979 resultados para biological models


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Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

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The evolution of reproductive strategies involves a complex calculus of costs and benefits to both parents and offspring. Many marine animals produce embryos packaged in tough egg capsules or gelatinous egg masses attached to benthic surfaces. While these egg structures can protect against environmental stresses, the packaging is energetically costly for parents to produce. In this series of studies, I examined a variety of ecological factors affecting the evolution of benthic development as a life history strategy. I used marine gastropods as my model system because they are incredibly diverse and abundant worldwide, and they exhibit a variety of reproductive and developmental strategies.

The first study examines predation on benthic egg masses. I investigated: 1) behavioral mechanisms of predation when embryos are targeted (rather than the whole egg mass); 2) the specific role of gelatinous matrix in predation. I hypothesized that gelatinous matrix does not facilitate predation. One study system was the sea slug Olea hansineensis, an obligate egg mass predator, feeding on the sea slug Haminoea vesicula. Olea fed intensely and efficiently on individual Haminoea embryos inside egg masses but showed no response to live embryos removed from gel, suggesting that gelatinous matrix enables predation. This may be due to mechanical support of the feeding predator by the matrix. However, Haminoea egg masses outnumber Olea by two orders of magnitude in the field, and each egg mass can contain many tens of thousands of embryos, so predation pressure on individuals is likely not strong. The second system involved the snail Nassarius vibex, a non-obligate egg mass predator, feeding on the polychaete worm Clymenella mucosa. Gel neither inhibits nor promotes embryo predation for Nassarius, but because it cannot target individual embryos inside an egg mass, its feeding is slow and inefficient, and feeding rates in the field are quite low. However, snails that compete with Nassarius for scavenged food have not been seen to eat egg masses in the field, leaving Nassarius free to exploit the resource. Overall, egg mass predation in these two systems likely benefits the predators much more than it negatively affects the prey. Thus, selection for environmentally protective aspects of egg mass production may be much stronger than selection for defense against predation.

In the second study, I examined desiccation resistance in intertidal egg masses made by Haminoea vesicula, which preferentially attaches its flat, ribbon-shaped egg masses to submerged substrata. Egg masses occasionally detach and become stranded on exposed sand at low tide. Unlike adults, the encased embryos cannot avoid desiccation by selectively moving about the habitat, and the egg mass shape has high surface-area-to-volume ratio that should make it prone to drying out. Thus, I hypothesized that the embryos would not survive stranding. I tested this by deploying individual egg masses of two age classes on exposed sand bars for the duration of low tide. After rehydration, embryos midway through development showed higher rates of survival than newly-laid embryos, though for both stages survival rates over 25% were frequently observed. Laboratory desiccation trials showed that >75% survival is possible in an egg mass that has lost 65% of its water weight, and some survival (<25%) was observed even after 83% water weight lost. Although many surviving embryos in both experiments showed damage, these data demonstrate that egg mass stranding is not necessarily fatal to embryos. They may be able to survive a far greater range of conditions than they normally encounter, compensating for their lack of ability to move. Also, desiccation tolerance of embryos may reduce pressure on parents to find optimal laying substrata.

The third study takes a big-picture approach to investigating the evolution of different developmental strategies in cone snails, the largest genus of marine invertebrates. Cone snail species hatch out of their capsules as either swimming larvae or non-dispersing forms, and their developmental mode has direct consequences for biogeographic patterns. Variability in life history strategies among taxa may be influenced by biological, environmental, or phylogenetic factors, or a combination of these. While most prior research has examined these factors singularly, my aim was to investigate the effects of a host of intrinsic, extrinsic, and historical factors on two fundamental aspects of life history: egg size and egg number. I used phylogenetic generalized least-squares regression models to examine relationships between these two egg traits and a variety of hypothesized intrinsic and extrinsic variables. Adult shell morphology and spatial variability in productivity and salinity across a species geographic range had the strongest effects on egg diameter and number of eggs per capsule. Phylogeny had no significant influence. Developmental mode in Conus appears to be influenced mostly by species-level adaptations and niche specificity rather than phylogenetic conservatism. Patterns of egg size and egg number appear to reflect energetic tradeoffs with body size and specific morphologies as well as adaptations to variable environments. Overall, this series of studies highlights the importance of organism-scale biotic and abiotic interactions in evolutionary patterns.

