Morphological and functional study of cerebral aging in rat

Aging is a physiological process characterized by a progressive decline of the “cellular homeostatic reserve”, refereed as the capability to respond suitably to exogenous and endogenous stressful stimuli. Due to their high energetic requests and post-mitotic nature, neurons are peculiarly susceptible to this phenomenon. However, the aged brain maintains a certain level of adaptive capacities and if properly stimulated may warrant a considerable functional recovery. Aim of the present research was to verify the plastic potentialities of the aging brain of rats subjected to two kind of exogenous stimuli: A) the replacement of the standard diet with a ketogenic regimen (the change forces the brain to use ketone bodies (KB) in alternative to glucose to satisfy the energetic needs) and B) a behavioural task able to induce the formation of inhibitory avoidance memory. A) Fifteen male Wistar rats of 19 months of age were divided into three groups (average body weight pair-matched), and fed for 8 weeks with different dietary regimens: i) diet containing 10% medium chain triglycerides (MCT); ii) diet containing 20% MCT; iii) standard commercial chow. Five young (5 months of age) and five old (26-27 months of age) animals fed with the standard diet were used as further controls. The following morphological parameters reflecting synaptic plasticity were evaluated in the stratum moleculare of the hippocampal CA1 region (SM CA1), in the outer molecular layer of the hippocampal dentate gyrus (OML DG), and in the granule cell layer of the cerebellar cortex (GCL-CCx): average area (S), numeric density (Nvs), and surface density (Sv) of synapses, and average volume (V), numeric density (Nvm), and volume density (Vv) of synaptic mitochondria. Moreover, succinic dehydrogenase (SDH) activity was cytochemically determined in Purkinje cells (PC) and V, Nvm, Vv, and cytochemical precipitate area/mitochondrial area (R) of SDH-positive mitochondria were evaluated. In SM CA1, MCT-KDs induced the early appearance of the morphological patterns typical of old animals: higher S and V, and lower Nvs and Nvm. On the contrary, in OML DG, Sv and Vv of MCT-KDs-fed rats were higher (as a result of higher Nvs and Nvm) vs. controls; these modifications are known to improve synaptic function and metabolic supply. The opposite effects of MCT-KDs might reflect the different susceptibility of these brain regions to the aging processes: OML DG is less vulnerable than SM CA1, and the reactivation of ketone bodies uptake and catabolism might occur more efficiently in this region, allowing the exploitation of their peculiar metabolic properties. In GCL-CCx, the results described a new scenario in comparison to that found in the hippocampal formation: 10%MCT-KD induced the early appearance of senescent patterns (decreased Nvs and Nvm; increased V), whereas 20%MCT-KD caused no changes. Since GCL-CCx is more vulnerable to age than DG, and less than CA1, these data further support the hypothesis that MCT-KDs effects in the aging brain critically depend on neuronal vulnerability to age, besides MCT percentage. Regarding PC, it was decided to evaluate only the metabolic effect of the dietetic regimen (20%MCT-KD) characterized by less side effects. KD counteracted age-related decrease in numeric density of SDH-positive mitochondria, and enhanced their energetic efficiency (R was significantly higher in MCT-KD-fed rats vs. all the controls). Since it is well known that Purkinje and dentate gyrus cells are less vulnerable to aging than CA1 neurons, these results corroborate our previous hypothesis. In conclusion, the A) experimental line provides the first evidence that morphological and functional parameters reflecting synaptic plasticity and mitochondrial metabolic competence may be modulated by MCT-KDs in the pre-senescent central nervous system, and that the effects may be heterogeneous in different brain regions. MCT-KDs seem to supply high energy metabolic intermediates and to be beneficial (“anti-aging”) for those neurons that maintain the capability to exploit them. This implies risks but also promising potentialities for the therapeutic use of these diets during aging B) Morphological parameters of synapses and synaptic mitochondria in SM CA1 were investigated in old (26-27 month-old) female Wistar rats following a single trial inhibitory avoidance task. In this memory protocol animals learn to avoid a dark compartment in which they received a mild, inescapable foot-shock. Rats were tested 3 and 6 or 9 hours after the training, divided into good and bad responders according to their performance (retention times above or below 100 s, respectively) and immediately sacrificed. Nvs, S, Sv, Nvm, V, and Vv were evaluated. In the good responder group, the numeric density of synapses and mitochondria was significantly higher and the average mitochondrial volume was significantly smaller 9 hours vs. 6 hours after the training. No significant differences were observed among bad responders. Thus, better performances in passive avoidance memory task are correlated with more efficient plastic remodeling of synaptic contacts and mitochondria in hippocampal CA1. These findings indicate that maintenance of synaptic plastic reactivity during aging is a critical requirement for preserving long-term memory consolidation.

