Investigating the developmental and behavioral consequences of maternal immune activation on affected offspring

Maternal infection during pregnancy increases the risk of several neuropsychiatric disorders later in life, many of which have a component of dopaminergic (DA) dysfunction, including schizophrenia, autism spectrum disorders (ASD), and attention deficit hyperactivity disorder (ADHD). The majority of DA neurons are found in the adult midbrain; as such the midbrain is a key region of interest regarding these disorders. The literature is conflicting regarding the behavioral alterations following maternal immune activation (MIA) exposure, and the cellular and molecular consequences of MIA on the developing midbrain remain to be fully elucidated. Thus, this thesis aimed to establish the consequences of acute and mild MIA on offspring dopamine-related behaviors, as well as the associated cellular and molecular disturbances of MIA on offspring midbrains. We utilized a rat model of MIA using low dose (50μg/kg, I.P.) of LPS administered at different gestational ages. Our first study indicated that MIA at later gestational ages significantly increased pro-inflammatory IL-1β expression, and reduced HSD11B2 expression in the placenta, which is an important regulator of fetal development. In utero LPS exposure at later gestational ages also impaired the growth of neurons from affected offspring. This study identified key gestational stages during which MIA resulted in differential effects. We utilized these time points in subsequent studies, the next of which investigated neurobehavioral outcomes following MIA. Our results from that study showed that motor differences occurred in juvenile offspring following MIA at E16 only, and these differences were compensated for in adolescence. Then, there was a decline in motor behavior capabilities in adulthood, again only for animals exposed to MIA on E16 (and not E12). Furthermore, our results also demonstrated adolescent and adult offspring that were exposed to MIA at E12 had diminished responses to amphetamine in reward seeking behaviors. In our final study, we aimed to investigate the molecular and cellular changes following MIA which might explain these behavioral alterations. This final study showed a differential inflammatory response in fetal midbrains depending on gestational age of exposure as well as differential developmental alterations. For example, LPS exposure at E16 resulted in decreased VM neurosphere size after 7DIV and this was associated with an increased susceptibility to neurotoxic effects of pro-inflammatory cytokines for VM neurospheres and VM DA neurons treated in culture. In utero LPS exposure at E16 also reduced DA neuron count of fetal VM, measured by TH staining. However, there were no differences in DA neuron number in juvenile, adolescent, or adult offspring. Similarly, LPS exposure did not alter cell number or morphology of glial cells in the midbrains of affected offspring. In conclusion, this thesis indicated later rat pregnancy (E16) as vulnerable time for MIA to affect the development of the nigrostriatal pathway and subsequent behavioral outcomes, possibly implicating a role for MIA in increased risk for disorders associated with motor behavior, like PD. These effects may be mediated through alterations in the placenta and altered inflammatory mediators in the offspring brain. This thesis has also shown that MIA in earlier rat pregnancy (E12) results in altered mesocorticolimbic function, and in particular MIA on E12 resulted in a differential response to amphetamine in affected offspring, which may implicate a role for MIA in increasing the risk for disorders associated with this pathway, including drug tolerance and addiction.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Hepatitis C virus modulation of lipid and autophagy pathways

Hepatitis C virus [HCV] infects 170 million people worldwide. We investigated interactions between HCV proteins and cellular proteins involved in autophagy and lipid metabolism. We sought to develop an infection model using patient derived human serum containing HCV and human hepatocytes, Huh7 cells. Using the model, we have shown intracellular expression of incoming HCV RNA (5′ UTR region and region spanning the E1/E2 glycoproteins), expression of the HCV proteins, core and NS5B, and a cellular response to HCV infection. These data suggests this model can be used to analyse the early stage of HCV infection. HCV utilises the autophagy pathway to both establish infection and to complete its life cycle. We investigated HCV interaction with the early stage autophagy protein ATG5. We found that although ATG5 mRNA is unchanged in HCV infected cells, protein expression of ATG5 is significantly upregulated. These data indicated HCV controls the post-transcriptional regulation of ATG5. We used the upstream open reading frame (uORF) and the 5′ UTR region of ATG5 to examine the post-transcriptional regulation. Our data suggest HCV RNA replication either directly or indirectly causes post-transcriptional regulation of the early autophagy protein, ATG5 in a 5′ UTR and uORF independent manner. HCV infection leads to an increase in SREBP controlled genes e.g. HMG-CoA Reductase, cholesterol, LDL and fatty acid synthesis. We hypothesised that HCV infection causes the activation of SREBP pathway by interacting directly or indirectly with proteins involved in the initiation of the pathway. We sought to determine if HCV interacts with SCAP or INSIG. We confirmed a change in LD distribution and HMG-CoA reductase activity as a result of HCV RNA replication. Significantly, we show SCAP protein expression was also altered during HCV RNA replication and HCV core protein possibly interacts with SCAP.

