In today’s aging population, cerebrovascular health plays a pivotal role in maintaining independence. The identification of early markers of change might help to plan more appropriate preventative and/or therapeutic measures. Recent focus has been placed on the relationship between peripheral vascular characteristics and cerebral hemodynamics. Given the compliant nature of the cerebral circulation, examination of passive properties, including critical closing pressure (CrCP) and resistance area product (RAP), might provide sensitive information about early functional changes. The purpose of this thesis was to provide a comprehensive view of peripheral vascular and cerebrovascular regulation in community-living older adults. In doing so, the thesis covered a spectrum, ranging from an examination of lifestyle factors, including habitual physical activity and sleep quality, to the impact of cerebrovascular health on functional status, characterized by gait speed. Key findings included the observation that while participants showed the ability to regulate cerebral blood flow (CBF) appropriately in most circumstances, the underlying mechanisms used to achieve this regulation was dependent on baseline vascular tone. During sit-to-stand transitions, individuals with lower baseline resistance relied primarily on fluctuations in RAP, which have been suggested to more closely reflect myogenic pathways. In contrast, individuals with elevated resistance had lower baseline CBF and relied relatively more on fluctuations in CrCP during the dynamic transition. The greater reliance on CrCP might indicate that these individuals were required to tap further into reserve pools to avoid hypoperfusion during the transition. Notably, those who exhibited a smaller dynamic RAP response during the posture change also had slower gait speed and higher occurrence of falls over the past year. These results provide evidence that passive cerebrovascular dynamics are sensitive markers linking peripheral and cerebrovascular properties with functional consequences for brain health in the elderly.

The har1-1 mutant of Lotus japonicus line Gifu is characterised by increased nodulation and significantly inhibited root growth in the presence of its microsymbiont Mesorhizoboium loti (for example strain NZP2235). A sexual cross between the mutant and another L. japonicus genotype Funakura (with wild-type root and nodule morphology) demonstrated Mendelian recessive segregation of both phenotypes (for root and nodule) in 242 F2 individuals. No separation of phenotypes was observed, suggesting a single mutation with pleiotropic effects. Reciprocal grafting showed that the har1-1 controlled phenotype is governed by the shoot. Using a skeletal genetic map of arbitrary molecular markers produced from a Gifu x Funakura cross, the har1-1 locus was positioned between two markers at about 7 and 13 cM distance. Single nucleotide polymorphisms (SNPs) and transgene sequences were detected by allele-specific PCR in DNA isolated from small (1 mg mass) individual seeds and half-cotyledon of the model legume Lotus japonicus, allowing fast determination of a seedling’s genomic status. This permitted a shortening of the breeding cycle for multi-trait seed lines. Fast neutron mutagenesis of Lotus japonicus wild-type genotype Gifu resulted in the first time isolation of a stable mutant (FNN5-2) unable to form nitrogen-fixing nodules in symbiosis with Mesorhizobium loti, though being infected by mycorrhizal fungi. The mutation behaves as a loss-of-function recessive, and has no other apparent phenotypic effects. Molecular characterization indicates a partial loss of the LjNFR1 LysM type receptor kinase gene. Additionally part of the LjNIN gene (encoding a putative transcription factor needed for nodulation) is also missing. Transcript levels for both genes are severely reduced. As LjNIN and LjNFR1 are in the same chromosomal region we tested whether this terminal portion is lacking. PCR analysis confirms that genes within the relevant interval (such as LjPAL1 (encoding phenylalanine ammonia lyase) and LjEIL2 (encoding an ethylene insensitive-like response regulator)) are present, suggesting that the mutational event induced by the fast neutrons was either a double hit coincidently involving two nodulation-related genes, a major genome rearrangement, or a major segmental inversion. To develop an integrated nodule developmental model based on gene interactions in autoregulation, nodulation and plant hormone response deficient lines, HE double mutants have been built using the har1-1 mutant (hypernodulation and aberrant root) and the ethylene insensitive transgenic line Etr1-1. The homozygous loss-of-function mutant har1-1 has increased nodulation and decreased root growth. Ethylene insensitivity mediated by the transgene 35S::AtETR1-1 restores the normal root growth. The HE double mutants were confirmed by triple response test and allele- or gene-specific PCR. The current results in this study indicate that a) HE double mutants shown the same nodulation pattern as har1-1 and normal root formation as Etr1-1, suggesting that nodule and root control diverge at some stage with root control being ethylene-mediated and the Har1 gene, the orthologue of GmNARK is involved in nodulation. b) Grafting demonstrated that the shoot is the source of ethylene suppression of the har1-1 induced inhibition of root growth. c) The mutated Etr1-1 gene was able to replace AVG in BAP root inhibition; d) IPT-dependent cytokinin overproduction led to aberrant root architecture in har1-1; e) Crosstalk between ethylene and cytokinin in HE double mutant by qRT-PCR.