Interaction between APOE4 genotype and environmental risk factors in Alzheimer's disease

Alzheimer's disease (AD) is probably caused by both genetic and environmental risk factors. The major genetic risk factor is the E4 variant of apolipoprotein E gene called apoE4. Several risk factors for developing AD have been identified including lifestyle, such as dietary habits. The mechanisms behind the AD pathogenesis and the onset of cognitive decline in the AD brain are presently unknown. In this study we wanted to characterize the effects of the interaction between environmental risk factors and apoE genotype on neurodegeneration processes, with particular focus on behavioural studies and neurodegenerative processes at molecular level. Towards this aim, we used 6 months-old apoE4 and apoE3 Target Replacement (TR) mice fed on different diets (high intake of cholesterol and high intake of carbohydrates). These mice were evaluated for learning and memory deficits in spatial reference (Morris Water Maze (MWM)) and contextual learning (Passive Avoidance) tasks, which involve the hippocampus and the amygdala, respectively. From these behavioural studies we found that the initial cognitive impairments manifested as a retention deficit in apoE4 mice fed on high carbohydrate diet. Thus, the genetic risk factor apoE4 genotype associated with a high carbohydrate diet seems to affect cognitive functions in young mice, corroborating the theory that the combination of genetic and environmental risk factors greatly increases the risk of developing AD and leads to an earlier onset of cognitive deficits. The cellular and molecular bases of the cognitive decline in AD are largely unknown. In order to determine the molecular changes for the onset of the early cognitive impairment observed in the behavioural studies, we performed molecular studies, with particular focus on synaptic integrity and Tau phosphorylation. The most relevant finding of our molecular studies showed a significant decrease of Brain-derived Neurotrophic Factor (BDNF) in apoE4 mice fed on high carbohydrate diet. Our results may suggest that BDNF decrease found in apoE4 HS mice could be involved in the earliest impairment in long-term reference memory observed in behavioural studies. The second aim of this thesis was to study possible involvement of leptin in AD. There is growing evidence that leptin has neuroprotective properties in the Central Nervous System (CNS). Recent evidence has shown that leptin and its receptors are widespread in the CNS and may provide neuronal survival signals. However, there are still numerous questions, regarding the molecular mechanism by which leptin acts, that remain unanswered. Thus, given to the importance of the involvement of leptin in AD, we wanted to clarify the function of leptin in the pathogenesis of AD and to investigate if apoE genotype affect leptin levels through studies in vitro, in mice and in human. Our findings suggest that apoE4 TR mice showed an increase of leptin in the brain. Leptin levels are also increased in the cerebral spinal fluid of AD patients and apoE4 carriers with AD have higher levels of leptin than apoE3 carriers. Moreover, leptin seems to be expressed by reactive glial cells in AD brains. In vitro, ApoE4 together with Amyloid beta increases leptin production by microglia and astrocytes. Taken together, all these findings suggest that leptin replacement might not be a good strategy for AD therapy. Our results show that high leptin levels were found in AD brains. These findings suggest that, as high leptin levels do not promote satiety in obese individuals, it might be possible that they do not promote neuroprotection in AD patients. Therefore, we hypothesized that AD brain could suffer from leptin resistance. Further studies will be critical to determine whether or not the central leptin resistance in SNC could affect its potential neuroprotective effects.

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Spatial mechanisms for modelling the human ankle passive motion

Knowledge on how ligaments and articular surfaces guide passive motion at the human ankle joint complex is fundamental for the design of relevant surgical treatments. The dissertation presents a possible improvement of this knowledge by a new kinematic model of the tibiotalar articulation. In this dissertation two one-DOF spatial equivalent mechanisms are presented for the simulation of the passive motion of the human ankle joint: the 5-5 fully parallel mechanism and the fully parallel spherical wrist mechanism. These mechanisms are based on the main anatomical structures of the ankle joint, namely the talus/calcaneus and the tibio/fibula bones at their interface, and the TiCaL and CaFiL ligaments. In order to show the accuracy of the models and the efficiency of the proposed procedure, these mechanisms are synthesized from experimental data and the results are compared with those obtained both during experimental sessions and with data published in the literature. Experimental results proved the efficiency of the proposed new mechanisms to simulate the ankle passive motion and, at the same time, the potentiality of the mechanism to replicate the ankle’s main anatomical structures quite well. The new mechanisms represent a powerful tool for both pre-operation planning and new prosthesis design.