Wounds that heal and wounds that don't - The role of the IL-33/ST2 pathway in tissue repair and tumorigenesis

IL-33 is a member of the IL-1 family of cytokines. IL-33 is predominantly located within the nucleus of cells where it plays a role in gene regulation. Given the right combination of signals and cellular damage, stored IL-33 is released from the cell where it can interact with its receptor ST2, triggering danger-associated responses and act as a cellular "alarmin". Whilst IL-33/ST2 signalling has been shown to induce potent pro-inflammatory responses that can be detrimental in certain disease states, a dichotomous, protective role of IL-33 in promoting wound healing has also emerged in multiple tissues types. This review will explore the current literature concerning this homeostatic role of IL-33/ST2 in tissue repair and also review its role in uncontrolled wound responses as seen in both fibrosis and tumorigenesis.

Seawater carbonate chemistry and energy status in the periwinkle Littorina littorea during experiments, 2011

In the future, marine organisms will face the challenge of coping with multiple environmental changes associated with increased levels of atmospheric Pco2, such as ocean warming and acidification. To predict how organisms may or may not meet these challenges, an in-depth understanding of the physiological and biochemical mechanisms underpinning organismal responses to climate change is needed. Here, we investigate the effects of elevated Pco2 and temperature on the whole-organism and cellular physiology of the periwinkle Littorina littorea. Metabolic rates (measured as respiration rates), adenylate energy nucleotide concentrations and indexes, and end-product metabolite concentrations were measured. Compared with values for control conditions, snails decreased their respiration rate by 31% in response to elevated Pco2 and by 15% in response to a combination of increased Pco2 and temperature. Decreased respiration rates were associated with metabolic reduction and an increase in end-product metabolites in acidified treatments, indicating an increased reliance on anaerobic metabolism. There was also an interactive effect of elevated Pco2 and temperature on total adenylate nucleotides, which was apparently compensated for by the maintenance of adenylate energy charge via AMP deaminase activity. Our findings suggest that marine intertidal organisms are likely to exhibit complex physiological responses to future environmental drivers, with likely negative effects on growth, population dynamics, and, ultimately, ecosystem processes.

The white gene and locomotor recovery from anoxia in Drosophila melanogaster

Locomotor recovery from anoxia is complicated and little is known about the molecular and cellular mechanisms regulating anoxic recovery in Drosophila. For this thesis I established a protocol for large-scale analysis of locomotor activity in adult flies with exposure to a transient anoxia. Using this protocol I observed that wild-type Canton-S flies recovered faster and more consistently from anoxia than the white-eyed mutant w1118, which carries a null allele of w1118 in an isogenic genetic background. Both Canton-S and w1118 are commonly used controls in the Drosophila community. Genetic analysis including serial backcrossing, RNAi knockdown, w+ duplication to Y chromosome as well as gene mutation revealed a strong association between the white gene and the timing of locomotor recovery. I also found that the locomotor recovery phenotype is independent of white-associated eye pigmentation, that heterozygous w+ allele was haplo-insufficient to induce fast and consistent locomotor recovery from anoxia in female flies, and that mini-white is insufficient to promote fast and consistent locomotor recovery. Moreover, locomotor recovery was delayed in flies with RNAi knockdown of white in subsets of serotonin neurons in the central nervous system. I further demonstrated that mutations of phosphodiesterase genes (PDE) displayed wild-type-like fast and consistent locomotor recovery, and that locomotor recovery was light-sensitive in the night in w1118. The delayed locomotor recovery and the light sensitivity were eliminated in PDE mutants that were dual-specific or cyclic guanosine monophosphate (cGMP)-specific. Up-regulation of cGMP using multiple approaches including PDE mutation, sildenafil feeding or specific expression of an atypical soluble guanylyl cyclase (Gyc88E) was sufficient to suppress w-RNAi induced delay of locomotor recovery. Taken together, these data strongly support the hypothesis that White transports cGMP and promotes fast and consistent locomotor recovery from anoxia.