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Diffuse intrinsic pontine glioma (DIPG) is a rare and incurable brain tumor that arises in the brainstem of children predominantly between the ages of 6 and 8. Its intricate morphology and involvement of normal pons tissue precludes surgical resection, and the standard of care today remains fractionated radiation alone. In the past 30 years, there have been no significant advances made in the treatment of DIPG. This is largely because we lack good models of DIPG and therefore have little biological basis for treatment. In recent years, however, due to increased biopsy and acquisition of autopsy specimens, research is beginning to unravel the genetic and epigenetic drivers of DIPG. Insight gleaned from these studies has led to improvements in approaches to both model these tumors in the lab and to potentially treat them in the clinic. This review will detail the initial strides toward modeling DIPG in animals, which included allograft and xenograft rodent models using non-DIPG glioma cells. Important advances in the field came with the development of in vitro cell and in vivo xenograft models derived directly from autopsy material of DIPG patients or from human embryonic stem cells. Finally, we will summarize the progress made in the development of genetically engineered mouse models of DIPG. Cooperation of studies incorporating all of these modeling systems to both investigate the unique mechanisms of gliomagenesis in the brainstem and to test potential novel therapeutic agents in a preclinical setting will result in improvement in treatments for DIPG patients.

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To provide biological insights into transcriptional regulation, a couple of groups have recently presented models relating the promoter DNA-bound transcription factors (TFs) to downstream gene’s mean transcript level or transcript production rates over time. However, transcript production is dynamic in response to changes of TF concentrations over time. Also, TFs are not the only factors binding to promoters; other DNA binding factors (DBFs) bind as well, especially nucleosomes, resulting in competition between DBFs for binding at same genomic location. Additionally, not only TFs, but also some other elements regulate transcription. Within core promoter, various regulatory elements influence RNAPII recruitment, PIC formation, RNAPII searching for TSS, and RNAPII initiating transcription. Moreover, it is proposed that downstream from TSS, nucleosomes resist RNAPII elongation.

Here, we provide a machine learning framework to predict transcript production rates from DNA sequences. We applied this framework in the S. cerevisiae yeast for two scenarios: a) to predict the dynamic transcript production rate during the cell cycle for native promoters; b) to predict the mean transcript production rate over time for synthetic promoters. As far as we know, our framework is the first successful attempt to have a model that can predict dynamic transcript production rates from DNA sequences only: with cell cycle data set, we got Pearson correlation coefficient Cp = 0.751 and coefficient of determination r2 = 0.564 on test set for predicting dynamic transcript production rate over time. Also, for DREAM6 Gene Promoter Expression Prediction challenge, our fitted model outperformed all participant teams, best of all teams, and a model combining best team’s k-mer based sequence features and another paper’s biologically mechanistic features, in terms of all scoring metrics.

Moreover, our framework shows its capability of identifying generalizable fea- tures by interpreting the highly predictive models, and thereby provide support for associated hypothesized mechanisms about transcriptional regulation. With the learned sparse linear models, we got results supporting the following biological insights: a) TFs govern the probability of RNAPII recruitment and initiation possibly through interactions with PIC components and transcription cofactors; b) the core promoter amplifies the transcript production probably by influencing PIC formation, RNAPII recruitment, DNA melting, RNAPII searching for and selecting TSS, releasing RNAPII from general transcription factors, and thereby initiation; c) there is strong transcriptional synergy between TFs and core promoter elements; d) the regulatory elements within core promoter region are more than TATA box and nucleosome free region, suggesting the existence of still unidentified TAF-dependent and cofactor-dependent core promoter elements in yeast S. cerevisiae; e) nucleosome occupancy is helpful for representing +1 and -1 nucleosomes’ regulatory roles on transcription.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.

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Artificial immune systems (AISs) to date have generally been inspired by naive biological metaphors. This has limited the effectiveness of these systems. In this position paper two ways in which AISs could be made more biologically realistic are discussed. We propose that AISs should draw their inspiration from organisms which possess only innate immune systems, and that AISs should employ systemic models of the immune system to structure their overall design. An outline of plant and invertebrate immune systems is presented, and a number of contemporary systemic models are reviewed. The implications for interdisciplinary research that more biologically-realistic AISs could have is also discussed.