Global scale investigation of cirrus clouds properties using active and passive sensors

A year of satellite-borne lidar CALIOP data is analyzed and statistics on occurrence and distribution of bulk properties of cirri are provided. The relationship between environmental and cloud physical parameters and the shape of the backscatter profile (BSP) is investigated. It is found that CALIOP BSP is mainly affected by cloud geometrical thickness while only minor impacts can be attributed to other quantities such as optical depth or temperature. To fit mean BSPs as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. It is demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile. The IWC parameterization is included into the RT-RET retrieval algorithm, that is exploited to analyze infrared radiance measurements in presence of cirrus clouds during the ECOWAR field campaign. Retrieved microphysical and optical properties of the observed cloud are used as input parameters in a forward RT simulation run over the 100-1100 cm-1 spectral interval and compared with interferometric data to test the ability of the current single scattering properties database of ice crystal to reproduce realistic optical features. Finally a global scale investigation of cirrus clouds is performed by developing a collocation algorithm that exploits satellite data from multiple sensors (AIRS, CALIOP, MODIS). The resulting data set is utilized to test a new infrared hyperspectral retrieval algorithm. Retrieval products are compared to data and in particular the cloud top height (CTH) product is considered for this purpose. A better agreement of the retrieval with the CALIOP CTH than MODIS is found, even if some cases of underestimation and overestimation are observed.

The Dynamics of Passive Torsional Fatigue Test Rigs: Innovative Applications of Universal Joints

The dynamics of a passive back-to-back test rig have been characterised, leading to a multi-coordinate approach for the analysis of arbitrary test configurations. Universal joints have been introduced into a typical pre-loaded back-to-back system in order to produce an oscillating torsional moment in a test specimen. Two different arrangements have been investigated using a frequency-based sub-structuring approach: the receptance method. A numerical model has been developed in accordance with this theory, allowing interconnection of systems with two-coordinates and closed multi-loop schemes. The model calculates the receptance functions and modal and deflected shapes of a general system. Closed form expressions of the following individual elements have been developed: a servomotor, damped continuous shaft and a universal joint. Numerical results for specific cases have been compared with published data in literature and experimental measurements undertaken in the present work. Due to the complexity of the universal joint and its oscillating dynamic effects, a more detailed analysis of this component has been developed. Two models have been presented. The first represents the joint as two inertias connected by a massless cross-piece. The second, derived by the dynamic analysis of a spherical four-link mechanism, considers the contribution of the floating element and its gyroscopic effects. An investigation into non-linear behaviour has led to a time domain model that utilises the Runge-Kutta fourth order method for resolution of the dynamic equations. It has been demonstrated that the torsional receptances of a universal joint, derived using the simple model, result in representation of the joint as an equivalent variable inertia. In order to verify the model, a test rig has been built and experimental validation undertaken. The variable inertia of a universal joint has lead to a novel application of the component as a passive device for the balancing of inertia variations in slider-crank mechanisms.

Mental states monitoring through passive Brain-Computer Interface systems

The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.

Perceiving the 3d world from single images

Depth represents a crucial piece of information in many practical applications, such as obstacle avoidance and environment mapping. This information can be provided either by active sensors, such as LiDARs, or by passive devices like cameras. A popular passive device is the binocular rig, which allows triangulating the depth of the scene through two synchronized and aligned cameras. However, many devices that are already available in several infrastructures are monocular passive sensors, such as most of the surveillance cameras. The intrinsic ambiguity of the problem makes monocular depth estimation a challenging task. Nevertheless, the recent progress of deep learning strategies is paving the way towards a new class of algorithms able to handle this complexity. This work addresses many relevant topics related to the monocular depth estimation problem. It presents networks capable of predicting accurate depth values even on embedded devices and without the need of expensive ground-truth labels at training time. Moreover, it introduces strategies to estimate the uncertainty of these models, and it shows that monocular networks can easily generate training labels for different tasks at scale. Finally, it evaluates off-the-shelf monocular depth predictors for the relevant use case of social distance monitoring, and shows how this technology allows to overcome already existing strategies limitations.

Towards automation of constellation management with analytical models for collision avoidance

The growing interest for constellation of small, less expensive satellites is bringing space junk and traffic management to the attention of space community. At the same time, the continuous quest for more efficient propulsion systems put the spotlight on electric (low thrust) propulsion as an appealing solution for collision avoidance. Starting with an overview of the current techniques for conjunction assessment and avoidance, we then highlight the possible problems when a low thrust propulsion is used. The need for accurate propagation model shows up from the conducted simulations. Thus, aiming at propagation models with low computational burden, we study the available models from the literature and propose an analytical alternative to improve propagation accuracy. The model is then tested in the particular case of a tangential maneuver. Results show that the proposed solution significantly improve on state of the art methods and is a good candidate to be used in collision avoidance operations. For instance to propagate satellite uncertainty or optimizing avoidance maneuver when conjunction occurs within few (3-4) orbits from measurements time.