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  • Brand : BIOFRON

  • Catalogue Number : BN-O0945

  • Specification : 98%(HPLC)

  • CAS number : 83013-86-9

  • Formula : C21H24O11

  • Molecular Weight : 452.41

  • PUBCHEM ID : 13270048

  • Volume : 5mg

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Standards;Natural Pytochemical;API






[(2R,3S,4S,5R,6R)-3,4,5-trihydroxy-6-[2-(4-hydroxyphenyl)ethoxy]oxan-2-yl]methyl 3,4,5-trihydroxybenzoate



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#:83013-86-9) 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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Metabolic Syndrome (MS) has been correlated to breast carcinogenesis. MS is common in the general population (34%) and increases with age and body mass index. Although the link between obesity, MS and hormone related cancer incidence is now widely recognized, the molecular mechanisms at the basis of such increase are still poorly characterized. A crucial role is supposed to be played by the altered insulin signalling, occurring in obese patients, which fuels cancer cell growth, proliferation and survival. Therefore we focused specifically on insulin resistance to investigate clinically the potential role of insulin in breast carcinogenesis.

975 patients were enrolled and the association between MS, insulin resistance, and breast cancer was evaluated. Women were stratified by age and menopausal status. Insulin resistance was measured through the Homeostasis Model Assessment score (HOMA-IR). The cut off value to define insulin resistance was HOMA-IR ≥ 2.50.

Higher prevalence of MS (35%) was found among postmenopausal women with breast cancer compared to postmenopausal healthy women (19%) [OR 2.16]. A broad range of BMI spanning 19-48 Kg/m2 was calculated. Both cases and controls were characterized by BMI ≥ 25 Kg/m2 (58% of cases compared to 61% of controls). Waist circumference >88 cm was measured in 53% of cases – OR 1.58- (95% CI 0.8-2.8) and in 46% of controls. Hyperinsulinemia was detected in 7% of cases – OR 2.14 (95% CI 1.78-2.99) and only in 3% of controls. HOMA-IR score was elevated in 49% of cases compared to 34% of controls [OR 1.86], suggesting that insulin resistance can nearly double the risk of breast cancer development. Interestingly 61% of women operated for breast cancer (cases) with HOMA-IR ≥ 2.5 presented subclinical insulin resistance with fasting plasma glucose levels and fasting plasma insulin levels in the normal range. Both android fat distribution and insulin resistance correlated to MS in the subgroup of postmenopausal women affected by breast cancer.

Our results further support the hypothesis that MS, in particular insulin resistance and abdominal fat, can be considered as risk factors for developing breast cancer after menopause. We suggest that HOMA-IR, rather than fasting plasma glucose and fasting plasma insulin levels alone, could be a valuable tool to identify patients with subclinical insulin resistance, which could be relevant for primary prevention and for high risk patient screening.


Metabolic syndrome, Insulin resistance, Breast cancer, Postmenopausal, HOMA-IR


Homeostasis model assessment to detect insulin resistance and identify patients at high risk of breast cancer development: National Cancer Institute of Naples experience


Immacolata Capasso,corresponding author1 Emanuela Esposito,1 Francesca Pentimalli,2 Maurizio Montella,3 Anna Crispo,3 Nicola Maurea,4 Massimiliano D’Aiuto,1 Alfredo Fucito,1 Maria Grimaldi,3 Ernesta Cavalcanti,5 Giuseppe Esposito,5 Giuseppe Brillante,1 Sergio Lodato,1 Tonino Pedicini,6 Giuseppe D’Aiuto,1 Gennaro Ciliberto,7 and Antonio Giordanocorresponding author2,8,9

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Where population coverage is limited, the exclusive use of Cancer Registries might limit ascertainment of incident cancer cases. We explored the potentials of Nationwide hospital discharge records (NHDRs) to capture incident breast cancer cases in Italy.

We analyzed NHDRs for mastectomies and quadrantectomies performed between 2001 and 2008. The average annual percentage change (AAPC) and related 95% Confidence Interval (CI) in the actual number of mastectomies and quadrantectomies performed during the study period were computed for the full sample and for subgroups defined by age, surgical procedure, macro-area and singular Region. Re-admissions of the same patients were separately presented.

