), inter-rater agreement for CEUS for all other rater pairs was nonsignificant (κ = .25-0.51, P ≥ .07). Agreement for conventional US was moderate and statistically significant for 3 rater pairs (κ = .55-0.78) and nonsignificant for the remaining 3 rater pairs (P ≥ .06). CONCLUSIONS: CEUS adds diagnostic value to the assessment of a variety of chest abnormalities. The data support further evaluation of the role of CEUS as a non-invasive, problem-solving technique in children.

Modulatory effects of fMRI acquisition time of day, week and year on adolescent functional connectomes across spatial scales: Implications for inference.

Metabolic, hormonal, autonomic and physiological rhythms may have a significant impact on cerebral hemodynamics and intrinsic brain synchronization measured with fMRI (the resting-state connectome). The impact of their characteristic time scales (hourly, circadian, seasonal), and consequently scan timing effects, on brain topology in inherently heterogeneous developing connectomes remains elusive. In a cohort of 4102 early adolescents with resting-state fMRI (median age = 120.0 months; 53.1 % females) from the Adolescent Brain Cognitive Development Study, this study investigated associations between scan time-of-day, time-of-week (school day vs weekend) and time-of-year (school year vs summer vacation) and topological properties of resting-state connectomes at multiple spatial scales. On average, participants were scanned around 2 pm, primarily during school days (60.9 %), and during the school year (74.6 %). Scan time-of-day was negatively correlated with multiple whole-brain, network-specific and regional topological properties (with the exception of a positive correlation with modularity), primarily of visual, dorsal attention, salience, frontoparietal control networks, and the basal ganglia. Being scanned during the weekend (vs a school day) was correlated with topological differences in the hippocampus and temporoparietal networks. Being scanned during the summer vacation (vs the school year) was consistently positively associated with multiple topological properties of bilateral visual, and to a lesser extent somatomotor, dorsal attention and temporoparietal networks. Time parameter interactions suggested that being scanned during the weekend and summer vacation enhanced the positive effects of being scanned in the morning. Time-of-day effects were overall small but spatially extensive, and time-of-week and time-of-year effects varied from small to large (Cohen's f ≤ 0.1, Cohen's d<0.82, p < 0.05). Together, these parameters were also positively correlated with temporal fMRI signal variability but only in the left hemisphere. Finally, confounding effects of scan time parameters on relationships between connectome properties and cognitive task performance were assessed using the ABCD neurocognitive battery. Although most relationships were unaffected by scan time parameters, their combined inclusion eliminated associations between properties of visual and somatomotor networks and performance in the Matrix Reasoning and Pattern Comparison Processing Speed tasks. Thus, scan time of day, week and year may impact measurements of adolescent brain's functional circuits, and should be accounted for in studies on their associations with cognitive performance, in order to reduce the probability of incorrect inference.

Effects of multidomain environmental and mental health factors on the development of empathetic behaviors and emotions in adolescence.

Empathy is at the core of our social world, yet multidomain factors that affect its development in socially sensitive periods, such as adolescence, are incompletely understood. To address this gap, this study investigated associations between social, environmental and mental health factors, and their temporal changes, on adolescent empathetic behaviors/emotions and, for comparison, callous unemotional (CU) traits and behaviors, in the early longitudinal Adolescent Brain Cognitive Development sample (baseline: n = 11062; 2-year follow-up: n = 9832, median age = 119 and 144 months, respectively). Caregiver affection towards the youth, liking school, having a close friend, and importance of religious beliefs/spirituality in the youth's life were consistently positively correlated with empathetic behaviors/emotions across assessments (p<0.001, Cohen's f = ~0.10). Positive family dynamics and cohesion, living in a neighborhood that shared the family's values, but also parent history of substance use and (aggregated) internalizing problems were additionally positively associated with one or more empathetic behaviors at follow-up (p<0.001, f = ~0.10). In contrast, externalizing problems, anxiety, depression, fear of social situations, and being withdrawn were negatively associated with empathetic behaviors and positively associated with CU traits and behaviors (p<0.001, f = ~0.1-0.44). The latter were also correlated with being cyberbullied and/or discriminated against, anhedonia, and impulsivity, and their interactions with externalizing and internalizing issues. Significant positive temporal correlations of behaviors at the two assessments indicated positive (early) developmental empathetic behavior trajectories, and negative CU traits' trajectories. Negative changes in mental health adversely moderated positive trajectories and facilitated negative ones. These findings highlight that adolescent empathetic behaviors/emotions are positively related to multidomain protective social environmental factors, but simultaneously adversely associated with risk factors in the same domains, as well as bully victimization, discrimination, and mental health problems. Risk factors instead facilitate the development of CU traits and behaviors.

