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  • Brand : BIOFRON

  • Catalogue Number : BN-O1843

  • Specification : 98%(HPLC)

  • CAS number : 16910-39-7

  • Formula : C29H50O

  • Molecular Weight : 414.71

  • Volume : 20mg

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WGK Germany


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For Reference Standard and R&D, Not for Human Use Directly.

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provides coniferyl ferulate(CAS#:16910-39-7) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

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Conducting research in partnership with stakeholders (e.g. policy-makers, practitioners, organisations, patients) is a promising and popular approach to improving the implementation of research findings in policy and practice. This study aimed to identify the principles, strategies, outcomes and impacts reported in different types of reviews of research partnerships in order to obtain a better understanding of the scope of the research partnership literature.

This review of reviews is part of a Coordinated Multicenter Team approach to synthesise the research partnership literature with five conceptually linked literature reviews. The main research question was ‘What principles, strategies, outcomes and impacts are reported in different types of research partnership approaches?’. We included articles describing a literature review of research partnerships using a systematic search strategy. We used an adapted version of the Revised Assessment of Multiple Systematic Reviews tool to assess quality. Nine electronic databases were searched from inception to April 2018. Principles, strategies, outcomes and impacts were extracted from the included reviews and analysed using direct content analysis.

We included 86 reviews using terms describing several research partnership approaches (e.g. community-based participatory research, participatory research, integrated knowledge translation). After the analyses, we synthesised 17 overarching principles and 11 overarching strategies and grouped them into one of the following subcategories: relationship between partners; co-production of knowledge; meaningful stakeholder engagement; capacity-building, support and resources; communication process; and ethical issues related to the collaborative research activities. Similarly, we synthesised 20 overarching outcomes and impacts on researchers, stakeholders, the community or society, and the research process.

This review of reviews is the first that presents overarching principles, strategies, outcomes and impacts of research partnerships. This review is unique in scope as we synthesised literature across multiple research areas, involving different stakeholder groups. Our findings can be used as a first step to guide the initiation and maintenance of research partnerships and to create a classification system of the key domains of research partnerships, which may improve reporting consistency in the research partnership literature.

Trial registration
This study is registered via Open Science Framework: 10.17605/OSF.IO/GVR7Y.


Collaborative research partnerships, Integrated knowledge translation, Community-based participatory research, Stakeholder engagement, Research principles and strategies, Research outcomes and impact, Knowledge syntheses


A review of reviews on principles, strategies, outcomes and impacts of research partnerships approaches: a first step in synthesising the research partnership literature


F. Hoekstra,1,2 K. J. Mrklas,3,4 M. Khan,5 R. C. McKay,1,2 M. Vis-Dunbar,6 K. M. Sibley,5,7 T. Nguyen,8,9 I. D. Graham,10,11 SCI Guiding Principles Consensus Panel, and H. L. Gainforthcorresponding author1,2

Publish date





Plasmonic gas sensors are optical sensors that use localized surface plasmons or extended surface plasmons as transducing platform. Surface plasmons are very sensitive to dielectric variations of the environment or to electron exchange, and these effects have been exploited for the realization of sensitive gas sensors. In this paper, we review our research work of the last few years on the synthesis and the gas sensing properties of sol-gel based nanomaterials for plasmonic sensors.


surface plasmon resonance, nanoparticles, optical sensors, metal oxide, TiO2, ZnO, NiO, Au, Ag


Sol-Gel Thin Films for Plasmonic Gas Sensors


Enrico Della Gaspera1 and Alessandro Martucci2,*

Publish date

2015 Jul;




We present an allele-specific copy number analysis of the in vivo breast cancer genome. We describe a unique bioinformatics approach, ASCAT (allele-specific copy number analysis of tumors), to accurately dissect the allele-specific copy number of solid tumors, simultaneously estimating and adjusting for both tumor ploidy and nonaberrant cell admixture. This allows calculation of “ASCAT profiles” (genome-wide allele-specific copy-number profiles) from which gains, losses, copy number-neutral events, and loss of heterozygosity (LOH) can accurately be determined. In an early-stage breast carcinoma series, we observe aneuploidy (>2.7n) in 45% of the cases and an average nonaberrant cell admixture of 49%. By aggregation of ASCAT profiles across our series, we obtain genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. In addition, the ASCAT profiles reveal differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between the five previously identified molecular breast cancer subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. Finally, from the ASCAT profiles, we construct a genome-wide map of allelic skewness in breast cancer, indicating loci where one allele is preferentially lost, whereas the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development.


breast carcinoma, single-nucleotide polymorphism arrays, bioinformatics, cancer


Allele-specific copy number analysis of tumors


Peter Van Loo,a,b,c,1 Silje H. Nordgard,a,d,1 Ole Christian Lingjærde,e Hege G. Russnes,a,f,g Inga H. Rye,f Wei Sun,d,h Victor J. Weigman,d Peter Marynen,c Anders Zetterberg,i Bjørn Naume,j Charles M. Perou,d Anne-Lise Børresen-Dale,corresponding authora,g,2 and Vessela N. Kristensena,g,k,2,3

Publish date

2010 Sep 28

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