Biomaterials and biophysical stimuli for bone regeneration.

First, we review basic concepts of Tissue Engineering, that is, how the tensegrity is able to modulate the cell behavior. Then, we review our experimental results regarding the bone tissue engineering via biomaterials and bioreactors.

Wool fibril sponges with perspective biomedical applications.

Sheep's wool was used as a natural source to prepare keratin microfibril sponges for scaffolding, by disruption of the histological structure of the fibres through mild alkali treatment, followed by ultrasonication, casting and salt-leaching. The wool sponges showed highly interconnected porosity (93%) and contain intrinsic sites of cellular recognition that mimic the extracellular matrix (ECM). They displayed good thermal and water stability due to the conversion of disulphide cystine bonds into shorter monosulphide lanthionine intermolecular bonds, but significantly swelled in water, because of the high hydrophilicity and porosity, with a volume increasing up to 38%. Nevertheless, sponges were stable in water without structural changes, with a neutral pH in aqueous media, and showed excellent resilience to repeated compression stresses. According to in vitro biocompatibility assays, wool fibril sponges showed a good cell adhesion and proliferation as proved by MTT, FDA assays and SEM observations. The unique structure of the cortical cell network made by wool keratin proteins with controlled-size macro-porosity suitable for cell guesting, and nutrient feeding, provides an excellent scaffold for future tissue engineering applications.

Comparison of data mining techniques applied to fetal heart rate parameters for the early identification of IUGR fetuses.

The onset of fetal pathologies can be screened during pregnancy by means of Fetal Heart Rate (FHR) monitoring and analysis. Noticeable advances in understanding FHR variations were obtained in the last twenty years, thanks to the introduction of quantitative indices extracted from the FHR signal. This study searches for discriminating Normal and Intra Uterine Growth Restricted (IUGR) fetuses by applying data mining techniques to FHR parameters, obtained from recordings in a population of 122 fetuses (61 healthy and 61 IUGRs), through standard CTG non-stress test. We computed N=12 indices (N=4 related to time domain FHR analysis, N=4 to frequency domain and N=4 to non-linear analysis) and normalized them with respect to the gestational week. We compared, through a 10-fold crossvalidation procedure, 15 data mining techniques in order to select the more reliable approach for identifying IUGR fetuses. The results of this comparison highlight that two techniques (Random Forest and Logistic Regression) show the best classification accuracy and that both outperform the best single parameter in terms of mean AUROC on the test sets.

Multivariate analysis based on linear and non-linear FHR parameters for the identification of IUGR fetuses.

Fetal Heart Rate (FHR) monitoring represents a powerful tool for checking the arousal of pathological fetal conditions during pregnancy. This paper proposes a multivariate approach for the discrimination of Normal and Intra Uterine Growth Restricted (IUGR) fetuses based on a small set of parameters computed on the FHR signal. We collected FHR recordings in a population of 120 fetuses (60 normals and 60 IUGRs) at approximately the same gestational week through a standard CTG non-stress test. A set of 8 linear and non-linear indices were selected and computed on each recording, on the basis of their "stand-alone" discriminative properties, demonstrated in previous studies. By using the Orange® data mining suite we checked various multivariate discrimination models. The results show that a Logistic Regression performed on a limited set of only 4 parameters can reach 92.5% accuracy in the correct identification of fetuses, with 93% sensitivity and 91.5% specificity.

High-Frequency Vibration Treatment of Human Bone Marrow Stromal Cells Increases Differentiation toward Bone Tissue.

In order to verify whether differentiation of adult stem cells toward bone tissue is promoted by high-frequency vibration (HFV), bone marrow stromal cells (BMSCs) were mechanically stimulated with HFV (30 Hz) for 45 minutes a day for 21 or 40 days. Cells were seeded in osteogenic medium, which enhances differentiation towards bone tissue. The effects of the mechanical treatment on differentiation were measured by Alizarin Red test, (q) real-time PCR, and protein content of the extracellular matrix. In addition, we analyzed the proliferation rate and apoptosis of BMSC subjected to mechanical stimulation. A strong increase in all parameters characterizing differentiation was observed. Deposition of calcium was almost double in the treated samples; the expression of genes involved in later differentiation was significantly increased and protein content was higher for all osteogenic proteins. Lastly, proliferation results indicated that stimulated BMSCs have a decreased growth rate in comparison with controls, but both treated and untreated cells do not enter the apoptosis process. These findings could reduce the gap between research and clinical application for bone substitutes derived from patient cells by improving the differentiation protocol for autologous cells and a further implant of the bone graft into the patient.

Electromagnetic stimulation to optimize the bone regeneration capacity of gelatin-based cryogels.