Pelvis radiographs in children with cerebral palsy: effects of patient positioning on calculating migration percentages.

BACKGROUND: Hip displacement in children with cerebral palsy (CP) is monitored by measuring migration percentage on anteroposterior pelvis radiographs. However, proper positioning for radiography in children with spasticity is difficult. The reliability and accuracy of migration percentage as a function of patient positioning is unknown. OBJECTIVE: To determine the effects of patient positioning on migration percentage measurements in children with CP. MATERIALS AND METHODS: We identified children with CP (≤18-year-old) with pelvis CT and anteroposterior pelvis radiograph obtained <6 months apart (10/2018-11/2021). Digitally reconstructed radiographs were generated from each pelvis CT, to simulate nine different patient positions: neutral; 10° and 20° lordosis and kyphosis; and 10° and 20° right rotation and left rotation. Two radiologists measured migration percentages from the simulated and real pelvis radiographs. We used Spearman's rho to assess inter-rater reliability, and Wilcoxon signed rank test to determine statistical significance. RESULTS: We studied sixty-three children (male=41; median age=8 years; range=4-18 years). The two radiologists' migration percentage measurements were highly correlated with each other across all simulated and real radiographs (Spearman's rho=0.86-0.99, P<0.01). For both readers and hips, migration percentages measured from real radiographs were significantly different from those measured from neutral simulated radiographs (P<0.01), with median absolute difference=5-6 percentage points (PP) and interquartile range (IQR)=9-12 PP. When comparing migration percentage measurements from neutral simulated radiographs to those in kyphosis/lordosis and right/left rotations, median absolute differences were 2-4 PP (IQR=3-8 PP) and 4-15 PP (IQR=6-17 PP), respectively. CONCLUSION: Inter-rater reliability of measured migration percentages is high, but accuracy decreases with patient positional changes.

Excess BMI in early adolescence adversely impacts maturating functional circuits supporting high-level cognition and their structural correlates.

BACKGROUND/OBJECTIVES: Adverse effects of excess BMI (affecting 1 in 5 children in the US) on brain circuits during neurodevelopmentally vulnerable periods are incompletely understood. This study investigated BMI-related alterations in maturating functional networks and their underlying brain structures, and high-level cognition in early adolescence. SUBJECTS/METHODS: Cross-sectional resting-state fMRI, structural sMRI, neurocognitive task scores, and BMI from 4922 youth [median (IQR) age = 120.0 (13.0) months, 2572 females (52.25%)] from the Adolescent Brain Cognitive Development (ABCD) cohort were analyzed. Comprehensive topological and morphometric network properties were estimated from fMRI and sMRI, respectively. Cross-validated linear regression models assessed correlations with BMI. Results were reproduced across multiple fMRI datasets. RESULTS: Almost 30% of youth had excess BMI, including 736 (15.0%) with overweight and 672 (13.7%) with obesity, and statistically more Black and Hispanic compared to white, Asian and non-Hispanic youth (p < 0.01). Those with obesity or overweight were less physically active, slept less than recommended, snored more frequently, and spent more time using an electronic device (p < 0.01). They also had lower topological efficiency, resilience, connectivity, connectedness and clustering in Default-Mode, dorsal attention, salience, control, limbic, and reward networks (p ≤ 0.04, Cohen's d: 0.07-0.39). Lower cortico-thalamic efficiency and connectivity were estimated only in youth with obesity (p < 0.01, Cohen's d: 0.09-0.19). Both groups had lower cortical thickness, volume and white matter intensity in these networks' constituent structures, particularly anterior cingulate, entorhinal, prefrontal, and lateral occipital cortices (p < 0.01, Cohen's d: 0.12-0.30), which also mediated inverse relationships between BMI and regional functional topologies. Youth with obesity or overweight had lower scores in a task measuring fluid reasoning - a core aspect of cognitive function, which were partially correlated with topological changes (p ≤ 0.04). CONCLUSIONS: Excess BMI in early adolescence may be associated with profound aberrant topological alterations in maturating functional circuits and underdeveloped brain structures that adversely impact core aspects of cognitive function.

