Sleep deprivation and brain energy metabolism : in vivo studies in rats and humans

Sleep deprivation leads to increased subsequent sleep length and depth and to deficits in cognitive performance in humans. In animals extreme sleep deprivation is eventually fatal. The cellular and molecular mechanisms causing the symptoms of sleep deprivation are unclear. This thesis was inspired by the hypothesis that during wakefulness brain energy stores would be depleted, and they would be replenished during sleep. The aim of this thesis was to elucidate the energy metabolic processes taking place in the brain during sleep deprivation. Endogenous brain energy metabolite levels were assessed in vivo in rats and in humans in four separate studies (Studies I-IV). In the first part (Study I) the effects of local energy depletion on brain energy metabolism and sleep were studied in rats with the use of in vivo microdialysis combined with high performance liquid chromatography. Energy depletion induced by 2,4-dinitrophenol infusion into the basal forebrain was comparable to the effects of sleep deprivation: both increased extracellular concentrations of adenosine, lactate, and pyruvate, and elevated subsequent sleep. This result supports the hypothesis of a connection between brain energy metabolism and sleep. The second part involved healthy human subjects (Studies II-IV). Study II aimed to assess the feasibility of applying proton magnetic resonance spectroscopy (1H MRS) to study brain lactate levels during cognitive stimulation. Cognitive stimulation induced an increase in lactate levels in the left inferior frontal gyrus, showing that metabolic imaging of neuronal activity related to cognition is possible with 1H MRS. Study III examined the effects of sleep deprivation and aging on the brain lactate response to cognitive stimulation. No physiologic, cognitive stimulation-induced lactate response appeared in the sleep-deprived and in the aging subjects, which can be interpreted as a sign of malfunctioning of brain energy metabolism. This malfunctioning may contribute to the functional impairment of the frontal cortex both during aging and sleep deprivation. Finally (Study IV), 1H MRS major metabolite levels in the occipital cortex were assessed during sleep deprivation and during photic stimulation. N-acetyl-aspartate (NAA/H2O) decreased during sleep deprivation, supporting the hypothesis of sleep deprivation-induced disturbance in brain energy metabolism. Choline containing compounds (Cho/H2O) decreased during sleep deprivation and recovered to alert levels during photic stimulation, pointing towards changes in membrane metabolism, and giving support to earlier observations of altered brain response to stimulation during sleep deprivation. Based on these findings, it can be concluded that sleep deprivation alters brain energy metabolism. However, the effects of sleep deprivation on brain energy metabolism may vary from one brain area to another. Although an effect of sleep deprivation might not in all cases be detectable in the non-stimulated baseline state, a challenge imposed by cognitive or photic stimulation can reveal significant changes. It can be hypothesized that brain energy metabolism during sleep deprivation is more vulnerable than in the alert state. Changes in brain energy metabolism may participate in the homeostatic regulation of sleep and contribute to the deficits in cognitive performance during sleep deprivation.

Spatial variation of climate and the impact of disturbances on local climate and forest recovery in northern Finland

The structure and function of northern ecosystems are strongly influenced by climate change and variability and by human-induced disturbances. The projected global change is likely to have a pronounced effect on the distribution and productivity of different species, generating large changes in the equilibrium at the tree-line. In turn, movement of the tree-line and the redistribution of species produce feedback to both the local and the regional climate. This research was initiated with the objective of examining the influence of natural conditions on the small-scale spatial variation of climate in Finnish Lapland, and to study the interaction and feedback mechanisms in the climate-disturbances-vegetation system near the climatological border of boreal forest. The high (1 km) resolution spatial variation of climate parameters over northern Finland was determined by applying the Kriging interpolation method that takes into account the effect of external forcing variables, i.e., geographical coordinates, elevation, sea and lake coverage. Of all the natural factors shaping the climate, the geographical position, local topography and altitude proved to be the determining ones. Spatial analyses of temperature- and precipitation-derived parameters based on a 30-year dataset (1971-2000) provide a detailed description of the local climate. Maps of the mean, maximum and minimum temperatures, the frost-free period and the growing season indicate that the most favourable thermal conditions exist in the south-western part of Lapland, around large water bodies and in the Kemijoki basin, while the coldest regions are in highland and fell Lapland. The distribution of precipitation is predominantly longitudinally dependent but with the definite influence of local features. The impact of human-induced disturbances, i.e., forest fires, on local climate and its implication for forest recovery near the northern timberline was evaluated in the Tuntsa area of eastern Lapland, damaged by a widespread forest fire in 1960 and suffering repeatedly-failed vegetation recovery since that. Direct measurements of the local climate and simulated heat and water fluxes indicated the development of a more severe climate and physical conditions on the fire-disturbed site. Removal of the original, predominantly Norway spruce and downy birch vegetation and its substitution by tundra vegetation has generated increased wind velocity and reduced snow accumulation, associated with a large variation in soil temperature and moisture and deep soil frost. The changed structural parameters of the canopy have determined changes in energy fluxes by reducing the latter over the tundra vegetation. The altered surface and soil conditions, as well as the evolved severe local climate, have negatively affected seedling growth and survival, leading to more unfavourable conditions for the reproduction of boreal vegetation and thereby causing deviations in the regional position of the timberline. However it should be noted that other factors, such as an inadequate seed source or seedbed, the poor quality of the soil and the intensive logging of damaged trees could also exacerbate the poor tree regeneration. In spite of the failed forest recovery at Tunsta, the position and composition of the timberline and tree-line in Finnish Lapland may also benefit from present and future changes in climate. The already-observed and the projected increase in temperature, the prolonged growing season, as well as changes in the precipitation regime foster tree growth and new regeneration, resulting in an advance of the timberline and tree-line northward and upward. This shift in the distribution of vegetation might be decelerated or even halted by local topoclimatic conditions and by the expected increase in the frequency of disturbances.

