7 and 18 2 %, respectively) as main straight carbon chains of sat

7 and 18.2 %, respectively) as main straight carbon chains of saturated fatty acids. Unsaturated fatty acids were also identified with 18:1n9c (18.8 %) and 16:1n7 (5 %) being the predominant

components. The effect of environmental factors on fatty acid composition was monitored by using principal component analysis and central composite design. Variation of light intensity (20 to 150 mu mol photons m(-2) s(-1)), temperature (20 to 60 A degrees C), and nitrogen concentration (0 to 3 g L-1) induced a significant variation in the amount of fatty acid proportions, whereas lipid content was only slightly modified. Results showed that light intensity had the strongest effect 4EGI-1 Others inhibitor Momelotinib in vivo on the composition of fatty acids. Temperature had a synergic effect with light intensity while nitrogen concentration had a trivial effect. The combined effect of high light intensity (150 mu mol photons m(-2) s(-1)) and high temperature (60 A degrees C) increased the proportion of saturated 16:0 and 18:0 fatty acids along with long-chain fatty acids to 82 % which was twofold higher than that in optimal growth conditions. This induced fatty acid profile

makes G. gelatinosa-based biofuels adaptable for higher energetic efficiency and higher oxidative stability.”
“The predictive validity of peer review at the National Institutes of Health (NIH) has not yet been demonstrated empirically. It might be assumed that the most efficient and expedient test of the predictive validity of NIH peer review would be an examination of the correlation between percentile scores from peer review and bibliometric indices of the publications produced from funded projects. The present study used a large dataset to examine the rationale for such a study, to determine if it would satisfy the requirements for a test of predictive validity. The results show significant restriction of range in

the applications selected for funding. Furthermore, PFTα those few applications that are funded with slightly worse peer review scores are not selected at random or representative of other applications in the same range. The funding institutes also negotiate with applicants to address issues identified during peer review. Therefore, the peer review scores assigned to the submitted applications, especially for those few funded applications with slightly worse peer review scores, do not reflect the changed and improved projects that are eventually funded. In addition, citation metrics by themselves are not valid or appropriate measures of scientific impact. The use of bibliometric indices on their own to measure scientific impact would likely increase the inefficiencies and problems with replicability already largely attributed to the current over-emphasis on bibliometric indices.

Leave a Reply

Your email address will not be published. Required fields are marked *

*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>