The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Eric Caudron - One of the best experts on this subject based on the ideXlab platform.
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A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents
Talanta, 2020Co-Authors: Antoine Dowek, Tom Rohmer, François-xavier Legrand, Hynd Remita, Isabelle Lampre, Ali Tfayli, Marc Lavielle, Eric CaudronAbstract:Antineoplastic agents are, for most of them, highly toxic drugs prepared at hospital following individualized prescription. To protect patients and healthcare workers, it is important to develop analytical tools able to identify and quantify such drugs on a wide concentration range. In this context, surface enhanced Raman spectroscopy (SERS) has been tested as a specific and sensitive technique. Despite the Standardization of the nanoparticle synthesis, a polydispersity of nanoparticles in the suspension and a lack of reproducibility persist. This study focuses on the development of a new mathematical approach to deal with this nanoparticle polydispersity and its consequences on SERS signal variability through the feasibility of 5-fluorouracil (5FU) quantification using silver nanoparticles (AgNPs) and a handled Raman spectrophotometer. Variability has been maximized by synthetizing six different batches of AgNPs for an average size of 24.9 nm determined by transmission electron microscopy, with Residual Standard Deviation of 17.0%. Regarding low performances of the Standard multivariate data processing, an alternative approach based on the nearest neighbors were developed to quantify 5FU. By this approach, the predictive performance of the 5FU concentration was significantly improved. The mean absolute relative error (MARE) decreased from 16.8% with the traditional approach based on PLS regression to 6.30% with the nearest neighbors approach (p-value < 0.001). This study highlights the importance of developing mathematics adapted to SERS analysis which could be a step to overcome the spectral variability in SERS and thus participate in the development of this technique as an analytical tool in quality control to quantify molecules with good performances, particularly in the pharmaceutical field.
Antoine Dowek - One of the best experts on this subject based on the ideXlab platform.
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A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents
Talanta, 2020Co-Authors: Antoine Dowek, Tom Rohmer, François-xavier Legrand, Hynd Remita, Isabelle Lampre, Ali Tfayli, Marc Lavielle, Eric CaudronAbstract:Antineoplastic agents are, for most of them, highly toxic drugs prepared at hospital following individualized prescription. To protect patients and healthcare workers, it is important to develop analytical tools able to identify and quantify such drugs on a wide concentration range. In this context, surface enhanced Raman spectroscopy (SERS) has been tested as a specific and sensitive technique. Despite the Standardization of the nanoparticle synthesis, a polydispersity of nanoparticles in the suspension and a lack of reproducibility persist. This study focuses on the development of a new mathematical approach to deal with this nanoparticle polydispersity and its consequences on SERS signal variability through the feasibility of 5-fluorouracil (5FU) quantification using silver nanoparticles (AgNPs) and a handled Raman spectrophotometer. Variability has been maximized by synthetizing six different batches of AgNPs for an average size of 24.9 nm determined by transmission electron microscopy, with Residual Standard Deviation of 17.0%. Regarding low performances of the Standard multivariate data processing, an alternative approach based on the nearest neighbors were developed to quantify 5FU. By this approach, the predictive performance of the 5FU concentration was significantly improved. The mean absolute relative error (MARE) decreased from 16.8% with the traditional approach based on PLS regression to 6.30% with the nearest neighbors approach (p-value < 0.001). This study highlights the importance of developing mathematics adapted to SERS analysis which could be a step to overcome the spectral variability in SERS and thus participate in the development of this technique as an analytical tool in quality control to quantify molecules with good performances, particularly in the pharmaceutical field.
Eva Baldrich - One of the best experts on this subject based on the ideXlab platform.