Accuracy of contrast-enhanced voiding urosonography using Optison™ for diagnosis of vesicoureteral reflux in children.

BACKGROUND: There is limited quality of evidence regarding the accuracy of contrast-enhanced voiding urosonography (ceVUS) for diagnosis of vesicoureteral reflux (VUR) compared to fluoroscopic voiding cystourethrography (VCUG), and minimal data on the use of the ultrasound contrast agent Optison™ for this purpose. OBJECTIVE: To compare the accuracy of ceVUS using Optison™ to VCUG, and to assess inter-rater agreement regarding presence and grading of VUR. STUDY DESIGN: In this retrospective investigation, all sequential ceVUS with Optison™ and VCUG studies performed in children between 2014 and 2017 were reviewed. Two raters independently graded all ceVUS studies using a 5-point scale. CeVUS sensitivity and specificity were estimated separately for each rater using the VCUG report as the ground truth for presence and degree of VUR. Logistic and ordinary linear regression models assessed rater-report agreement and inter-rater agreement for each kidney, Optison™ dose, and referral diagnosis. RESULTS: 97 children (51 females) with 101 paired studies were included. Sensitivity and specificity of ceVUS for VUR detection were identical for both raters: right kidney 75%/90.9%; left kidney 85.7%/78.9% (Figure). There was no statistically significant difference in disagreement between raters and the VCUG report for the right or left kidney. Inter-rater agreement on ceVUS grading was 90% and 88% for right and left kidneys, respectively. There was a significant negative association between fetal hydronephrosis vs urinary tract infection and disagreement between Rater 2 and the VCUG report for the left kidney. There were no other significant associations with respect to either kidney, Optison™ dose, or referral diagnosis. DISCUSSION: Our study showed that detection of VUR with ceVUS and Optison™ is comparable to fluoroscopic VCUG. Based on the VCUG reports, the incidence of VUR in our patient population was substantially lower than in the meta-analysis of Chua et al. and in the study of Kim et al. The explanation for the large discrepancy in VUR incidence may reflect differences in the patient populations, and in our reporting of VUR with respect to kidney number rather than to pelviureteral units. Study limitations include its retrospective nature and potential bias in terms of patient selection. Since VUR is an intermittent phenomenon, sequential rather than simultaneous performance of the ceVUS and fluoroscopic studies might have influenced VUR detection. CONCLUSION: A blinded comparison of ceVUS performed with Optison™ to fluoroscopic VCUG showed moderate-good sensitivity and specificity for diagnosis of VUR.

GENERATIVE MODELS FOR LARGE-SCALE SIMULATIONS OF CONNECTOME DEVELOPMENT.

Functional interactions and anatomic connections between brain regions form the connectome. Its mathematical representation in terms of a graph reflects the inherent neuroanatomical organization into structures and regions (nodes) that are interconnected through neural fiber tracts and/or interact functionally (edges). Without knowledge of the ground truth topology of the connectome, functional (directional or nondirectional) graphs represent estimates of signal correlations, from which underlying mechanisms and processes, such as development and aging, or neuropathologies, are difficult to unravel. Biologically meaningful simulations using synthetic graphs with controllable parameters can complement real data analyses and provide critical insights into mechanisms underlying the organization of the connectome. Generative models can be highly valuable tools for creating large datasets of synthetic graphs with known topological characteristics. However, for these graphs to be meaningful, the variation of model parameters needs to be driven by real data. This paper presents a novel, data-driven approach for tuning the parameters of the generative Lancichinetti-Fortunato-Radicchi (LFR) model, using a large dataset of connectomes (n = 5566) estimated from resting-state fMRI from early adolescents in the historically large Adolescent Brain Cognitive Development Study (ABCD). It also presents an application, i.e., simulations using the LFR, to generate large datasets of synthetic graphs representing brains at different stages of neural maturation, and gain insights into developmental changes in their topological organization.

Associations between nutritional intake, stress and hunger biomarkers, and anxiety and depression during the treatment of anorexia nervosa in adolescents and young adults.

