Martín Resano Ezcaray

@article{D3JA00420A,

title = {Boron elemental and isotopic determination via the BF diatomic molecule using high-resolution continuum source graphite furnace molecular absorption spectrometry},

author = {Maite Aramendía and André L. M. Souza and Flávio V. Nakadi and Martín Resano},

url = {http://dx.doi.org/10.1039/D3JA00420A},

doi = {10.1039/D3JA00420A},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {J. Anal. At. Spectrom.},

volume = {39},

pages = {767-779},

publisher = {The Royal Society of Chemistry},

abstract = {Boron trace determination in biological materials is needed in different fields of application. Direct B determination by means of Graphite Furnace Atomic Absorption Spectrometry (SS-GFAAS) has been used in the past for this purpose, offering good detection limits hardly achievable by other techniques. However, such methods require the use of high atomization temperatures combined with large integration times to promote B atomization, which dramatically reduces the lifetime of the instrument's graphite parts. In this work, a new perspective for B determination by means of Graphite Furnace Molecular Absorption Spectrometry (GFMAS) is proposed. B was detected as the diatomic molecule BF (boron monofluoride), deploying a gas phase reaction with CH3F as fluorinating agent. Based on this strategy, a method for the direct determination of B in two biological certified reference materials (NIST SRM 1570a spinach leaves and NIST SRM 1573a tomato leaves) has been developed, providing similar detection capabilities to the GFAAS method (LOD of 0.24 ng) but requiring much milder furnace conditions. Moreover, the appearance of memory effects, very common in GFAAS methods, is also avoided with this method. Straightforward calibration with aqueous standard solutions was also found to be possible. To this end, a mixture of W (permanent), citric acid, and Ca as chemical modifiers was found to be essential for obtaining a reproducible and sufficiently sensitive signal for boron solutions, comparable to the signals obtained for the solid samples. With this method, accurate results were obtained for the direct analysis of both certified reference materials, provided that spectral interferences from the PO molecule were properly corrected. Precision values in the range of 15% RSD, as typically reported for direct solid sampling GFAAS, were found. Finally, and as an additional advantage of the GFMAS method, a large isotopic shift in the absorbance of the 10BF and 11BF molecules can be accurately monitored at a secondary transition for the BF molecule. This offers novel analytical possibilities for the method, which are also explored in this study. In this regard, control of the B concentration was found to be critical for obtaining accurate and precise isotope ratios for this element.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FREIRE2024126417,

title = {Tracing isotopically labeled selenium nanoparticles in plants via single-particle ICP-mass spectrometry},

author = {Bruna Moreira Freire and Ana Rua-Ibarz and Flávio Venâncio Nakadi and Eduardo Bolea-Fernandez and Juan J. Barriuso-Vargas and Camila Neves Lange and Maite Aramendía and Bruno Lemos Batista and Martín Resano},

url = {https://www.sciencedirect.com/science/article/pii/S0039914024007963},

doi = {https://doi.org/10.1016/j.talanta.2024.126417},

issn = {0039-9140},

year  = {2024},

date = {2024-01-01},

journal = {Talanta},

volume = {277},

pages = {126417},

abstract = {Abstract 

Agronomic biofortification using selenium nanoparticles (SeNPs) shows potential for addressing selenium deficiency but further research on SeNPs-plants interaction is required before it can be effectively used to improve nutritional quality. In this work, single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) was used for tracing isotopically labeled SeNPs (82SeNPs) in Oryza sativa L. tissues. For this purpose, SeNPs with natural isotopic abundance and 82SeNPs were synthesized by a chemical method. The NPs characterization by transmission electron microscopy (TEM) confirmed that enriched NPs maintained the basic properties of unlabeled NPs, showing spherical shape, monodispersity, and sizes in the nano-range (82.8 ± 6.6 nm and 73.2 ± 4.4 nm for SeNPs and 82SeNPs, respectively). The use of 82SeNPs resulted in an 11-fold enhancement in the detection power for ICP-MS analysis, accompanied by an improvement in the signal-to-background ratio and a reduction of the size limits of detection from 89.9 to 39.9 nm in SP-ICP-MS analysis. This enabled 82SeNPs to be tracked in O. sativa L. plants cultivated under foliar application of 82SeNPs. Tracing studies combining SP-ICP-MS and TEM-energy-dispersive X-ray spectroscopy data confirmed the uptake of intact 82SeNPs by rice leaves, with most NPs remaining in the leaves and very few particles translocated to shoots and roots. Translocation of Se from leaves to roots and shoots was found to be lower when applied as NPs compared to selenite application. From the size distributions, as obtained by SP-ICP-MS, it can be concluded that a fraction of the 82SeNPs remained within the same size range as that of the applied NP suspension, while other fraction underwent an agglomeration process in the leaves, as confirmed by TEM images. This illustrates the potential of SP-ICP-MS analysis of isotopically enriched 82SeNPs for tracing NPs in the presence of background elements within complex plant matrices, providing important information about the uptake, accumulation, and biotransformation of SeNPs in rice plants.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Isotope Dilution Analysis for Particle Mass Determination Using Single-Particle Inductively Coupled Plasma Time-of-Flight Mass Spectrometry: Application to Size Determination of Silver Nanoparticles},

author = {Maite Aramendía and Diego Leite and Javier Resano and Martín Resano and Kharmen Billimoria and Heidi Goenaga-Infante},

doi = {10.3390/nano13172392},

year  = {2023},

date = {2023-08-22},

urldate = {2023-08-22},

journal = {Nanomaterials},

volume = {13},

issue = {17},

pages = {2392},

abstract = {This paper describes methodology based on the application of isotope dilution (ID) in

single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-ToFMS) mode

for the mass determination (and sizing) of silver nanoparticles (AgNPs). For this purpose, and

considering that the analytical signal in spICP-MS shows a transient nature, an isotope dilution

equation used for online work was adapted and used for the mass determination of individual NPs.

