Pattern recognition of sleep in rodents using piezoelectric signals generated by gross body movements.

Current research on sleep using experimental animals is limited by the expense and time-consuming nature of traditional EEG/EMG recordings. We present here an alternative, noninvasive approach utilizing piezoelectric films configured as highly sensitive motion detectors. These film strips attached to the floor of the rodent cage produce an electrical output in direct proportion to the distortion of the material. During sleep, movement associated with breathing is the predominant gross body movement and, thus, output from the piezoelectric transducer provided an accurate respiratory trace during sleep. During wake, respiratory movements are masked by other motor activities. An automatic pattern recognition system was developed to identify periods of sleep and wake using the piezoelectric generated signal. Due to the complex and highly variable waveforms that result from subtle postural adjustments in the animals, traditional signal analysis techniques were not sufficient for accurate classification of sleep versus wake. Therefore, a novel pattern recognition algorithm was developed that successfully distinguished sleep from wake in approximately 95% of all epochs. This algorithm may have general utility for a variety of signals in biomedical and engineering applications. This automated system for monitoring sleep is noninvasive, inexpensive, and may be useful for large-scale sleep studies including genetic approaches towards understanding sleep and sleep disorders, and the rapid screening of the efficacy of sleep or wake promoting drugs.

CERN-MEDICIS: une nouvelle infrastructure pour la production de radioisotopes a usage medical [CERN-MEDICIS (Medical Isotopes Collected from ISOLDE): a new facility].

CERN-MEDICIS (Medical Isotopes Collected from ISOLDE) est une plateforme de recherche destinée à la production de radioisotopes biomédicaux. Inauguré en 2014, il produira progressivement un nombre croissant de radioisotopes grâce au faisceau de protons ISOLDE déjà existant. Ce projet réunit des spécialistes du cancer, des chirurgiens, des experts en médecine nucléaire, en radiochimie et radiopharmacie et les scientifiques du CERN. Les radioisotopes ainsi produits seront destinés à la recherche fondamentale contre le cancer, à des études précliniques ainsi qu'au développement de protocoles d'imagerie et de thérapie destinés aux patients.Le CERN, les HUG, le CHUV, l'ISREC et l'EPFL qui soutiennent ce projet seront les premiers bénéficiaires de ces radioisotopes novateurs dont la distribution sera ensuite étendue à d'autres centres européens. CERN-MEDICIS is a facility dedicated to research and development in life science and medical applications. The research platform was inaugurated in October 2014 and will produce an increasing range of innovative isotopes using the proton beam of ISOLDE for fundamental studies in cancer research, for new imaging and therapy protocols in cell and animal models and for preclinical trials, possibly extended to specific early phase clinical studies (phase 0) up to phase I trials. CERN, the University Hospital of Geneva (HUG), the University Hospital of Lausanne (CHUV), the Swiss Institute for Experimental Cancer (ISREC) at Swiss Federal Institutes of Technology (EPFL) that currently support the project will benefit of the initial production that will then be extended to other centers.

In vivo measurement of tissue oxygenation by time-resolved luminescence spectroscopy: advantageous properties of dichlorotris(1, 10-phenanthroline)-ruthenium(II) hydrate.

Measuring tissue oxygenation in vivo is of interest in fundamental biological as well as medical applications. One minimally invasive approach to assess the oxygen partial pressure in tissue (pO2) is to measure the oxygen-dependent luminescence lifetime of molecular probes. The relation between tissue pO2 and the probes' luminescence lifetime is governed by the Stern-Volmer equation. Unfortunately, virtually all oxygen-sensitive probes based on this principle induce some degree of phototoxicity. For that reason, we studied the oxygen sensitivity and phototoxicity of dichlorotris(1, 10-phenanthroline)-ruthenium(II) hydrate [Ru(Phen)] using a dedicated optical fiber-based, time-resolved spectrometer in the chicken embryo chorioallantoic membrane. We demonstrated that, after intravenous injection, Ru(Phen)'s luminescence lifetime presents an easily detectable pO2 dependence at a low drug dose (1 mg∕kg) and low fluence (120 mJ∕cm2 at 470 nm). The phototoxic threshold was found to be at 10 J∕cm2 with the same wavelength and drug dose, i.e., about two orders of magnitude larger than the fluence necessary to perform a pO2 measurement. Finally, an illustrative application of this pO2 measurement approach in a hypoxic tumor environment is presented.

