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This study examines the effects of puberty and sex on the intrinsic functional connectivity (iFC) of brain networks, with a focus on the default-mode network (DMN). Consistently implicated in depressive disorders, the DMN’s function may interact with puberty and sex in the development of these disorders, whose onsets peak in adolescence, and which show strong sex disproportionality (females > males). The main question concerns how the DMN evolves with puberty as a function of sex. These effects are expected to involve within- and between-network iFC, particularly, the salience and the central-executive networks, consistent with the Triple-Network Model. Resting-state scans of an adolescent community sample ( n = 304, male/female: 157/147; mean/std age: 14.6/0.41 years), from the IMAGEN database, were analyzed using the AFNI software suite and a data reduction strategy for the effects of puberty and sex. Three midline regions (medial prefrontal, pregenual anterior cingulate, and posterior cingulate), within the DMN and consistently implicated in mood disorders, were selected as seeds. Within- and between-network clusters of the DMN iFC changed with pubertal maturation differently in boys and girls (puberty-X-sex). Specifically, pubertal maturation predicted weaker iFC in girls and stronger iFC in boys. Finally, iFC was stronger in boys than girls independently of puberty. Brain–behavior associations indicated that lower connectivity of the anterior cingulate seed predicted higher internalizing symptoms at 2-year follow-up. In conclusion, weaker iFC of the anterior DMN may signal disconnections among circuits supporting mood regulation, conferring risk for internalizing disorders.

Objective Medication nonadherence is more common in African Americans compared with Caucasians. We examined the racial adherence gaps among patients with systemic lupus erythematosus (SLE) and explored factors associated with nonadherence. Methods Cross‐sectional data were obtained from consecutive patients prescribed SLE medications seen at an academic lupus clinic between August 2018 and February 2019. Adherence was measured using both self‐report and pharmacy refill data. High composite adherence was defined as having both high self‐reported adherence and high refill rates. Covariates were patient‐provider interaction, patient‐reported health status, and clinical factors. We compared adherence rates by race and used race‐stratified analyses to identify factors associated with low composite adherence. Results Among 121 patients (37% Caucasian, 63% African American), the median age was 44 years (range 22‐72), 95% were female, 51% had a college education or more, 46% had private insurance, and 38% had high composite adherence. Those with low composite adherence had higher damage scores, patient‐reported disease activity scores, and more acute care visits. High composite adherence rate was lower among African Americans compared with Caucasians (30% vs 51%, P = 0.02), and the gap was largest for those taking mycophenolate (26% vs 75%, P = 0.01). Among African Americans, low composite adherence was associated with perceiving fewer “Compassionate respectful” interactions with providers and worse anxiety and negative affect. In contrast, among Caucasians, low composite adherence was only associated with higher SLE medication regimen burden and fibromyalgia pain score. Conclusion Significant racial disparities exist in SLE medication adherence, which likely contributes to racial disparities in SLE outcomes. Interventions may be more effective if tailored by race, such as improving patient‐provider interaction and mental health among African Americans.

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Endothelial production of nitric oxide (NO) and prostaglandins (PG) may be greater in females than in males, increasing vasodilatory responses in females. Does sex influence the cardiovascular responses to dynamic exercise through estrogen-dependent modulation of NO and PG vasodilatory pathways? After the administration of hexamethonium, we assessed terminal aortic blood flow (TAQ), mean arterial pressure (MAP), and hindlimb vascular conductance (VC) in four groups of rats (6 males, 5 females, 5 ovariectomized females, and 6 ovariectomized females with chronic estrogen supplementation) during graded mild-intensity treadmill locomotion (5-15 m/min, 0 degrees grade, 2 min). All rats repeated exercise after cyclooxygenase inhibition (indomethacin) and then again after NO synthase inhibition (nitro-l-arginine methyl ester) to examine the roles of NO and PG. Regression analysis was used to determine the influence of sex and plasma 17beta-estradiol on TAQ, MAP, and VC. The analysis revealed that female sex did not influence TAQ but reduced MAP and increased VC at rest and during exercise conditions. Plasma 17beta-estradiol (measured by immunoassay) significantly decreased MAP and increased TAQ and VC, irrespective of sex. Cyclooxygenase inhibition eliminated the significant association between MAP and estrogen, suggesting that estrogenic modulation occurred through PG-dependent processes. In contrast, the significant influence of estrogen on TAQ and VC was eliminated after NO synthase inhibition. On the basis of the overall findings of this study, estrogen influenced the vascular responses to dynamic exercise through PG- and NO-dependent pathways, but this occurred independent of sex.

Objective. Visual cohort analysis utilizing electronic health record (EHR) data has become an important tool in clinical assessment of patient outcomes. In this paper, we introduce Composer, a visual analysis tool for orthopedic surgeons to compare changes in physical functions of a patient cohort following various spinal procedures. The goal of our project is to help researchers analyze outcomes of procedures and facilitate informed decision-making about treatment options between patient and clinician. Methods. In collaboration with Orthopedic surgeons and researchers, we defined domain-specific user requirements to inform the design. We developed the tool in an iterative process with our collaborators to develop and refine functionality. With Composer, analysts can dynamically define a patient cohort using demographic information, clinical parameters, and events in patient medical histories and then analyze patient-reported outcome scores for the cohort over time, as well as compare it to other cohorts. Using Composer's current iteration, we provide a usage scenario for use of the tool in a clinical setting. Conclusion. We have developed a prototype cohort analysis tool to help clinicians assess patient treatment options by analyzing prior cases with similar characteristics. Though Composer was designed using patient data specific to Orthopedic research, we believe the tool is generalizable to other healthcare domains. A long term goal for Composer is to develop the application into a shared decision making tool that allows translation of comparison and analysis from a clinician-facing interface into visual representations to communicate treatment options to patients.