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iridium oxide ph sensor for biomedical applications case urea urease in real urine samples
Biosensors and Bioelectronics, 2013Co-Authors: Elisabet Pratsalfonso, Llibertat Abad, N Casanpastor, Javier Gonzaloruiz, Eva BaldrichAbstract:Abstract This work demonstrates the implementation of iridium oxide films (IROF) grown on silicon-based thin-film platinum microelectrodes, their utilization as a pH sensor, and their successful formatting into a urea pH sensor. In this context, Pt electrodes were fabricated on Silicon by using Standard photolithography and lift-off procedures and IROF thin films were growth by a dynamic oxidation electrodeposition method (AEIROF). The AEIROF pH sensor reported showed a super-Nerstian (72.9±0.9 mV/pH) response between pH 3 and 11, with Residual Standard Deviation of both repeatability and reproducibility below 5%, and resolution of 0.03 pH units. For their application as urea pH sensors, AEIROF electrodes were reversibly modified with urease-coated magnetic microparticles (MP) using a magnet. The urea pH sensor provided fast detection of urea between 78 μM and 20 mM in saline solution, in sample volumes of just 50 μL. The applicability to urea determination in real urine samples is discussed.
Tom Rohmer - One of the best experts on this subject based on the ideXlab platform.
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A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents
Talanta, 2020Co-Authors: Antoine Dowek, Tom Rohmer, François-xavier Legrand, Hynd Remita, Isabelle Lampre, Ali Tfayli, Marc Lavielle, Eric CaudronAbstract:Antineoplastic agents are, for most of them, highly toxic drugs prepared at hospital following individualized prescription. To protect patients and healthcare workers, it is important to develop analytical tools able to identify and quantify such drugs on a wide concentration range. In this context, surface enhanced Raman spectroscopy (SERS) has been tested as a specific and sensitive technique. Despite the Standardization of the nanoparticle synthesis, a polydispersity of nanoparticles in the suspension and a lack of reproducibility persist. This study focuses on the development of a new mathematical approach to deal with this nanoparticle polydispersity and its consequences on SERS signal variability through the feasibility of 5-fluorouracil (5FU) quantification using silver nanoparticles (AgNPs) and a handled Raman spectrophotometer. Variability has been maximized by synthetizing six different batches of AgNPs for an average size of 24.9 nm determined by transmission electron microscopy, with Residual Standard Deviation of 17.0%. Regarding low performances of the Standard multivariate data processing, an alternative approach based on the nearest neighbors were developed to quantify 5FU. By this approach, the predictive performance of the 5FU concentration was significantly improved. The mean absolute relative error (MARE) decreased from 16.8% with the traditional approach based on PLS regression to 6.30% with the nearest neighbors approach (p-value < 0.001). This study highlights the importance of developing mathematics adapted to SERS analysis which could be a step to overcome the spectral variability in SERS and thus participate in the development of this technique as an analytical tool in quality control to quantify molecules with good performances, particularly in the pharmaceutical field.
François-xavier Legrand - One of the best experts on this subject based on the ideXlab platform.
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A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents
Talanta, 2020Co-Authors: Antoine Dowek, Tom Rohmer, François-xavier Legrand, Hynd Remita, Isabelle Lampre, Ali Tfayli, Marc Lavielle, Eric CaudronAbstract:Antineoplastic agents are, for most of them, highly toxic drugs prepared at hospital following individualized prescription. To protect patients and healthcare workers, it is important to develop analytical tools able to identify and quantify such drugs on a wide concentration range. In this context, surface enhanced Raman spectroscopy (SERS) has been tested as a specific and sensitive technique. Despite the Standardization of the nanoparticle synthesis, a polydispersity of nanoparticles in the suspension and a lack of reproducibility persist. This study focuses on the development of a new mathematical approach to deal with this nanoparticle polydispersity and its consequences on SERS signal variability through the feasibility of 5-fluorouracil (5FU) quantification using silver nanoparticles (AgNPs) and a handled Raman spectrophotometer. Variability has been maximized by synthetizing six different batches of AgNPs for an average size of 24.9 nm determined by transmission electron microscopy, with Residual Standard Deviation of 17.0%. Regarding low performances of the Standard multivariate data processing, an alternative approach based on the nearest neighbors were developed to quantify 5FU. By this approach, the predictive performance of the 5FU concentration was significantly improved. The mean absolute relative error (MARE) decreased from 16.8% with the traditional approach based on PLS regression to 6.30% with the nearest neighbors approach (p-value < 0.001). This study highlights the importance of developing mathematics adapted to SERS analysis which could be a step to overcome the spectral variability in SERS and thus participate in the development of this technique as an analytical tool in quality control to quantify molecules with good performances, particularly in the pharmaceutical field.