Tracing multi-isotopically labelled CdSe/ZnS quantum dots in biological media

Supiandi, N. Izyan; Charron, Gaëlle; Tharaud, Mickaël; Benedetti, Marc F.; Sivry, Yann

doi:10.1038/s41598-020-59206-w

Cited by 12 publications

(6 citation statements)

References 34 publications

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“…The use of isotopically labeled ENMs shows a great potential for detecting and discerning ENMs apart from the natural background at realistic contamination concentrations and can be applied to a wide range of metal-, metalloid-, or carbon-based ENMs. For instance, similar techniques enabled the detection of 109 Ag-enriched Ag-ENMs or multi-isotopically labeled 111 Cd 77 Se/ 68 ZnS QDs , at concentrations as low as ng L –1 in complex matrices. Furthermore, understanding the isotopic fingerprint of ENMs can help distinguish natural from manufactured ENMs and even the synthetic methods and manufacturers of engineered ENMs .…”

Section: Large Panel Of Enm Environmental Exposure Scenariosmentioning

confidence: 99%

Aquatic Mesocosm Strategies for the Environmental Fate and Risk Assessment of Engineered Nanomaterials

Carboni

Slomberg

Nassar

et al. 2021

Environ. Sci. Technol.

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In the past decade, mesocosms have emerged as a useful tool for the environmental study of engineered nanomaterials (ENMs) as they can mimic the relevant exposure scenario of contamination. Herein, we analyzed the scientific outcomes of aquatic mesocosm experiments, with regard to their designs, the ENMs tested, and the end points investigated. Several mesocosm designs were consistently applied in the past decade to virtually mimic various contamination scenarios with regard to ecosystem setting as well as ENMs class, dose, and dosing. Statistical analyses were carried out with the literature data to identify the main parameters driving ENM distribution in the mesocosms and the potential risk posed to benthic and planktonic communities as well as global ecosystem responses. These analyses showed that at the end of the exposure, mesocosm size (water volume), experiment duration, and location indoor/outdoor had major roles in defining the ENMs/metal partitioning. Moreover, a higher exposure of the benthic communities is often observed but did not necessarily translate to a higher risk due to the lower hazard posed by transformed ENMs in the sediments (e.g., aggregated, sulfidized). However, planktonic organisms were generally exposed to lower concentrations of potentially more reactive and toxic ENM species. Hence, mesocosms can be complementary tools to existing standard operational procedures for regulatory purposes and environmental fate and risk assessment of ENMs. To date, the research was markedly unbalanced toward the investigation of metal-based ENMs compared to metalloid- and carbon-based ENMs but also nanoenabled products. Future studies are expected to fill this gap, with special regard to high production volume and potentially hazardous ENMs. Finally, to take full advantage of mesocosms, future studies must be carefully planned to incorporate interdisciplinary approaches and ensure that the large data sets produced are fully exploited.

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Section: Large Panel Of Enm Environmental Exposure Scenariosmentioning

confidence: 99%

Aquatic Mesocosm Strategies for the Environmental Fate and Risk Assessment of Engineered Nanomaterials

Carboni

Slomberg

Nassar

et al. 2021

Environ. Sci. Technol.

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“…As a rule, calculating TOF requires processing data on hundreds of particles from several points of the catalyst, the more the better. A similar task arises for researchers in the synthesis and characterization of quantum dots [ 3 , 4 , 5 , 6 ]. Software products, widely used in probe methods, including scanning tunneling microscopy, such as WSxM [ 7 ], Gwyddion [ 8 ], allow the operator to measure particle parameters manually.…”

Section: Introductionmentioning

confidence: 99%

Nanoparticle Recognition on Scanning Probe Microscopy Images Using Computer Vision and Deep Learning

et al. 2020

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Identifying, counting and measuring particles is an important component of many research studies. Images with particles are usually processed by hand using a software ruler. Automated processing, based on conventional image processing methods (edge detection, segmentation, etc.) are not universal, can only be used on good-quality images and need to set a number of parameters empirically. In this paper, we present results from the application of deep learning to automated recognition of metal nanoparticles deposited on highly oriented pyrolytic graphite on images obtained by scanning tunneling microscopy (STM). We used the Cascade Mask-RCNN neural network. Training was performed on a dataset containing 23 STM images with 5157 nanoparticles. Three images containing 695 nanoparticles were used for verification. As a result, the trained neural network recognized nanoparticles in the verification set with 0.93 precision and 0.78 recall. Predicted contour refining with 2D Gaussian function was a proposed option. The accuracies for mean particle size calculated from predicted contours compared with ground truth were in the range of 0.87–0.99. The results were compared with outcomes from other generally available software, based on conventional image processing methods. The advantages of deep learning methods for automatic particle recognition were clearly demonstrated. We developed a free open-access web service “ParticlesNN” based on the trained neural network, which can be used by any researcher in the world.