Optimisation Problems in Wireless Sensor Networks : Local Algorithms and Local Graphs

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

Measurement of the top pair production cross section in the dilepton decay channel in pp̅ collisions at √s=1.96 TeV

A measurement of the $\ttbar$ production cross section in $\ppbar$ collisions at $\sqrt{{\rm s}}$ = 1.96 TeV using events with two leptons, missing transverse energy, and jets is reported. The data were collected with the CDF II Detector. The result in a data sample corresponding to an integrated luminosity 2.8 fb$^{-1}$ is: $\sigma_{\ttbar}$ = 6.27 $\pm$ 0.73(stat) $\pm$ 0.63(syst) $\pm$ 0.39(lum) pb. for an assumed top mass of 175 GeV/$c^{2}$.

Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b-Quark Jets in pp̅ Collisions at √s=1.96 TeV

We report on a search for the standard model Higgs boson produced in association with a $W$ or $Z$ boson in $p\bar{p}$ collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb$^{-1}$. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a $b$ hadron. We find good agreement between data and predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110$\gevm$ to 150$\gevm$. For a mass of 115$\gevm$ the observed (expected) limit is 6.9 (5.6) times the standard model prediction.

Searching the inclusive ℓγE̸T+b-quark signature for radiative top quark decay and non-standard-model processes

In a search for new phenomena in a signature suppressed in the standard model of elementary particles (SM), we compare the inclusive production of events containing a lepton, a photon, significant transverse momentum imbalance (MET), and a jet identified as containing a b-quark, to SM predictions. The search uses data produced in proton-antiproton collisions at 1.96 TeV corresponding to 1.9 fb-1 of integrated luminosity taken with the CDF detector at the Fermilab Tevatron. We find 28 lepton+photon+MET+b events versus an expectation of 31.0+4.1/-3.5 events. If we further require events to contain at least three jets and large total transverse energy, simulations predict that the largest SM source is top-quark pair production with an additional radiated photon, ttbar+photon. In the data we observe 16 ttbar+photon candidate events versus an expectation from SM sources of 11.2+2.3/-2.1. Assuming the difference between the observed number and the predicted non-top-quark total is due to SM top quark production, we estimate the ttg cross section to be 0.15 +- 0.08 pb.

Molecular mechanisms of hypertension-induced heart failure : Experimental studies with special emphasis on local renin-angiotensin system, cardiac metabolism and levosimendan

