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Hydroxy-α-sanshool

$476

  • Brand : BIOFRON

  • Catalogue Number : BD-P0485

  • Specification : 98.0%(HPLC)

  • CAS number : 83883-10-7

  • PUBCHEM ID : 10084135

  • Volume : 25mg

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Catalogue Number

BD-P0485

Analysis Method

HPLC,NMR,MS

Specification

98.0%(HPLC)

Storage

-20℃

Molecular Weight

Appearance

Powder

Botanical Source

Zanthoxyli pericarpium

Structure Type

Alkaloids

Category

Standards;Natural Pytochemical;API

SMILES

CC=CC=CC=CCCC=CC(=O)NCC(C)(C)O

Synonyms

(2E,6Z,8E,10E)-N-(2-HYDROXY-2-METHYL-PROPYL)DODECA-2,6,8,10-TETRAENAMIDE/(2E,6Z,8E,10E)-N-(2-hydroxy-2-methylpropyl)dodeca-2,6,8,10-tetraenamide

IUPAC Name

(2E,6Z,8E,10E)-N-(2-hydroxy-2-methylpropyl)dodeca-2,6,8,10-tetraenamide

Applications

Hydroxy-​α-​sanshool is an alkylamide isolated from pepper, acts as a TRPA1 covalent and TRPV1 non-covalent agonist, with EC50s of 69 and 1.1 µM, respectively[1].

Density

Solubility

Methanol

Flash Point

Boiling Point

Melting Point

InChl

InChI=1S/C16H25NO2/c1-4-5-6-7-8-9-10-11-12-13-15(18)17-14-16(2,3)19/h4-9,12-13,19H,10-11,14H2,1-3H3,(H,17,18)/b5-4+,7-6+,9-8-,13-12+

InChl Key

LHFKHAVGGJJQFF-UEOYEZOQSA-N

WGK Germany

RID/ADR

HS Code Reference

2924190000

Personal Projective Equipment

Correct Usage

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

Meta Tag

provides coniferyl ferulate(CAS#:83883-10-7) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

No Technical Documents Available For This Product.

PMID

29541282

Abstract

Background
Type 1 diabetes is a condition in which the pancreas produces little or no insulin. People with type 1 diabetes must manage their blood glucose levels by monitoring the amount of glucose in their blood and administering appropriate amounts of insulin via injection or an insulin pump. Continuous glucose monitoring may be beneficial compared to self-monitoring of blood glucose using a blood glucose meter. It provides insight into a person’s blood glucose levels on a continuous basis, and can identify whether blood glucose levels are trending up or down.

Methods
We conducted a health technology assessment, which included an evaluation of clinical benefit, value for money, and patient preferences related to continuous glucose monitoring. We compared continuous glucose monitoring with self-monitoring of blood glucose using a finger-prick and a blood glucose meter. We performed a systematic literature search for studies published since January 1, 2010. We created a Markov model projecting the lifetime horizon of adults with type 1 diabetes, and performed a budget impact analysis from the perspective of the health care payer. We also conducted interviews and focus group discussions with people who self-manage their type 1 diabetes or support the management of a child with type 1 diabetes.

Results
Twenty studies were included in the clinical evidence review. Compared with self-monitoring of blood glucose, continuous glucose monitoring improved the percentage of time patients spent in the target glycemic range by 9.6% (95% confidence interval 8.0-11.2) to 10.0% (95% confidence interval 6.75-13.25) and decreased the number of severe hypoglycemic events.

Continuous glucose monitoring was associated with higher costs and small increases in health benefits (quality-adjusted life-years). Incremental cost-effectiveness ratios (ICERs) ranged from $592,206 to $1,108,812 per quality-adjusted life-year gained in analyses comparing four continuous glucose monitoring interventions to usual care. However, the uncertainty around the ICERs was large. The net budget impact of publicly funding continuous glucose monitoring assuming a 20% annual increase in adoption of continuous glucose monitoring would range from $8.5 million in year 1 to $16.2 million in year 5.

Patient engagement surrounding the topic of continuous glucose monitoring was robust. Patients perceived that these devices provided important social, emotional, and medical and safety benefits in managing type 1 diabetes, especially in children.

