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  • Brand : BIOFRON

  • Catalogue Number : BF-P2017

  • Specification : 98%

  • CAS number : 118555-82-1

  • Formula : C14H18 O9

  • Molecular Weight : 330.287

  • PUBCHEM ID : 14104237

  • Volume : 20mg

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Standards;Natural Pytochemical;API




2-[5-hydroxy-2-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyphenyl]acetic acid


2-[5-hydroxy-2-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyphenyl]acetic acid



Soluble in Chloroform,Dichloromethane,Ethyl Acetate,DMSO,Acetone,etc.

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

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provides coniferyl ferulate(CAS#:118555-82-1) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate




Childhood aggression and its resulting consequences inflict a huge burden on affected children, their relatives, teachers, peers and society as a whole. Aggression during childhood rarely occurs in isolation and is correlated with other symptoms of childhood psychopathology. In this paper, we aim to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. We focus on the co-occurrence of aggression and other childhood behavioural and emotional problems, including other externalising problems, attention problems and anxiety-depression. The data were brought together within the EU-ACTION (Aggression in Children: unravelling gene-environment interplay to inform Treatment and InterventiON strategies) project. We analysed the co-occurrence of aggression and other childhood behavioural and emotional problems as a function of the child’s age (ages 3 through 16 years), gender, the person rating the behaviour (father, mother or self) and assessment instrument. The data came from six large population-based European cohort studies from the Netherlands (2x), the UK, Finland and Sweden (2x). Multiple assessment instruments, including the Child Behaviour Checklist (CBCL), the Strengths and Difficulties Questionnaire (SDQ) and Multidimensional Peer Nomination Inventory (MPNI), were used. There was a good representation of boys and girls in each age category, with data for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds (49.0% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 12- to 13-year-olds (48.9% boys) and 10,088 15- to 16-year-olds (46.6% boys). We replicated the well-established gender differences in average aggression scores at most ages for parental ratings. The gender differences decreased with age and were not present for self-reports. Aggression co-occurred with the majority of other behavioural and social problems, from both externalising and internalising domains. At each age, the co-occurrence was particularly prevalent for aggression and oppositional and ADHD-related problems, with correlations of around 0.5 in general. Aggression also showed substantial associations with anxiety-depression and other internalizing symptoms (correlations around 0.4). Co-occurrence for self-reported problems was somewhat higher than for parental reports, but we found neither rater differences, nor differences across assessment instruments in co-occurrence patterns. There were large similarities in co-occurrence patterns across the different European countries. Finally, co-occurrence was generally stable across age and sex, and if any change was observed, it indicated stronger correlations when children grew older. We present an online tool to visualise these associations as a function of rater, gender, instrument and cohort. In addition, we present a description of the full EU-ACTION projects, its first results and the future perspectives.


Aggression, Childhood, Comorbidity, Co-occurence, Behavioural and emotional problems


Childhood aggression and the co-occurrence of behavioural and emotional problems: results across ages 3-16 years from multiple raters in six cohorts in the EU-ACTION project


Meike Bartels,corresponding author1,2,3 Anne Hendriks,1,2 Matteo Mauri,4 Eva Krapohl,5 Alyce Whipp,6 Koen Bolhuis,7 Lucia Colodro Conde,8 Justin Luningham,9 Hill Fung Ip,1,2 Fiona Hagenbeek,1,2 Peter Roetman,10 Raluca Gatej,10 Audri Lamers,10 Michel Nivard,1,2 Jenny van Dongen,1,2 Yi Lu,11 Christel Middeldorp,1,3,12 Toos van Beijsterveldt,1,2 Robert Vermeiren,10,13 Thomas Hankemeijer,14 Cees Kluft,15 Sarah Medland,8 Sebastian Lundstrom,16,17 Richard Rose,18 Lea Pulkkinen,19 Eero Vuoksimaa,6,20 Tellervo Korhonen,6,20,21 Nicholas G. Martin,22 Gitta Lubke,9 Catrin Finkenauer,1,23 Vassilios Fanos,4 Henning Tiemeier,7,24,25 Paul Lichtenstein,11 Robert Plomin,5 Jaakko Kaprio,6,20 and Dorret I. Boomsma1,2,3

