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I2765

Sigma-Aldrich

鹅膏氨酸

~95% (TLC), solid, neurotoxin

同義詞:

α-氨基-3-羟基-5-异噁唑乙酸

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About This Item

經驗公式(希爾表示法):
C5H6N2O4
CAS號碼:
分子量::
158.11
MDL號碼:
分類程式碼代碼:
12352209
PubChem物質ID:
NACRES:
NA.32

product name

鹅膏氨酸, ~95%, solid

化驗

~95%

形狀

solid

顏色

white

溶解度

H2O: 1 mg/mL, clear, colorless (with sonication)
0.1 M NaOH: 10.7 mg/mL
0.1 M HCl: 4.7 mg/mL

SMILES 字串

NC(C(O)=O)C1=CC(=O)NO1

InChI

1S/C5H6N2O4/c6-4(5(9)10)2-1-3(8)7-11-2/h1,4H,6H2,(H,7,8)(H,9,10)

InChI 密鑰

IRJCBFDCFXCWGO-UHFFFAOYSA-N

基因資訊

尋找類似的產品? 前往 產品比較指南

應用

鹅膏蕈氨酸作为神经毒素用于大鼠。也可用于诱导猴大脑皮层M1神经元发生原发永久性病变。
鹅膏蕈氨酸被用于成年雄性斑胸草雀 ( Taeniopygia guttata ) 手术,以研究逆转增强剂诱导的发声变化。

生化/生理作用

对NMDA谷氨酸受体优先选择的非选择性激动剂;神经毒素。神经兴奋性氨基酸最初分离自鹅膏菌种。
鹅膏蕈氨酸是谷氨酸类似物。参与兴奋细胞体,破坏丘脑网状核(NRT)。它能诱导大量钙离子流入,导致神经元损伤。由于其具有兴奋性毒性功能,鹅膏蕈氨酸用于诱导产生神经退行性变。

注意

吸湿

象形圖

Skull and crossbones

訊號詞

Danger

危險聲明

防範說明

危險分類

Acute Tox. 3 Oral

儲存類別代碼

6.1C - Combustible acute toxic Cat.3 / toxic compounds or compounds which causing chronic effects

水污染物質分類(WGK)

WGK 3

閃點(°F)

Not applicable

閃點(°C)

Not applicable

個人防護裝備

Eyeshields, Faceshields, Gloves, type P2 (EN 143) respirator cartridges


分析證明 (COA)

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Su-Rong Yang et al.
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Frontiers in Molecular Neuroscience, 9, 28-28 (2016)
Loïc J Chareyron et al.
Brain structure & function, 222(9), 3899-3914 (2017-05-11)
Hippocampal damage in adult humans impairs episodic and semantic memory, whereas hippocampal damage early in life impairs episodic memory but leaves semantic learning relatively preserved. We have previously shown a similar behavioral dissociation in nonhuman primates. Hippocampal lesion in adult
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eLife, 7 (2018-07-26)
Speech is a complex sensorimotor skill, and vocal learning involves both the basal ganglia and the cerebellum. These subcortical structures interact indirectly through their respective loops with thalamo-cortical and brainstem networks, and directly via subcortical pathways, but the role of
Samuel A Neymotin et al.
Journal of neuroscience methods, 275, 1-9 (2016-10-18)
Correlated neuronal activity in the brain is hypothesized to contribute to information representation, and is important for gauging brain dynamics in health and disease. Due to high dimensional neural datasets, it is difficult to study temporal variations in correlation structure.

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