One of the key challenges in reconstructive bone surgery is to provide living constructs that possess the ability to integrate in the surrounding host tissue. Bone graft substitutes and biomaterials have already been widely used to heal critical-size bone defects due to trauma, tumor resection and tissue degeneration. In the present study, gelatin-based cryogels have been seeded with human SAOS-2 osteoblasts followed by the in vitro culture of the cells. In order to overcome the drawbacks associated with static culture systems, including limited diffusion and in homogeneous cell-matrix distribution, the present work describes the application of a bioreactor to physically enhance the cell culture in vitro using an electromagnetic stimulus. The results indicate that the physical stimulation of cell-seeded gelatin-based cryogels upregulates the bone matrix production. We anticipate that the scaffolds developed consisting of human bone proteins and cells could be applied for clinical purposes related to bone repair.

AUTOCOUNTER, an ImageJ JavaScript to analyze LC3B-GFP expression dynamics in autophagy-induced astrocytoma cells.

An ImageJ JavaScript, AUTOCOUNTER, was specifically developed to monitor and measure LC3B-GFP expression in living human astrocytoma cells, namely T98G and U373-MG. Discrete intracellular GFP fluorescent spots derived from transduction of a Baculovirus replication-defective vector (BacMam LC3B-GFP), followed by microscope examinations at different times. After viral transgene expression, autophagy was induced by Rapamycin administration and assayed in ph-p70S6K/p70S6K and LC3B immunoblotting expression as well as by electron microscopy examinations. A mutated transgene, defective in LC3B lipidation, was employed as a negative control to further exclude fluorescent dots derived from protein intracellular aggregation. The ImageJ JavaScript was then employed to evaluate and score the dynamics changes of the number and area of LC3B-GFP puncta per cell in time course assays and in complex microscope examinations. In conclusion, AUTOCOUNTER enabled to quantify LC3B-GFP expression and to monitor dynamics changes in number and shapes of autophagosomal-like vesicles: it might therefore represent a suitable algorithmic tool for in vitro autophagy modulation studies.

Effects of electromagnetic stimulation on osteogenic differentiation of human mesenchymal stromal cells seeded onto gelatin cryogel.

Bone tissue engineering typically uses biomaterial scaffolds, osteoblasts or cells that can become osteoblasts, and biophysical stimulations to promote cell attachment and differentiation. In this study, we investigated the effects of an electromagnetic wave on mesenchymal stromal cells isolated from the bone marrow and seeded upon gelatin cryogel disks. In comparison with control conditions without electromagnetic stimulus, the electromagnetic treatment (magnetic field, 2 mT; frequency, 75 Hz) increased the cell proliferation and differentiation and enhanced the biomaterial surface coating with bone extracellular matrix proteins. Using this tissue-engineering approach, the gelatin biomaterial, coated with differentiated cells and their extracellular matrix proteins, may be used in clinical applications as an implant for bone defect repair.

The differentiation of human adipose-derived stem cells (hASCs) into osteoblasts is promoted by low amplitude, high frequency vibration treatment.

Several studies have demonstrated that tissue culture conditions influence the differentiation of human adipose-derived stem cells (hASCs). Recently, studies performed on SAOS-2 and bone marrow stromal cells (BMSCs) have shown the effectiveness of high frequency vibration treatment on cell differentiation to osteoblasts. The aim of this study was to evaluate the effects of low amplitude, high frequency vibrations on the differentiation of hASCs toward bone tissue. In view of this goal, hASCs were cultured in proliferative or osteogenic media and stimulated daily at 30Hz for 45min for 28days. The state of calcification of the extracellular matrix was determined using the alizarin assay, while the expression of extracellular matrix and associated mRNA was determined by ELISA assays and quantitative RT-PCR (qRT-PCR). The results showed the osteogenic effect of high frequency vibration treatment in the early stages of hASC differentiation (after 14 and 21days). On the contrary, no additional significant differences were observed after 28days cell culture. Transmission Electron Microscopy (TEM) images performed on 21day samples showed evidence of structured collagen fibers in the treated samples. All together, these results demonstrate the effectiveness of high frequency vibration treatment on hASC differentiation toward osteoblasts.

Advances in monitoring cardiovascular signals. Contribution of nonlinear signal processing.

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their status, thus providing necessary interventions in time. To obtain this important objective it is necessary to integrate technological development with systems performing biomedical knowledge extraction and classification. Methods extracting non linear characteristics from HRV signal are presented and discussed to stress that integrated and multiparametric signal processing approaches can contribute to new diagnostic and classification indices. Examples report heart rate variability analysis in long periods in patients with cardiovascular disease. Fetal ECG monitoring is another example. In this case, coupling nonlinear parameters and linear time and frequency techniques increases diagnostic power and reliability of the monitoring. The paper shows that integrated signal analysis is very helpful to describe pathophysiological mechanisms involved in the cardiovascular and neural system control. It is a reliable basis to set up knowledge-based monitoring systems.

