Scanning Probe Microscopies for the Study at Nanoscale of Nanomaterials and Nanosystems: Magnetic Properties for Bio-applications

Magnetic nanomaterials due to their various features different from the ordinary bulk matter in their mechanical, thermal, magnetic, optical properties, are attracting more and more attention in both theoretical research and practical applications in various fields. Magnetic nanoparticles (MNPs) are a very important branch of magnetic nanomaterials due to their nanoscale sizes, being relatively long in vivo half-life and limited agglomeration. These make them ideal for biomedical applications such as magnetic labeling, hyperthermia cancer treatment, targeted drug delivery, and contrast enhancement agents in magnetic resonance imaging (MRI). In drug delivery applications, MNPs can be determined with high accuracy [1]. It would be of interest to localize and characterize MNPs at the nanoscale for biological applications. However, very limited studies exist on detecting and characterizing the magnetic signals of nanoparticles in biological science. Many methods in surface structure analysis are used as nano-characterization techniques, such as transmission electron microscopy (TEM), scanning electron microscopy (SEM), field electron microscopy (FEM), field ion microscope (FIM), low energy electron diffraction (LEED), Auger electron spectroscopy (AES), photoelectron spectroscopy (ESCA) and electron probe. These techniques detect the surface or interface to show the physical and chemical properties at the nanoscale. But any kind of these techniques has the limitations of one kind or another. For example, LEED and X-ray diffraction method require that the sample has a periodic structure; the resolution of optical microscopy and SEM are insufficient to distinguish surface atoms; high-resolution TEM is mainly used for thin bulk samples and interfacial studies to detect the magnetic properties, but the sample preparation process to get cell sections for TEM analysis is time consuming, and only a small part of cell section can be analyzed; FEM and FIM can only detect the tip radius of less than 100 nm of the atomic structure in two-dimensional geometry. Most commonly, studies which analyze the magnetic nature of MNPs use a superconducting quantum interference device (SQUID) and vibrating sample magnetometer (VSM). But due to low sensitivity and ultimately poor accuracy neither is an appropriate technique to measure the magnetic moment of individual MNPs, whatever in air or in liquid environment. Proper characterization and monitoring the properties of MNPs system are important for their potential applications. Currently, one of the most common methods for intracellular imaging of magnetic nanoparticles is fluorescence microscopy [2]. A disadvantage of this technique is that nanoparticles must first be labeled with fluorescent probes in order to be visualized. Due to the inherent limitations, the resolution of optical instruments is restricted by the wavelength of the light [3]. In 2010, Sun et al. conjugated fluorescent probes to the surface of magnetic nanoparticles to map cellular uptake pathways [4]. Relative to fluorescence microscopy, two-photon microscopy (TPM) offers improved resolution to study cellular interactions with magnetic nanoparticles, requiring the particles to be labeled with a two-photon fluorescent dye [5]. However it has been known that the imaging depth in TPM cannot be increased indefinitely, meanwhile optimization of the two-photon excitation efficiency is limited by the degree of damage the specimen can tolerate [6]. Due to the relatively poor resolution and reliability of these techniques, scanning probe microscopes (SPM) emerged out. SPM is a generation of scanning tunneling microscope based on a variety of new probe microscopes, such as atomic force microscopy (AFM), lateral force microscopy (LFM) and electrostatic force microscope (EFM). Among these techniques magnetic force microscope (MFM), a label-free in vitro detection method for magnetic materials, has the capability to detect nanoscale magnetic domains and simultaneously obtain atomic force microscopy topography images. Due to its ability to localize, characterize and distinguish magnetic materials from other materials at the nanoscale, as well as the advantage of three-dimensional information, MFM offers the great potential for the in vivo research. The scope for MFM lies in detecting the presence of magnetic nanomaterials and spatially localizing magnetic domains. It is likely that magnetic nanomaterials (occur in clusters or aggregates) are embedded in a biological matrix to different depth, and surrounded by bio-molecules. The development and application of MFM for detecting MNPs hold great promise in biology. Spatially localizing magnetic plaques, at nanometer resolution in ambient atmospheric environment, will provide a better understanding of the deposition mechanism of magnetic material derivatives in the biological tissues. The background on magnetic materials and nanoparticles is presented in chapter 1 and AFM/MFM experimental apparatus and technique is illustrated in chapter 2. In the last three chapters of the thesis the results of three different typologies of experiments are reported. The studies I have conducted are developed in the framework of the research activities of the laboratory of Scanning Probe Microscopy of EMiNaLab (coordinator prof. Marco Rossi), at the Department of Basic and Applied Sciences for Engineering of Sapienza University of Rome. In particular, in Chapter 3, we investigate bacterial biofilms at the first time, which are colonies of microbes embedded in a self-produced exopolysaccharides extracellular matrix presenting a major concern in health care. We will demonstrate an approach based on magnetic force microscopy to perform accurate measurement of the thickness of soft thin films - although it may easily extended even to stiff films - deposited on periodically patterned magnetic substrates. By detecting the biofilm thickness MFM will provide a novel method to study the thin film. In the second part of the thesis, MFM is applied to visualize and quantitatively measure magnetically labeled vesicular system. Vesicles containing magnetic nanoparticles as magnetic target carrier can be used for a wide range of biological application. The encapsulation of drugs in vesicles can minimize drug degradation and inactivation by increasing drug bioavailability and targeting to the pathological area. Many different non-contact techniques have been proposed. Nevertheless, MFM has never been used to study vesicular systems embedding MNPs, either qualitatively or quantitatively. MFM will be illustrated to evaluate the amount of MNPs incorporated in single vesicle, together with discussion on its merits and possible sources of uncertainty. In the last part of the thesis, we developed the capability of AFM/MFM to detect magnetically labeled materials of biological interest, which are magnetoferritin, APTES functionalized Fe3O4 nanoparticles and cells labeled Fe@Au nanoparticle. AFM/MFM will allow us to detect magnetic nanoparticles within submembranes and without severe deformation of samples. In our study, We expect to demonstrate the potential of MFM for the study of magnetic properties of different nano-biosystems, illustrating our approaches which aim at deducing quantitative information from MFM characterizations. Such a research is useful for future applications of MFM, indicating the potential to image magnetic nanoparticles unlabelled and unmodified in living cellular systems. The overall target of the thesis is to develop and standardize reliable innovative protocols, using scanning probe microscopy-based techniques that could be implemented in rapid and early theranostic methods

Multi-turn Inference Matching Network for Natural Language Inference

Natural Language Inference (NLI) is a fundamental and challenging task in Natural Language Processing (NLP). Most existing methods only apply one-pass inference process on a mixed matching feature, which is a concatenation of different matching features between a premise and a hypothesis. In this paper, we propose a new model called Multi-turn Inference Matching Network (MIMN) to perform multi-turn inference on different matching features. In each turn, the model focuses on one particular matching feature instead of the mixed matching feature. To enhance the interaction between different matching features, a memory component is employed to store the history inference information. The inference of each turn is performed on the current matching feature and the memory. We conduct experiments on three different NLI datasets. The experimental results show that our model outperforms or achieves the state-of-the-art performance on all the three datasets