Adolescents and young adults (AYA) with anorexia nervosa (AN) frequently have co-occurring anxiety and depression, which can negatively impact prognosis. To inform treatment of co-occurring anxiety and depression, we assessed the association of nutritional intake and hunger/stress hormones on anxiety and depression using a six-month longitudinal study of 50 AYA females receiving care for AN. At baseline and six months, we measured anxiety (Spielberger State/Trait Anxiety Inventory [STAI]), depression (Beck Depression Inventory [BDI]), body mass index (BMI), 3-day dietary intake (total calories and proportion of fat, carbohydrate, protein), and serum cortisol, leptin, and adiponectin. We performed mixed effects linear regression analyses, adjusting for age, duration of AN, and percentage of median BMI (%mBMI). At baseline, median age was 16.3 (interquartile range [IQR]=2.5) years, duration of AN was 6 (IQR=8.8) months and %mBMI was 87.2 (IQR=10.5)%. Fifty-six percent had clinically significant anxiety; 30% had depression. Over 6 months, participants had significant improvements in %mBMI (+2.2[IQR=9.2]%, p<.01), STAI (-9.0[IQR=25.0], p<.01), and BDI (-5.0[IQR=13.8], p<.01) scores. Participants with larger improvements in caloric intake had greater improvements in STAI (p=.03) and BDI scores (p=.04). Larger improvement in BDI was significantly associated with increased fat intake (p<.01), but not carbohydrate or protein intake. Change in STAI was not associated with changes in fat, carbohydrate, or protein intake. Changes in STAI or BDI scores were not associated with changes in cortisol, leptin, or adiponectin. Increased caloric intake may augment treatment of co-occurring anxiety and depression, and increased fat intake may improve depression for AYA with AN.

Parental religiosity is associated with changes in youth functional network organization and cognitive performance in early adolescence.

Parental religious beliefs and practices (religiosity) may have profound effects on youth, especially in neurodevelopmentally complex periods such as adolescence. In n = 5566 children (median age = 120.0 months; 52.1% females; 71.2% with religious affiliation) from the Adolescent Brain Cognitive Development study, relationships between parental religiosity and non-religious beliefs on family values (data on youth beliefs were not available), topological properties of youth resting-state brain networks, and executive function, inhibitory control, and cognitive flexibility were investigated. Lower caregiver education and family income were associated with stronger parental beliefs (p < 0.01). Strength of both belief types was correlated with lower efficiency, community structure, and robustness of frontoparietal control, temporoparietal, and dorsal attention networks (p < 0.05), and lower Matrix Reasoning scores. Stronger religious beliefs were negatively associated (directly and indirectly) with multiscale properties of salience and default-mode networks, and lower Flanker and Dimensional Card Sort scores, but positively associated with properties of the precuneus. Overall, these effects were small (Cohen's d ~ 0.2 to ~ 0.4). Overlapping neuromodulatory and cognitive effects of parental beliefs suggest that early adolescents may perceive religious beliefs partly as context-independent rules on expected behavior. However, religious beliefs may also differentially affect cognitive flexibility, attention, and inhibitory control and their neural substrates.

Shorter Duration and Lower Quality Sleep Have Widespread Detrimental Effects on Developing Functional Brain Networks in Early Adolescence.

Sleep is critical for cognitive health, especially during complex developmental periods such as adolescence. However, its effects on maturating brain networks that support cognitive function are only partially understood. We investigated the impact of shorter duration and reduced quality sleep, common stressors during development, on functional network properties in early adolescence-a period of significant neural maturation, using resting-state functional magnetic resonance imaging from 5566 children (median age = 120.0 months; 52.1% females) in the Adolescent Brain Cognitive Development cohort. Decreased sleep duration, increased sleep latency, frequent waking up at night, and sleep-disordered breathing symptoms were associated with lower topological efficiency, flexibility, and robustness of visual, sensorimotor, attention, fronto-parietal control, default-mode and/or limbic networks, and with aberrant changes in the thalamus, basal ganglia, hippocampus, and cerebellum (P < 0.05). These widespread effects, many of which were body mass index-independent, suggest that unhealthy sleep in early adolescence may impair neural information processing and integration across incompletely developed networks, potentially leading to deficits in their cognitive correlates, including attention, reward, emotion processing and regulation, memory, and executive control. Shorter sleep duration, frequent snoring, difficulty waking up, and daytime sleepiness had additional detrimental network effects in nonwhite participants, indicating racial disparities in the influence of sleep metrics.