Publish date





Modestly prevalent in the general population (~ 4%), but highly prevalent in prison populations (> 40%), the diagnosis of antisocial personality disorder (ASPD) involves aggression as one of several possible criteria. Using multiple informants, we aimed to determine if general aggression, as well as direct and indirect subtypes, assessed in early adolescence (ages 12, 14) predict young adulthood ASPD in a population-based sample. Using data from a Finnish population-based longitudinal twin cohort study with psychiatric interviews available at age 22 (N = 1347), we obtained DSM-IV-based ASPD diagnoses. Aggression measures from ages 12 (parental and teacher ratings) and 14 (teacher, self, and co-twin ratings) were used to calculate odds ratios (OR) of ASPD from logistic regression models and the area under the curve (AUC) from receiver operating characteristic curve analysis. Analyses were adjusted for sex, age, and family structure. All informants’ aggression ratings were significant (p < 0.05) predictors of ASPD (OR range 1.3-1.8; AUC range 0.65-0.72). Correlations between informants ranged from 0.13 to 0.33. Models including two or more aggression ratings, particularly age 14 teacher and self ratings, more accurately predicted ASPD (AUC: 0.80; 95% confidence interval 0.73-0.87). Direct aggression rated by all informants significantly predicted ASPD (OR range 1.4-1.9), whereas only self-rated indirect aggression was significantly associated with ASPD (OR = 1.4). Across different informants, general and direct aggression at ages 12 and 14 predicted ASPD in a population-based sample. Psychiatric, social, and parenting interventions for ASPD prevention should focus on children and adolescents with high aggression levels, with an aim to gather information from multiple informants.

Electronic supplementary material
The online version of this article (10.1007/s00787-018-1198-9) contains supplementary material, which is available to authorized users.


Adolescent, Aggression, Antisocial personality disorder, Population-based, Psychiatric prediction


Early adolescent aggression predicts antisocial personality disorder in young adults: a population-based study


Alyce M. Whipp,corresponding author1 Tellervo Korhonen,1,2 Anu Raevuori,2,3 Kauko Heikkila,1 Lea Pulkkinen,4 Richard J. Rose,5 Jaakko Kaprio,1,2 and Eero Vuoksimaa1

Publish date





Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest GWAS to date of DSM-IV diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case/control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, N = 46,568; African; N = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; p = 9.8E-13) and African ancestries (rs2066702; p = 2.2E-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, ADHD, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and non-pathological drinking behaviors.


Genome-wide association study, alcoholism, psychiatric disorders, alcohol use, pleiotropy


