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Hydroxytyrosol 4-O-glucoside


  • Brand : BIOFRON

  • Catalogue Number : BN-O0972

  • Specification : 98%(HPLC)

  • CAS number : 54695-80-6

  • Formula : C14H20O8

  • Molecular Weight : 316.3

  • PUBCHEM ID : 6453057

  • Volume : 5mg

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Standards;Natural Pytochemical;API




hydroxytyrosol 4-glucoside/2-(3-hydroxy-4-O-D-β-glucopyranosylphenyl)ethanol/4'-O-SS-D-GLUCOPYRANOSIDE





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#:54695-80-6) 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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In the mol­ecular structure of the title compound, C15H13ClNO2 +·CF3SO3 −, the meth­oxy groups are nearly coplanar with the acridine ring system, making dihedral angles of 0.4 (2) and 5.1 (2)°. Multidirectional π-π contacts between acridine units are observed in the crystal structure. N—H⋯O and C—H⋯O hydrogen bonds link cations and anions, forming a layer structure.


9-Chloro-2,4-dimethoxy­acridinium trifluoro­methane­sulfonate


Beata Zadykowicz,a Karol Krzymiński,a Damian Trzybiński,a Artur Sikorski,a and Jerzy Błażejowskia,*

Publish date

2009 Apr 1




Simple Summary
Euthanasia is used in developed countries as a method of population control for dogs and cats entering shelters and council pounds. This study analyzed all available dog and cat population, registration, intake and outcome data for the 79 Victorian councils. The majority (74%) of councils achieved euthanasia rates for dogs of ≤10%, but only one achieved that for cats, and mean cat euthanasia was 48%. Low euthanasia rates were associated with high rates of reclaim, and adoption of unclaimed animals. A telephone survey of 35 councils (44%) was undertaken to identify policies, practices and attitudes of staff to identify strategies that reduce euthanasia. It is envisaged this data could be used as a resource for councils to lower euthanasia rates.

Using euthanasia to manage dog and cat overpopulation causes health issues and emotional stress in employees involved, increases staff turnover, and has financial, moral and ethical ramifications for communities. Welfare agencies and local government agencies (councils) share responsibility for managing companion animal populations. This study investigated Australian councils in the state of Victoria, to identify strategies used to reduce euthanasia. Statistics regarding animal populations, registration, intake, reclaim, rehome and euthanasia were obtained from the Domestic Animal Management Plan of each council. Of the 79 Victorian councils, 74% achieved ≤10% euthanasia of impounded dogs, which is widely quoted as zero euthanasia of adoptable and treatable animals. The mean euthanasia rates for cats by the councils was 48%, with only one council achieving a euthanasia rate of ≤10% for cats. Mean reclaim rates for dogs were higher (73%) than for cats (13%), as was the mean proportion of unclaimed dogs rehomed (71%), compared to cats (45%). Telephone questionnaires were conducted with animal management officers from 35 councils (44%). Those with low euthanasia rates had high reclaim rates and/or rehome rates. Reclaim, rehome and euthanasia rates for dogs and cats were not significantly different between councils that operated their own pound facilities and those that utilized the services of welfare organizations to operate pounds on behalf of the council. More council managers believed they would never achieve ≤10% euthanasia for cats (49%) than for dogs (11%). A variety of strategies were used by councils to achieve high reclaim and rehoming rates.


council pound, dog, cat, euthanasia, Australia


Strategies to Reduce the Euthanasia of Impounded Dogs and Cats Used by Councils in Victoria, Australia


Jacquie Rand,1,2,* Emily Lancaster,2 Georgina Inwood,1 Carolyn Cluderay,1 and Linda Marston2

Publish date

2018 Jul;




Techniques of data mining and machine learning were applied to a large database of medical and facility claims from commercially insured patients to determine the prevalence, gender demographics, and costs for individuals with provider-assigned diagnosis codes for myalgic encephalomyelitis (ME) or chronic fatigue syndrome (CFS). The frequency of diagnosis was 519-1,038/100,000 with the relative risk of females being diagnosed with ME or CFS compared to males 1.238 and 1.178, respectively. While the percentage of women diagnosed with ME/CFS is higher than the percentage of men, ME/CFS is not a “women’s disease.” Thirty-five to forty percent of diagnosed patients are men. Extrapolating from this frequency of diagnosis and based on the estimated 2017 population of the United States, a rough estimate for the number of patients who may be diagnosed with ME or CFS in the U.S. is 1.7 million to 3.38 million. Patients diagnosed with CFS appear to represent a more heterogeneous group than those diagnosed with ME. A machine learning model based on characteristics of individuals diagnosed with ME was developed and applied, resulting in a predicted prevalence of 857/100,000 (p > 0.01), or roughly 2.8 million in the U.S. Average annual costs for individuals with a diagnosis of ME or CFS were compared with those for lupus (all categories) and multiple sclerosis (MS), and found to be 50% higher for ME and CFS than for lupus or MS, and three to four times higher than for the general insured population. A separate aspect of the study attempted to determine if a diagnosis of ME or CFS could be predicted based on symptom codes in the insurance claims records. Due to the absence of specific codes for some core symptoms, we were unable to validate that the information in insurance claims records is sufficient to identify diagnosed patients or suggest that a diagnosis of ME or CFS should be considered based solely on looking for presence of those symptoms. These results show that a prevalence rate of 857/100,000 for ME/CFS is not unreasonable; therefore, it is not a rare disease, but in fact a relatively common one.


ME/CFS, myalgic encephalomyelitis, chronic fatigue syndrome, prevalence, costs, machine learning, data mining


Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning


Ashley R. Valdez,1 Elizabeth E. Hancock,1 Seyi Adebayo,1 David J. Kiernicki,1 Daniel Proskauer,2 John R. Attewell,3 Lucinda Bateman,4 Alfred DeMaria, Jr.,5 Charles W. Lapp,6 Peter C. Rowe,7 and Charmian Proskauer8,*

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