Chances and risks of nanomaterials for health and environment

Nanomaterials have properties that are often very different from normal materials made of the same substance, which can be used to create novel products with exciting properties. However, the health and environmental impact of these nanomaterials is also changed and their potential risk needs to be studied. There is evidence that some nanomaterials can pass through tissue barriers (including the blood-brain barrier) and cell membranes. This is interesting for medical applications, but it raises concerns about the impact of non-medical nanomaterials. Current research aims at better coordinating research efforts and at better communication between researchers and involved stakeholders. Many research labs and production sites currently follow strategies that were established for dealing with very toxic chemicals and powders, until future research in this field helps identify the appropriate level of protection. All these efforts will ultimately ensure a safe, healthy and environmental friendly production, use and disposal of nanomaterials.

Ambulatory monitoring of physical activities in patients with Parkinson's disease.

A new ambulatory method of monitoring physical activities in Parkinson's disease (PD) patients is proposed based on a portable data-logger with three body-fixed inertial sensors. A group of ten PD patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) and ten normal control subjects followed a protocol of typical daily activities and the whole period of the measurement was recorded by video. Walking periods were recognized using two sensors on shanks and lying periods were detected using a sensor on trunk. By calculating kinematics features of the trunk movements during the transitions between sitting and standing postures and using a statistical classifier, sit-to-stand (SiSt) and stand-to-sit (StSi) transitions were detected and separated from other body movements. Finally, a fuzzy classifier used this information to detect periods of sitting and standing. The proposed method showed a high sensitivity and specificity for the detection of basic body postures allocations: sitting, standing, lying, and walking periods, both in PD patients and healthy subjects. We found significant differences in parameters related to SiSt and StSi transitions between PD patients and controls and also between PD patients with and without STN-DBS turned on. We concluded that our method provides a simple, accurate, and effective means to objectively quantify physical activities in both normal and PD patients and may prove useful to assess the level of motor functions in the latter.

Atlas-based segmentation of pathological brain MR images

We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.

Monitoring of posture allocations and activities by a shoe-based wearable sensor.

Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) without significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.

Synthetic RGD-containing alpha-helical coiled coil peptides promote integrin-dependent cell adhesion.

Integrin receptors are the main mediators of cell adhesion to the extracellular matrix. They bind to their ligands by interacting with short amino acid sequences, such as the RGD sequence. Soluble, small RGD-based peptides have been used to block integrin-binding to ligands, thereby interfering with cell adhesion, migration and survival, while substrate-immobilized RGD sequences have been used to enhance cell binding to artificial surfaces. This approach has several important medical applications, e.g. in suppression of tumor angiogenesis or stimulation of bone formation around implants. However, the relatively weak affinity of short RGD-containing peptides often results in incomplete integrin inhibition or ineffective ligation. In this work, we designed and synthesized several new multivalent RGD-containing molecules and tested their ability to inhibit or to promote integrin-dependent cell adhesion when used in solution or immobilized on substrates, respectively. These molecules consist of an oligomeric structure formed by alpha-helical coiled coil peptides fused at their amino-terminal ends with an RGD-containing fragment. When immobilized on a substrate, these peptides specifically promoted integrin alphaVbeta3-dependent cell adhesion, but when used in solution, they blocked alphaVbeta3-dependent cell adhesion to the natural substrates fibronectin and vitronectin. One of the peptides was nearly 10-fold more efficient than fibronectin or vitronectin in promoting cell adhesion, and almost 100-fold more efficient than a linear RGD tripeptide in blocking adhesion. These results indicate that alpha-helical coiled coil peptides carrying an amino-terminal RGD motif can be used as soluble antagonists or surface-immobilized agonists to efficiently inhibit or promote integrin alphaVbeta3-mediated cell adhesion, respectively.

Landmark detection for fusion of fundus and MRI toward a patient-specific multimodal eye model.

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes.

A new method of measuring joint angle using a combination of accelerometers and gyroscopes is presented. The method proposes a minimal sensor configuration with one sensor module mounted on each segment. The model is based on estimating the acceleration of the joint center of rotation by placing a pair of virtual sensors on the adjacent segments at the center of rotation. In the proposed technique, joint angles are found without the need for integration, so absolute angles can be obtained which are free from any source of drift. The model considers anatomical aspects and is personalized for each subject prior to each measurement. The method was validated by measuring knee flexion-extension angles of eight subjects, walking at three different speeds, and comparing the results with a reference motion measurement system. The results are very close to those of the reference system presenting very small errors (rms = 1.3, mean = 0.2, SD = 1.1 deg) and excellent correlation coefficients (0.997). The algorithm is able to provide joint angles in real-time, and ready for use in gait analysis. Technically, the system is portable, easily mountable, and can be used for long term monitoring without hindrance to natural activities.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.