Fmoc-Aeg-OtBu HCl
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Fmoc-Aeg-OtBu HCl

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A backbone for PNA synthesis.

Category
Fmoc-Amino Acids
Catalog number
BAT-003644
CAS number
169396-88-7
Molecular Formula
C23H28N2O4·HCl
Molecular Weight
432.95
Fmoc-Aeg-OtBu HCl
IUPAC Name
tert-butyl 2-[2-(9H-fluoren-9-ylmethoxycarbonylamino)ethylamino]acetate;hydrochloride
Synonyms
N-[2-(Fmoc-amino)-ethyl]-Gly-OtBu HCl; tert-Butyl[2-(Fmoc-amino)ethylamino]acetate hydrochloride; N-[2-(Fmoc-amino)-ethyl]glycine tert-butylester hydrochloride; tert-Butyl [2-(Fmoc-amino)ethylamino]acetate hydrochloride; N-[2-(FMOC-AMINO)-ETHYL]-GLY-O-TBU HCl
Appearance
White to Off-white Powder
Purity
98%
Boiling Point
582.5 °C at 760 mmHg
Storage
-20°C for long term storage
InChI
InChI=1S/C23H28N2O4.ClH/c1-23(2,3)29-21(26)14-24-12-13-25-22(27)28-15-20-18-10-6-4-8-16(18)17-9-5-7-11-19(17)20;/h4-11,20,24H,12-15H2,1-3H3,(H,25,27);1H
InChI Key
LVIQOMHZCMGMIG-UHFFFAOYSA-N
Canonical SMILES
CC(C)(C)OC(=O)CNCCNC(=O)OCC1C2=CC=CC=C2C3=CC=CC=C13.Cl
1. Biology and Treatment of Hairy Cell Leukemia
Jérôme Paillassa, Xavier Troussard Curr Treat Options Oncol. 2020 Apr 30;21(6):44. doi: 10.1007/s11864-020-00732-0.
Despite its rarity, hairy cell leukemia (HCL) remains a fascinating disease and the physiopathology is becoming more and more understood. The accurate diagnosis of HCL relies on the recognition of hairy cells by morphology and flow cytometry (FCM) in the blood and/or bone marrow (BM). The BRAF V600E mutation, an HCL-defining mutation, represents a novel diagnostic parameter and a potential therapeutic target. The precise cellular origin of HCL is a late-activated postgerminal center memory B cell. BRAF mutations were detected in hematopoietic stem cells (HSCs) of patients with HCL, suggesting that this is an early HCL-defining event. Watch-and-wait strategy is necessary in approximately 10% of asymptomatic HCL patients, sometimes for several years. Purine analogs (PNAs) are the established first-line options for symptomatic HCL patients. In second-line treatment, chemoimmunotherapy combining PNA plus rituximab should be considered in high-risk HCL patients. The three options for relapsed/refractory HCL patients include recombinant immunoconjugates targeting CD22, BRAF inhibitors, and BCR inhibitors. The clinical interest to investigate blood minimal residual disease (MRD) was recently demonstrated, with a high risk of relapse in patients with positive testing for MRD and a low risk in patients with negative testing. However, efforts must be made to standardize MRD analyses in the near future. Patients with HCL are at risk of second malignancies. The increased risk could be related to the disease and/or the treatment, and the respective role of PNAs in the development of secondary malignancies remains a topic of debate.
2. Standardized Hybrid Closed-Loop System Reporting
Viral N Shah, Satish K Garg Diabetes Technol Ther. 2021 May;23(5):323-331. doi: 10.1089/dia.2020.0622. Epub 2020 Nov 25.
The hybrid closed-loop (HCL) system has been shown to improve glycemic control and reduce hypoglycemia. Optimization of HCL settings requires interpretation of the glucose, insulin, and factors affecting glucose such as food intake and exercise. To the best of our knowledge, there is no published guidance on the standardized reporting of HCL systems. Standardization of HCL reporting would make interpretation of data easy across different systems. We reviewed the literature on patient and provider perspectives on downloading and reporting glucose metric preferences. We also incorporated international consensus on standardized reporting for glucose metrics. We describe a single-page HCL data reporting, referred to here as "artificial pancreas (AP) Dashboard." We propose seven components in the AP Dashboard that can provide detailed information and visualization of glucose, insulin, and HCL-specific metrics. The seven components include (A) glucose metrics, (B) hypoglycemia, (C) insulin, (D) user experience, (E) hyperglycemia, (F) glucose modal-day profile, and (G) insight. A single-page report similar to an electrocardiogram can help providers and patients interpret HCL data easily and take the necessary steps to improve glycemic outcomes. We also describe the optimal sampling duration for HCL data download and color coding for visualization ease. We believe that this is a first step in creating a standardized HCL reporting, which may result in better uptake of the systems. For increased adoption, standardized reporting will require input from providers, patients, diabetes device manufacturers, and regulators.
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