Glycerophospho-N-Arachidonoyl Ethanolamine
(Synonyms: Glycerophosphoanandamide, GlycerophosphoArachidonoyl Ethanolamide, GPNArE) 目录号 : GC43774
Precursor of anandamide
Cas No.:201738-25-2
Sample solution is provided at 25 µL, 10mM.
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Quality Control & SDS
- View current batch:
- Purity: >97.00%
- COA (Certificate Of Analysis)
- SDS (Safety Data Sheet)
- Datasheet
N-Acylated ethanolamines (NAE) are naturally-occurring lipids that have diverse bioactivities. The different types of NAE can be derived from glycerophospho-linked precursors by the activity of glycerophosphodiesterase 1 (GDE1). Glycerophospho-N-arachidonoyl ethanolamine is the precursor of arachidonoyl ethanolamide (AEA), also known as anandamide. AEA is an endogenous cannabinoid neurotransmitter that binds to both central cannabinoid (CB1) and peripheral cannabinoid (CB2) receptors. It inhibits the specific binding of [3H]-HU-243 to synaptosomal membranes with a Ki value of 52 nM, compared to 46 nM for δ9-THC.
| Cas No. | 201738-25-2 | SDF | |
| 别名 | Glycerophosphoanandamide, GlycerophosphoArachidonoyl Ethanolamide, GPNArE | ||
| Canonical SMILES | CCCCC/C=C\C/C=C\C/C=C\C/C=C\CCCC(=O)NCCOP(=O)(O)OCC(O)CO | ||
| 分子式 | C25H44NO7P | 分子量 | 501.6 |
| 溶解度 | DMF: 20 mg/ml,DMSO: 20 mg/ml,PBS (pH 7.2): 10 mg/ml | 储存条件 | Store at -20°C |
| General tips | 请根据产品在不同溶剂中的溶解度选择合适的溶剂配制储备液；一旦配成溶液，请分装保存，避免反复冻融造成的产品失效。 储备液的保存方式和期限：-80°C 储存时，请在 6 个月内使用，-20°C 储存时，请在 1 个月内使用。 为了提高溶解度，请将管子加热至37℃，然后在超声波浴中震荡一段时间。 |
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| Shipping Condition | 评估样品解决方案：配备蓝冰进行发货。所有其他可用尺寸：配备RT，或根据请求配备蓝冰。 | ||
| 制备储备液 | |||
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1 mg | 5 mg | 10 mg |
| 1 mM | 1.9936 mL | 9.9681 mL | 19.9362 mL |
| 5 mM | 0.3987 mL | 1.9936 mL | 3.9872 mL |
| 10 mM | 0.1994 mL | 0.9968 mL | 1.9936 mL |
| 第一步：请输入基本实验信息（考虑到实验过程中的损耗，建议多配一只动物的药量） | ||||||||||
| 给药剂量 | mg/kg |  |
动物平均体重 | g | |
每只动物给药体积 | ul | |
动物数量 | 只 |
| 第二步：请输入动物体内配方组成（配方适用于不溶于水的药物；不同批次药物配方比例不同，请联系GLPBIO为您提供正确的澄清溶液配方） | ||||||||||
| % DMSO % % Tween 80 % saline | ||||||||||
| 计算重置 | ||||||||||
计算结果:
工作液浓度： mg/ml；
DMSO母液配制方法： mg 药物溶于 μL DMSO溶液（母液浓度 mg/mL，
体内配方配制方法：取 μL DMSO母液，加入 μL PEG300，混匀澄清后加入μL Tween 80，混匀澄清后加入 μL saline，混匀澄清。
1. 首先保证母液是澄清的；
2.
一定要按照顺序依次将溶剂加入，进行下一步操作之前必须保证上一步操作得到的是澄清的溶液，可采用涡旋、超声或水浴加热等物理方法助溶。
3. 以上所有助溶剂都可在 GlpBio 网站选购。
Serum Metabonomics Reveals Key Metabolites in Different Types of Childhood Short Stature
Front Pharmacol 2022 May 5;13:818952.PMID:35600884DOI:10.3389/fphar.2022.818952.
Nowadays, short stature (SS) in childhood is a common condition encountered by pediatricians, with an increase in not just a few families. Various studies related to the variations in key metabolites and their biological mechanisms that lead to SS have increased our understanding of the pathophysiology of the disease. However, little is known about the role of metabolite variation in different types of childhood SS that influence these biological processes and whether the understanding of the key metabolites from different types of childhood SS would predict the disease progression better. We performed a systematic investigation using the metabonomics method and studied the correlation between the three groups, namely, the control, idiopathic short stature (ISS), and short stature due to growth hormone deficiency (GHD). We observed that three pathways (viz., purine metabolism, sphingolipid signaling pathway, and sphingolipid metabolism) were significantly enriched in childhood SS. Moreover, we reported that two short peptides (Thr Val Leu Thr Ser and Trp Ile Lys) might play a significant role in childhood SS. Various metabolites in different pathways including 9,10-DiHOME, 12-HETE, 12(13)-EpOME, arachidonic acid methyl ester, Glycerophospho-N-Arachidonoyl Ethanolamine, curvulinic acid (2-acetyl-3,5-dihydroxyphenyl acetic acid), nonanoic acid, and N'-(2,4-dimethylphenyl)-N-methylformamidine in human serum were compared between 60 children diagnosed with SS and 30 normal-height children. More investigations in this area may provide insights and enhance the personalized treatment approaches in clinical practice for SS by elucidating pathophysiology mechanisms of experimental verification.
