Analysis of Volatile Organic Compounds in Virgin Coconut Oil and their Sensory Attibutes

The volatile compounds in the headspace of twenty-four commercial virgin coconut oil (VCO) samples prepared by different methods (i.e. expeller, centrifugation, and fermentation with and without heat) were analyzed by solid phase microextraction-gas chromatography mass spectrometry (SPME-GCMS). The following volatile organic compounds (VOCs) were identified: ethyl acetate, acetic acid, 2-pentanone, hexanal, n-octane, 2-heptanone, limonene, nonanal, octanoic acid, ethyl octanoate, δ-octalactone, ethyl decanoate, δ-decalactone, and dodecanoic acid. Fermentation-produced samples were found to have higher levels of acetic acid and free fatty acids in the headspace compared to VCO produced using the centrifuge and expeller methods. Descriptive sensory analysis of the VCO samples by a trained panel was carried out to determine its sensory attributes and to correlate the volatile compounds that are responsible for VCO aroma. Principal components regression (PCR) of the SPME-derived analytical and sensory data indicates that lactones impart coconut-like aroma, while octanoic acid is mainly responsible for the rancid and acid aroma. SPME-GCMS can be used to differentiate VCO produced by physical means from fermentationproduced samples and can be used as a method to monitor VCO product quality

Quality characteristics of virgin coconut oil:Comparisons with refined coconut oil

Virgin coconut oil (VCO) is a vegetable oil that is extracted from fresh coconut meat and is processed using only physical and other natural means. VCO was compared to refined, bleached, and deodorized coconut oil (RCO) using standard quality parameters, 31 P nuclear magnetic resonance (NMR) spectroscopy, and headspace solid-phase micro - extraction/gas chromatography mass spectrometry (SPME/GCMS). VCO tends to have higher free fatty acids (FFAs), moisture, and volatile matter and lower peroxide value than RCO. However, the range of values overlap and no single standard parameter alone can be 31 used to differentiate VCO from RCO. Using 31P NMR, VCO and RCO can be distinguished in terms of the total amount of diglycerides: VCO showed an average content (w/w %) of 1.55, whereas RCO gave an average of 4.10. There was no overlap in the values found for individual VCO and RCO samples. There are four common methods of producing VCO: expeller (EXP), centrifuge (CEN), and fermentation with and without heat. VCO products prepared using these four methods could not be differentiated using standard quality parameters. Sensory analysis showed that VCO produced by fermentation (with and without heat) could be distinguished from those produced using the EXP and CEN methods; this sensory differentiation correlated with the higher levels of acetic acid and octanoic acid in the VCO produced by fermentation. Studies on physicochemical deterioration of VCO showed that VCO is stable to chemical and photochemical oxidation and hydrolysis. VCO is most susceptible to microbial attack, which leads to the formation of various organic acids, in particular, lactic acid. However, at moisture levels below 0.06 %, microbial action is significantly lessened

Physico-Chemical and Microbiological Parameters in the Deterioration of Virgin Coconut Oil

The deterioration of virgin coconut oil (VCO) due to physico-chemical oxidation and hydrolysis and microbiological processes was studied. The physico-chemical oxidation of VCO in the air at room temperature was negligible. Oxidation of VCO was observed only in the presence of air, UV radiation, ferric ion (Fe3+), and high free fatty acid (FFA) content. Chemical hydrolysis was performed at varying moisture levels and temperatures. The rate of hydrolysis to produce FFAs was measured using 31P NMR under conditions of saturated water (0.22%) and 80°C was found to be 0.066 µmol/g-hr (expressed as lauric acid). At 0.084% moisture and 80°C, the rate of FFA formation was found to be 0.008 µmol/g-hr. The microbial decomposition of VCO was determined after four days of incubation at 37°C. At low moisture levels (\u3c0.06%), VCO was stable to microbial decomposition. However, at higher moisture levels, there was an increase in the formation of organic acids, in particular, lactic acid, dodecanoic acid, succinic acid, acetic acid, and fumaric acid, indicating that microbial action had occurred. The most important conditions that influence the physicochemical and microbial degradation of VCO are moisture, temperature, and the presence of microorganisms. These degradation processes can be minimized if the moisture level is maintained below 0.06%

An inclusive Research and Education Community (iREC) model to facilitate undergraduate science education reform

Funding: This work was supported by Howard Hughes Medical Institute grants to DIH is GT12052 and MJG is GT15338.Over the last two decades, there have been numerous initiatives to improve undergraduate student outcomes in STEM. One model for scalable reform is the inclusive Research Education Community (iREC). In an iREC, STEM faculty from colleges and universities across the nation are supported to adopt and sustainably implement course-based research – a form of science pedagogy that enhances student learning and persistence in science. In this study, we used pathway modeling to develop a qualitative description that explicates the HHMI Science Education Alliance (SEA) iREC as a model for facilitating the successful adoption and continued advancement of new curricular content and pedagogy. In particular, outcomes that faculty realize through their participation in the SEA iREC were identified, organized by time, and functionally linked. The resulting pathway model was then revised and refined based on several rounds of feedback from over 100 faculty members in the SEA iREC who participated in the study. Our results show that in an iREC, STEM faculty organized as a long-standing community of practice leverage one another, outside expertise, and data to adopt, implement, and iteratively advance their pedagogy. The opportunity to collaborate in this manner and, additionally, to be recognized for pedagogical contributions sustainably engages STEM faculty in the advancement of their pedagogy. Here, we present a detailed pathway model of SEA that, together with underpinning features of an iREC identified in this study, offers a framework to facilitate transformations in undergraduate science education.Peer reviewe

