Nanomedicines: From Bench to Bedside and Beyond

Advancing nanomedicines from concept to clinic requires integration of new science with traditional pharmaceutical development. The medical and commercial success of nanomedicines is greatly facilitated when those charged with developing nanomedicines are cognizant of the unique opportunities and technical challenges that these products present. These individuals must also be knowledgeable about the processes of clinical and product development, including regulatory considerations, to maximize the odds for successful product registration. This article outlines these topics with a goal to accelerate the combination of academic innovation with collaborative industrial scientists who understand pharmaceutical development and regulatory approval requirements—only together can they realize the full potential of nanomedicines for patients.     

Reciprocal Peer Support for Post-partum Patients with Diabetes: A Needs Assessment for the Diabetes Buddy Program

While peer support has been investigated in multiple clinical contexts, its application to the postpartum setting is unknown. The aim was to assess acceptability of a postpartum peer support program for women with diabetes. Observational survey-based needs assessment of forty low-income women with diabetes, receiving care at a major medical institution. Mean age and gravidity were 30.7 years and 3.15 ± 1.67 respectively. 45 % expressed interest in a “buddy.” There was no significant difference between groups desiring and not desiring this program. A majority of respondents desired telephone, text messaging, and in-person contacts (79.2, 72.1, 83.8 %), with 72.5 % of patients desiring diabetes-related activities during clinic waiting time. Many women desire a postpartum diabetes reciprocal peer program for support outside of clinician visits. Patients are receptive to educational services during their wait and outside of clinic time, a potentially valuable opportunity to share important health information.     

Sample size re-estimation for clinical trials with longitudinal negative binomial counts including time trends

In some diseases, such as multiple sclerosis, lesion counts obtained from magnetic resonance imaging (MRI) are used as markers of disease progression. This leads to longitudinal, and typically overdispersed, count data outcomes in clinical trials. Models for such data invariably include a number of nuisance parameters, which can be difficult to specify at the planning stage, leading to considerable uncertainty in sample size specification. Consequently, blinded sample size re-estimation procedures are used, allowing for an adjustment of the sample size within an ongoing trial by estimating relevant nuisance parameters at an interim point, without compromising trial integrity. To date, the methods available for re-estimation have required an assumption that the mean count is time-constant within patients. We propose a new modeling approach that maintains the advantages of established procedures but allows for general underlying and treatment-specific time trends in the mean response. A simulation study is conducted to assess the effectiveness of blinded sample size re-estimation methods over fixed designs. Sample sizes attained through blinded sample size re-estimation procedures are shown to maintain the desired study power without inflating the Type I error rate and the procedure is demonstrated on MRI data from a recent study in multiple sclerosis.     

Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.     

Adolescent neighborhood quality predicts adult dACC response to social exclusion

Neuroimaging studies using the social-exclusion paradigm Cyberball indicate increased dorsal anterior cingulate cortex (dACC) and right insula activity as a function of exclusion. However, comparatively less work has been done on how social status factors may moderate this finding. This study used the Cyberball paradigm with 85 (45 females) socio-economically diverse participants from a larger longitudinal sample. We tested whether neighborhood quality during adolescence would predict subsequent neural responding to social exclusion in young adulthood. Given previous behavioral studies indicating greater social vigilance and negative evaluation as a function of lower status, we expected that lower adolescent neighborhood quality would predict greater dACC activity during exclusion at young adulthood. Our findings indicate that young adults who lived in low-quality neighborhoods in adolescence showed greater dACC activity to social exclusion than those who lived in higher quality neighborhoods. Lower neighborhood quality also predicted greater prefrontal activation in the superior frontal gyrus, dorsal medial prefrontal cortex and the middle frontal gyrus, possibly indicating greater regulatory effort. Finally, this effect was not driven by subsequent ratings of distress during exclusion. In sum, adolescent neighborhood quality appears to potentiate neural responses to social exclusion in young adulthood, effects that are independent of felt distress.     

Knowledge and Usage of Emergency Contraceptives Among University Students in Ghana

Contraceptive use is an important strategy for the prevention of unwanted pregnancy and avoidance of induced abortion. Of all the contraception methods, emergency contraceptive (EC) offers the last chance to achieve this. However, few studies have documented the use of EC among young people in Ghana. This study explored knowledge and usage of EC as well as the factors associated with it among University of Cape Coast students. Data were obtained on the knowledge and usage of ECs among University of Cape Coast students in 2013. Logistic regression analysis was used to investigate the association between students’ socio-demographic characteristics and EC knowledge and use. More male students (72 %) than females (59 %) were sexually active. Fifty-seven percent of the respondents had ever heard of EC and 36 % had ever used EC. Although males were more likely to be sexually active, females were more likely to have knowledge of EC use compared to males. The study underscores the need to increase awareness regarding EC among University students in order to offer them the opportunity that EC provides if other forms of contraceptives are missed.