Evaluation of extra-virgin olive oils shelf life using an electronic tongue-chemometric approach

Physicochemical quality parameters, olfactory and gustatoryretronasal positive sensations of extra-virgin olive oils vary during storage leading to a decrease in the overall quality. Olive oil quality decline may prevent the compliance of olive oil quality with labeling and significantly reduce shelf life, resulting in important economic losses and negatively condition the consumer confidence. The feasibility of applying an electronic tongue to assess olive oils usual commercial light storage conditions and storage time was evaluated and compared with the discrimination potential of physicochemical or positive olfactory/gustatory sensorial parameters. Linear discriminant models, based on subsets of 58 electronic tongue sensor signals, selected by the meta-heuristic simulated annealing variable selection algorithm, allowed the correct classification of olive oils according to the light exposition conditions and/or storage time (sensitivities and specificities for leave-one-out cross-validation: 8296 %). The predictive performance of the E-tongue approach was further evaluated using an external independent dataset selected using the KennardStone algorithm and, in general, better classification rates (sensitivities and specificities for external dataset: 67100 %) were obtained compared to those achieved using physicochemical or sensorial data. So, the work carried out is a proof-of-principle that the proposed electrochemical device could be a practical and versatile tool for, in a single and fast electrochemical assay, successfully discriminate olive oils with different storage times and/or exposed to different light conditions.The authors acknowledge the financial support from the strategic funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRELCM funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia and under the strategic funding of UID/BIO/04469/2013 unit. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).info:eu-repo/semantics/publishedVersio

Our Voice NOLA: Leveraging a Community Engaged Citizen Science Method to Contextualize the New Orleans Food Environment

Objective: We employed the Our Voice citizen scientist method using a mobile application (app) to identify and contextualize neighborhood-level features influencing food access and wellbeing in New Orleans, Louisiana. Design: A three-phase, multi-method study comprised of: (1) a researcher-assisted tag-a-long neighborhood walk (referred to as a ‘journey’) with the Discovery Tool (DT) app to document neighborhood-level features via geo-coded photos and audio-recorded narratives; (2) a post-journey interview to enable citizen scientists to share their lived experiences; and (3) a community meeting with citizen scientists and local stakeholders. Setting: Various neighborhoods in New Orleans, Louisiana, USA. Participants: Citizen Scientists (i.e., residents) aged 18 years and older. Main Outcome Measure(s): Features that influence food access and health behaviors. Analysis: Descriptive statistics and a thematic content analysis were conducted to assess survey and app data. Results: Citizen scientists (N = 14) captured 178 photos and 184 audio narratives. Eight major themes were identified: safety; walkability; aesthetics; amenities; food; health services; neighborhood changes; and infrastructure/city planning. The post-journey interview provided insights around the abovementioned themes. The community meeting demonstrated the willingness of citizen scientists and stakeholders to convene and discuss issues and relevant solutions. Conclusions and Implications: Findings demonstrate the ability of technology and citizen science to help better understand the complexities of New Orleans’ past, present and distinct culture—and implications for food access and wellbeing in the context of trauma in an urban ecosystem

Steroid Avoidance in Two-Haplotype-Matched Living Donor Renal Transplants with Basiliximab Induction Therapy

Background. Induction therapy and haplotype matching are utilized to mitigate immunologic risk in renal transplantation. The incidence of acute rejection (AR) of renal allografts has been reported to be as low as 9.3% within the first year among two-haplotype-matched siblings with no induction and triple-drug maintenance immunosuppression. We report our use of basiliximab induction in a series of two-haplotype-matched living donor renal transplants (LDRT). Methods. We retrospectively reviewed 25 patients who received a two-haplotype-matched LDRT with basiliximab induction therapy. The primary endpoints were acute rejection (AR) episodes at 6 and 12 months and 1-year patient and graft survival rates. The secondary endpoints were the incidence of delayed graft function (DGF), cytomegalovirus (CMV), and BK virus (BKV). Results. The rate of AR at 6 months was 0% (0/25) and 4% (1/25) at 12 months. The 1-year graft and patient survival rates were 100%. The incidence of DGF was 4% (1/25), while the incidences of CMV and BKV were 0%. Conclusion. Basiliximab induction therapy with a steroid-sparing regimen yields favorable results in two-haplotype-matched LDRT, including a notable reduction in the rates of AR as compared to triple-drug maintenance immunosuppression without induction. These patients have excellent graft survival with no increased incidences of secondary infections