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Imaging and Particle Therapy
Published in Manjit Dosanjh, Jacques Bernier, Advances in Particle Therapy, 2018
G. Landry, G. Dedes, M. Pinto, K. Parodi
Single particle-tracking detectors typically consist of tracker modules which detect the position of each particle before and after the scanned object and a residual energy/range detector after the object. An example of such a prototype scanner for pCT is shown in Figure 6.5a. Imaging systems based on range telescopes as residual range detector were developed in Paul Scherrer Institute (PSI) (Pemler et al., 1999), by the foundation Terapio con Radiazioni Adroniche (TERA) (Amaldi et al., 2011), and the Proton Radiotherapy Verification and Dosimetry Applications (PRaVDA) consortium (Poludniowski et al., 2014a). Imaging systems based on calorimetry were developed by the Loma Linda University (LLU) and the University of California Santa Cruz (UCSC) (Sadrozinski et al., 2013), the Proton IMAging (PRIMA) collaboration (Sipala et al., 2011; Civinini et al., 2013), and the Niigata University (Saraya et al., 2014). For 12C ions, a prototype system based on calorimetry was developed at National Institute of Radiological Sciences (NIRS) (Shinoda et al., 2006). A hybrid system for protons combining the concepts of a range telescope and a calorimeter was presented by the LLU/UCSC collaboration (Johnson et al., 2014; Bashkirov et al., 2016).
Intraperitoneal nonviral nucleic acid delivery in the treatment of peritoneal cancer
Published in Wim P. Ceelen, Edward A. Levine, Intraperitoneal Cancer Therapy, 2015
George R. Dakwar, Stefaan S.C. De Smedt, Katrien Remaut
In this chapter, we restricted our discussion on IP injection of nonviral vectors to deliver nucleic acids into tumors residing in the peritoneal space. IP delivery of nucleic acids is indeed an attractive approach to target peritoneal carcinomatosis. Although several nonviral gene delivery systems carrying pDNA or siRNA have proven antitumor effect to some extent, none of the tested formulations have been approved for use in clinical oncology so far. Translation into the clinic still awaits a new class of formulations that can overcome both the intracellular and extracellular barriers as discussed in the preceding text. The main problem in optimizing nonviral gene delivery systems is the lack of knowledge on the relation between the physicochemical properties of delivery systems (e.g., charge and size) and their obtained therapeutic effect. Also, carrier properties that assure stability on the extracellular level (for example, surface PEGylation) still often interfere with the intracellular performance of the same carrier. It should be noted that the efficiency of a delivery system can greatly depend on the extracellular barriers that are encountered and thus on the administration route. It is crucial to evaluate and optimize gene delivery vehicles with the intended administration route in mind. For IP delivery, this implies that carrier properties should be studied in the IP fluid. In an attempt to perform reliable measurements in more complex biological fluids, we have proven that advanced microscopy techniques such as fluorescence correlation spectroscopy and single particle tracking enable to monitor the disassembly and aggregation of nonviral vectors in undiluted biological fluids [13]. By employing these powerful techniques, we can simulate the in vivo situation and screen for formulations that show minimal aggregation properties while keeping the maximal amount of their siRNA or pDNA load in the IP fluid. For local IP delivery, it should be noted that having colloidal stable particles in the IP cavity is not the only requirement for optimal tumor targeting. It has been reported that nanosized vectors are rapidly cleared from the peritoneal cavity following IP administration compared to microparticles [81] (Figure 32.1a, step 4). This rapid absorption from the peritoneal cavity to the systemic circulation, most likely seriously limits the amount of complexes that actually reach and enter the tumor target cells. The rapid clearance of nanoparticles from the IP cavity has however also been exploited in some studies, where the IP route is being used for systemic gene delivery, to target systemic tumors. In a study by Aigner and coworkers, siRNA against c-erbB2/neu (HER-2) receptor complexed with PEI was injected IP into mice bearing subcutaneous SKOV-3 tumors and exhibited a remarkable reduction in tumor growth, whereas no reduction in tumor growth was observed following injection of naked siRNA [82]. In this case, the IP delivery is thus used as a depot system, from which systemic delivery of nanoparticles is aimed.
Live imaging of single platelets at work
Published in Platelets, 2020
Karin Sadoul, Laurence Lafanechère, Alexei Grichine
For all the above-listed reasons, the necessary compromise between the spatial resolution, sensitivity and the imaging speed seems to be of particular importance in the case of live platelet microscopy. Fortunately, recent spectacular advances in content-aware image restoration [58] look very promising for low-light optical imaging. Thanks to deep-learning training with synthetic or physical data this algorithm allows denoising, recovery of isotropic resolution, 3D projection, and even restoration of sub-diffraction structures. Artificial intelligence techniques are also unavoidable in the future for single particle tracking approaches, which currently encounter limitations due to low signal-to-noise ratios and model biases [59]. Together with the development of parallel imaging modalities for cells and tissues like soSPIM [51] or light-sheet microscopy [50] and correlative optical and non-optical superresolution approaches, a promising future for platelet imaging can be foreseen.
An overview of nanosomes delivery mechanisms: trafficking, orders, barriers and cellular effects
Published in Artificial Cells, Nanomedicine, and Biotechnology, 2018
Gamaleldin I. Harisa, Mohamed M. Badran, Fars K. Alanazi, Sabry M. Attia
Nanosomes exocytosis from human colonic adenocarcinoma HT-29 cells was directly related to the extracellular calcium concentration [20]. Calcium triggers lysosomal exocytosis by changing the conformation of integral membrane proteins and enhancing the fusion of the lysosomal membrane with the plasma membrane. Conversely, cholesterol-depleting agents interfere with nanoparticle exocytosis [20]. Nanocarriers eliminated from the cells as EVs undergo endocytosis by other cells and can act as cell signalling agent [17]. Study of nanosystem exocytosis is complicated have methodology limitations, advanced techniques are needed to elucidate exocytosis. Usually nanoparticle-tracking analysis requires the combination of different techniques [11]. These techniques include elemental analysis, fluorescence microscopy and inductively coupled plasma spectrometry. Nanoparticle tracking by transmission electron microscopy can help discriminate between excretion of intact particles and ions. Single particle tracking cannot be used when particles aggregate; however, transmission electron microscopy cannot track individual particles [9]. Figure 3 displays that displays exocytotic machinery of nanosystems across biological membranes.
Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans
Published in Biofouling, 2018
Gael Pérez-Rodríguez, Sónia Dias, Martín Pérez-Pérez, Florentino Fdez-Riverola, Nuno F. Azevedo, Anália Lourenço
The present work shows, for the first time, the potential of ABM to understand biofilm dynamics at the single-cell and single-molecule levels. One of the main advantages of the ABM approach when compared with algebraic models and other existing models is a reduction in model complexity, which enables the practical simulation of more realistic biological scenarios (Fozard et al. 2012; Emerenini et al. 2015). Notably, ABM enables the simulation of multiple scenarios of cell spatial distribution, and thus the observation of the impact that cell location has in molecular diffusion and, consequently, in QS communication. Moreover, these models are also able to describe the trajectory of individual molecules, and hence obtain spatial and temporal information at the single-molecule level. These data can be more easily validated by direct comparison with single particle tracking experiments, as well as provide detailed information on the behaviour of more complex scenarios involving multiple cells in a seemingly random distribution.