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Nanoparticles with novel physico-chemical properties have an impact on various scientific disciplines, including medical diagnostics, energy conversion, catalysis, and solid-state lighting. Here, I present examples from my previous work on organic and inorganic nanoscale systems, such as superparamagnetic iron oxide nanoparticles (SPIONs) for blood platelet labeling and magnetic copper-doped bioactive glasses for bone cancer therapy. Additionally, I provide a first insight into my recently started Ph.D. project focusing on bichromophoric organic fluorophores exhibiting Aggregation-Induced Dual-Emission (AIDE) and their integration into nanostructures for water-dispersible nanoscale reporters and nanosensors.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
Organic and inorganic micro- and nanoparticles are increasingly used as drug carriers, fluorescent sensors, and multimodal labels in the life and material sciences. Typically, these applications require further functionalization of the particles with, e.g., antifouling ligands, targeting bioligands, stimuli-responjsive caps, or sensor molecules. Besides serving as an anchor point for subsequent functionalization, the surface chemistry of these particles also fundamentally influences their interaction with the surrounding medium and can have a significant effect on colloidal stability, particle uptake, biodistribution, and particle toxicity in biological systems. Moreover, functional groups enable size control and tuning of the surface during the synthesis of particle systems.
For these reasons, a precise knowledge of the chemical nature, the total number of surface groups, and the number of groups on the particle surface that are accessible for further functionalization is highly important. In this contribution, we will will discuss the advantages and limitiations of different approaches to quantify the amount of commonly used surface functional groups such as amino,[1,2] carboxy,[1,2] and aldehyde groups.[3] Preferably, the quantification is carried out using sensitive and fast photometric or fluorometric assays, which can be read out with simple, inexpensive instrumentation and can be validated by complimentary analytic techniques such as ICP-OES and quantitative NMR.
Many applications of nanomaterials in the life sciences require the controlled functionalization of these materials with ligands like polyethylene glycol (PEG) and/or biomolecules such as peptides, proteins, and DNA. This enables to tune their hydrophilicity and biocompatibility, minimize unspecific interactions, improve biofunctionalization efficiencies, and enhance blood circulation times. Moreover, it is the ultimate prerequisite for their use as reporters in assays or the design of targeted optial probes for bioimaging. At the core of these functionalization strategies are reliable and validated methods for surface group and ligand quantification that can be preferably performed with routine laboratory instrumentation, require only small amounts of substances, and are suitable for many different types of nanomaterials.
We present here versatile and simple concepts for the quantification of common functional groups, ligands, and biomolecules on different types of organic and inorganic nano-materials, using different types of optical reporters and method validation with the aid of multimodal reporters, method comparisons, and mass balances.
Polymer nanoparticles (NPs) are of increasing importance for a wide range of applications in the material and life sciences. This includes their application as carriers for e.g., analyte-responsive ligands for DNA sequencing platforms, drugs as well as dye molecules for use as multichromophoric reporters for signal enhancement in optical assays or the fabrication of nanosensors and targeted probes in bioimaging studies. All these applications require surface functionalization of the particles with e.g., ligands, sensor dyes, or analyte recognition moieties like biomolecules, and subsequently, the knowledge of the chemical nature and total number of surface groups as well as the number of groups accessible for coupling reactions. Particularly attractive for the latter are optically active reporters together with sensitive and fast optical assays, which can be read out with simple, inexpensive instrumentation.
We assessed a variety of conventional and newly developed colorimetric and fluorometric labels for optical surface group analysis, utilizing e.g., changes in intensity and/or color for signal generation. Moreover, novel cleavable and multimodal reporters were developed which consist of a reactive group, a cleavable linker, and an optically active moiety, chosen to contain also heteroatoms for straightforward method validation by elemental analysis, ICP-OES, ICP-MS or NMR. In contrast to conventional labels measured bound at the particle surface, which can favor signal distortions by scattering and encoding dyes, cleavable reporters can be detected colorimetrically or fluorometrically both attached at the particle surface and after quantitative cleavage of the linker in the transparent supernatant after particle removal e.g., by centrifugation. Here, we present first results obtained for the optical quantification of carboxylic and amino groups on a series of self-made polystyrene NPs with different types of labels and compare their potential and drawbacks for surface group analysis.
Carboxy, amino, and thiol groups play a critical role in a variety of physiological and biological processes and are frequently used for bioconjugation reactions. Moreover, they enable size control and tuning of the surface during the synthesis of particle systems. Especially, thiols have a high binding affinity to noble metals and semiconductors (SC). Thus, simple, inexpensive, robust, and fast methods for the quantification of surface groups and the monitoring of reactions involving ligands are of considerable importance for the characterization of modified or stabilized nanomaterials including polymers.
We studied the potential of the Ellman’s assay, recently used for the quantification of thiol ligands on SC nanocrystals by us1 and the 4-aldrithiol assay for the determination of thiol groups in molecular systems and on polymeric, noble and SC nanomaterials. The results were validated with ICP-OES and reaction mechanisms of both methods were studied photometrically and with ESI-TOF-MS.
The investigation of the reaction mechanisms of both methods revealed the influence of different thiols on the stoichiometry of the reactions2, yielding different mixed disulfides and the thiol-specific products spectroscopically detected. The used methods can quantify freely accessible surface groups on nanoparticles, e.g., modified polystyrene nanoparticles. For thiol ligands coordinatively bound to surface atoms of, e.g., noble or SC nanomaterials, depending on the strength of the thiol-surface bonds, particle dissolution prior to assay performance can be necessary.
We could demonstrate the reliability of the Ellman’s and aldrithiol assay for the quantification of surface groups on nanomaterials by ICP-OES and derived assay-specific requirements and limitations. Generally, it is strongly recommended to carefully control assay performance for new samples, components, and sample ingredients to timely identify possible interferences distorting quantification.