Risk factors and biomarkers of age-related macular degeneration

A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings.

Fasciola hepatica surface tegument: glycoproteins at the interface of parasite and host

Fasciola hepatica, commonly known as liver fluke, is a trematode which causes Fasciolosis in ruminants and humans. The outer tegumental coat of F. hepatica (FhTeg) is a complex metabolically active biological matrix that is continually exposed to the host immune system and therefore makes a good vaccine target. F. hepatica tegumental coat is highly glycosylated and helminth-derived immunogenic oligosaccharide motifs and glycoproteins are currently being investigated as novel vaccine candidates. This report presents the first systematic characterisation of FhTeg glycosylation using lectin microarrays to characterise carbohydrates motifs present, and lectin histochemistry to localize these on the F. hepatica tegument. We discovered that FhTeg glycoproteins are predominantly oligomannose oligosaccharides that are expressed on the spines, suckers and tegumental coat of F. hepatica and lectin blot analysis confirmed the abundance of N- glycosylated proteins. While some oligosaccharides are widely distributed on the fluke surface other subsets are restricted to distinct anatomical regions. We selectively enriched for FhTeg mannosylated glycoprotein subsets using lectin affinity chromatography and identified 369 proteins by mass spectrometric analysis. Among these proteins are a number of potential vaccine candidates with known immune modulatory properties including proteases, protease inhibitors, paramyosin, Venom Allergen-like II, Enolase and two proteins, nardilysin and TRIL, that have not been previously associated with F. hepatica Furthermore, we provide a comprehensive insight regarding the putative glycosylation of FhTeg components which could highlight the importance of further studies examining glycoconjugates in host-parasite interactions in the context of F. hepatica infection and the development of an effective vaccine.

Frequency of mutations and polymorphisms in borderline ovarian tumors of known cancer genes.

Borderline ovarian tumors represent an understudied subset of ovarian tumors. Most studies investigating aberrations in borderline tumors have focused on KRAS/BRAF mutations. In this study, we conducted an extensive analysis of mutations and single-nucleotide polymorphisms (SNPs) in borderline ovarian tumors. Using the Sequenom MassArray platform, we investigated 160 mutations/polymorphisms in 33 genes involved in cell signaling, apoptosis, angiogenesis, cell cycle regulation and cellular senescence. Of 52 tumors analyzed, 33 were serous, 18 mucinous and 1 endometrioid. KRAS c.35G>A p.Gly12Asp mutations were detected in eight tumors (six serous and two mucinous), BRAF V600E mutations in two serous tumors, and PIK3CA H1047Y and PIK3CA E542K mutations in a serous and an endometrioid BOT, respectively. CTNNB1 mutation was detected in a serous tumor. Potentially functional polymorphisms were found in vascular endothelial growth factor (VEGF), ABCB1, FGFR2 and PHLPP2. VEGF polymorphisms were the most common and detected at four loci. PHLPP2 polymorphisms were more frequent in mucinous as compared with serous tumors (P=0.04), with allelic imbalance in one case. This study represents the largest and most comprehensive analysis of mutations and functional SNPs in borderline ovarian tumors to date. At least 25% of borderline ovarian tumors harbor somatic mutations associated with potential response to targeted therapeutics.

