Quantitative performance characterization of three-dimensional noncontact fluorescence molecular tomography

© 2016 The Authors.Fluorescent proteins and dyes are routine tools for biological research to describe the behavior of genes, proteins, and cells, as well as more complex physiological dynamics such as vessel permeability and pharmacokinetics. The use of these probes in whole body in vivo imaging would allow extending the range and scope of current biomedical applications and would be of great interest. In order to comply with a wide variety of application demands, in vivo imaging platform requirements span from wide spectral coverage to precise quantification capabilities. Fluorescence molecular tomography (FMT) detects and reconstructs in three dimensions the distribution of a fluorophore in vivo. Noncontact FMT allows fast scanning of an excitation source and noninvasive measurement of emitted fluorescent light using a virtual array detector operating in free space. Here, a rigorous process is defined that fully characterizes the performance of a custom-built horizontal noncontact FMT setup. Dynamic range, sensitivity, and quantitative accuracy across the visible spectrum were evaluated using fluorophores with emissions between 520 and 660 nm. These results demonstrate that high-performance quantitative three-dimensional visible light FMT allowed the detection of challenging mesenteric lymph nodes in vivo and the comparison of spectrally distinct fluorescent reporters in cell culture

Colloidal Assemblies of Oriented Maghemite Nanocrystals and their NMR Relaxometric Properties

Elevated-temperature polyol-based colloidal-chemistry approach allows for the development of size-tunable (50 and 86 nm) assemblies of maghemite iso-oriented nanocrystals, with enhanced magnetization. 1H-Nuclear Magnetic Resonance (NMR) relaxometric experiments show that the ferrimagnetic cluster-like colloidal entities exhibit a remarkable enhancement (4 to 5 times) in the transverse relaxivity, if compared to that of the superparamagnetic contrast agent Endorem, over an extended frequency range (1-60 MHz). The marked increase of the transverse relaxivity r2 at a clinical magnetic field strength (1.41 T), which is 405.1 and 508.3 mM-1 s-1 for small and large assemblies respectively, allows to relate the observed response to the raised intra-aggregate magnetic material volume fraction. Furthermore, cell tests with murine fibroblast culture medium confirmed the cell viability in presence of the clusters. We discuss the NMR dispersion profiles on the basis of relaxivity models to highlight the magneto-structural characteristics of the materials for improved T2-weighted magnetic resonance images.Comment: Includes supporting informatio

Estimation of errors in force platform data.

Force platforms (FPs) are regularly used in the biomechanical analysis of sport and exercise techniques, often in combination with image-based motion analysis (e.g., Begg & Kamruzzaman, 2005; Kuitunen, Komi, & Kyrolainen, 2002; Rahmani, Dalleau, Viale, Hautier, & Lacour, 2000; Rodano & Squadrone, 2002). Force time data, particularly when combined with joint positions and segmental inertia parameters, can be used to evaluate the effectiveness of a wide range of movement patterns in sport and exercise (Bartlett, Messenger, & Lindsay, 1997). According to Dainty and Norman (1987) and Bartlett et al. (1997), valid and reliable force measures depend on low threshold, hysteresis and cross-talk, high linearity, adequate sensitivity and the elimination of cable interference, electrical inductance, and temperature and humidity variations. Moreover, a platform must possess high stiffness and high natural frequency and be located such that extraneous vibrations are excluded. Given that FPs are regularly used in sport and exercise research not only for data collection but also for evaluating other biomechanical equipment (e.g., Rahmani et al., 2000), the lack of attention paid to the likelihood of errors in their measurements is somewhat surprising. Although the scientific literature for kinematic data has established and consistently reported the estimation and propagation of errors, FP data are often taken as error-free. For example, Johnson and Buckley (2001) used a FP to measure ground reaction forces during sprinting, without calculating or reporting possible errors in FP data. Reporting FP data to an unjustifiably high precision and assuming they are acceptably accurate is potentially problematic. For example, when the force data are used for further calculations, such as estimating joint moments from external forces, the error in the force measures will propagate through the calculation--especially in the absence of postprocessing techniques--and directly affect the final result. Some investigators, however, have tried to assess the accuracy and reliability of their measurements. Bobbert and Schamhardt (1990) and Mita et al. (1993) found inaccuracies in estimates of the center of pressure position, especially toward the platform edges, and identified poor calibration and differences in the individual characteristics among the load cell amplifiers as possible causes. Although FP calibration data are usually available from manufacturers, researchers should not assume the manufacturer-quoted values are retained following installation and over time. Experimental error is inevitable in a study that uses FP as a data collection tool and can arise from a variety of sources, which may influence the reliability of the findings and the study's validity. Despite this, neither calibration of FP nor estimation of potential errors in FP measurements is reported in most investigations. Furthermore, because the existing methods reported in studies for FP error calculation require sophisticated equipment and are time-consuming, their application in other FP studies would be rather complicated and, in many laboratories, not possible. Therefore, the purpose of the present study was to establish the magnitude of possible measurement errors from a FP typically used in sport and exercise biomechanics, by applying an easy-to-use, rime-efficient method

Comparison of the effects of active, passive and mixed warm ups on swimming performance.