The method proposed measures NP isotope ratios in a particle-to-particle approach, which allows for

the characterization of NP mass (and size) distributions and not only the mean size of the distribution.

For the best results to be obtained, our method development (undertaken through the analysis of

the reference material NIST RM 8017) included the optimization of the working conditions for the

best precision and accuracy in isotope ratios of individual NPs, which had been only reported to

date with multicollector instruments. It is shown that the precision of the measurement of these

ratios is limited by the magnitude of the signals obtained for each NP in the mass analyzer (counting

statistics). However, the uncertainty obtained for the sizing of NPs in this approach can be improved

by careful method optimization, where the most important parameters are shown to be the selection

of the spike isotopic composition and concentration. Although only AgNPs were targeted in this

study, the method presented, with the corresponding adaptations, could be applied to NPs of any

other composition that include an element with different naturally available isotopes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nano13121838,

title = {An Approach Based on an Increased Bandpass for Enabling the Use of Internal Standards in Single Particle ICP-MS: Application to AuNPs Characterization},

author = {Antonio Bazo and Maite Aramendía and Flávio V. Nakadi and Martín Resano},

url = {https://www.mdpi.com/2079-4991/13/12/1838},

doi = {10.3390/nano13121838},

issn = {2079-4991},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Nanomaterials},

volume = {13},

number = {12},

abstract = {This paper proposes a novel approach to implement an internal standard (IS) correction in single particle inductively coupled plasma mass spectrometry (SP ICP-MS), as exemplified for the characterization of Au nanoparticles (NPs) in complex matrices. This approach is based on the use of the mass spectrometer (quadrupole) in bandpass mode, enhancing the sensitivity for the monitoring of AuNPs while also allowing for the detection of PtNPs in the same measurement run, such that they can serve as an internal standard. The performance of the method developed was proved for three different matrices: pure water, a 5 g L−1 NaCl water solution, and another water solution containing 2.5% (m/v) tetramethylammonium hydroxide (TMAH)/0.1% Triton X-100. It was observed that matrix-effects impacted both the sensitivity of the NPs and their transport efficiencies. To circumvent this problem, two methods were used to determine the TE: the particle size method for sizing and the dynamic mass flow method for the determination of the particle number concentration (PNC). This fact, together with the use of the IS, enabled us to attain accurate results in all cases, both for sizing and for the PNC determination. Additionally, the use of the bandpass mode provides additional flexibility for this characterization, as it is possible to easily tune the sensitivity achieved for each NP type to ensure that their distributions are sufficiently resolved.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{D2JA00267A,

title = {Cu fractionation, isotopic analysis, and data processing via machine learning: new approaches for the diagnosis and follow up of Wilson's disease via ICP-MS},

author = {M. Carmen García-Poyo and Sylvain Bérail and Anne Laure Ronzani and Luis Rello and Elena García-González and Flávio V. Nakadi and Maite Aramendía and Javier Resano and Martín Resano and Christophe Pécheyran},

url = {http://dx.doi.org/10.1039/D2JA00267A},

doi = {10.1039/D2JA00267A},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {J. Anal. At. Spectrom.},

volume = {38},

issue = {1},

pages = {229-242},

publisher = {The Royal Society of Chemistry},

abstract = {Information about Cu fractionation and Cu isotopic composition can be paramount when investigating Wilson's disease (WD). This information can provide a better understanding of the metabolism of Cu. Most importantly, it may provide an easy way to diagnose and to follow the evolution of WD patients. For such purposes, protocols for Cu determination and Cu isotopic analysis via inductively coupled plasma mass spectrometry were investigated in this work, both in bulk serum and in the exchangeable copper (CuEXC) fractions. The CuEXC protocol provided satisfactory recovery values. Also, no significant mass fractionation during the whole analytical procedure (CuEXC production and/or Cu isolation) was detected. Analyses were carried out in controls (healthy persons), newborns, patients with hepatic disorders, and WD patients. While the results for Cu isotopic analysis are relevant (e.g., δ65Cu values were lower for both WD patients under chelating treatment and patients with hepatic problems in comparison with those values obtained for WD patients under Zn treatments, controls, and newborns) to comprehend Cu metabolism and to follow up the disease, the parameter that can help to better discern between WD patients and the rest of the patients tested (non-WD) was found to be the REC (relative exchangeable Cu). In this study, all the WD patients showed a REC higher than 17%, while the rest showed lower values. However, since establishing a universal threshold is complicated, machine learning was investigated to produce a model that can differentiate between WD and non-WD samples with excellent results (100% accuracy, albeit for a limited sample set). Most importantly, unlike other ML approaches, our model can also provide an uncertainty metric to indicate the reliability of the prediction, overall opening new ways to diagnose WD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}