Telefetalcare: a first prototype of a wearable fetal electrocardiograph.

Fetal heart rate monitoring is fundamental to infer information about fetal health state during pregnancy. The cardiotocography (CTG) is the most common antepartum monitoring technique. Abdominal ECG recording represents the most valuable alternative to cardiotocography, as it allows passive, non invasive and long term fetal monitoring. Unluckily fetal ECG has low SNR and needs to be extracted from abdominal recordings using ad hoc algorithms. This work describes a prototype of a wearable fetal ECG electrocardiograph. The system has flat band frequency response between 1-60 Hz and guarantees good signal quality. It was tested on pregnant women between the 30(th) and 34(th) gestational week. Several electrodes configurations were tested, in order to identify the best solution. Implementation of a simple algorithm for FECG extraction permitted the reliable detection of maternal and fetal QRS complexes. The system will allow continuative and deep screening of fetal heart rate, introducing the possibility of home fetal monitoring.

Biosensing and environmental sensing for emergency and protection e-Textiles.

The ProeTEX project introduced for the first time a complete set of smart garments integrating sensors for the physiological and environmental monitoring of emergency operators. These "smart" garments have been deeply tested in emergency-like contexts by professional rescuers, in order to assess real-time acquisition, processing and transmission of data from moving subjects while operating in harsh conditions. Here we report an overview of the main results obtained during field trials performed in 2010 by Italian and French professional firefighters, in specialized training centers, while dressing the ProeTEX prototypes. Results clearly demonstrate the benefit and step forward of such a system in order to monitor and coordinate rescuers even during intervention far away from the emergency headquarter.

Modeling and simulation of ultrasound fields generated by 2D phased array transducers for medical applications.

Modern ultrasound imaging instrumentation for clinical applications allows real-time volumetric scanning of the patients' body. 4D imaging has been made possible thanks to the development of new echographic probes which consist in 2D phased arrays of piezoelectric transducers. In these new devices it is the system electronics which properly drives the matrix elements and focuses the beam in order to obtain a sequence of volumetric images. This paper introduces an ultrasound field simulator based on the Spatial Impulse Response method which is being properly developed to analyze the characteristics of the ultrasound field generated by a 2D phased array of transducers. Thanks to its high configurability by the user, it will represent a very useful tool for electronics designers in developing 4D ultrasound imaging systems components.

Heart rate and accelerometer data fusion for activity assessment of rescuers during emergency interventions.

The current state of the art in wearable electronics is the integration of very small devices into textile fabrics, the so-called ¿smart garment.¿ The ProeTEX project is one of many initiatives dedicated to the development of smart garments specifically designed for people who risk their lives in the line of duty such as fire fighters and Civil Protection rescuers. These garments have integrated multipurpose sensors that monitor their activities while in action. To this aim, we have developed an algorithm that combines both features extracted from the signal of a triaxial accelerometer and one ECG lead. Microprocessors integrated in the garments detect the signal magnitude area of inertial acceleration, step frequency, trunk inclination, heart rate (HR), and HR trend in real time. Given these inputs, a classifier assigns these signals to nine classes differentiating between certain physical activities (walking, running, moving on site), intensities (intense, mild, or at rest) and postures (lying down, standing up). Specific classes will be identified as dangerous to the rescuer during operation, such as, ¿subject motionless lying down¿ or ¿subject resting with abnormal HR.¿ Laboratory tests were carried out on seven healthy adult subjects with the collection of over 4.5 h of data. The results were very positive, achieving an overall classification accuracy of 88.8%.

Bio-inspired controller for a dexterous prosthetic hand based on Principal Components Analysis.

Controlling a dexterous myoelectric prosthetic hand with many degrees of freedom (DoFs) could be a very demanding task, which requires the amputee for high concentration and ability in modulating many different muscular contraction signals. In this work a new approach to multi-DoF control is proposed, which makes use of Principal Component Analysis (PCA) to reduce the DoFs space dimensionality and allow to drive a 15 DoFs hand by means of a 2 DoFs signal. This approach has been tested and properly adapted to work onto the underactuated robotic hand named CyberHand, using mouse cursor coordinates as input signals and a principal components (PCs) matrix taken from the literature. First trials show the feasibility of performing grasps using this method. Further tests with real EMG signals are foreseen.