Intracranial monitoring after severe traumatic brain injury offers the possibility for early detection and amelioration of physiological insults. In this thesis, I explore cerebral insults due raised intracranial pressure, decreased cerebral perfusion pressure and impaired cerebral pressure reactivity after traumatic brain injury. In chapter 2, the importance of intracranial pressure, cerebral perfusion pressure and pressure reactivity in regulating the cerebral circulation is elucidated along with a summary of the existing evidence supporting intracranial monitoring in traumatic brain injury. In chapter 4, intracranial pressure, cerebral perfusion pressure, and pressure reactivity insults are demonstrated to be common, prognostically important, and responsive to long-term changes in management policies. Further, while these insults often occur independently, coexisting insults portend worse prognosis. In chapter 5, I examine possible imaging antecedents of raised intracranial pressure and demonstrate that initial subarachnoid haemorrhage is associated with the subsequent development of elevated intracranial pressure. In addition, elevated glucose during the intensive care stay is associated with worse pressure reactivity. Cortical blood flow and brain tissue oxygenation are demonstrated to be sensitive to increases in intracranial pressure in chapter 6. In chapter 7, a method is proposed to estimate the cerebral perfusion pressure limits of reactivity in real-time, which may allow for more nuanced intensive care treatment. Finally, I explore a recently developed visualisation technique for intracranial physiological insults and apply it to the cerebral perfusion pressure limits of reactivity. Taken together, this thesis outlines the scope, risk factors and consequences of intracranial insults after severe traumatic brain injury. Novel signal processing applications are presented that may serve to facilitate a physiological, personalised and precision approach to patient therapy.

The role of CEA for stroke prevention in the presence of symptomatic carotid artery stenosis is well established. In order to maximize the benefit of surgery, several perioperative processes of care have been under scrutiny, of which one is the choice of anaesthetic method. The differing effects of GA vs. LA on the cerebral circulation after CEA may be of significance, since changes in the cerebral circulation post-CEA may give rise to cerebral hyperperfusion and intracerebral haemorrhage. This work assessed the effect of GA vs. LA on cerebral haemodynamic control after CEA using transcranial Doppler (TCD) techniques, and correlated these changes with serum markers of cerebral injury. Subjects undergoing CEA had perioperative TCD monitoring of middle cerebral artery blood flow velocity (MCAV). Pre- and postoperative (within 48 hours of surgery) testing of cerebral autoregulation [CA] (tilt-testing) and cerebral vasoreactivity to CO2 [CVR] (rebreathing expired air) was conducted. Cerebral haemodynamic parameters and clinical outcome were correlated with changes in jugular venous and peripheral levels of protein S100β and neurone-specific enolase (NSE).The change in CA and CVR was not different between GA (n=16) and LA (n=20). Overall, CA and CVR improved significantly within 48 hours of CEA for patients with preoperative impairment of these parameters, although some patients with normal baseline CA and CVR exhibited postoperative impairment. Increase of MCAV >100% from baseline after restoration of carotid blood flow was observed in patients with impaired CVR, but resolved by the first postoperative day. Transient elevation in jugular venous (but not peripheral) S100β during surgery was seen. Both jugular and peripheral NSE levels dropped during surgery. Neither anaesthetic method nor CA or CVR status had any effect on changes in serum S100β or NSE. Cerebral autoregulatory parameters thus improve rapidly after CEA, but appear unaffected by anaesthetic technique. This supports the concept that cerebral hyperperfusion is dependent on factors in addition to impaired CA or CVR. Changes in serum S100β or NSE do not reflect cerebral haemodynamic changes. However, the variability encountered between patients warrants further investigation. The implications for clinical practice and directions for further research are discussed.

