Hexadecyl Acetyl Glycerol
(Synonyms: HAG) 目录号 : GC40413An analog of DAG
Cas No.:77133-35-8
Sample solution is provided at 25 µL, 10mM.
Quality Control & SDS
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- Purity: >90.00%
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- SDS (Safety Data Sheet)
- Datasheet
Hexadecyl acetyl glycerol (HAG) is an analog of DAG, which inhibits the activation of PKC by DAG. It also inhibits the growth of HL-60 cells and induces differentiation to cells resembling mononuclear phagocytes. Following treatment with 5 µg/ml HAG for six days, HL-60 cells demonstrated a 10-fold increase in non-specific esterase activity.
Cas No. | 77133-35-8 | SDF | |
别名 | HAG | ||
Canonical SMILES | CCCCCCCCCCCCCCCCOC[C@H](CO)OC(=O)C | ||
分子式 | C21H42O4 | 分子量 | 358.6 |
溶解度 | DMSO: 10 mg/ml,Ethanol: Miscible,PBS (pH 7.2): ~150 µ g/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 | |||
1 mg | 5 mg | 10 mg | |
1 mM | 2.7886 mL | 13.9431 mL | 27.8862 mL |
5 mM | 0.5577 mL | 2.7886 mL | 5.5772 mL |
10 mM | 0.2789 mL | 1.3943 mL | 2.7886 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。
Metabolomics Profiling Discriminates Prostate Cancer From Benign Prostatic Hyperplasia Within the Prostate-Specific Antigen Gray Zone
Front Oncol 2021 Oct 15;11:730638.PMID:34722271DOI:10.3389/fonc.2021.730638.
Objective: Prostate cancer (PCa) is the second most common male malignancy globally. Prostate-specific antigen (PSA) is an important biomarker for PCa diagnosis. However, it is not accurate in the diagnostic gray zone of 4-10 ng/ml of PSA. In the current study, the performance of serum metabolomics profiling in discriminating PCa patients from benign prostatic hyperplasia (BPH) individuals with a PSA concentration in the range of 4-10 ng/ml was explored. Methods: A total of 220 individuals, including patients diagnosed with PCa and BPH within PSA levels in the range of 4-10 ng/ml and healthy controls, were enrolled in the study. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomics method was utilized to characterize serum metabolic profiles of participants. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods were used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic value of candidate metabolites in differentiating PCa from BPH. Correlation analysis was conducted to explore the relationship between serum metabolites and common clinically used fasting lipid profiles. Results: Several differential metabolites were identified. The top enriched pathways in PCa subjects such as glycerophospholipid and glycerolipid metabolisms were associated with lipid metabolism. Lipids and lipid-like compounds were the predominant metabolites within the top 50 differential metabolites selected using fold-change threshold >1.5 or <2/3, variable importance in projection (VIP) > 1, and Student's t-test threshold p < 0.05. Eighteen lipid or lipid-related metabolites were selected including 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, dl-dihydrosphingosine, 2-methoxy-6Z-hexadecenoic acid, 3-oxo-nonadecanoic acid, 2-hydroxy-nonadecanoic acid, N-palmitoyl glycine, 2-palmitoylglycerol, hexadecenal, d-erythro-sphingosine C-15, N-methyl arachidonoyl amine, 9-octadecenal, Hexadecyl Acetyl Glycerol, 1-(9Z-pentadecenoyl)-2-eicosanoyl-glycero-3-phosphate, 3Z,6Z,9Z-octadecatriene, and glycidyl stearate. Selected metabolites effectively discriminated PCa from BPH when PSA levels were in the range of 4-10 ng/ml (area under the curve (AUC) > 0.80). Notably, the 18 identified metabolites were negatively corrected with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and Apo-B levels in PCa patients; and some were negatively correlated with high-density lipoprotein cholesterol (HDL-C) and Apo-A levels. However, the metabolites were not correlated with triglycerides (TG). Conclusion: The findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism, is a key signature of PCa. The 18 lipid or lipid-associated metabolites identified in this study are potential diagnostic markers for differential diagnosis of PCa patients and BPH individuals within a PSA level in the gray zone of 4-10 ng/ml.