Search for: levodopa
Design of a ratiometric fluorescence nanoprobe to detect plasma levels of levodopa, Article Microchemical Journal ; Volume 148 , 2019 , Pages 591-596 ; 0026265X (ISSN) ; Bigdeli, A ; Ghasemi, F ; Hormozi Nezhad, M. R ; Sharif University of Technology
Elsevier Inc 2019
Simply obtained by the oxidation of levodopa in alkaline media, polylevodopa nanoparticles are able to quench the fluorescence emission of CdTe quantum dots (QDs) via energy transfer mechanism. The extent of this quenching can be exploited for the quantification of levodopa, as an important therapeutic agent in the treatment of Parkinson's disease. However, to effectively improve the detection performance, in this study, we have designed a ratiometric probe by making use of variations in both the emission of QDs and the intrinsic emission of polylevodopa nanoparticles. The enhanced sensitivity, in particular, arose from the measurement of the ratio of fluorescence intensities at two...
A smartphone-based fluorescent electronic tongue for tracing dopaminergic agents in human urine, Article ACS Chemical Neuroscience ; Volume 12, Issue 17 , 2021 , Pages 3157-3166 ; 19487193 (ISSN) ; Bigdeli, A ; Hormozi Nezhad, M. R ; Sharif University of Technology
American Chemical Society 2021
The importance of tracing dopaminergic agents in the progression assessment of Parkinson's disease has boosted the demand for fast, sensitive, and real-time multi-analyte detection. Herein, visual and fingerprint fluorimetric patterns have been created by an optical sensor array to simultaneously detect and discriminate among levodopa, carbidopa, benserazide, and entacapone, as important dopaminergic agents. A dual emissive nanoprobe consisting of red quantum dots and blue carbon dots with an overall pink emission has been fabricated to provide unique emission patterns in the presence of the target analytes. The sensor elements in the array come from it's differential response in the absence...
Detection of L-Dopa Based on Fluorescent of levodopa Nanopolymers and CdTe Quantum Dots, M.Sc. Thesis Sharif University of Technology ; Hormozi Nezhad, Mohammad Reza
Levodopa [L-3, 4-dihydroxyphenylalanine, or L-DOPA] is an important neurotransmitter used for the treatment of neural disorders such as Parkinson’s disease. Abnormal L-Dopa concentrations in biological fluids can be used for evaluation of diseases such as Parkinson’s diseases. In the first part of this thesis, a rapid and sensitive method for levodopa detection was reported which is based on in situ formation of polylevodopa nanoparticles. The assay is very simple and low cost and uses only NaOH and HCl as reagents. Under alkaline conditions, levodopa is spontaneously oxidized to its quinone derivative and shows the fluorescence properties. The fluorescence signal of the oxidation product of...
Application of silver nanoparticles and principal component-artificial neural network models for simultaneous determination of levodopa and benserazide hydrochloride by a kinetic spectrophotometric method, Article Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy ; Volume 82, Issue 1 , November , 2011 , Pages 25-30 ; 13861425 (ISSN) ; Hormozi Nezhad, M. R ; Khodaveisi, J ; Sharif University of Technology
A multicomponent analysis method based on principal component analysis-artificial neural network model (PC-ANN) is proposed for the simultaneous determination of levodopa (LD) and benserazide hydrochloride (BH). The method is based on the reaction of levodopa and benserazide hydrochloride with silver nitrate as an oxidizing agent in the presence of PVP and formation of silver nanoparticles. The reaction monitored at analytical wavelength 440 nm related to surface plasmon resonance band of silver nanoparticles. Differences in the kinetic behavior of the levodopa and benserazide hydrochloride were exploited by using principal component analysis, an artificial neural network (PC-ANN) to resolve...
Modeling the Parkinson's tremor and its treatments, Article Journal of Theoretical Biology ; Volume 236, Issue 3 , 2005 , Pages 311-322 ; 00225193 (ISSN) ; Sarbaz, Y ; Gharibzadeh, S ; Sharif University of Technology
In this paper, we discuss modeling issues of the Parkinson's tremor. Through the work we have employed physiological structure as well as functioning of the parts in brain that are involved in the disease. To obtain more practical similarity, random behaviors of the connection paths are also considered. Medication or treatment of the disease both by drug prescription and electrical signal stimulation are modeled based on the same model introduced for the disease itself. Two new medication strategies are proposed based on the model to reduce the side effects caused by the present drug prescription. © 2005 Elsevier Ltd. All rights reserved
Identification of catecholamine neurotransmitters using fluorescence sensor array, Article Analytica Chimica Acta ; Volume 917 , 2016 , Pages 85-92 ; 00032670 (ISSN) ; Hormozi Nezhad, M. R ; Mahmoudi, M ; Sharif University of Technology
Elsevier B.V 2016
A nano-based sensor array has been developed for identification and discrimination of catecholamine neurotransmitters based on optical properties of their oxidation products under alkaline conditions. To produce distinct fluorescence response patterns for individual catecholamine, quenching of thioglycolic acid functionalized cadmium telluride (CdTe) quantum dots, by oxidation products, were employed along with the variation of fluorescence spectra of oxidation products. The spectral changes were analyzed with hierarchical cluster analysis (HCA) and principal component analysis (PCA) to identify catecholamine patterns. The proposed sensor could efficiently discriminate the individual...
The metabolomics signature associated with responsiveness to steroid therapy in focal segmental glomerulosclerosis: A pilot study, Article Revista de Investigacion Clinica ; Volume 71, Issue 2 , 2019 , Pages 106-115 ; 00348376 (ISSN) ; Kalantari, S ; Nafar, M ; Boroumandnia, N ; Sharif University of Technology
Instituto Nacional de la Nutricion Salvador Zubiran 2019
Background: Focal segmental glomerulosclerosis (FSGS) is considered one of the most severe glomerular diseases and around 80% of cases are resistant to steroid treatment. Since a large proportion of steroid-resistant (SR) FSGS patients progress to end-stage renal disease, other therapeutic strategies may benefit this population. However, identification of non-invasive biomarkers to predict this high-risk population is needed. Objective: We aimed to identify the biomarker candidates to distinguish SR from steroid-sensitive (SS) patients using metabolomics approach and to identify the possible molecular mechanism of resistance. Methods: Urine was collected from biopsy-proven FSGS patients...