African American Cancer Survivors' Perspectives on Cancer Clinical Trial Participation in a Safety-Net Hospital: Considering the Role of the Social Determinants of Health.

Although there has been an increase focus on recruitment of minority populations at safety-net hospitals into cancer clinical trials, there is still a paucity of research exploring minority participation in cancer clinical trials at safety-net settings. The study utilized a multi-level, qualitative approach to assess the clinical and non-clinical facilitators and barriers to African American participation in cancer clinical trials at a safety-net hospital. From June 2018 to July 2019, cancer survivors (n = 25) were recruited from a cancer center at a safety-net hospital in the southeastern USA and participated in a 60-min focus group. Data was coded and analyzed to identify the most prominent themes. Most participants were female (78%), with a mean age of 56 years. The majority were diagnosed with breast cancer (68%) and disabled or unemployed (55%). Major themes identified were (1) lack of understanding of cancer clinical trials, (2) perceptions and fears of cancer clinical trials, and (3) preferred role and characteristics of patient navigator. The barriers and facilitators to enrollment in cancer clinical trials were more pronounced in the safety-net setting, given the overdue burden of social determinants of health. Study findings yield important insights and essential practices for recruiting and engaging underrepresented Black cancer patients into cancer clinical trials, specifically for safety-net settings. Including patient navigators may help traverse potential barriers to cancer clinical trial participation and will allow for the attention to social determinants of health, and ultimately increase the number of African Americans participating in cancer clinical trials.

Accurate method for rapid biomass quantification based on specific absorbance of microalgae species with biofuel importance.

The development of microalgae culture technology has been an integral part to produce biomass feedstock to biofuel production. Due to this, numerous attempts have been made to improve some operational parameters of microalgae production. Despite this, specialized research in cell growth monitoring, considered as a fundamental parameter to achieve profitable applications of microalgae for biofuels production, presents some opportunity areas mainly related to the development of specific and accurate methodologies for growth monitoring. In this work, predictive models were developed through statistical tools that correlate a specific micro-algal absorbance with cell density measured by cell count (cells∙per ml), for three species of interest for biofuels production. The results allow the precise prediction of cell density through a logistic model based on spectrophotometry, valid for all the kinetics analysed. The adjusted determination coefficients ( r adj 2 ) for the developed models were 0·993, 0·995 and 0·994 for Dunaliella tertiolecta, Nannochloropsis oculata and Chaetoceros muelleri respectively. The results showed that the equations obtained here can be used with an extremely low error (≤2%) for all the cell growth ranges analysed, with low operational cost and high potential of automation. Finally, a user-friendly software was designed to give practical use to the developed predictive models.