Aldolase A _ ALDOA
- Known as:
- Aldolase A _ ALDOA
- Catalog number:
- AP06656PU-N
- Product Quantity:
- 100 µg
- Category:
- -
- Supplier:
- ACR
- Gene target:
- Aldolase _ ALDOA
Related genes to: Aldolase A _ ALDOA
- Gene:
- ALDOA NIH gene
- Name:
- aldolase, fructose-bisphosphate A
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 16p11.2
- Locus Type:
- gene with protein product
- Date approved:
- 1986-01-01
- Date modifiied:
- 2019-04-23
Related products to: Aldolase A _ ALDOA
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- Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide, which poses a severe threat to human health. COVID-19 is a systemic ailment affecting various tissues and organs, including the lungs and liver. Intrahepatic cholangiocarcinoma (ICC) is one of the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. Nonetheless, few studies have investigated the impact of COVID-19 on ICC patients. - Source: PubMed
Publication date: 2024/04/22
Zhou XinyiHuang TengdaPan HongyuanDu AoWu TianLan JiangSong YujiaLv YueHe FangYuan Kefei - Medial arterial calcification is a chronic systemic vascular disorder distinct from atherosclerosis and is commonly observed in patients with chronic kidney disease, diabetes, and aging individuals. We previously showed that NR4A3 (nuclear receptor subfamily 4 group A member 3), an orphan nuclear receptor, is a key regulator in apo (apolipoprotein) A-IV-induced atherosclerosis progression; however, its role in vascular calcification is poorly understood. - Source: PubMed
Publication date: 2024/04/17
Ma WenqiJia KangniCheng HaomaiXu HongLi ZhigangZhang HangXie HongyangZhuang LingfangWang ZiyangCui YukeSun HangYi LeiChen ZhiyongDuan ShengzhongSano MotoakiFukuda KeiichiLu LinGao FeiZhang RuiyanYan Xiaoxiang - Prostate cancer (PCa) is one of the most common malignancies in men with a poor prognosis. It is therefore of great clinical importance to find reliable prognostic indicators for PCa. Many studies have revealed the pivotal role of protein lactylation in tumor development and progression. This research aims to analyze the effect of lactylation-related genes on PCa prognosis. By downloading mRNA-Seq data of TCGA PCa, we obtained the differential genes related to lactylation in PCa. Five machine learning algorithms were used to screen for lactylation-related key genes for PCa, then the five overlapping key genes were used to construct a survival prognostic model by lasso cox regression analysis. Furthermore, the relationships between the model and related pathways, tumor mutation and immune cell subpopulations, and drug sensitivity were explored. Moreover, two risk groups were established according to the risk score calculated by the five lactylation-related genes (LRGs). Subsequently, a nomogram scoring system was established to predict disease-free survival (DFS) of patients by combining clinicopathological features and lactylation-related risk scores. In addition, the mRNA expression levels of five genes were verified in PCa cell lines by qPCR. We identified 5 key LRGs (ALDOA, DDX39A, H2AX, KIF2C, RACGAP1) and constructed the LRGs prognostic model. The AUC values for 1 -, 3 -, and 5-year DFS in the TCGA dataset were 0.762, 0.745, and 0.709, respectively. The risk score was found a better predictor of DFS than traditional clinicopathological features in PCa. A nomogram that combined the risk score with clinical variables accurately predicted the outcome of the patients. The PCa patients in the high-risk group have a higher proportion of regulatory T cells and M2 macrophage, a higher tumor mutation burden, and a worse prognosis than those in the low-risk group. The high-risk group had a lower IC50 for certain chemotherapeutic drugs, such as Docetaxel, and Paclitaxel than the low-risk group. Furthermore, five key LRGs were found to be highly expressed in castration-resistant PCa cells. The lactylation-related genes prognostic model can effectively predict the DFS and therapeutic responses in patients with PCa. - Source: PubMed
Publication date: 2024/03/19
Pan JinyouZhang JianpengLin JingweiCai YinxinZhao Zhigang - Hepatitis E represents an emerging zoonotic disease caused by the Hepatitis E virus (HEV), for which the main route of transmission is foodborne. In particular, infection in humans has been associated with the consumption of contaminated undercooked meat of pig origin. The aim of this study was to apply comparative proteomics to determine if porcine liver protein profiles could be used to distinguish between pigs seropositive and seronegative for HEV. Preliminarily, an ELISA was used to evaluate the presence of anti-HEV antibodies in the blood serum of 136 animals sent to slaughter. Among the analyzed samples, a seroprevalence of 72.8% was estimated, and it was also possible to identify 10 animals, 5 positive and 5 negative, coming from the same farm. This condition created the basis for the quantitative proteomics comparison between homogeneous animals, in which only the contact with HEV should represent the discriminating factor. The analysis of the proteome in all samples of liver exudate led to the identification of 554 proteins differentially expressed between the two experimental groups, with 293 proteins having greater abundance in positive samples and 261 more represented in negative exudates. The pathway enrichment analysis allowed us to highlight the effect of the interaction between HEV and the host biological system in inducing the potential enrichment of 69 pathways. Among these, carbon metabolism stands out with the involvement of 41 proteins, which were subjected to interactomic analysis. This approach allowed us to focus our attention on three enzymes involved in glycolysis: glucose-6-phosphate isomerase (GPI), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and fructose-bisphosphate aldolase A (ALDOA). It therefore appears that infection with HEV induced a strengthening of the process, which involves the breakdown of glucose to obtain energy and carbon residues useful for the virus's survival. In conclusion, the label-free LC-MS/MS approach showed effectiveness in highlighting the main differences induced on the porcine liver proteome by the interaction with HEV, providing crucial information in identifying a viral signature on the host metabolism. - Source: PubMed
Publication date: 2024/03/06
Martino CamilloDi Luca AlessioBennato FrancescaIanni AndreaPassamonti FabrizioRampacci ElisaHenry MichaelMeleady PaulaMartino Giuseppe - Colorectal cancer (CRC) is one of the most common malignant tumors of the digestive tract and a leading cause of cancer-related death worldwide. Since many CRC patients are diagnosed already in the advanced stage, and traditional chemoradiotherapy is prone to drug resistance, it is important to find new therapeutic targets. In this study, the expression levels of ALDOA and p-AKT were detected in cancer tissues and paired normal tissues, and it was found that they were significantly increased in CRC tissues, and their high expression indicated poor prognosis. Moreover, a positive correlation between the expression of ALDOA and p-AKT was found in CRC tissues and paired normal tissues. In addition, the Kaplan-Meier analysis revealed that the group with both negative of ALDOA/p-AKT expression had longer five-year survival rates compared with the other group. Besides, the group with both high expression of ALDOA/p-AKT had a worse prognosis compared with the other group. Based on the expression of ALDOA and p-AKT in tumor tissues, we can effectively distinguish tumor tissues from normal tissues through cluster analysis. Furthermore, we constructed nomograms to predict 3-year and 5-year overall survival, showing that the expression of ALDOA/p-AKT plays a crucial role in predicting the prognosis of CRC patients. Therefore, ALDOA/p-AKT may act as a crucial role in CRC, which may provide new horizons for targeted therapies for CRC. - Source: PubMed
Publication date: 2024/03/18
Xu MenglinXi ShihangLi HaoranXia YongMei GuangliangCheng Zhengwu