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Merck

49161

D-(+)-Glucose monohydrate

tested according to Ph. Eur.

Synonym(s):

Dextrosum (Glucosum) monohydricum, Dextrose monohydrate

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About This Item

Empirical Formula (Hill Notation):
C6H12O6 · H2O
CAS Number:
14431-43-7
Molecular Weight:
198.17
UNSPSC Code:
12352201
NACRES:
NA.21
PubChem Substance ID:
329757441
EC Number:
218-914-5
Beilstein/REAXYS Number:
5250278
MDL number:
MFCD00149450

Key Documents

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Quality Level

200

agency

tested according to Ph. Eur.

assay

97.5-102.0% anhydrous basis (HPLC)

form

powder

color

white

SMILES string

O.OC[C@@H](O)[C@@H](O)[C@H](O)[C@@H](O)C=O

InChI

1S/C6H12O6.H2O/c7-1-3(9)5(11)6(12)4(10)2-8;/h1,3-6,8-12H,2H2;1H2/t3-,4+,5+,6+;/m0./s1

InChI key

SPFMQWBKVUQXJV-BTVCFUMJSA-N

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Application


  • Effects of mammalian blood with different glucose levels on reproduction, growth and survival of the southern medicinal leech, Hirudo verbana Carena, 1820.: This study explores the effects of varying glucose levels in mammalian blood on the reproduction, growth, and survival of the medicinal leech. The research highlights the role of D-(+)-Glucose monohydrate in biological systems and its potential applications in aquaculture and biomedical research. (Karataş et al., 2022).

  • Evaluation of the variations in chemical and microbiological properties of the sourdoughs produced with selected lactic acid bacteria strains during fermentation.: This research evaluates the chemical and microbiological changes in sourdoughs fermented with specific lactic acid bacteria, with a focus on the role of D-(+)-Glucose monohydrate in the fermentation process. The findings are significant for the food industry, particularly in the production of high-quality sourdough bread. (Boyaci Gunduz et al., 2022).


Other Notes

To gain a comprehensive understanding of our extensive range of Monosaccharides for your research, we encourage you to visit our Carbohydrates Category page.

Storage Class

11 - Combustible Solids

flash_point_f

Not applicable

flash_point_c

Not applicable

ppe

Eyeshields, Gloves, type N95 (US)

Regulatory Listings

Regulatory Listings are mainly provided for chemical products. Only limited information can be provided here for non-chemical products. No entry means none of the components are listed. It is the user’s obligation to ensure the safe and legal use of the product.

49161-25KG: + 49161-BULK: + 49161-1KG: + 49161-VAR:

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Daphne H E W Huberts et al.
Proceedings of the National Academy of Sciences of the United States of America, 111(32), 11727-11731 (2014-07-30)
Calorie restriction (CR) is often described as the most robust manner to extend lifespan in a large variety of organisms. Hence, considerable research effort is directed toward understanding the mechanisms underlying CR, especially in the yeast Saccharomyces cerevisiae. However, the
Sweta Rathore et al.
Journal of microencapsulation, 31(5), 469-478 (2014-04-05)
This work evaluated the feasibility of microencapsulating Clostridium acetobutylicum ATCC 824 cells by emulsification for fermentation to produce biobutanol. The effects of selected emulsification process on viability of the vegetative cells and spores were investigated to enable the selection of
Jesper T Andreasen et al.
Brain research, 1601, 117-126 (2015-01-13)
Depression and anxiety often co-occur, and conventional monoamine-facilitating antidepressants show efficacy against symptoms in both disorders. Rodent studies indicate that antidepressant effects of monoamine-based antidepressants involve increased α-amino-3-hydroxy-5- methyl-4-isoxazolepropionic acid glutamate receptor (AMPAR) neurotransmission, and positive allosteric modulators (PAMs) at
Brooke Tata et al.
PLoS biology, 12(9), e1001952-e1001952 (2014-09-24)
Characterization of the genetic defects causing gonadotropic deficiency has made a major contribution to elucidation of the fundamental role of Kisspeptins and Neurokinin B in puberty onset and reproduction. The absence of puberty may also reveal neurodevelopmental disorders caused by
Jun Cheng et al.
Food chemistry, 168, 90-99 (2014-08-31)
The aim of this study was to investigate the applicability of artificial neural network (ANN) and multiple linear regression (MLR) models for the estimation of acrylamide reduction by flavonoids, using multiple antioxidant capacities of Maillard reaction products as variables via

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