Trans-ancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders


Raymond K. Walters,1,2 Renato Polimanti,3 Emma C. Johnson,4 Jeanette N. McClintick,5 Mark J. Adams,6 Amy E. Adkins,7 Fazil Aliev,8 Silviu-Alin Bacanu,9 Anthony Batzler,10 Sarah Bertelsen,11 Joanna M. Biernacka,12 Tim B. Bigdeli,13 Li-Shiun Chen,4 Toni-Kim Clarke,6 Yi-Ling Chou,4 Franziska Degenhardt,14 Anna R. Docherty,15 Alexis C. Edwards,16 Pierre Fontanillas,17 Jerome C. Foo,18 Louis Fox,4 Josef Frank,18 Ina Giegling,19 Scott Gordon,20 Laura M. Hack,21 Annette M. Hartmann,19 Sarah M. Hartz,4 Stefanie Heilmann-Heimbach,14 Stefan Herms,14,22 Colin Hodgkinson,23 Per Hoffmann,14,22 Jouke Jan Hottenga,24 Martin A. Kennedy,25 Mervi Alanne-Kinnunen,26 Bettina Konte,19 Jari Lahti,27,28 Marius Lahti-Pulkkinen,28 Dongbing Lai,29 Lannie Ligthart,24 Anu Loukola,26 Brion S. Maher,30 Hamdi Mbarek,24 Andrew M. McIntosh,31 Matthew B. McQueen,32 Jacquelyn L. Meyers,33 Yuri Milaneschi,34 Teemu Palviainen,26 John F. Pearson,35 Roseann E. Peterson,16 Samuli Ripatti,1,2,26,36 Euijung Ryu,37 Nancy L. Saccone,38 Jessica E. Salvatore,8,16 Sandra Sanchez-Roige,39 Melanie Schwandt,40 Richard Sherva,41 Fabian Streit,18 Jana Strohmaier,18 Nathaniel Thomas,7 Jen-Chyong Wang,11 Bradley T. Webb,9 Robbee Wedow,1,2,42,43 Leah Wetherill,29 Amanda G. Wills,44 23andMe Research Team,45 Jason D. Boardman,46 Danfeng Chen,2 Doo-Sup Choi,47 William E. Copeland,48 Robert C. Culverhouse,49 Norbert Dahmen,50 Louisa Degenhardt,51 Benjamin W. Domingue,52 Sarah L. Elson,17 Mark A. Frye,53 Wolfgang Gabel,54 Caroline Hayward,55 Marcus Ising,56 Margaret Keyes,57 Falk Kiefer,58 John Kramer,59 Samuel Kuperman,59 Susanne Lucae,56 Michael T. Lynskey,60 Wolfgang Maier,61 Karl Mann,58 Satu Mannisto,62 Bertram Muller-Myhsok,63 Alison D. Murray,64 John I. Nurnberger,29,65 Aarno Palotie,1,2,26,66 Ulrich Preuss,19,67 Katri Raikkonen,28 Maureen D. Reynolds,68 Monika Ridinger,69 Norbert Scherbaum,70 Marc A. Schuckit,39 Michael Soyka,71,72 Jens Treutlein,18 Stephanie Witt,18 Norbert Wodarz,73 Peter Zill,72 Daniel E. Adkins,15,74 Joseph M. Boden,25 Dorret I. Boomsma,24 Laura J. Bierut,4 Sandra A. Brown,39,75 Kathleen K. Bucholz,4 Sven Cichon,22 E. Jane Costello,48 Harriet de Wit,76 Nancy Diazgranados,76 Danielle M. Dick,7,77 Johan G. Eriksson,78 Lindsay A. Farrer,41,79 Tatiana M. Foroud,29 Nathan A. Gillespie,16 Alison M. Goate,11 David Goldman,23,40 Richard A. Grucza,4 Dana B. Hancock,80 Kathleen Mullan Harris,81 Andrew C. Heath,4 Victor Hesselbrock,82 John K. Hewitt,83 Christian J. Hopfer,84 John Horwood,25 William Iacono,57 Eric O. Johnson,85 Jaakko A. Kaprio,26,36 Victor M. Karpyak,53 Kenneth S. Kendler,9 Henry R. Kranzler,86 Kenneth Krauter,87 Paul Lichtenstein,88 Penelope A. Lind,20 Matt McGue,57 James MacKillop,89 Pamela A. F. Madden,4 Hermine H. Maes,90 Patrik Magnusson,88 Nicholas G. Martin,20 Sarah E. Medland,20 Grant W. Montgomery,91 Elliot C. Nelson,4 Markus M. Nothen,92 Abraham A. Palmer,39,93 Nancy L. Pedersen,88 Brenda W.J.H. Penninx,34 Bernice Porjesz,33 John P. Rice,4 Marcella Rietschel,18 Brien P. Riley,9 Richard Rose,94 Dan Rujescu,19 Pei-Hong Shen,23 Judy Silberg,16 Michael C. Stallings,83 Ralph E. Tarter,68 Michael M. Vanyukov,68 Scott Vrieze,57 Tamara L. Wall,39 John B. Whitfield,20 Hongyu Zhao,95 Benjamin M. Neale,1,2 Joel Gelernter,96,* Howard J. Edenberg,5,29,* and Arpana Agrawal4,*

Publish date

2019 May 26.

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