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5-Dehydroxyparatocarpin K

$730

  • Brand : BIOFRON

  • Catalogue Number : AV-B02882

  • Specification : 98%

  • CAS number : 124858-37-3

  • Formula : C20H18O4

  • Molecular Weight : 322.35

  • PUBCHEM ID : 72991213

  • Volume : 5mg

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Catalogue Number

AV-B02882

Analysis Method

HPLC,NMR,MS

Specification

98%

Storage

2-8°C

Molecular Weight

322.35

Appearance

Powder

Botanical Source

Structure Type

Flavonoids

Category

Standards;Natural Pytochemical;API

SMILES

CC1(C=CC2=CC3=C(C=C2O1)OC(CC3=O)C4=CC=C(C=C4)O)C

Synonyms

2H,6H-Benzo[1,2-b:5,4-b']dipyran-6-one, 7,8-dihydro-8-(4-hydroxyphenyl)-2,2-dimethyl-, (8S)-/(8S)-8-(4-Hydroxyphenyl)-2,2-dimethyl-7,8-dihydro-2H,6H-pyrano[3,2-g]chromen-6-one

IUPAC Name

8-(4-hydroxyphenyl)-2,2-dimethyl-7,8-dihydropyrano[3,2-g]chromen-6-one

Applications

Density

1.3±0.1 g/cm3

Solubility

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

Flash Point

197.2±23.6 °C

Boiling Point

540.0±50.0 °C at 760 mmHg

Melting Point

InChl

InChl Key

AZNAWXMYPBINIJ-KRWDZBQOSA-N

WGK Germany

RID/ADR

HS Code Reference

Personal Projective Equipment

Correct Usage

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

Meta Tag

provides coniferyl ferulate(CAS#:124858-37-3) 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

29761766

Abstract

A decade after the Global Malaria Eradication Program, El Salvador had the highest burden of malaria in Mesoamerica, with approximately 20% due to Plasmodium falciparum. A resurgence of malaria in the 1970s led El Salvador to alter its national malaria control strategy. By 1995, El Salvador recorded its last autochthonous P. falciparum case with fewer than 20 Plasmodium vivax cases annually since 2011. By contrast, its immediate neighbors continue to have the highest incidences of malaria in the region. We reviewed and evaluated the policies and interventions implemented by the Salvadoran National Malaria Program that likely contributed to this progress toward malaria elimination. Decentralization of the malaria program, early regional stratification by risk, and data-driven stratum-specific actions resulted in the timely and targeted allocation of resources for vector control, surveillance, case detection, and treatment. Weekly reporting by health workers and volunteer collaborators?distributed throughout the country by strata and informed via the national surveillance system?enabled local malaria teams to provide rapid, adaptive, and focalized program actions. Sustained investments in surveillance and response have led to a dramatic reduction in local transmission, with most current malaria cases in El Salvador due to importation from neighboring countries. Additional support for systematic elimination efforts in neighboring countries would benefit the region and may be needed for El Salvador to achieve and maintain malaria elimination. El Salvador’s experience provides a relevant case study that can guide the application of similar strategies in other countries committed to malaria elimination.

Title

Factors Associated with the Rapid and Durable Decline in Malaria Incidence in El Salvador, 1980-2017

Author

Robert A. Burton,1 Jose Eduardo Romero Chevez,2 Mauricio Sauerbrey,3 Caterina Guinovart,4 Angela Hartley,5 Geoffrey Kirkwood,5 Matthew Boslego,5 Mirna Elizabeth Gavidia,2 Jaime Enrique Aleman Escobar,2 Rachel Turkel,5 Richard W. Steketee,5 Laurence Slutsker,5 Kammerle Schneider,5,* and Carlos C. (Kent) Campbell5