Hypertension is a major risk factor for stroke, ischaemic heart disease, and the development of heart failure. Hypertension-induced heart failure is usually preceded by the development of left ventricular hypertrophy (LVH), which represents an adaptive and compensatory response to the increased cardiac workload. Biomechanical stress and neurohumoral activation are the most important triggers of pathologic hypertrophy and the transition of cardiac hypertrophy to heart failure. Non-clinical and clinical studies have also revealed derangements of energy metabolism in hypertensive heart failure. The goal of this study was to investigate in experimental models the molecular mechanisms and signalling pathways involved in hypertension-induced heart failure with special emphasis on local renin-angiotensin-aldosterone system (RAAS), cardiac metabolism, and calcium sensitizers, a novel class of inotropic agents used currently in the treatment of acute decompensated heart failure. Two different animal models of hypertensive heart failure were used in the present study, i.e. hypertensive and salt-sensitive Dahl/Rapp rats on a high salt diet (a salt-sensitive model of hypertensive heart failure) and double transgenic rats (dTGR) harboring human renin and human angiotensinogen genes (a transgenic model of hypertensive heart failure with increased local RAAS activity). The influence of angiotensin II (Ang II) on cardiac substrate utilization and cardiac metabolomic profile was investigated by using gas chromatography coupled to time-of-flight mass spectrometry to detect 247 intermediary metabolites. It was found that Ang II could alter cardiac metabolomics both in normotensive and hypertensive rats in an Ang II receptor type 1 (AT1)-dependent manner. A distinct substrate use from fatty acid oxidation towards glycolysis was found in dTGR. Altered cardiac substrate utilization in dTGR was associated with mitochondrial dysfunction. Cardiac expression of the redox-sensitive metabolic sensor sirtuin1 (SIRT1) was increased in dTGR. Resveratrol supplementation prevented cardiovascular mortality and ameliorated Ang II-induced cardiac remodeling in dTGR via blood pressure-dependent pathways and mechanisms linked to increased mitochondrial biogenesis. Resveratrol dose-dependently increased SIRT1 activity in vitro. Oral levosimendan treatment was also found to improve survival and systolic function in dTGR via blood pressure-independent mechanisms, and ameliorate Ang II-induced coronary and cardiomyocyte damage. Finally, using Dahl/Rapp rats it was demonstrated that oral levosimendan as well as the AT1 receptor antagonist valsartan improved survival and prevented cardiac remodeling. The beneficial effects of levosimendan were associated with improved diastolic function without significantly improved systolic changes. These positive effects were potentiated when the drug combination was administered. In conclusion, the present study points to an important role for local RAAS in the pathophysiology of hypertension-induced heart failure as well as its involvement as a regulator of cardiac substrate utilization and mitochondrial function. Our findings suggest a therapeutic role for natural polyphenol resveratrol and calcium sensitizer, levosimendan, and the novel drug combination of valsartan and levosimendan, in prevention of hypertension-induced heart failure. The present study also provides a better understanding of the pathophysiology of hypertension-induced heart failure, and may help identify potential targets for novel therapeutic interventions.

Local systems, global impacts : Using life cycle assessment to analyse the potential and constraints of industrial symbioses

Human activities extract and displace different substances and materials from the earth s crust, thus causing various environmental problems, such as climate change, acidification and eutrophication. As problems have become more complicated, more holistic measures that consider the origins and sources of pollutants have been called for. Industrial ecology is a field of science that forms a comprehensive framework for studying the interactions between the modern technological society and the environment. Industrial ecology considers humans and their technologies to be part of the natural environment, not separate from it. Industrial operations form natural systems that must also function as such within the constraints set by the biosphere. Industrial symbiosis (IS) is a central concept of industrial ecology. Industrial symbiosis studies look at the physical flows of materials and energy in local industrial systems. In an ideal IS, waste material and energy are exchanged by the actors of the system, thereby reducing the consumption of virgin material and energy inputs and the generation of waste and emissions. Companies are seen as part of the chains of suppliers and consumers that resemble those of natural ecosystems. The aim of this study was to analyse the environmental performance of an industrial symbiosis based on pulp and paper production, taking into account life cycle impacts as well. Life Cycle Assessment (LCA) is a tool for quantitatively and systematically evaluating the environmental aspects of a product, technology or service throughout its whole life cycle. Moreover, the Natural Step Sustainability Principles formed a conceptual framework for assessing the environmental performance of the case study symbiosis (Paper I). The environmental performance of the case study symbiosis was compared to four counterfactual reference scenarios in which the actors of the symbiosis operated on their own. The research methods used were process-based life cycle assessment (LCA) (Papers II and III) and hybrid LCA, which combines both process and input-output LCA (Paper IV). The results showed that the environmental impacts caused by the extraction and processing of the materials and the energy used by the symbiosis were considerable. If only the direct emissions and resource use of the symbiosis had been considered, less than half of the total environmental impacts of the system would have been taken into account. When the results were compared with the counterfactual reference scenarios, the net environmental impacts of the symbiosis were smaller than those of the reference scenarios. The reduction in environmental impacts was mainly due to changes in the way energy was produced. However, the results are sensitive to the way the reference scenarios are defined. LCA is a useful tool for assessing the overall environmental performance of industrial symbioses. It is recommended that in addition to the direct effects, the upstream impacts should be taken into account as well when assessing the environmental performance of industrial symbioses. Industrial symbiosis should be seen as part of the process of improving the environmental performance of a system. In some cases, it may be more efficient, from an environmental point of view, to focus on supply chain management instead.