Development and characterization of Poly(L-lactic acid) (PLLA) platforms for bone tissue engineering

The development of scaffolds based on biomaterials is a promising strategy for Tissue Engineering and cellular regeneration. This work focuses on Bone Tissue Engineering, the aim is to develop electrically tailored biomaterials with different crystalline and electric features, and study their impacts onto cell biological behavior, so as to predict the materials output in the enhancement of bone tissue regeneration. It is accepted that bone exhibits piezoelectricity, a property that has been proved to be involved in bone growth/repair mechanism regulation. In addition electrical stimulations have been proved to influence bone growth and repair. Piezoelectric materials are therefore widely investigated for a potential use in bone tissue engineering. The main goal is the development of novel strategies to produce and employ piezoelectric biomaterials, with detailed knowledge of mechanisms involved in cell-material interaction. In the current work, poly (L-lactic) acid (PLLA), a synthetic semi-crystalline polymer, exhibiting biodegradibility, biocompatibility and piezoelectricity is studied and proposed as a promoter of enhanced tissue regeneration. PLLA has already been approved for implantation in human body by the Food and Drug Administration (FDA), and at the moment it is being used in several clinical strategies. The present study consists of first preparing films with different degrees of crystallinity and characterizing these PLLA films, in terms of surface and structural properties, and subsequently assessing the behavior of cells in terms of viability, proliferation, morphology and mineralization for each PLLA configuration. PLLA films were prepared using the solvent cast technique and submitted to different thermal treatments in order to obtain different degrees of crystallinity. Those platforms were then electrically poled, positively and negatively, by corona discharge in order to tailor their electrical properties. The cellular assays were conducted by using two different osteoblast cell lines grown directly onto the PLLA films:Human osteoblast Hob, a primary cell culture and Human osteosarcoma MG-63 cell line. This thesis gives also a comprehensive introduction to the area of Bone Tissue Engineering and provides a review of the work done in this field in the past until today, in that same field, including the one related with bone’s piezoelectricity. Then the experimental part deals with the effects of the crystallinity degrees and of the polarization in terms of surface properties and cellular bio assays. Three different degrees of crystallinity, and three different polarization conditions were prepared; which results in 9 different configurations under investigation.

Nme Gene Family Evolutionary History Reveals Pre-Metazoan Origins and High Conservation between Humans and the Sea Anemone, Nematostella vectensis

Background: The Nme gene family is involved in multiple physiological and pathological processes such as cellular differentiation, development, metastatic dissemination, and cilia functions. Despite the known importance of Nme genes and their use as clinical markers of tumor aggressiveness, the associated cellular mechanisms remain poorly understood. Over the last 20 years, several non-vertebrate model species have been used to investigate Nme functions. However, the evolutionary history of the family remains poorly understood outside the vertebrate lineage. The aim of the study was thus to elucidate the evolutionary history of the Nme gene family in Metazoans. Methodology/Principal Findings: Using a total of 21 eukaryote species including 14 metazoans, the evolutionary history of Nme genes was reconstructed in the metazoan lineage. We demonstrated that the complexity of the Nme gene family, initially thought to be restricted to chordates, was also shared by the metazoan ancestor. We also provide evidence suggesting that the complexity of the family is mainly a eukaryotic innovation, with the exception of Nme8 that is likely to be a choanoflagellate/metazoan innovation. Highly conserved gene structure, genomic linkage, and protein domains were identified among metazoans, some features being also conserved in eukaryotes. When considering the entire Nme family, the starlet sea anemone is the studied metazoan species exhibiting the most conserved gene and protein sequence features with humans. In addition, we were able to show that most of the proteins known to interact with human NME proteins were also found in starlet sea anemone. Conclusion/Significance: Together, our observations further support the association of Nme genes with key cellular functions that have been conserved throughout metazoan evolution. Future investigations of evolutionarily conserved Nme gene functions using the starlet sea anemone could shed new light on a wide variety of key developmental and cellular processes.