AIM: The aim of this paper was to compare the effects of an active (AWU), passive (PWU) and mixed warm up (MWU) on swimming performance. METHODS: Eight male competitive swimmers completed each type of WU and, following a 20-minute rest, performed a maximum 100m test on their specialised stroke. The order of WUs was randomized and there was a 7-day period between subsequent testing sessions. The time taken to complete the 100m trial was the performance measure. The rating of perceived exertion (RPE) was measured immediately post WU, while heart rate (HR) was measured pre and post WU and pre and post the maximum swim. During the 20-minute rest, the swimmers' psychological state was assessed with the CSAI-2 questionnaire. RESULTS: Post WU HR and RPE had the lowest values following the AWU and the highest values following the PWU (

Estimation of errors in force platform data.

Force platforms (FPs) are regularly used in the biomechanical analysis of sport and exercise techniques, often in combination with image-based motion analysis (e.g., Begg & Kamruzzaman, 2005; Kuitunen, Komi, & Kyrolainen, 2002; Rahmani, Dalleau, Viale, Hautier, & Lacour, 2000; Rodano & Squadrone, 2002). Force time data, particularly when combined with joint positions and segmental inertia parameters, can be used to evaluate the effectiveness of a wide range of movement patterns in sport and exercise (Bartlett, Messenger, & Lindsay, 1997). According to Dainty and Norman (1987) and Bartlett et al. (1997), valid and reliable force measures depend on low threshold, hysteresis and cross-talk, high linearity, adequate sensitivity and the elimination of cable interference, electrical inductance, and temperature and humidity variations. Moreover, a platform must possess high stiffness and high natural frequency and be located such that extraneous vibrations are excluded. Given that FPs are regularly used in sport and exercise research not only for data collection but also for evaluating other biomechanical equipment (e.g., Rahmani et al., 2000), the lack of attention paid to the likelihood of errors in their measurements is somewhat surprising. Although the scientific literature for kinematic data has established and consistently reported the estimation and propagation of errors, FP data are often taken as error-free. For example, Johnson and Buckley (2001) used a FP to measure ground reaction forces during sprinting, without calculating or reporting possible errors in FP data. Reporting FP data to an unjustifiably high precision and assuming they are acceptably accurate is potentially problematic. For example, when the force data are used for further calculations, such as estimating joint moments from external forces, the error in the force measures will propagate through the calculation--especially in the absence of postprocessing techniques--and directly affect the final result. Some investigators, however, have tried to assess the accuracy and reliability of their measurements. Bobbert and Schamhardt (1990) and Mita et al. (1993) found inaccuracies in estimates of the center of pressure position, especially toward the platform edges, and identified poor calibration and differences in the individual characteristics among the load cell amplifiers as possible causes. Although FP calibration data are usually available from manufacturers, researchers should not assume the manufacturer-quoted values are retained following installation and over time. Experimental error is inevitable in a study that uses FP as a data collection tool and can arise from a variety of sources, which may influence the reliability of the findings and the study's validity. Despite this, neither calibration of FP nor estimation of potential errors in FP measurements is reported in most investigations. Furthermore, because the existing methods reported in studies for FP error calculation require sophisticated equipment and are time-consuming, their application in other FP studies would be rather complicated and, in many laboratories, not possible. Therefore, the purpose of the present study was to establish the magnitude of possible measurement errors from a FP typically used in sport and exercise biomechanics, by applying an easy-to-use, rime-efficient method

Comparison of the effects of active, passive and mixed warm ups on swimming performance.

AIM: The aim of this paper was to compare the effects of an active (AWU), passive (PWU) and mixed warm up (MWU) on swimming performance. METHODS: Eight male competitive swimmers completed each type of WU and, following a 20-minute rest, performed a maximum 100m test on their specialised stroke. The order of WUs was randomized and there was a 7-day period between subsequent testing sessions. The time taken to complete the 100m trial was the performance measure. The rating of perceived exertion (RPE) was measured immediately post WU, while heart rate (HR) was measured pre and post WU and pre and post the maximum swim. During the 20-minute rest, the swimmers' psychological state was assessed with the CSAI-2 questionnaire. RESULTS: Post WU HR and RPE had the lowest values following the AWU and the highest values following the PWU (