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“…The CdSe/ZnS QDs used in this study were enriched in 111 Cd, 77 Se, and 68 Zn. The chemicals used including the synthesis protocol and the characterization methods of the multi-spiked QDs were described in previous works (Supiandi et al, 2019(Supiandi et al, , 2020. Briefly, a stock solution of the QDs in an organic phase was synthesized and used to prepare water-soluble QDs, i.e., functionalized with thioglycolic acid (TGA).…”

Section: Methodsmentioning

confidence: 99%

“…Batch experiments were performed, using mixtures of QDs and water with different chemical compositions and analogs of suspended matter to follow, as a function of time, the changes in chemical composition of the model surface waters. The use of isotopically modified (or "spiked") ENPs (Supiandi et al, 2019(Supiandi et al, , 2020 with centrifugal ultrafiltration (CU) separation and detection by high-resolution inductively coupled plasma mass spectrometry (HR-ICP-MS) overcame the analytical barriers (detection limits and geochemical background) to obtain the metal ion concentration and origins in the dissolved fraction. The speciation of QDs constituting metal ions (Cd and Zn) in the experimental systems (Domingos et al, 2008) was followed by scanned stripping chronopotentiometry (SSCP).…”

Section: Introductionmentioning

confidence: 99%

Geochemistry of Engineered Nanoparticles (CdSe/ZnS Quantum Dots) in Surface Waters

Supiandi

Domingos

Benedetti

et al. 2020

Front. Environ. Sci.

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The difficulties when studying the behavior of engineered nanoparticles (ENPs), and the subsequent metal speciation in aquatic ecosystems, at environmentally relevant concentrations (i.e., ppt level) are often related to the occurrence of ENP constitutive elements at high concentrations as a background in aquatic media. In this study, the physicochemical behavior of CdSe/ZnS quantum dots (QDs) when spread at very low concentrations in surface waters was investigated. The above-mentioned issues were overcome with the use of isotopically labeled QDs, separated by centrifugal ultrafiltration (CU) and measured by high-resolution inductively coupled plasma mass spectrometry (HR-ICP-MS), combined with the detection of free and labile metal ions by scanned stripping chronopotentiometry (SSCP). They firmly provided a thorough comprehension regarding the transformation of QDs in surface waters. The physicochemical conditions of the medium including the presence of an analog of natural organic matter and a mineral (i.e., fulvic acid and goethite), the manufactured coating of the QDs [here thioglycolic acid (TGA)], and the occurrence of added Zn in the medium were considered in the study. The overall results show that, in the absence of mineral/organic matter, the TGA ligands in solution that detached from the QD surface after dissolution control the metal speciation, especially for Cd. Conversely, in a more representative aquatic ecosystem condition (i.e., with Zn in the background media together with fulvic acid and goethite), almost no Zn or Cd dissolution from the QDs is detected. SSCP measurements reveal that the Zn complexes formed with the organic/mineral material in the system are inert, whereas the speciation model calculations indicated that Cd 2+ is bound to TGA ligands in solution and organic/inorganic matter-therefore suggesting that, under the studied conditions, aquatic organisms will be exposed to a very low concentration of free and labile metal ions issued from the QDs.

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Tracing multi-isotopically labelled CdSe/ZnS quantum dots in biological media

Cited by 12 publications

References 34 publications

Aquatic Mesocosm Strategies for the Environmental Fate and Risk Assessment of Engineered Nanomaterials

Aquatic Mesocosm Strategies for the Environmental Fate and Risk Assessment of Engineered Nanomaterials

Nanoparticle Recognition on Scanning Probe Microscopy Images Using Computer Vision and Deep Learning

Geochemistry of Engineered Nanoparticles (CdSe/ZnS Quantum Dots) in Surface Waters

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