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D-(+)-Lactose Monohydrate

$52

  • Brand : BIOFRON

  • Catalogue Number : BD-P0279

  • Specification : 98.0%(HPLC)

  • CAS number : 64044-51-5

  • Formula : C12H24O12

  • Molecular Weight : 360.312

  • Volume : 100mg

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Catalogue Number

BD-P0279

Analysis Method

HPLC,NMR,MS

Specification

98.0%(HPLC)

Storage

2-8°C

Molecular Weight

360.312

Appearance

powder

Botanical Source

Structure Type

Carbohydrates

Category

SMILES

Synonyms

IUPAC Name

Applications

Density

1.525

Solubility

Flash Point

462.7ºC

Boiling Point

841.4ºC at 760 mmHg

Melting Point

~215 °C (dec.)

InChl

InChl Key

WGK Germany

RID/ADR

HS Code Reference

2940000000

Personal Projective Equipment

Correct Usage

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

Meta Tag

provides coniferyl ferulate(CAS#:64044-51-5) 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

31711568

Abstract

While the rare occurrence of child loss is accompanied by reduced life expectancy of parents in contemporary affluent populations, its impact in developing societies with high child mortality rates is unclear. We identified all parents in Iceland born 1800-1996 and compared the mortality rates of 47,711 parents who lost a child to those of their siblings (N = 126,342) who did not. The proportion of parents who experienced child loss decreased from 61.1% of those born 1800-1880 to 5.2% of those born after 1930. Child loss was consistently associated with increased rate of maternal, but not paternal, death before the age of 50 across all parent birth cohorts; the relative increase in maternal mortality rate ranged from 35% among mothers born 1800-1930 to 64% among mothers born after 1930. The loss of a child poses a threat to the survival of young mothers, even during periods of high infant mortality rates.

Research organism: Human

Title

The mother’s risk of premature death after child loss across two centuries

Author

Unnur A Valdimarsdottir,#1,2,3,† Donghao Lu,#1,2,3,4,† Sigrún H Lund,5 Katja Fall,3,6 Fang Fang,3 Þorður Kristjansson,5 Daniel Guðbjartsson,5,7 Agnar Helgason,#5,8,‡ and Kari Stefansson#5,9,‡ M Dawn Teare, Reviewing Editor and Eduardo Franco, Senior Editor M Dawn Teare, Newcastle University, United Kingdom; Contributor Information.

Publish date

2019;

PMID

29951245

Abstract

The solid-state structures of two metal-pyridine-sulfate compounds, namely catena-poly[[tetra­kis­(pyridine-κN)iron(II)]-μ-sulfato-κ2 O:O′], [Fe(SO4)(C5H5N)4]n, (1), and catena-poly[[tetra­kis­(pyridine-κN)cobalt(II)]-μ-sulfato-κ2 O:O′-[tetra­kis­(pyridine-κN)cobalt(II)]-μ-sulfato-κ3 O,O′:O′′-[tris­(pyridine-κN)cobalt(II)]-μ-sulfato-κ2 O:O′], [Co3(SO4)3(C5H5N)11]n, (2), are reported. The iron compound (1) displays a polymeric structure, with infinite chains of FeII atoms adopting octa­hedral N4O2 coordination environments that involve four pyridine ligands and two bridging sulfate ligands. The cobalt compound (2) displays a polymeric structure, with infinite chains of CoII atoms. Two of the three Co centers have an octa­hedral N4O2 coordination environment that involves four pyridine ligands and two bridging sulfate ligands. The third Co center has an octa­hedral N3O3 coordination environment that involves three pyridine ligands, and two bridging sulfate ligands with one sulfate chelating the cobalt atom.

KEYWORDS

crystal structure, pyridine, sulfate, transition metals, crystal field theory, coordination chemistry

Title

The crystal structures of iron and cobalt pyridine (py)-sulfates, [Fe(SO4)(py)4]n and [Co3(SO4)3(py)11]n

Author

Duyen N. K. Pham,a Mrittika Roy,a Ava Kreider-Mueller,a James A. Golen,a and David R. Mankea,*

Publish date

2018 Jun 1;

PMID

21057720

Abstract

Objective
To evaluate the effectiveness of a Lexico-Syntactic Pattern (LSP) matching method for ontology enrichment using clinical documents.

Methods
Two domains were separately studied using the same methodology. We used radiology documents to enrich RadLex and pathology documents to enrich National Cancer Institute Thesaurus (NCIT). Several known LSPs were used for semantic knowledge extraction. We first retrieved all sentences that contained LSPs across two large clinical repositories, and examined the frequency of the LSPs. From this set, we randomly sampled LSP instances which were examined by human judges. We used a two-step method to determine the utility of these patterns for enrichment. In the first step, domain experts annotated Medically Meaningful Terms (MMTs) from each sentence within the LSP. In the second step, RadLex and NCIT curators evaluated how many of these MMTs could be added to the resource. To quantify the utility of this LSP method, we defined two evaluation metrics: Suggestion Rate (SR) and Acceptance Rate (AR). We used these measures to estimate the yield of concepts and relationships, for each of the two domains.

Results
For NCIT, the concept SR was 24%, and the relationship SR was 65%. The concept AR was 21%, and the relationship AR was 14%. For RadLex, the concept SR was 37%, and the relationship SR was 55%. The concept AR was 11%, and the relationship AR was 44%.

Conclusion
The LSP matching method is an effective method for concept and concept relationship discovery in biomedical domains.

KEYWORDS

Ontology Learning from Text, Knowledge Acquisition, Ontology Enrichment, Natural Language Processing, Lexico-Syntactic Pattern

Title

Effectiveness of Lexico-Syntactic Pattern Matching for Ontology Enrichment with Clinical Documents

Author

K. Liu, MD, MS,1 W.W. Chapman, PhD,1,2 G. Savova, PhD,3 C.G. Chute, MD, Dr.PH,3 N. Sioutos, MD,4 and R.S. Crowley, MD, MS1,2,5

Publish date

2011 Oct 25.