Comparison between fetal heart rate standard parameters and complexity indexes for the identification of severe intrauterine growth restriction.

OBJECTIVES: The intrauterine growth restriction (IUGR) is a pathological state: the fetus is at risk of hypoxia and this condition is associated with increased perinatal morbidity and mortality. However, evidence-based guidelines for clinical surveillance are poor and lack reliable indexes. This study introduces new procedures to extract parameters from the fetal heart rate signal in order to identify severe intrauterine growth restricted (IUGR) fetuses METHODS: Standard parameters (time domain and frequency domain indexes) are compared to a new parameter, the Lempel Ziv complexity, and to two regularity estimators (approximate entropy and sample entropy). The paper analyzes the robustness of the indexes coming from the parameter extraction procedure. RESULTS AND CONCLUSIONS: The results show that the LZ complexity is a stable parameter and it is able to significantly discriminate the severe IUGR (preterm delivered) from moderate IUGR (at term delivered) and from healthy fetuses.

Surface modification of a porous polyurethane through a culture of human osteoblasts and an electromagnetic bioreactor.

There is increasing interest in new biomaterials and new culture methods for bone tissue engineering, in order to produce, in vitro, living constructs able to integrate in the surrounding tissue. Using an electromagnetic bioreactor (magnetic field intensity, 2 mT; frequency, 75 Hz), we investigated the effects of electromagnetic stimulation on SAOS-2 human osteoblasts seeded onto a porous polyurethane. In comparison with control conditions, the electromagnetic stimulation caused higher cell proliferation, increased surface coating with decorin and type-I collagen, and higher calcium deposition. The immunolocalization of decorin and type-I collagen showed their colocalization in the cell-rich areas. The use of an electromagnetic bioreactor aimed at obtaining the surface modification of the porous polyurethane in terms of cell colonization and coating with calcified matrix. The superficially modified biomaterial could be used, in clinical applications, as an implant for bone repair.

An internal model of self-motion based on inertial signals.

The question of how the central nervous system can distinguish tilt with respect to gravity from inertial acceleration due to translation in a horizontal plane using vestibular information has long been debated by the scientific community over the past ten years. Recently, it was hypothesized that such discrimination may be based on the multisensory integration of information provided by the otolith organs and the semicircular canals. Some evidence of such processing was found in the neural activity of cells in the fastigial nuclei and vestibular nuclei. To investigate the ability of the central nervous system to build an internal model of self motion based on vestibular signals, we developed an artificial vestibular sensor composed of accelerometers and gyroscopes providing movement data of the same nature as that transduced by the otoliths and canals, respectively. Here we show that the processing of these signals based on the multisensory integration hypothesis can be successfully used to discriminate tilt from translation and that the internal model based on such processing can successfully track angular and linear displacements over short periods of time.

Automatic classification of heartbeats using neural network classifier based on a Bayesian framework.

This paper presents a method of automatic processing the electrocardiogram (ECG) signal for the classification of heart beats. Data were obtained from 48 records of the MIT-BIH arrhythmia database (only one lead). Five types of arrhythmic beats were classified using our method, Premature Ventricular Conduction beat (PVC), Atrial Premature Conduction beat (APC), Right Bundle Branch Block beat (RBBB), Left Bundle Branch Block beat (LBBB), and Paced Rhythm Beat (PRB), in addition to the Normal Beat (NB). A learning dataset for the neural network was obtained from a five records set (124, 214, 111, 100, and 107) which were manually classified using MIT-BIH Arrhythmia Database Directory and documentation, taking advantage of the professional experience of a cardiologist. Feature set was based on ECG morphology and time intervals. Our system resulted in a minimal sensitivity of 86% and minimal specificity of 90%

Self-similarity behavior characterization of fetal heart rate signal in healthy and intrauterine growth retarded fetuses.

In this paper we deal with the problem of the interpretation of the fetal heart rate (FHR) signal. From literature is known that FHR contains both linear and non linear components. Starting from this consideration we analyzed FHR as a fractal time series and we evaluated its self similarity behavior using the Hurst's coefficient (H). We first evaluated the stationarity of FHR time series and then we estimated H with Detrend fluctuation analysis (DFA) method. We calculated Hurst's coefficient for healthy fetuses and for fetuses affected by Intrauterine grow retardation (IUGR). Results provided H = 0.350 +/- 0.064 (avg +/- std) for healthy patients and H = 0.461 +/- 0.059 for IUGR. It is also shown that IUGR patients exhibit a "less non-stationary" and longer-memory behavior than normals with a reduced information content of FHR signal. We propose for this phenomenon a physiological explanation connected with the abnormal autonomic nervous system development of IUGR patients.