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We present the results of a recent reverberation mapping campaign for UGC 06728, a nearby low-luminosity Seyfert 1 in a late-type galaxy. Nightly monitoring in the spring of 2015 allowed us to determine an Hβ time delay of τ = 1.4 ± 0.8 days. Combined with the width of the variable Hβ line profile, we determine a black hole mass of M BH = (7.1 ± 4.0) × 10 5 M ⊙ . We also constrain the bulge stellar velocity dispersion from higher-resolution long slit spectroscopy along the galaxy minor axis and find σ ⋆ = 51.6 ± 4.9 km s −1 . The measurements presented here are in good agreement with both the R BLR − L relationship and the M BH − σ ⋆ relationship for AGNs. Combined with a previously published spin measurement, our mass determination for UGC 06728 makes it the lowest-mass black hole that has been fully characterized, and thus an important object to help anchor the low-mass end of black hole evolutionary models.

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Introduction:The lack of racial/ethnic diversity in research potentially limits the generalizability of findings to a broader population, highlighting the need for greater diversity and inclusion in clinical research. Qualitative research (i.e., focus groups) was conducted to identify (i) the potential motivators and barriers to study participation across different races and ethnicities; (ii) preferred delivery of education and information to support healthcare decision-making and the role of the community.Methods: Patient focus groups were conducted with 26 participants from the sponsor's Patient Engagement Research Councils selected through subjective sampling.Recruitment prioritized adequate representation across different race/ethnic groups.Participation was voluntary and participants underwent a confidential interview process before selection. Narrative analysis was used to identify themes and draw insights from interactions. Experienced research specialists identified emerging concepts, and these were tested against new observations. The frequency of each concept was examined to understand its importance.Results: Based on self-selected race/ethnicity, participants were divided into five focus groups (Groups: African American/Black: 2; Hispanic/Latino, Asian American, and white: 1 each) and were asked to share their experiences/opinions regarding the stated objectives. Barriers to study participation included: limited awareness of opportunities to participate in research, fears about changes in standard therapy, breaking cultural norms/stigma, religion-related concerns and mistrust of clinical research. Participants identified the importance of transparency by pharmaceutical companies and other entities to build trust and partnership and cited key roles that

We present optical BVRI photometry, Hα IFU velocity fields, and Hα long-slit rotation curves for a sample of four nearby spiral galaxies having a range of morphologies and inclinations. We show that the DiskFit code can be used to model the photometric and kinematic data of these four galaxies and explore how well the photometric data can be decomposed into structures like bars and bulges and to look for non-circular motions in the kinematic data. In general, we find good agreement between our photometric and kinematic models for most parameters. We find the best consistency between our photometric and kinematic models for NGC 6674, a relatively face-on spiral with clear and distinct bulge and bar components. We also find excellent consistency for NGC 2841, and find a bar ∼10 • south of the disc major axis in the inner 20 . Due to geometric effects caused by its high inclination, we find the kinematic model for NGC 2654 to be less accurate than its photometry. We find the bar in NGC 2654 to be roughly parallel to the major axis of the galaxy. We are unable to photometrically model our most highly inclined galaxy, NGC 5746, with DiskFit and instead use the galaxy isophotes to determine that the system contains a bar ∼5 • to ∼10 • east of the disc major axis. The high inclination and extinction in this galaxy also prevent our kinematic model from accurately determining parameters about the bar, though the data are better modeled when a bar is included.