Unravelling Molecular and Cellular Disease Mechanisms in Infantile Neuronal Ceroid Lipofuscinosis (INCL)

Studying neurodegeneration provides an opportunity to gain insights into normal cell physiology, and not just pathophysiology. In this thesis work the focus is on Infantile Neuronal Ceroid Lipofuscinosis (INCL). It is a recessively inherited lysosomal storage disorder. The disease belongs to the neuronal ceroid lipofuscinoses (NCLs), a group of common progressive neurodegenerative diseases of the childhood. Characteristic accumulation of autofluorescent storage material is seen in most tissues but only neurons of the central nervous system are damaged and eventually lost during the course of the disease leaving most other cell types unaffected. The disease is caused by mutations in the CLN1 gene, but the physiological function of the corresponding protein the palmitoyl protein thioesterase (PPT1) has remained elusive. The aim of this thesis work was to shed light on the molecular and cell biological mechanisms behind INCL. This study pinpointed the localization of PPT1 in axonal presynapses of neurons. It also established the role of PPT1 in early neuronal maturation as well as importance in mature neuronal synapses. This study revealed an endocytic defect in INCL patient cells manifesting itself as delayed trafficking of receptor and non-receptor mediated endocytic markers. Furthermore, this study was the first to connect the INCL storage proteins the sphingolipid activator proteins (SAPs) A and D to pathological events on the cellular level. Abnormal endocytic processing and intracellular re-localization was demonstrated in patient cells and disease model knock-out mouse neurons. To identify early affected cellular and metabolic pathways in INCL, knock-out mouse neurons were studied by global transcript profiling and functional analysis. The gene expression analysis revealed changes in neuronal maturation and cell communication strongly associated with the regulated secretory system. Furthermore, cholesterol metabolic pathways were found to be affected. Functional studies with the knock-out mouse model revealed abnormalities in neuronal maturation as well as key neuronal functions including abnormalities in intracellular calcium homeostasis and cholesterol metabolism. Together the findings, introduced in this thesis work, support the essential role of PPT1 in developing neurons as well as synaptic sites of mature neurons. Results of this thesis also elucidate early events in INCL pathogenesis revealing defective pathways ultimately leading to the neurodegenerative process. These results contribute to the understanding of the vital physiological function of PPT1 and broader knowledge of common cellular mechanisms behind neurodegeneration. These results add to the knowledge of these severe diseases offering basis for new approaches in treatment strategies.

A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.

Automata and logics over finitely varying functions

We extend some of the classical connections between automata and logic due to Büchi (1960) [5] and McNaughton and Papert (1971) [12] to languages of finitely varying functions or “signals”. In particular, we introduce a natural class of automata for generating finitely varying functions called View the MathML source’s, and show that it coincides in terms of language definability with a natural monadic second-order logic interpreted over finitely varying functions Rabinovich (2002) [15]. We also identify a “counter-free” subclass of View the MathML source’s which characterise the first-order definable languages of finitely varying functions. Our proofs mainly factor through the classical results for word languages. These results have applications in automata characterisations for continuously interpreted real-time logics like Metric Temporal Logic (MTL) Chevalier et al. (2006, 2007) [6] and [7].

Cellular and molecular regulation of mammalian blastocyst hatching

In mammals including humans, failure in blastocyst hatching and implantation leads to early embryonic loss and infertility. Prior to implantation, the blastocyst must hatch out of its acellular glycoprotein coat, the zona pellucida (ZP). The phenomenon of blastocyst hatching is believed to be regulated by (i) dynamic cellular components such as actin-based trophectodermal projections (TEPs), and (ii) a variety of autocrine and paracrine molecules such as growth factors, cytokines and proteases. The spatio-temporal regulation of zona lysis by blastocyst-derived cellular and molecular signaling factors is being keenly investigated. Our studies show that hamster blastocyst hatching is acelerated by growth factors such as heparin binding-epidermal growth factor and leukemia inhibitory factor and that embryo-derived, cysteine proteases including cathepsins are responsible for blastocyst hatching. Additionally, we believe that cyclooxygenase-generated prostaglandins, estradiol-17 beta mediated estrogen receptor-alpha signaling and possibly NF kappa B could be involved in peri-hatching development. Moreover, we show that TEPs are intimately involved with lysing ZP and that the TEPs potentially enrich and harbor hatching-enabling factors. These observations provide new insights into our understanding of the key cellular and molecular regulators involved in the phenomenon of mammalian blastocyst hatching, which is essential for the establishment of early pregnancy.