Leveraging Multiple Features for Image Retrieval and Matching

The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task. In this work, we focus on leveraging multiple features for accurate and efficient image retrieval and matching. We first propose two graph-based approaches to rerank initially retrieved images for generic image retrieval. In the graph, vertices are images while edges are similarities between image pairs. Our first approach employs a mixture Markov model based on a random walk model on multiple graphs to fuse graphs. We introduce a probabilistic model to compute the importance of each feature for graph fusion under a naive Bayesian formulation, which requires statistics of similarities from a manually labeled dataset containing irrelevant images. To reduce human labeling, we further propose a fully unsupervised reranking algorithm based on a submodular objective function that can be efficiently optimized by greedy algorithm. By maximizing an information gain term over the graph, our submodular function favors a subset of database images that are similar to query images and resemble each other. The function also exploits the rank relationships of images from multiple ranked lists obtained by different features. We then study a more well-defined application, person re-identification, where the database contains labeled images of human bodies captured by multiple cameras. Re-identifications from multiple cameras are regarded as related tasks to exploit shared information. We apply a novel multi-task learning algorithm using both low level features and attributes. A low rank attribute embedding is joint learned within the multi-task learning formulation to embed original binary attributes to a continuous attribute space, where incorrect and incomplete attributes are rectified and recovered. To locate objects in images, we design an object detector based on object proposals and deep convolutional neural networks (CNN) in view of the emergence of deep networks. We improve a Fast RCNN framework and investigate two new strategies to detect objects accurately and efficiently: scale-dependent pooling (SDP) and cascaded rejection classifiers (CRC). The SDP improves detection accuracy by exploiting appropriate convolutional features depending on the scale of input object proposals. The CRC effectively utilizes convolutional features and greatly eliminates negative proposals in a cascaded manner, while maintaining a high recall for true objects. The two strategies together improve the detection accuracy and reduce the computational cost.

Telomeres in aging and disease: lessons from zebrafish

Age is the highest risk factor for some of the most prevalent human diseases, including cancer. Telomere shortening is thought to play a central role in the aging process in humans. The link between telomeres and aging is highlighted by the fact that genetic diseases causing telomerase deficiency are associated with premature aging and increased risk of cancer. For the last two decades, this link has been mostly investigated using mice that have long telomeres. However, zebrafish has recently emerged as a powerful and complementary model system to study telomere biology. Zebrafish possess human-like short telomeres that progressively decline with age, reaching lengths in old age that are observed when telomerase is mutated. The extensive characterization of its well-conserved molecular and cellular physiology makes this vertebrate an excellent model to unravel the underlying relationship between telomere shortening, tissue regeneration, aging and disease. In this Review, we explore the advantages of using zebrafish in telomere research and discuss the primary discoveries made in this model that have contributed to expanding our knowledge of how telomere attrition contributes to cellular senescence, organ dysfunction and disease.

Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality) frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease), and the main cells in each community. We analyze our approach in two cases: TGF-β and the Alzheimer Disease.

Molecular Characterization and Localization of the NAD(P)H Oxidase Components gp91-phox and p22-phox in Endothelial Cells

The production of reactive oxygen species (ROS) within endothelial cells may have several effects, including alterations in the activity of paracrine factors, gene expression, apoptosis, and cellular injury. Recent studies indicate that a phagocyte-type NAD(P)H oxidase is a major source of endothelial ROS. In contrast to the high-output phagocytic oxidase, the endothelial enzyme has much lower biochemical activity and a different substrate specificity (NADH.NADPH). In the present study, we (1) cloned and characterized the cDNA and predicted amino acid structures of the 2 major subunits of rat coronary microvascular endothelial cell NAD(P)H oxidase, gp91-phox and p22-phox; (2) undertook a detailed comparison with phagocytic NADPH oxidase sequences; and (3) studied the subcellular location of these subunits in endothelial cells. Although these studies revealed an overall high degree of homology (.90%) between the endothelial and phagocytic oxidase subunits, the endothelial gp91-phox sequence has potentially important differences in a putative NADPH-binding domain and in putative glycosylation sites. In addition, the subcellular location of the endothelial gp91-phox and p22-phox subunits is significantly different from that reported for the neutrophil oxidase, in that they are predominantly intracellular and collocated in the vicinity of the endoplasmic reticulum. This first detailed characterization of gp91-phox and p22-phox structure and location in endothelial cells provides new data that may account, in part, for the differences in function between the phagocytic and endothelial NAD(P)H oxidases.