RESUMEN

Medical imaging plays an important role in diagnosis and treatment of multiple diseases. It is a field which seeks for improved sensitivity and spatiotemporal resolution to allow the dynamic monitoring of diverse biological processes that occur at the micro- and nanoscale. Emerging technologies for targeted diagnosis and therapy such as nanotherapeutics, microimplants, catheters, and small medical tools also need to be precisely located and monitored while performing their function inside the human body. In this work, we show for the first time the real-time tracking of moving single micro-objects below centimeter thick phantom tissue and ex vivo chicken breast, using multispectral optoacoustic tomography (MSOT). This technique combines the advantages of ultrasound imaging regarding depth and resolution with the molecular specificity of optical methods, thereby facilitating the discrimination between the spectral signatures of the micro-objects from those of intrinsic tissue molecules. The resulting MSOT signal is further improved in terms of contrast and specificity by coating the micro-objects' surface with gold nanorods, possessing a unique absorption spectrum, which facilitate their discrimination from surrounding biological tissues when translated to future in vivo settings.

Asunto(s)

RESUMEN

A position-sensitive detector/device (PSD) is a sensor that is capable of tracking the location of a laser beam on its surface. PSDs are used in many scientific instruments and technical applications including but not limited to atomic force microscopy, human eye movement monitoring, mirrors or machine tool alignment, vibration analysis, beam position control and so on. This work intends to propose a new application using the PSD. That is a new microscopy system called scanning PSD microscopy. The working mechanism is about putting an object on the surface of the PSD and fast scanning its area with a laser beam. To achieve a high degree of accuracy and precision, a reliable framework was designed using the PSD. In this work, we first tried to improve the PSD reading and its measurement performance. This was done by minimizing the effects of noise, distortion and other disturbing parameters. After achieving a high degree of confidence, the microscopy system can be implemented based on the improved PSD measurement performance. Later to improve the scanning efficiency, we developed an adaptive local scanning system to scan the whole area of the PSD in a short matter of time. It was validated that our comprehensive and adaptive local scanning method can shorten the scanning time in order of hundreds of times in comparison with the traditional raster scanning without losing any important information about the scanned 2D objects. Methods are also introduced to scan very complicated objects with bifurcations and crossings. By incorporating all these methods, the new microscopy system is capable of scanning very complicated objects in the matter of a few seconds with a resolution that is in order of a few micrometers.

RESUMEN

Tracking micro-objects in the noisy microscopy image sequences is important for the analysis of dynamic processes in biological objects. In this paper, an automated tracking framework is proposed to extract the trajectories of micro-objects. This framework uses a probability hypothesis density particle filtering (PF-PHD) tracker to implement a recursive state estimation and trajectories association. In order to increase the efficiency of this approach, an elliptical target model is presented to describe the micro-objects using shape parameters instead of point-like targets which may cause inaccurate tracking. A novel likelihood function, not only covering the spatiotemporal distance but also dealing with geometric shape function based on the Mahalanobis norm, is proposed to improve the accuracy of particle weight in the update process of the PF-PHD tracker. Using this framework, a larger number of tracks are obtained. The experiments are performed on simulated data of microtubule movements and real mouse stem cells. We compare the PF-PHD tracker with the nearest neighbor method and the multiple hypothesis tracking method. Our PF-PHD tracker can simultaneously track hundreds of micro-objects in the microscopy image sequence.

Asunto(s)

RESUMEN

A material-based bottom-up approach is proposed towards an assembly of cells and engineered micro-objects at the macroscale. We show how shape, size and wettability of engineered micro-objects play an important role in the behavior of cells on these objects. This approach can, among other applications, be used as a tool to engineer complex 3D tissues of clinically relevant size.

Asunto(s)

RESUMEN

Methods for the continuous monitoring and removal of ultra-trace levels of toxic inorganic species (e.g., mercury, copper, and cadmium ions) from aqueous media such as drinking water and biological fluids are essential. In this paper, the design and engineering of a simple, pH-dependent, micro-object optical sensor is described based on mesoporous aluminosilica pellets with an adsorbed dressing receptor (a porphyrinic chelating ligand). This tailor-made optical sensor permits ultra-fast (≤ 60 s), specific, pH-dependent visualization and removal of Cu(2+) , Cd(2+) , and Hg(2+) at sub-picomolar concentrations (∼10(-11) mol dm(-3) ) from aqueous media, including drinking water and a suspension of red blood cells. The acidic active acid sites of the pellets consist of heteroatoms arranged around uniformly shaped pores in 3D nanoscale gyroidal mesostructures densely coated with the chelating ligand. The sensor can be used in batch mode, as well as in a flow-through system in which sampling, target ion recognition and removal, and analysis are integrated in a highly automated and efficient manner. Because the pellets exhibit long-term stability, reproducibility, and versatility over a number of analysis/regeneration cycles, they can be expected to be useful for the fabrication of inexpensive sensor devices for naked-eye detection of toxic pollutants.

Asunto(s)