Home>>Signaling Pathways>> Proteases>> Endogenous Metabolite>>3b-Hydroxy-5-cholenoic acid

3b-Hydroxy-5-cholenoic acid Sale

(Synonyms: 3B-羟基-D5-胆烯酸) 目录号 : GC31553

A bile acid

3b-Hydroxy-5-cholenoic acid Chemical Structure

Cas No.:5255-17-4

规格 价格 库存 购买数量
10mg
¥536.00
现货
50mg
¥1,339.00
现货

电话:400-920-5774 Email: sales@glpbio.cn

Customer Reviews

Based on customer reviews.

Sample solution is provided at 25 µL, 10mM.

产品文档

Quality Control & SDS

View current batch:

产品描述

Cholenic acid is a monohydroxy bile acid.1 It is a cholesterol oxidation product formed by 7α-hydroxylation of 27-hydroxycholesterol , as well as a precursor in the biosynthesis of chenodeoxycholic acid . Levels of cholenic acid are increased in patients with neonatal liver disease harboring mutations in CYP7A1, the gene encoding 7α-hydroxylase, as well as in patients with intrahepatic and extrahepatic cholestasis.2,3

1.Lee, C., Martin, K.O., and Javitt, N.B.Bile acid synthesis: 7α-Hydroxylation of intermediates in the sterol 27-hydroxylase metabolic pathwayJ. Lipid. Res.37(6)1356-1362(2006) 2.Setchell, K.D.R., Schwarz, M., O'Connell, N.C., et al.Identification of a new inborn error in bile acid synthesis: Mutation of the oxysterol 7α-hydroxylase gene causes severe neonatal liver diseaseJ. Clin. Invest.102(9)1690-1703(1998) 3.Sugiyama, K., Okuyama, S., Imoto, M., et al.Clinical evaluation of serum 3β-hydroxy-5-cholenoic acid in hepatobiliary diseaseGastroenterologia Japonica21(6)608-616(1986)

Chemical Properties

Cas No. 5255-17-4 SDF
别名 3B-羟基-D5-胆烯酸
Canonical SMILES C[C@H](CCC(O)=O)[C@H]1CC[C@@]2([H])[C@]3([H])CC=C4C[C@@H](O)CC[C@]4(C)[C@@]3([H])CC[C@]12C
分子式 C24H38O3 分子量 374.56
溶解度 Ethanol: 5 mg/mL (13.35 mM) 储存条件 Store at -20°C, protect from light
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。
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。

溶解性数据

制备储备液
1 mg 5 mg 10 mg
1 mM 2.6698 mL 13.349 mL 26.698 mL
5 mM 0.534 mL 2.6698 mL 5.3396 mL
10 mM 0.267 mL 1.3349 mL 2.6698 mL
  • 摩尔浓度计算器

  • 稀释计算器

  • 分子量计算器

质量
=
浓度
x
体积
x
分子量
 
 
 
*在配置溶液时,请务必参考产品标签上、MSDS / COA(可在Glpbio的产品页面获得)批次特异的分子量使用本工具。

计算

动物体内配方计算器 (澄清溶液)

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
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

Research Update

Identification of biomarkers and the mechanisms of multiple trauma complicated with sepsis using metabolomics

Sepsis after trauma increases the risk of mortality rate for patients in intensive care unit (ICUs). Currently, it is difficult to predict outcomes in individual patients with sepsis due to the complexity of causative pathogens and the lack of specific treatment. This study aimed to identify metabolomic biomarkers in patients with multiple trauma and those with multiple trauma accompanied with sepsis. Therefore, the metabolic profiles of healthy persons designated as normal controls (NC), multiple trauma patients (MT), and multiple trauma complicated with sepsis (MTS) (30 cases in each group) were analyzed with ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS)-based untargeted plasma metabolomics using collected plasma samples. The differential metabolites were enriched in amino acid metabolism, lipid metabolism, glycometabolism and nucleotide metabolism. Then, nine potential biomarkers, namely, acrylic acid, 5-amino-3-oxohexanoate, 3b-hydroxy-5-cholenoic acid, cytidine, succinic acid semialdehyde, PE [P-18:1(9Z)/16:1(9Z)], sphinganine, uracil, and uridine, were found to be correlated with clinical variables and validated using receiver operating characteristic (ROC) curves. Finally, the three potential biomarkers succinic acid semialdehyde, uracil and uridine were validated and can be applied in the clinical diagnosis of multiple traumas complicated with sepsis.

Alteration of Serum Metabolites in Women of Reproductive Age with Chronic Constipation

BACKGROUND Chronic constipation is a common gastrointestinal disease. Our previous studies confirmed that there are differences in the composition and function of gut microbiota between women of reproductive age with chronic constipation and healthy controls. However, little is known about the differences in the metabolic profile of the 2 groups. The aim of this study was to observe changes in serum metabolites and identify potential metabolic pathways in the development of chronic constipation. MATERIAL AND METHODS A total of 50 participants were included in this study: 25 female patients of childbearing age with chronic constipation who met the inclusion and exclusion criteria and 25 healthy participants as a control group. Serum samples of these participants were collected; 1 portion of the serum sample was used for clinical biochemical analysis, and the other was used for non-targeted metabolomic testing. RESULTS Compared with the control group, serum 2-hydroxyphenylacetic acid levels were higher (P<0.05) and DL-phenylalanine levels were lower (P<0.05) in the constipation group. Other amino acids, such as 5-hydroxy-l-lysine and l-pipecolic acid, were upregulated, and L-valine, glycine, L-leucyl-L-proline, and N-formylmethionine were downregulated in the constipation group. In addition, levels of the bile acid, 3b-hydroxy-5-cholenoic acid, were higher in the constipation group than in the control group. Pathway analysis showed that the significantly altered pathways were phenylalanine metabolism and glycine, serine, and threonine metabolism. CONCLUSIONS These results strongly suggest that serum metabolites and pathways are significantly altered in women of reproductive age with chronic constipation.

Integrative metagenomic and metabolomic analyses reveal the role of gut microbiota in antibody-mediated renal allograft rejection

Background: Antibody-mediated rejection (AMR) remains one of the major barriers for graft survival after kidney transplantation. Our previous study suggested a gut microbiota dysbiosis in kidney transplantation recipients with AMR. However, alternations in gut microbial function and structure at species level have not been identified. In the present study, we investigated the metagenomic and metabolic patterns of gut microbiota in AMR patients to provide a comprehensive and in-depth understanding of gut microbiota dysbiosis in AMR.
Methods: We enrolled 60 kidney transplantation recipients, 28 showed AMR and 32 were non-AMR controls with stable post-transplant renal functions. Shotgun sequencing and untargeted LC/MS metabolomic profiling of fecal samples were performed in kidney transplantation recipients with AMR and controls.
Results: Totally, we identified 311 down-regulated and 27 up-regulated gut microbial species associated with AMR after kidney transplantation, resulting in the altered expression levels of 437 genes enriched in 22 pathways, of which 13 were related to metabolism. Moreover, 32 differential fecal metabolites were found in recipients with AMR. Among them, alterations in 3b-hydroxy-5-cholenoic acid, L-pipecolic acid, taurocholate, and 6k-PGF1alpha-d4 directly correlated with changes in gut microbial species and functions. Specific differential fecal species and metabolites were strongly associated with clinical indexes (Cr, BUN, etc.), and could distinguish the recipients with AMR from controls as potential biomarkers.
Conclusions: Altogether, our findings provided a comprehensive and in-depth understanding of the correlation between AMR and gut microbiota, which is important for the etiological and diagnostic study of AMR after kidney transplantation.