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When studying a biological regulatory network, it is usual to use boolean network models. In these models, boolean variables represent the behavior of each component of the biological system. Taking in account that the size of these state transition models grows exponentially along with the number of components considered, it becomes important to have tools to minimize such models. In this paper, we relate bisimulations, which are relations used in the study of automata (general state transition models) with attractors, which are an important feature of biological boolean models. Hence, we support the idea that bisimulations can be important tools in the study some main features of boolean network models.We also discuss the differences between using this approach and other well-known methodologies to study this kind of systems and we illustrate it with some examples.

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Acute myeloid leukemia (AML) involves the proliferation, abnormal survival and arrest of cells at a very early stage of myeloid cell differentiation. The biological and clinical heterogeneity of this disease complicates treatment and highlights the significance of understanding the underlying causes of AML, which may constitute potential therapeutic targets, as well as offer prognostic information. Tribbles homolog 2 (Trib2) is a potent murine oncogene capable of inducing transplantable AML with complete penetrance. The pathogenicity of Trib2 is attributed to its ability to induce proteasomal degradation of the full length isoform of the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα p42). The role of TRIB2 in human AML cells, however, has not been systematically investigated or targeted. Across human cancers, TRIB2 oncogenic activity was found to be associated with its elevated expression. In the context of AML, TRIB2 overexpression was suggested to be associated with the large and heterogeneous subset of cytogenetically normal AML patients. Based upon the observation that overexpression of TRIB2 has a role in cellular transformation, the effect of modulating its expression in human AML was examined in a human AML cell line that expresses high levels of TRIB2, U937 cells. Specific suppression of TRIB2 led to impaired cell growth, as a consequence of both an increase in apoptosis and a decrease in cell proliferation. Consistent with these in vitro results, TRIB2 silencing strongly reduced progression of the U937 in vivo xenografts, accompanied by detection of a lower spleen weight when compared with mice transplanted with TRIB2- expressing control cells. Gene expression analysis suggested that TRIB2 modulates apoptosis and cell-cycle sensitivity by influencing the expression of a subset of genes known to have implications on these phenotypes. Furthermore, TRIB2 was found to be expressed in a significant subset of AML patient samples analysed. To investigate whether increased expression of this gene could be afforded prognostic significance, primary AML cells with dichotomized levels of TRIB2 transcripts were evaluated in terms of their xenoengraftment potential, an assay reported to correlate with disease aggressiveness observed in humans. A small cohort of analysed samples with higher TRIB2 expression did not associate with preferential leukaemic cell engraftment in highly immune-deficient mice, hence, not predicting for an adverse prognosis. However, further experiments including a larger cohort of well characterized AML patients would be needed to clarify TRIB2 significance in the diagnostic setting. Collectively, these data support a functional role for TRIB2 in the maintenance of the oncogenic properties of human AML cells and suggest TRIB2 can be considered a rational therapeutic target. Proteasome inhibition has emerged as an attractive target for the development of novel anti-cancer therapies and results from translational research and clinical trials support the idea that proteasome inhibitors should be considered in the treatment of AML. The present study argued that proteasome inhibition would effectively inhibit the function of TRIB2 by abrogating C/EBPα p42 protein degradation and that it would be an effective pharmacological targeting strategy in TRIB2-positive AMLs. Here, a number of cell models expressing high levels of TRIB2 were successfully targeted by treatment with proteasome inhibitors, as demonstrated by multiple measurements that included increased cytotoxicity, inhibition of clonogenic growth and anti-AML activity in vivo. Mechanistically, it was shown that block of the TRIB2 degradative function led to an increase of C/EBPα p42 and that response was specific to the TRIB2-C/EBPα axis. Specificity was addressed by a panel of experiments showing that U937 cells (express detectable levels of endogenous TRIB2 and C/EBPα) treated with the proteasome inhibitor bortezomib (Brtz) displayed a higher cytotoxic response upon TRIB2 overexpression and that ectopic expression of C/EBPα rescued cell death. Additionally, in C/EBPα-negative leukaemia cells, K562 and Kasumi 1, Brtz-induced toxicity was not increased following TRIB2 overexpression supporting the specificity of the compound on the TRIB2-C/EBPα axis. Together these findings provide pre-clinical evidence that TRIB2- expressing AML cells can be pharmacologically targeted with proteasome inhibition due, in part, to blockage of the TRIB2 proteolytic function on C/EBPα p42. A large body of evidence indicates that AML arises through the stepwise acquisition of genetic and epigenetic changes. Mass spectrometry data has identified an interaction between TRIB2 and the epigenetic regulator Protein Arginine Methyltransferase 5 (PRMT5). Following assessment of TRIB2‟s role in AML cell survival and effective targeting of the TRIB2-C/EBPα degradation pathway, a putative TRIB2/PRMT5 cooperation was investigated in order to gain a deeper understanding of the molecular network in which TRIB2 acts as a potent myeloid oncogene. First, a microarray data set was interrogated for PRMT5 expression levels and the primary enzyme responsible for symmetric dimethylation was found to be transcribed at significantly higher levels in AML patients when compared to healthy controls. Next, depletion of PRMT5 in the U937 cell line was shown to reduce the transformative phenotype in the high expressing TRIB2 AML cells, which suggests that PRMT5 and TRIB2 may cooperate to maintain the leukaemogenic potential. Importantly, PRMT5 was identified as a TRIB2-interacting protein by means of a protein tagging approach to purify TRIB2 complexes from 293T cells. These findings trigger further research aimed at understanding the underlying mechanism and the functional significance of this interplay. In summary, the present study provides experimental evidence that TRIB2 has an important oncogenic role in human AML maintenance and, importantly in such a molecularly heterogeneous disease, provides the rational basis to consider proteasome inhibition as an effective targeting strategy for AML patients with high TRIB2 expression. Finally, the identification of PRMT5 as a TRIB2-interacting protein opens a new level of regulation to consider in AML. This work may contribute to our further understanding and therapeutic strategies in acute leukaemias.