Conclusions
Continuous glucose monitoring was more effective than self-monitoring of blood glucose in managing type 1 diabetes for some outcomes, such as time spent in the target glucose range and time spent outside the target glucose range (moderate certainty in this evidence). We were less certain that continuous glucose monitoring would reduce the number of severe hypoglycemic events. Compared with self-monitoring of blood glucose, the costs of continuous glucose monitoring were higher, with only small increases in health benefits. Publicly funding continuous glucose monitoring for the type 1 diabetes population in Ontario would result in additional costs to the health system over the next 5 years. Adult patients and parents of children with type 1 diabetes reported very positive experiences with continuous glucose monitoring. The high ongoing cost of continuous glucose monitoring devices was seen as the greatest barrier to their widespread use.

Title

Continuous Monitoring of Glucose for Type 1 Diabetes: A Health Technology Assessment

Author

Health Quality Ontario

Publish date

2018;

PMID

31295279

Abstract

Introduction
The study presents the results of the genomic surveillance of invasive meningococcal disease (IMD) in the Czech Republic for the period of 2015-2017.

Material and methods
The study set includes all available IMD isolates recovered in the Czech Republic and referred to the National Reference Laboratory for Meningococcal Infections in 2015-2017, a total of 89 Neissseria meningitidis isolates—from 2015 (n = 20), 2016 (n = 27), and from 2017 (n = 42). All isolates were studied by whole genome sequencing (WGS).

Results
Serogroup B (MenB) was the most common, followed by serogroups C, W, and Y. Altogether 17 clonal complexes were identified, the most common of which was hypervirulent complex cc11, followed by complexes cc32, cc41/44, cc269, and cc865. Over the three study years, hypervirulent cc11 (MenC) showed an upward trend. The WGS method showed two clearly differentiated clusters of N. meningitidis C: P1.5,2:F3-3:ST-11 (cc11). The first cluster is represented by nine isolates, all of which are from 2017. The second cluster consisted of five isolates from 2016 and eight isolates from 2017. Their genetic discordance is illustrated by the changing nadA allele and subsequently by the variance in BAST type. Clonal complex cc269 (MenB) also increased over the time frame. WGS identified the presence of MenB vaccine antigen genes in all B and non-B isolates of N. meningitidis. Altogether 49 different Bexsero antigen sequence types (BAST) were identified and 10 combinations of these have not been previously described in the PubMLST database.

Conclusions
The genomic surveillance of IMD in the Czech Republic provides data needed to update immunisation guidelines for this disease. WGS showed a higher discrimination power and provided more accurate data on molecular characteristics and genetic relationships among invasive N. meningitidis isolates.

Title

Genomic surveillance of invasive meningococcal disease in the Czech Republic, 2015-2017

Author

Pavla Krizova, Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing - original draft, Writing - review & editing* and Michal Honskus, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing - original draft, Writing - review & editing

Publish date

2019;

PMID

26870437

Abstract

In the title complex, [Ni(C21H17F2N3)2]2Br4·9H2O, there are two independent metal complexes per asymmetric unit and two ligands per metal complex. The structural features (bond lengths and angles) of the two complexes are almost identical. In each complex, the nickel(II) ion is coordinated in an octa­hedral environment by six N atoms from two chelating (9E)-N-({6-[(E)-(4-fluoro­benzyl­imino)­meth­yl]pyridin-2-yl}methyl­ene)(4-fluoro­phen­yl)methanammine ligands. The Ni—N bond lengths range from 1.973 (2) to 2.169 (2) a, while the chelate N—Ni—N angles range from 77.01 (10) to 105.89 (9)°. Additionally, there are four bromide anions and nine solvent water mol­ecules within the asymmetric unit. The water mol­ecules form a hydrogen-bonded network, displaying C—H⋯O, C—H⋯Br, O—H⋯Br, O—H⋯O and O—H⋯F inter­actions into layers parallel to (111). In each unit, the fluoro­phenyl rings of one ligand are stacked with the central ring of the other ligand via π-π inter­actions, with the closest centroid-to-plane distances being 3.445 (5), 3.636 (5), 3.397 (5) and 3.396 (5) a.

KEYWORDS

crystal structure, nickel(II) complex, octa­hedral geometry, Schiff base, π-π inter­actions, pyridine derivatives

Title

Crystal structure of bis(bis{(E)-[(6-{(E)-[(4-fluorobenzyl)imino]methyl}pyridin-2-yl)methylidene](4-fluorophenyl)amine}nickel(II)) tetra­bromide nona­hydrate

Author

Ismet Basaran,a Md Mhahabubur Rhaman,b Douglas R. Powell,c and Md. Alamgir Hossainb,*

Publish date

2015 Dec 1;