Background and purposeEffective mentorship is critical to the success of early stage investigators, and has been linked to enhanced mentee productivity, self-efficacy, and career satisfaction. The mission of the National Research Mentoring Network (NRMN) is to provide all trainees across the biomedical, behavioral, clinical, and social sciences with evidence-based mentorship and professional development programming that emphasizes the benefits and challenges of diversity, inclusivity, and culture within mentoring relationships, and more broadly the research workforce. The purpose of this paper is to describe the structure and activities of NRMN.Key highlightsNRMN serves as a national training hub for mentors and mentees striving to improve their relationships by better aligning expectations, promoting professional development, maintaining effective communication, addressing equity and inclusion, assessing understanding, fostering independence, and cultivating ethical behavior. Training is offered in-person at institutions, regional training, or national meetings, as well as via synchronous and asynchronous platforms; the growing training demand is being met by a cadre of NRMN Master Facilitators. NRMN offers career stage-focused coaching models for grant writing, and other professional development programs. NRMN partners with diverse stakeholders from the NIH-sponsored Diversity Program Consortium (DPC), as well as organizations outside the DPC to work synergistically towards common diversity goals. NRMN offers a virtual portal to the Network and all NRMN program offerings for mentees and mentors across career development stages. NRMNet provides access to a wide array of mentoring experiences and resources including MyNRMN, Guided Virtual Mentorship Program, news, training calendar, videos, and workshops. National scale and sustainability are being addressed by NRMN “Coaches-in-Training” offerings for more senior researchers to implement coaching models across the nation. “Shark Tanks” provide intensive review and coaching for early career health disparities investigators, focusing on grant writing for graduate students, postdoctoral trainees, and junior faculty.ImplicationsPartners from diverse perspectives are building the national capacity and sparking the institutional changes necessary to truly diversify and transform the biomedical research workforce. NRMN works to leverage resources towards the goals of sustainability, scalability, and expanded reach.

Background Food deserts (FD), neighborhoods defined as low-income areas with low access to healthy food, are a public health concern. We evaluated the impact of living in FD on cardiovascular risk factors and subclinical cardiovascular disease (CVD) with the hypothesis that people living in FD will have an unfavorable CVD risk profile. We further assessed whether the impact of FD on these measures is driven by area income, individual household income or area access to healthy food. Methods and Results We studied 1421 subjects residing in the Atlanta metropolitan area who participated in the META-Health (n = 712) and the Predictive Health (n = 709) studies. Participants’ zip codes were entered into the United States Food Access Research Atlas for FD status. Demographic data, metabolic profiles, high-sensitivity C-reactive protein (hs-CRP) levels, oxidative stress markers (glutathione and cystine) and arterial stiffness were evaluated. Mean age was 49.4 years, 38.5% male and 36.6% Black. Compared to those not living in FD, subjects living in FD (n=187, 13.2%) had a higher prevalence of hypertension and smoking, higher BMI, fasting glucose and 10-year risk for CVD. They also had higher hs-CRP (p=0.014), higher central augmentation index (p=0.015), and lower glutathione level (p=0.003), indicative of increased oxidative stress. Area income and individual income, rather than food access, were associated with CVD risk measures. In a multivariate analysis that included food access, area income and individual income, both low-income area and low individual household income were independent predictors of a higher 10-year risk for CVD. Only low individual income was an independent predictor of higher hs-CRP and augmentation index. Conclusions Although living in FD is associated with a higher burden of cardiovascular risk factors and preclinical indices of CVD, these associations are mainly driven by area income and individual income rather than access to healthy food.

Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of ''Big Data'' that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of