Institutional organizations are characterized by countless states and processes which take different values over time. This behaviour expressed by a change is a response to impulses and dynamics of external as well as internal environment. The changes may take different character, some of them can have a negative or almost destructive effect and therefore it is necessary to prevent such states. An adequate tool for reduction of these negative processes is management representing fundamental methods and activities for administration of an organization. Since the interpretation of the word management is broad, the main goal of the paper is to find such a concept of administration, which is not only a set of isolated activities, but puts facts into context. Such defined concept should adequately signalize possible changes of a state and evaluate them before they lead to cumulative and synergistic effects. A particular solution is seen in the autoregulation of an organization, which mainly on the principle of causal dependence and feedback can determine its further behaviour. This phenomenon may be considered common with open systems but for the purpose of this paper it is necessary to identify if it is possible to organize a system so that it is able to provide feedback expected and also if it is able to adapt the system in time. In order to fulfil the goals stated above some organisational principles have been formulated. They enable organizations to make use of autoregulation on the basis of available information of theoretical as well as practical nature. Then this concept is applied in a specific environment of an institutional organization and then it is verified if autoregulational mechanisms can effectively not only support and maintain a state of an organization if adequately arranged, but also activate a continuous process of a change, which have been demonstrated in practical applications.

Le mécanisme de production des protéines, qui monopolise la majorité des ressources d'une bactérie, est hautement stochastique: chaque réaction biochimique qui y participe est due à des collisions aléatoires entre molécules, potentiellement présentes en petites quantités. La bonne compréhension de l'expression génétique nécessite donc de recourir à des modèles stochastiques qui sont à même de caractériser les différentes origines de la variabilité dans la production ainsi que les dispositifs biologiques permettant éventuellement de la contrôler.Dans ce contexte, nous avons analysé la variabilité d'une protéine produite avec un mécanisme d'autorégulation négatif: c'est-à-dire dans le cas où la protéine est un répresseur pour son propre gène. Le but est de clarifier l'effet de l'autorégulation sur la variance du nombre de protéines exprimées. Pour une même production moyenne de protéine, nous avons cherché à comparer la variance à l'équilibre d'une protéine produite avec le mécanisme d'autorégulation et celle produite en « boucle ouverte ». En étudiant un modèle limite, avec une mise à l'échelle (scaling), nous avons pu faire une telle comparaison de manière analytique. Il apparaît que l'autorégulation réduit effectivement la variance, mais cela reste néanmoins limité : un résultat asymptotique montre que la variance ne pourra pas être réduite de plus de 50%. L'effet sur la variance à l'équilibre étant modéré, nous avons cherché un autre effet possible de l'autorégulation: nous avons observé que la vitesse de convergence à l'équilibre est plus rapide dans le cadre d'un modèle avec autorégulation.Les modèles classiques de production des protéines considèrent un volume constant, sans phénomènes de division ou de réplication du gène, avec des ARN-polymérases et les ribosomes en concentrations constantes. Pourtant, les variation au cours du cycle de chacune de ces quantités a été proposée dans la littérature comme participant à la variabilité des protéines. Nous proposons une série de modèles de complexité croissante qui vise à aboutir à une représentation réaliste de l'expression génétique. Dans un modèle avec un volume suivant le cycle cellulaire, nous intégrons successivement le mécanisme de production des protéines (transcription et traduction), la répartition aléatoire des composés à la division et la réplication du gène. Le dernier modèle intègre enfin l'ensemble des gènes de la cellule et considère leurs interactions dans la production des différentes protéines à travers un partage commun des ARN-polymérases et des ribosomes, présents en quantités limitées. Pour les modèles où cela était possible, la moyenne et la variance de la concentration de chacune des protéines ont été déterminées analytiquement en ayant eu recours au formalisme des Processus Ponctuels de Poisson Marqués. Pour les cas plus complexes, nous avons