The overall number of mastectomies decreased, with an AAPC of −2.1% (−2.3 -1.8). This result was largely driven by the values observed for women in the 45 to 64 and 65 to 74 age subgroups (−3.0%, -3.4 -3.6 and −3.3%, -3.8 -2.8, respectively). We observed no significant reduction in mastectomies for women in the remaining age groups. Quadrantectomies showed an overall +4.7 AAPC (95%CI:4.5-4.9), with no substantial differences by age. Analyses by geographical area showed a remarkable decrease in mastectomies, with inter-regional discrepancies possibly depending upon variability in mammography screening coverage and adherence. Quadrantectomies significantly increased, with Southern Regions presenting the highest average rates. Data on repeat admissions within a year revealed a total number of 46,610 major breast surgeries between 2001 and 2008, with an overall +3.2% AAPC (95%CI:2.8-3.6).

In Italy, NHDRs might represent a valuable supplemental data source to integrate Cancer Registries in cancer surveillance.


Hospital discharge records, Breast cancer, Mastectomies, Quadrantectomies, Cancer surveillance


The burden of breast cancer in Italy: mastectomies and quadrantectomies performed between 2001 and 2008 based on nationwide hospital discharge records


Prisco Piscitelli,1 Maddalena Barba,2 Massimo Crespi,3 Massimo Di Maio,4 Antonio Santoriello,5 Massiliamo D’Aiuto,6 Alfredo Fucito,6,7 Arturo Losco,8 Francesca Pentimalli,9 Pasquale Maranta,7,10 Giovanna Chitano,11 Alberto Argentiero,11 Cosimo Neglia,11 Alessandro Distante,11 Gian luca Di Tanna,12 Maria Luisa Brandi,1 Alfredo Mazza,7 Ignazio R Marino,13 and Antonio Giordanocorresponding author7,9,10,14, on behalf of the Human Health Foundation Study Group, in memory of Prof. Giovan Giacomo Giordano

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The number of predictive biomarkers that will be necessary to assess in clinical practice will increase with the availability of drugs that target specific molecular alterations. Therefore, diagnostic laboratories are confronted with new challenges: costs, turn-around-time and the amount of material required for testing will increase with the number of tests performed on a sample. Our consortium of European clinical research laboratories set out to test if semi-conductor sequencing provides a solution for these challenges.

We designed a multiplex PCR targeting 87 hotspot regions in 22 genes that are of clinical interest for lung and/or colorectal cancer. The gene-panel was tested by 7 different labs in their own clinical setting using ion-semiconductor sequencing.

We analyzed 155 samples containing 112 previously identified mutations in the KRAS, EGFR en BRAF genes. Only 1 sample failed analysis due to poor quality of the DNA. All other samples were correctly genotyped for the known mutations, even as low as 2%, but also revealed other mutations. Optimization of the primers used in the multiplex PCR resulted in a uniform coverage distribution over the amplicons that allows for efficient pooling of samples in a sequencing run.

We show that a semi-conductor based sequencing approach to stratify colon and lung cancer patients is feasible in a clinical setting.

Electronic supplementary material
The online version of this article (doi:10.1186/s12885-015-1015-5) contains supplementary material, which is available to authorized users.


Next-generation sequencing, Semi-conductor sequencing, Colorectal cancer, Non-small cell lung cancer, Multiplex PCR, Ion Torrent


Development of a semi-conductor sequencing-based panel for genotyping of colon and lung cancer by the Onconetwork consortium


Bastiaan BJ Tops,corresponding author1 Nicola Normanno,corresponding author2,3 Henriette Kurth,4 Eliana Amato,5 Andrea Mafficini,5 Nora Rieber,6 Delphine Le Corre,7 Anna Maria Rachiglio,2 Anne Reiman,8 Orla Sheils,9 Christoph Noppen,4 Ludovic Lacroix,10 Ian A Cree,8 Aldo Scarpa,5,11 Marjolijn JL Ligtenberg,1,12 and Pierre Laurent-Puig7

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