A Novel Mobile Phone App for Optimizing Dynamic Discrete Data Collection in Pediatric Epilepsy Studies.

Mobile technologies, including applications (apps) and wearable devices, are playing an increasingly important role in health monitoring. In particular, apps are becoming a critical component of m-health, which promises to transform personalized care management, optimize clinical outcomes, and improve patient-provider communication. They may also play a central role in research, to facilitate rapid and inexpensive collection of repeated data, such as momentary clinical, physiological, and/or behavioral assessments and optimize their sampling. This is particularly important for measuring systems/processes with characteristic temporal patterns, e.g., circadian rhythms, which need to be adequately sampled in order to be accurately estimated from discrete measurements. Temporal sampling of these patterns may also be critical for elucidating their modulation by pathological events. This paper presents a novel app, developed with the overarching goal to optimize repeated salivary hormone collection in pediatric patients with epilepsy through improved patient-investigator communication and enhanced alerts. The ultimate goal of the app is to maximize regularity of the data collection (up to 8 samples/day for ~4-5 days of hospitalization) while minimizing intrusion on patients during clinical monitoring. In addition, the app facilitates flexible collection of data on stress and seizure symptoms at the time of saliva sampling, which can then be correlated with hormone levels and physiological changes indicating impending seizures.

Big Data-Driven Brain Parcellation from fMRI: Impact of Cohort Heterogeneity on Functional Connectivity Maps.

Ongoing large-scale human brain studies are generating complex neuroimaging data from thousands of individuals that can be leveraged to derive data-driven, anatomically accurate brain parcellations. However, despite their promise and many strengths, these data are highly heterogeneous, a characteristic that may affect the anatomical accuracy and generalization of the template but has received relatively little attention. Using multiple similarity measures and thresholding approaches, this study investigated the topological intra- and inter-individual variability of restingstate (rs) functional edge maps (often used for brain parcellation), estimated from rs-fMRI connectivity in n = 5878 children from the Adolescent Brain Cognitive Development (ABCD) study. Findings from this initial investigation indicate that choosing a subject- vs cohort-based threshold for estimating edge maps from connectivity matrices does not significantly impact the map topology. In contrast, the choice of similarity measure and non-linear relationship between similarity and edge map sparsity may have a significant impact on map classification and the generation of parcellation atlases. Multi-level classification revealed multiple clusters with a potentially complex mapping onto biological variables beyond simple demographics.Clinical Relevance- Case-control neuroimaging studies should use domain-specific (e.g., demographics-specific) atlases for parcellating the brain, to improve accuracy and rigor of cohort comparisons. To be generalizable, such atlases need to be derived from large datasets, which are inherently heterogeneous. In a cohort of 5878 children (age ~9-10 years), this study systematically assessed the impact of heterogeneity and similarity of edge maps, which are derived from rs-fMRI connectivity and typically used to generate parcellation atlases.

Novel Seizure Biomarkers in Continuous Electrocardiograms from Pediatric Epilepsy Patients.

There is growing evidence that seizures are accompanied by multi-system changes, not only in the brain but also in organs and systems under its control. Non-EEG measurements from these systems could be leveraged to improve seizure prediction, which is difficult but critical to the success of next-generation epilepsy therapies. Clinical electrophysiology studies during presurgical patient evaluations routinely collect continuous EEG but also ECG data that span multiple days. Prior work has reported electrocardiographic changes but has primarily focused on ventricular activity and brief peri-ictal intervals. Using novel data-driven classification and separation of the ECG high-dimensional signal space, this study investigated seizure-related changes in both ventricular and atrial activity. Measures of complexity as well as heart rate and R-R interval length were analyzed over time in continuous ECGs from 22 pediatric patients with pharmacoresistant seizures and no diagnosed cardiovascular anomalies. Fifteen patients (>68%) had significant changes in atrial or ventricular activity (or both) in intervals containing seizures. Thus, for a substantial number of patients, cardiac markers may be specifically modulated by seizures and could be leveraged to improve and personalize seizure prediction.

Nonhormonal therapy for endometriosis: a randomized, placebo-controlled, pilot study of cabergoline versus norethindrone acetate.