estimé la variance au moyen de simulations stochastiques. Il apparaît que, dans l'ensemble des mécanismes étudiés, la source principale de la variabilité provient du mécanisme de production des protéines lui-même (bruit dit « intrinsèque »). Ensuite, parmi les autres aspects « extrinsèques », seule la répartition aléatoire des composés semble avoir potentiellement un effet significatif sur la variance; les autres ne montrent qu'un effet limité sur la concentration des protéines. Ces résultats ont été confrontés à certaines mesures expérimentales, et montrent un décalage encore inexpliqué entre la prédiction théorique et les données biologiques, ce qui appelle à de nouvelles hypothèses quant aux possibles sources de variabilité.En conclusion, les processus étudiés ont permis une meilleure compréhension des phénomènes biologiques en explorant certaines hypothèses difficilement testables expérimentalement. Des modèles étudiés, nous avons pu dégager théoriquement certaines tendances, montrant que la modélisation stochastique est un outil important pour la bonne compréhension des mécanismes d'expression génétique. / The mechanism of protein production, to which is dedicated the majority of resources of the bacteria, is highly stochastic: every biochemical reaction that is involved in this process is due to random collisions between molecules, potentially present in low quantities. The good understanding of gene expression requires therefore to resort to stochastic models that are able to characterise the different origins of protein production variability as well as the biological devices that potentially control it.In this context, we have analysed the variability of a protein produced with a negative autoregulation mechanism: i.e. in the case where the protein is a repressor of its own gene. The goal is to clarify the effect of this feedback on the variance of the number of produced proteins. With the same average protein production, we sought to compare the equilibrium variance of a protein produced with the autoregulation mechanism and the one produced in “open loop”. By studying the model under a scaling regime, we have been able to perform such comparison analytically. It appears that the autoregulation indeed reduces the variance; but it is nonetheless limited: an asymptotic result shows that the variance won't be reduced by more than 50%. The effect on the variance being moderate, we have searched for another possible effect for autoregulation: it havs been observed that the convergence to equilibrium is quicker in the case of a model with autoregulation.Classical models of protein production usually consider a constant volume, without any division or gene replication and with constant concentrations of RNA-polymerases and ribosomes. Yet, it has been suggested in the literature that the variations of these quantities during the cell cycle may participate to protein variability. We propose a series of models of increasing complexity that aims to reach a realistic representation of gene expression. In a model with a changing volume that follows the cell cycle, we integrate successively the protein production mechanism (transcription and translation), the random segregation of compounds at division, and the gene replication. The last model integrates then all the genes of the cell and takes into account their interactions in the productions of different proteins through a common sharing of RNA-polymerases and ribosomes, available in limited quantities. For the models for which it was possible, the mean and the variance of the concentration of each proteins have been analytically determined using the Marked Poisson Point Processes. In the more complex cases, we have estimated the variance using computational simulations. It appears that, among all the studied mechanisms, the main source of variability comes from the protein production mechanism itself (referred as “intrinsic noise”). Then, among the other “extrinsic” aspects, only the random segregation of compounds at division seems to have potentially a significant impact on the variance; the other aspects show only a limited effect on protein concentration. These results have been confronted to some experimental measures, and show a still unexplained decay between the theoretical predictions and the biological data; it instigates the formulations of new hypotheses for other possible sources of variability.To conclude, the processes studied have allowed a better understanding of biological phenomena by exploring some hypotheses that are difficult to test experimentally. In the studied models, we have been able to indicate theoretically some trends; hence showing that the stochastic modelling is an important tool for a good understanding of gene expression mechanisms.

