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Background:The Glycemia Risk Index (GRI) was developed in adults with diabetes and is a validated metric of quality of glycemia. Little is known about the relationship between GRI and type 1 diabetes (T1D) self-management habits, a validated assessment of youths’ engagement in habits associated with glycemic outcomes. Method:We retrospectively examined the relationship between GRI and T1D self-management habits in youth with T1D who received care from a Midwest pediatric diabetes clinic network. The GRI was calculated using seven days of continuous glucose monitor (CGM) data, and T1D self-management habits were assessed ±seven days from the GRI score. A mixed-effects Poisson regression model was used to evaluate the total number of habits youth engaged in with GRI, glycated hemoglobin A1c (HbA1c), age, race, ethnicity, and insurance type as fixed effects and participant ID as a random effect to account for multiple clinic visits per individual. Results:The cohort included 1182 youth aged 2.5 to 18.0 years (mean = 13.8, SD = 3.5) comprising 50.8% male, 84.6% non-Hispanic White, and 64.8% commercial insurance users across a total of 6029 clinic visits. Glycemia Risk Index scores decreased as total number of habits performed increased, suggesting youth who performed more self-management habits achieved a higher quality of glycemia. Conclusions:In youth using CGMs, GRI may serve as an easily obtainable metric to help identify youth with above target glycemia, and engagement/disengagement in the T1D self-management habits may inform clinicians with suitable interventions for improving glycemic outcomes. 

The American Institute of Biological Sciences (AIBS) is an umbrella organization of biological societies. In 2020, AIBS developed a plan to intentionally assess its current programs, as well as to develop and expand programs and policies to increase diversity, equity, and inclusion (DEI) in the biological sciences. Therefore, AIBS decided, for the next 5 years, to focus its annual meeting of member societies and organizations, the AIBS Council Meeting, on topics related to DEI. In 2021, AIBS was funded by the National Science Foundation and received additional support from the Doris Duke Charitable Foundation for its expanded annual council meeting, Enabling Scientific Societies to Create Inclusive, Diverse, Equitable, and Accepting (IDEA) Environments. The IDEA conference was created to engage like-minded organizations committed to increasing diversity in the biological sciences. The conference consists of two meetings, an initial virtual 2-day meeting followed by a virtual 1.5-day workshop. The initial meeting included 27 scientific societies with representatives from five minority-serving scientific organizations. This meeting of the IDEA conference, held 4–5 November 2021, served as a call to action that would allow participants to come together to learn, plan, and strategize. This report provides details of the discussions around characteristics of IDEA environments, barriers to creating IDEA environments, strategies to overcome these barriers, and opportunities for action. The agenda can be found within the supplemental material. 

A<sc>bstract</sc> A measurement of the angular structure of inclusive jets and those containing a prompt D⁰meson in proton-proton collisions at the LHC at a center-of-mass energy of 5.02 TeV is presented. The data corresponding to an integrated luminosity of 301 pb⁻¹were collected by the CMS experiment in 2017. Two jet grooming algorithms, late-k_Tand soft drop, are used to study the intrajet radiation pattern using iterative Cambridge-Aachen declustering. The splitting-angle distributions of jets with transverse momentum (p_T) of around 100 GeV, obtained with these two algorithms, show that there is a shift of the distribution for jets containing a prompt D⁰meson with respect to inclusive jets. The suppression of emissions at small angles observed in the late-k_Tgrooming approach is consistent with the dead-cone effect, whereas the similar suppression for splittings selected with the soft-drop algorithm appears to be induced by gluon splitting to charm quark-antiquark pairs at large angles. The measured distributions are corrected to the particle level and can be used to constrain model predictions for the substructure of high-p_Tcharm quark jets.