Biomarker identification and pathway analysis by serum metabolomics of lung cancer
Biomed Res Int 2015;2015:183624.PMID:25961003DOI:10.1155/2015/183624.
Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top altered pathways for analysis and visualization. We constructed a diagnostic model using potential serum biomarkers from patients with lung cancer. We assessed their specificity and sensitivity according to the area under the curve of the receiver operator characteristic (ROC) curves, which could be used to distinguish patients with lung cancer from normal subjects. The pathway analysis indicated that sphingolipid metabolism was the top altered pathway in lung cancer. ROC curve analysis indicated that Glycerophospho-N-Arachidonoyl Ethanolamine (GpAEA) and sphingosine were potential sensitive and specific biomarkers for lung cancer diagnosis and prognosis. Compared with the traditional lung cancer diagnostic biomarkers carcinoembryonic antigen and cytokeratin 19 fragment, GpAEA and sphingosine were as good or more appropriate for detecting lung cancer. We report our identification of potential metabolic diagnostic and prognostic biomarkers of lung cancer and clarify the metabolic alterations in lung cancer.
Modified Jiu Wei Qiang Huo decoction improves dysfunctional metabolomics in influenza A pneumonia-infected mice
Biomed Chromatogr 2014 Apr;28(4):468-74.PMID:24132661DOI:10.1002/bmc.3055.
In order to study the effective mechanism of a traditional Chinese medicine (TCM), modified Jiu Wei Qiang Huo decoction (MJWQH), against H1N1-induced pneumonia in mice, we chose a holistic approach. A reverse-phase liquid chromatography with quadruple time-of-flight mass spectrometry (LC-Q-TOF-MS) was developed to determine metabolomic biomarkers in mouse serum for the MJWQH effects. Thirteen biomarkers of H1N1-induced pneumonia in mice serum were identified, which comprised l-valine, lauroylcarnitine, palmitoyl-l-carnitine, l-ornithine, uric acid, taurine, O-succinyl-l-homoserine, l-leucine, l-phenylalanine, PGF2α, 20-ethyl-PGE2, arachidonic acid, and Glycerophospho-N-Arachidonoyl Ethanolamine. Among them, metabolites of amino acids, fatty acids and arachidonic acid had the most relevant changes in mice with H1N1-induced pneumonia. MJWQH effectively improved weight loss, lung index, biomarkers and inflammatory mediators such as prostaglandin E2 and phospholipase A2 in the infected mice. Importantly, MJWQH reversed the elevated biomarkers to the control levels from the infection, which provided a systematic view and a theoretical basis for its prevention or treatment. The results suggest that the protective effect of MJWQH against H1N1-induced pneumonia is possibly through regulation of pathways for amino acid, fatty acid and arachidonic acid metabolism. They also suggest that the LC-MS-based metabolomic strategy is a powerful tool for elucidation of the mechanisms of TCM.
Metabolomic profiling of human serum in lung cancer patients using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry
J Cancer Res Clin Oncol 2015 Apr;141(4):705-18.PMID:25293627DOI:10.1007/s00432-014-1846-5.
Purpose: Lung cancer is one of the most common causes of death from cancer. Serum markers that enable diagnosis of the disease in the early stage have not been found. Methods: Serum samples were collected from 30 healthy volunteers and from 30 lung cancer patients preoperatively and postoperatively. Samples were subjected to metabolomic analysis using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry. Differences in metabolomic profiles among the three groups were characterized by multivariate statistical techniques such as principal components analysis and partial least squares discriminant analysis (PLS-DA). An independent t test was used to determine whether levels of biomarker candidates identified using PLS-DA modeling were significantly different among groups at the univariate analysis level (p < 0.05). Results: Based on pattern recognition results and univariate analysis, we showed that levels of ten potential biomarkers in serum were significantly different in the preoperative lung cancer patients compared with healthy volunteers and/or the postoperative lung cancer patients. The levels of sphingosine, phosphorylcholine, Glycerophospho-N-Arachidonoyl Ethanolamine, γ-linolenic acid, 9,12-octadecadienoic acid, oleic acid, and serine were significantly different in preoperative lung cancer patients compared to healthy volunteers and to postoperative lung cancer patients. For prasterone sulfate, α-hydroxyisobutyric acid, 2,3,4-trihydroxybutyric acid, the levels were statistically different in preoperative and postoperative lung cancer patients compared with the healthy volunteers. Conclusions: Our study identified potential metabolic biomarkers for diagnosis of lung cancer.