Indiana University-Purdue University Indianapolis (IUPUI) / Glaucoma is a multi-factorial ocular disease associated with death of retinal ganglion cells and irreversible vision loss. Many risk factors contribute to glaucomatous damage, including elevated intraocular pressure (IOP), age, genetics, and other diseases such as diabetes and systemic hypertension. Interestingly, alterations in retinal hemodynamics have also been associated with glaucoma. A better understanding of the factors that contribute to these hemodynamic alterations could lead to improved and more appropriate clinical approaches to manage and hopefully treat glaucoma patients. In this thesis, we develop several mathematical models aimed at describing ocular hemodynamics and oxygenation in health and disease. Precisely we describe: (i) a time-dependent mathematical model for the retinal circulation that includes macrocirculation, microcirculation, phenomenological vascular regulation, and the mechanical effect of IOP on the retinal vasculature; (ii) a steady-state mathematical model for the retinal circulation that includes macrocirculation, microcirculation, mechanistic vascular regulation, the effect of IOP on the central retinal artery and central retinal vein, and the transport of oxygen in the retinal tissue using a Krogh cylinder type model; (iii) a steady-state mathematical model for the transport of oxygen in the retinal microcirculation and tissue based on a realistic retinal anatomy; and (iv) a steady-state mathematical model for the production and drainage of aqueous humor (AH). The main objective of this work is to study the relationship between IOP, systemic blood pressure, and the functionality of vascular autoregulation; the transport and exchange of oxygen in the retinal vasculature and tissue; and the production and drainage of AH, that contributes to the level of IOP. The models developed in this thesis predict that (i) the autoregulation plateau occurs for different values of IOP in hypertensive and normotensive patients. Thus, the level of blood pressure and functionality of autoregulation affect the changes in retinal hemodynamics caused by IOP and might explain the inconsistent outcomes of clinical studies; (ii) the metabolic and carbon dioxide mechanisms play a major role in the vascular regulation of the retina. Thus, the impairment of either of these mechanisms could cause ischemic damage to the retinal tissue; (iii) the multi-layer description of transport of oxygen in the retinal tissue accounts for the effect of the inner and outer retina, thereby improving the predictive ability of the model; (iv) a greater reduction in IOP is obtained if topical medications target AH production rather that AH drainage and if IOP-lowering medications are administrated to patients that exhibit a high initial level of IOP. Thus, the effectiveness of IOP-lowering medications depend on a patient’s value of IOP. In conclusion, the results of this thesis demonstrate that the insight provided by mathematical modeling alongside clinical studies can improve the understanding of diseases and potentially contribute to the clinical development of new treatments.

No description available.

An 23 wachen Ratten wurde die dynamische Regulation der Nierengefäße als Antwort auf schwingungsförmige Änderung des renalen Perfusionsdruckes (RPP) gemessen. Es wurden der Renale Perfusionsdruck (RPP), der Nierenarterienfluss (RBF) sowie lokale Gefäßflüsse der Nierenrinde und des äußeren Nierenmark (Laser-Doppler) aufgezeichnet und daraus die entsprechende Conductance (Leitwert) der Gefäße errechnet. Der mittlere RPP wurde rampenförmig mit einer langsamen Änderungsrate gesenkt (dp/dt), wobei nach jeder absteigenden Flanke eine aufsteigende Rampe gleicher Geschwindigkeit gemessen wurde. Eine Überlagerung des RPP mit Schwingungen unterschiedlicher Frequenz (f=0,005, f=0,01 und f=0,02 Hz) bei einer Amplitude von 20 mmHg führte zu einem Anstieg von dp/dt und einem erhöhten Shearstress an der Gefäßwand (WSS). Der Einfluss der Schwingungen auf RCV war signifikant abhängig vom mittleren RPP. So war die Conductance in tieferen Druckbereichen des RPP mehrfach höher als in den Ausgangsdruckwerten. Innerhalb der absteigenden Rampen führte ein Erhöhung der Frequenz zu einem Anstieg der maximalen Amplitude des RVC des Nierengesamtflusses. Die größten Amplituden wurden bei RPP Werten zwischen 58 und 46 mmHg gemessen. Diese Abhängigkeit war bei den ansteigenden Flanken nicht gegeben. Außerdem zeigte sich in den abfallenden Versuchsteilen ein plötzlicher Phasenwechsel zwischen