Downregulation of microRNA-498 in colorectal cancers and its cellular effects

miR-498 is a non-coding RNA located intergenically in 19q13.41. Due to its predicted targeting of several genes involved in control of cellular growth, we examined the expression of miR-498 in colon cancer cell lines and a large cohort of patients with colorectal adenocarcinoma. Two colon cancer cancer cell lines (SW480 and SW48) and one normal colonic epithelial cell line (FHC) were recruited. The expression of miR-498 was tested in these cell lines by using quantitative real-time polymerase chain reaction (qRT-PCR). Tissues from 80 patients with surgical resection of colorectum (60 adenocarcinomas and 20 non-neoplastic tissues) were tested for miR-498 expression by qRT-PCR. In addition, an exogenous miR-498 (mimic) was used to detect the miRNA׳s effects on cell proliferation and cell cycle events in SW480 using MTT calorimetric assay and flow cytometry respectively. The colon cancer cell lines showed reduced expression of miR-498 compared to a normal colonic epithelial cell line. Mimic driven over expression of miR-498 in the SW480 cell line resulted in reduced cell proliferation and increased proportions of G2-M phase cells. In tissues, miR-498 expression was too low to be detected in all colorectal adenocarcinoma compared to non-neoplastic tissues. This suggests that the down regulation of miR-498 in colorectal cancer tissues and the direct suppressive cellular effect noted in cancer cell lines implies that miR-498 has some direct or indirect role in the pathogenesis of colorectal adenocarcinomas.

Uplink Power Control and Base Station Association in Multichannel Cellular Networks

A combined base station association and power control problem is studied for the uplink of multichannel multicell cellular networks, in which each channel is used by exactly one cell (i.e., base station). A distributed association and power update algorithm is proposed and shown to converge to a Nash equilibrium of a noncooperative game. We consider network models with discrete mobiles (yielding an atomic congestion game), as well as a continuum of mobiles (yielding a population game). We find that the equilibria need not be Pareto efficient, nor need they be system optimal. To address the lack of system optimality, we propose pricing mechanisms. It is shown that these mechanisms can be implemented in a distributed fashion.

Optimal non-linear reinforcement schemes for stochastic automata

Two optimal non-linear reinforcement schemes—the Reward-Inaction and the Penalty-Inaction—for the two-state automaton functioning in a stationary random environment are considered. Very simple conditions of symmetry of the non-linear function figuring in the reinforcement scheme are shown to be necessary and sufficient for optimality. General expressions for the variance and rate of learning are derived. These schemes are compared with the already existing optimal linear schemes in the light of average variance and average rate of learning.

An Estimator Algorithm For Learning Automata With Changing Number Of Actions

In many problems of decision making under uncertainty the system has to acquire knowledge of its environment and learn the optimal decision through its experience. Such problems may also involve the system having to arrive at the globally optimal decision, when at each instant only a subset of the entire set of possible alternatives is available. These problems can be successfully modelled and analysed by learning automata. In this paper an estimator learning algorithm, which maintains estimates of the reward characteristics of the random environment, is presented for an automaton with changing number of actions. A learning automaton using the new scheme is shown to be e-optimal. The simulation results demonstrate the fast convergence properties of the new algorithm. The results of this study can be extended to the design of other types of estimator algorithms with good convergence properties.

Simultaneous effect of lead and cadmium on granulosa cells: A cellular model for ovarian toxicity

Lead (Pb) and cadmium (Cd) are known reproductive toxicants, which accumulate in granulosa cells of the ovary. Female Charles foster rats were treated with sodium acetate (control), lead acetate and cadmium acetate either alone or in combination at a dose 0.05 mg/kg body weight intra-peritoneally for 15 days daily. Animals were killed at proestrous stage and granulosa cells were isolated from the ovaries. Binding of I-125-luteinizing hormone (I-125-LH), I-125-follicle stimulating hormone (I-125-FSH) and 17 beta-hydroxysteroid dehydrogenase activity were measured. As these receptors are localized on the surface of the cell membrane, we also estimated the membrane parameters of these cells. Our results demonstrated that both lead and cadmium caused a significant reduction in gonadotropin binding, which altered steroidogenic enzyme activity of granulosa cells. These changes exhibited a positive correlation with membrane changes of the granulosa cells.

Genetic Heterogeneity in Wild Isolates of Cellular Slime Mold Social Groups

This study addresses the issues of spatial distribution, dispersal, and genetic heterogeneity in social groups of the cellular slime molds (CSMs). The CSMs are soil amoebae with an unusual life cycle that consists of alternating solitary and social phases. Because the social phase involves division of labor with what appears to be an extreme form of "altruism", the CSMs raise interesting evolutionary questions regarding the origin and maintenance of sociality. Knowledge of the genetic structure of social groups in the wild is necessary for answering these questions. We confirm that CSMs are widespread in undisturbed forest soil from South India. They are dispersed over long distances via the dung of a variety of large mammals. Consistent with this mode of dispersal, most social groups in the two species examined for detailed study, Dictyostelium giganteum and Dictyostelium purpureum, are multi-clonal.

A Cellular Array for Multivalued Logic Functions

An algebraic generalization of the well-known binary q-function array to a multivalued q-function array is presented. It is possible to associate tree-structure realizations for binary q-functions and multivalued q-functions. Synthesis of multivalued functions using this array is very simple