OBJECTIVE: To estimate the efficacy and safety of a novel nonhormonal therapeutic agent, cabergoline, compared with that of the standard clinical therapy, norethindrone acetate (NETA), for the treatment of endometriosis-associated pain in young women with endometriosis. DESIGN: Randomized, double-blind, placebo-controlled pilot study. SETTING: Tertiary care center. PATIENTS: Women (n = 9) with surgically confirmed endometriosis. INTERVENTIONS: A random, double-blind assignment to either NETA (5 mg/day) + placebo twice weekly or cabergoline (0.5 mg) twice weekly + placebo daily for 6 months. MAIN OUTCOME MEASURES: We collected the measures of pelvic pain and laboratory parameters every 3 months. RESULTS: We observed a decrease in pain scores and increase in pain relief in women randomized to receive cabergoline, who appeared to show similar or more improvements than women treated with NETA. The serum measures of vascular endothelial growth factor receptor 1 declined over 6 months in those who received cabergoline. Cabergoline was well tolerated, and no serious adverse events occurred. CONCLUSIONS: Safe, effective adjunct treatments are lacking for patients with endometriosis who do not respond to standard care. Because the growth of endometriosis requires angiogenesis, blood vessel growth is an attractive therapeutic target. This pilot study suggests that cabergoline, a vascular endothelial growth factor pathway inhibitor, is an effective therapeutic option for women with chronic pain due to endometriosis. Building upon this investigation, we will conduct larger, randomized trials of cabergoline, advancing research on the best treatments for endometriosis-particularly disease resistant to hormonal therapies. CLINICAL TRIAL REGISTRATION NUMBER: clinicaltrials.gov; registration number NCT02542410.

Widespread Positive Direct and Indirect Effects of Regular Physical Activity on the Developing Functional Connectome in Early Adolescence.

Adolescence is a period of profound but incompletely understood changes in the brain's neural circuitry (the connectome), which is vulnerable to risk factors such as unhealthy weight, but may be protected by positive factors such as regular physical activity. In 5955 children (median age = 120 months; 50.86% females) from the Adolescent Brain Cognitive Development (ABCD) cohort, we investigated direct and indirect (through impact on body mass index [BMI]) effects of physical activity on resting-state networks, the backbone of the functional connectome that ubiquitously affects cognitive function. We estimated significant positive effects of regular physical activity on network connectivity, efficiency, robustness and stability (P ≤ 0.01), and on local topologies of attention, somatomotor, frontoparietal, limbic, and default-mode networks (P < 0.05), which support extensive processes, from memory and executive control to emotional processing. In contrast, we estimated widespread negative BMI effects in the same network properties and brain regions (P < 0.05). Additional mediation analyses suggested that physical activity could also modulate network topologies leading to better control of food intake, appetite and satiety, and ultimately lower BMI. Thus, regular physical activity may have extensive positive effects on the development of the functional connectome, and may be critical for improving the detrimental effects of unhealthy weight on cognitive health.

Developing a Database of Structural Racism-Related State Laws for Health Equity Research and Practice in the United States.

OBJECTIVES: Although US state laws shape population health and health equity, few studies have examined how state laws affect the health of marginalized racial/ethnic groups (eg, Black, Indigenous, and Latinx populations) and racial/ethnic health inequities. A team of public health researchers and legal scholars with expertise in racial equity used systematic policy surveillance methods to develop a comprehensive database of state laws that are explicitly or implicitly related to structural racism, with the goal of evaluating their effect on health outcomes among marginalized racial/ethnic groups. METHODS: Legal scholars used primary and secondary sources to identify state laws related to structural racism pertaining to 10 legal domains and developed a coding scheme that assigned a numeric code representing a mutually exclusive category for each salient feature of each law using a subset of randomly selected states. Legal scholars systematically applied this coding scheme to laws in all 50 US states and the District of Columbia from 2010 through 2013. RESULTS: We identified 843 state laws linked to structural racism. Most states had in place laws that disproportionately discriminate against marginalized racial/ethnic groups and had not enacted laws that prevent the unjust treatment of individuals from marginalized racial/ethnic populations from 2010 to 2013. CONCLUSIONS: By providing comprehensive, detailed data on structural racism-related state laws in all 50 states and the District of Columbia over time, our database will provide public health researchers, social scientists, policy makers, and advocates with rigorous evidence to assess states' racial equity climates and evaluate and address their effect on racial/ethnic health inequities in the United States.