Publish date

2018 Jul;

PMID

31565573

Abstract

Chromatin contacts between regulatory elements are of crucial importance for the interpretation of transcriptional regulation and the understanding of disease mechanisms. However, existing computational methods mainly focus on the prediction of interactions between enhancers and promoters, leaving enhancer-enhancer (E-E) interactions not well explored. In this work, we develop a novel deep learning approach, named Enhancer-enhancer contacts prediction (EnContact), to predict E-E contacts using genomic sequences as input. We statistically demonstrated the predicting ability of EnContact using training sets and testing sets derived from HiChIP data of seven cell lines. We also show that our model significantly outperforms other baseline methods. Besides, our model identifies finer-mapping E-E interactions from region-based chromatin contacts, where each region contains several enhancers. In addition, we identify a class of hub enhancers using the predicted E-E interactions and find that hub enhancers tend to be active across cell lines. We summarize that our EnContact model is capable of predicting E-E interactions using features automatically learned from genomic sequences

KEYWORDS

Deep learning, HiChIP data, Attention-based RNN, Hub enhancers, Enhancer-enhancer contacts

Title

EnContact: predicting enhancer-enhancer contacts using sequence-based deep learning model

Author

Mingxin Gan,#1 Wenran Li,#2,3,4 and Rui Jiangcorresponding author2

Publish date

2019

PMID

31620145

Abstract

The world’s herbaria collectively house millions of diverse plant specimens, including endangered or extinct species and type specimens. Unlocking genetic data from the typically highly degraded DNA obtained from herbarium specimens was difficult until the arrival of high-throughput sequencing approaches, which can be applied to low quantities of severely fragmented DNA. Target enrichment involves using short molecular probes that hybridise and capture genomic regions of interest for high-throughput sequencing. In this study on herbariomics, we used this targeted sequencing approach and the Angiosperms353 universal probe set to recover up to 351 nuclear genes from 435 herbarium specimens that are up to 204 years old and span the breadth of angiosperm diversity. We show that on average 207 genes were successfully retrieved from herbarium specimens, although the mean number of genes retrieved and target enrichment efficiency is significantly higher for silica gel-dried specimens. Forty-seven target nuclear genes were recovered from a herbarium specimen of the critically endangered St Helena boxwood, Mellissia begoniifolia, collected in 1815. Herbarium specimens yield significantly less high-molecular-weight DNA than silica gel-dried specimens, and genomic DNA quality declines with sample age, which is negatively correlated with target enrichment efficiency. Climate, taxon-specific traits, and collection strategies additionally impact target sequence recovery. We also detected taxonomic bias in targeted sequencing outcomes for the 10 most numerous angiosperm families that were investigated in depth. We recommend that (1) for species distributed in wet tropical climates, silica gel-dried specimens should be used preferentially; (2) for species distributed in seasonally dry tropical climates, herbarium and silica gel-dried specimens yield similar results, and either collection can be used; (3) taxon-specific traits should be explored and established for effective optimisation of taxon-specific studies using herbarium specimens; (4) all herbarium sheets should, in future, be annotated with details of the preservation method used; (5) long-term storage of herbarium specimens should be in stable, low-humidity, and low-temperature environments; and (6) targeted sequencing with universal probes, such as Angiosperms353, should be investigated closely as a new approach for DNA barcoding that will ensure better exploitation of herbarium specimens than traditional Sanger sequencing approaches.

KEYWORDS

angiosperms, herbarium specimens, degraded DNA, genomics, high-throughput sequencing, target enrichment, DNA barcoding, herbariomics

Title

Factors Affecting Targeted Sequencing of 353 Nuclear Genes From Herbarium Specimens Spanning the Diversity of Angiosperms

Author

Grace E. Brewer, 1 , * , † James J. Clarkson, 1 , * , † Olivier Maurin, 1 , * , † Alexandre R. Zuntini, 1 , * , † Vanessa Barber, 1 Sidonie Bellot, 1 Nicola Biggs, 1 Robyn S. Cowan, 1 Nina M. J. Davies, 1 Steven Dodsworth, 2 Sara L. Edwards, 1 Wolf L. Eiserhardt, 1 , 3 Niroshini Epitawalage, 1 Sue Frisby, 1 Aurelie Grall, 1 Paul J. Kersey, 1 Lisa Pokorny, 1 , 4 Ilia J. Leitch, 1 Felix Forest, 1 , ‡ and William J. Baker 1 , ‡

Publish date

2019;