der RPP- und der RVC-Schwingung bei mittleren RPP-Werten zwischen 95 und 80 mmHg. Dies lässt schließen, dass oberhalb dieses Druckwertes aktive myogenen Vasokonstriktion die passiven Gefäßdilatation vollständig ausgleicht, während unterhalb dieses RPP-Wertes die Vasokonstriktion insuffizient reagiert, bis bei ca. 50 mmHg die RCV ausschließlich der passiven Vasodilatation folgt. Höhere Schwingungsfrequenzen führen durch einen Anstieg des WSS zu einer Erhöhung der Amplitude des RVC. Dies bewirkt eine Änderung der charakteristischen renalen Autoregulation des RPP. Auf diese Weise ändert sich die Effizienz der Autoregulation. / In 23 conscious rats, the dynamic features of renal vascular conductance (RVC) in response to oscillatory changes in renal perfusion pressure (RPP) were studied at different mean RPPs. RPP, renal blood flow, and regional cortical and outer-medullary fluxes (laser-Doppler) were continuously recorded and the respective RVCs calculated. Mean RPP was changed ramp-wise with a low rate of change (dp/dt), whereby a decremental ramp was immediately followed by an incremental ramp. Superimposing RPP oscillations (amplitude 20 mmHg) of different frequencies (f=0.005, f=0.01, and f=0.02 Hz) increased maximum dp/dt, and thus increased vascular wall shear stress (WSS). The impact of RPP oscillations on RVC critically depended on mean RPP. RVC oscillations were several times higher at lower mean RPPs than at control RPP During the decremental ramps, increasing the frequency led to an increase in the maximum amplitude of total RVC, and decreased mean RPP where maximum amplitude occurred from 58 to 46 mmHg. This frequency dependence was abolished during incremental ramps. Lowering mean RPP resulted in a sudden reversal of phase between RPP and RVC oscillations at mean RPP between 95 and 80 mmHg. It is concluded that, above this RPP, myogenic vasoconstriction fully counterbalances passive vasodilatation, whereas, below that RPP, myogenic constriction gradually tapers off until, at about 50 mmHg, RVC is exclusively determined by passive dilation. Higher oscillatory frequencies, assumed to be due to increased WSS, elicit a greater response in RVC amplitude as an expression of vessel compliance, and, thus change the RPP characteristics of renal autoregulation. However, the efficiency of autoregulation is thereby barely changed.

The methods that fueled the microscale revolution (top-down design/fabrication, combined with application of forces large enough to overpower stochasticity) constitute an approach that will not scale down to nanoscale systems. In contrast, in nanotechnology, we strive to embrace nature’s quite different paradigms to create functional systems, such as self-assembly to create structures, exploiting stochasticity, rather than overwhelming it, in order to create deterministic, yet highly adaptable, behavior. Nature’s approach, through billions of years of evolutionary development, has achieved self-assembling, self-duplicating, self-healing, adaptive systems. Compared to microprocessors, nature’s approach has achieved eight orders of magnitude higher memory density and three orders of magnitude higher computing capacity while utilizing eight orders of magnitude less power. Perhaps the most complex of functions, homeostatis by a biological cell – i.e., the regulation of its internal environment to maintain stability and function – in a fluctuating and unpredictable environment, emerges from the interactions between perhaps 50M molecules of a few thousand different types. Many of these molecules (e.g. proteins, RNA) are produced in the stochastic processes of gene expression, and the resulting populations of these molecules are distributed across a range of values. So although homeostasis is maintained at the system (i.e. cell) level, there are considerable and unavoidable fluctuations at the component (protein, RNA) level. While on at least some level, we understand the variability in individual components, we have no understanding of how to integrate these fluctuating components together to achieve complex function at the system level. This thesis will explore the regulation and control of stochasticity in cells. In particular, the focus will be on (1) how genetic circuits use noise to generate more function in less space; (2) how stochastic and deterministic responses are co-regulated to enhance function at a system level; and (3) the development of high-throughput analytical techniques that enable a comprehensive view of the structure and distribution of noise on a whole organism level.