Models of classroom assessment for course-based research experiences

Course-based research pedagogy involves positioning students as contributors to authentic research projects as part of an engaging educational experience that promotes their learning and persistence in science. To develop a model for assessing and grading students engaged in this type of learning experience, the assessment aims and practices of a community of experienced course-based research instructors were collected and analyzed. This approach defines four aims of course-based research assessment—(1) Assessing Laboratory Work and Scientific Thinking; (2) Evaluating Mastery of Concepts, Quantitative Thinking and Skills; (3) Appraising Forms of Scientific Communication; and (4) Metacognition of Learning—along with a set of practices for each aim. These aims and practices of assessment were then integrated with previously developed models of course-based research instruction to reveal an assessment program in which instructors provide extensive feedback to support productive student engagement in research while grading those aspects of research that are necessary for the student to succeed. Assessment conducted in this way delicately balances the need to facilitate students’ ongoing research with the requirement of a final grade without undercutting the important aims of a CRE education

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Developing a chemical and hazardous waste inventory system

We describe the development of a chemical management information system (CMIS) that addresses the multiple requirements of university-based chemistry department. The CMIS is a web-based inventory-keeping software developed using PHP and MySQL that provides chemical information such as safety data sheets; tracks individual chemical bottles using a barcode system to monitor stock-levels, consumption, movement and expiration; complies with government regulations on controlled chemicals and hazardous chemical wastes; facilitates sharing of chemicals among different departments; and stores supplier information. It has four user levels with increasing functionality: students; faculty members and researchers; department heads and staff; and technicians and system administrator. Currently, the system manages over 11,000 chemical bottles of three departments in the university

Studies on Standards for Commercial Virgin Coconut Oil

A minimum set of analytical methods is recommended for the differentiation of virgin coconut oil (VCO) from refined, bleached and deodorized coconut oil (RBD CNO): % fatty acid composition,% moisture by Karl Fischer (0.10%), % volatile matter at 120°C (0.10-0.20%), % free fatty acids as lauric acid (0.2%), peroxide value (3 meq/kg), and microbial contamination by colony forming units (\u3c10 cfu/mL). The% fatty acid composition was determined using an internal standard and molecular weight correction from the fatty acid methyl ester to the fatty acid. This method yields absolute amounts of fatty acid in the oil. The absolute amount of oleic acid and linoleic acid can be used to replace the iodine value. Principal components analysis of the fatty acid composition indicates that it is not affected by the processing method

Standards for essential composition and quality factors of commercial virgin coconut oil and its differentiation from RBD coconut oil and copra oil

Commercial samples of virgin coconut oil (VCO), refined, bleached and deodorized coconut oil (RBD CNO), and copra oil were analyzed using standard chemical parameters: gas chromatography (GC) of the fatty acid methyl esters (FAME), % moisture by Karl Fischer titration, % volatile matter at 120° C, % free fatty acid, iodine value, peroxide value, and microbial contamination. Principal components analysis (PCA) of the GC-FAME results indicates that the various samples cannot be differentiated by their fatty acid composition, indicating that the fatty acid profile is not affected by the processing method. No trans-fatty acid was detected in all samples down to 0.01% (w/w) detection limit. VCO can be differentiated from RBD CNO and copra oil using the following tests: % moisture by Karl Fischer, % volatile matter volatile at 120° C, and peroxide value

Essential quality parameters of commercial virgin coconut oil

Chemical analyses conducted on commercial samples of virgin coconut oil (VCO) produced by four different methods gave the following ranges of values: % Fatty acid composition: C6: 0.24 to 0.49%; C8: 4.15 to 8.30%; C10: 4.27 to 5.75%; C12: 46.0 to 52.6%; C14: 16.0 to 19.7%; C16: 7.65 to 10.1%; C18: 2.86 to 4.63%; C18:1: 5.93 to 8.53%; C18:2: 1.00 to 2.16%; %moisture by Karl Fischer: 0.05 to 0.12%; %matter volatile at 120 0C: 0.12 to 0.18%; %free fatty acids as lauric acid: 0.042 to 0.329%; and peroxide value: none detected to 1.40. The tests for %moisture by Karl Fischer and %matter volatile at 120 0C can be used to differentiate VCO from and refined, bleached and deodorized coconut oil (RBD CNO). No trans-fatty acid was detected in both VCO and RBD CNO down to 0.01% (w/w) detection limit