Individual differences in striatum activity to food commercials predict weight gain in adolescents

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109559/1/oby20882.pd

Minimizing Obstetric Hemorrhage

Patients undergoing cesarean deliveries are at risk for hemorrhage. In fact, hemorrhage is the leading cause of preventable maternal mortality and accounts for more than 140,000 deaths each year worldwide (O’Brien & Ulh, 2016). Hemorrhage has been associated with a number of well-established risk factors which could be recognized prior to delivery. Women who do not have these risk factors could still experience postpartum hemorrhage, but using a risk assessment tool has been shown to identify 60-85% of women who will experience hemorrhage (Shields, Goffman, & Caughey, 2017). The postpartum hemorrhage (PPH) risk assessment tool, developed by the Association of Women’s Health, Obstetric and Neonatal Nurses (AWHONN), identifies women with PPH risk factors. The tool allows clinicians to prepare for possible interventions and close monitoring of women at increased risk of bleeding, to ultimately prevent mortality. At a metropolitan hospital PPH risk assessments were not being discussed during standard pre-procedure huddles. This quality improvement project added the PPH risk assessment tool to the pre procedure huddle sheet. This facilitated interdisciplinary team discussion of PPH risk factors for patients undergoing cesarean deliveries. There were a total of 575 mothers in the study with 297 in the pre intervention period and 278 in the post. There was a statistically significant increase in estimated blood loss (EBL) between the pre and post intervention groups. While the study tool did not result in a decrease in EBL, it increased awareness among the interdisciplinary care team by facilitating discussion about PPH

MOMENTUM: Microbial Optimization via Metabolic Network Minimization

We report a high-throughput metabolic engineering platform enabling the rapid optimization of microbial production strains. The platform, which bridges a gap between current in vivo and in vitro bio-production approaches, relies on dynamic minimization of the active metabolic network and is implemented in the context of standardized 2-stage bio-processes. Dynamic metabolic network minimization is accomplished using combinations of CRISPR interference and controlled proteolysis to reduce the activity of multiple enzymes in essential central metabolism. This approach not only results in a design space with greatly reduced complexity, but also in increased metabolic fluxes and production rates as well as in strains which are robust to environmental conditions. Robustness leads to predictable scalability from high-throughput µL-scale screens, to fully instrumented L-scale bioreactors. Predictive high-throughput approaches are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology. We have not only demonstrated proof of principle for this approach in two common industrial microbes: E. coli and S. cerevisiae, but also have validated this approach with the rapid optimization of E. coli strains producing two important industrial chemicals: alanine and mevalonic acid, at commercially meaningful rates, titers (147 g/L and 97 g/L, respectively), and yields.1 References: Ye, Z., Burg, J.M., Poplyk, M.R., Moreb, E.A., Trahan, A.D., Rodrigiuez, D.L., Sheikh, W., Kelly, G.M., Luo, M.L., Beisel C.L., and Lynch, M.D. (2017) MOMENTuM: Microbial Optimization via MEtabolic NeTwork Minimization., Nature Biotechnology in review

Preliminary validation of the Yale Food Addiction Scale.

Introduction: Evidence is growing that an addictive process may play a role in problematic eating behavior. The majority of research on this topic has examined the concept of "food addiction" solely in adult samples. If certain foods have addictive potential, children may be impacted as much as (or more) than adults due to psychological and neurobiological vulnerabilities at younger developmental stages. In the current study, we developed a measure of food addiction in children that reflects the diagnostic indicators of addiction. Materials and methods: The content and reading level of the Yale Food Addiction Scale (YFAS) was altered to be appropriate for children (YFAS-C). The YFAS-C and other eating-related measures were administered to study participants to examine the validity and reliability of the YFAS-C. Participants: 75 children were recruited from the community ranging from lean to obese. Results: The validation of the YFAC-C provides preliminary support for its convergent validity with like constructs and incremental validity in predicting body mass index. Internal consistency was adequate given the small number of items on the scale. Discussion: The YFAS-C appears to be a helpful tool for identifying addictive-like eating in children

Daily Stress Processes as Potential Intervention Targets to Reduce Gender Differences and Improve Mental Health Outcomes in Mid- and Later Life.

The current study examines daily stress processes as risk factors for comprised mental health in midlife and later life, specifically for gender differences in depression risk. Using data from the Midlife in the United States (MIDUS) study and the National Study of Daily Experiences (NSDE), we examine (1) gender differences in depression; (2) the prospective effects of differential exposure and affective responses on 10-year depression status; (3) gender differences in daily stress-depression links. Furthermore, we explore whether the protective factor of help-seeking behavior moderates the effects of daily stress on depression. Participants included 1289 (mage = 55; SD = 12; range = 34-83; 56% female) individuals who completed the second waves of MIDUS and the 8-day NSDE daily diary protocol and participated in the third wave of MIDUS approximately 10 years later. Respondents completed assessments of depression and their seeking assistance from a psychiatrist, mental health professional, counselor, or religious leader. Covariate-adjusted logistic regression analyses revealed increased odds of depression among women compared to men, but no significant gender difference after taking daily stress into account. Higher levels of stressor exposure, negative affect, and affective reactivity were associated with increased odds of depression for both men and women. Compared to those who did not engage in help-seeking behavior, those who did had significantly greater odds of depression, and there were asymmetric patterns of daily stress effects across groups. These findings highlight differential exposure, negative affect, and affective responses to daily stress as potentially accessible intervention targets for reducing stress in daily life and mitigating longer-term depression risk during mid- and later life