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This thesis focuses on biological activity of pyrrole-imidazole polyamides in vivo. The work presented includes experiments underlining sequence selectivity of these compounds in living cells and potential methods to improve it. A large fraction of this thesis is devoted to activity of Py-Im in murine models of cancer. We investigated the pharmacokinetics and biodistribution of two compounds – targeted to 5'-WGGWCW-3' and 5'-WTWCGW-3' sequences – and characterized their activity by measuring their effects on tumor growth, gene expression in vivo and in tissue culture, and their effects on physiology of tumors. The initial theoretical studies suggested that a large fraction of genomic sites are bound by Py-Im polyamides non-specifically and experimental data shows that the programmed binding sequence is not a sole determinant of the patterns of gene regulation. Despite the likely presence of non-specific effects of Py-Im polyamides in living cells, in vivo administration of Py-Im polyamides resulted in tolerable host toxicity and anti-tumor activity. Py-Im polyamide targeted to Estrogen Receptor Response Element showed downregulation of ER-driven gene expression in tumor cells, while the compound targeted to hypoxia response element reduced vascularization of tumors and their growth rate, induced apoptosis of cells in hypoxic areas and reduced expression of proangiogenic and prometastatic factors. Further studies, showed that polyamides distributed to many of the tested tissues and their FITC-conjugates showed nuclear uptake. The gene expression effects were also present in murine tissues, such as liver and kidneys, indicating a potential for use for Py-Im polyamides in non-cancerous diseases.

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In recent decades the importance of structuring sciences such as botany or phytosociology faced a declining attention from the scientific community. This was accompanied by a growing interest in theoretical ecology. For such scenario greatly contributed an hypothetical exhaustion of research topics in these areas, but especially the introduction of new technologies that have provided powerful tools for data analysis. This allowed, for example, to make predictions about the impacts of climate change on species and plant communities and the consequent recognition of theoretical ecology, as one of the most prestigious pieces of current biological sciences. However, theoretical ecology has been facing serious knoledge gaps that greatly compromise their results, putting again the spotligth on structuring sciences. For example there are enourmous gaps in knowledge and data on dispersal, species and communities chorology and abundace, as well as in biological interactions. These data is essential, since they will determine ecological behavior of species. Its omission always limits the understanding and proper execution of the models generated by theoretical ecology. In this conference we will present a review on the gaps in knowledge and data in flora and vegetation fields in order to identify situations where geobotanical knowledge can make their major contribution. Furthermore, we will emphasize the need to reformulate objectives in geobotanical sciences in order to give it the deserved scientific recognition, considering the relationship between different scientific knowledges.

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AGC1 deficiency is a rare demyelinating disease caused by mutations in the SLC25A12 gene, which encodes for the mitochondrial glutamate-aspartate carrier 1 (AGC1/Alarar), highly expressed in the central nervous system. In neurons, impairment in AGC1 activity leads to reduction in N-acetyl-aspartate, the main lipid precursor for myelin synthesis (Profilo et al., 2017); in oligodendrocytes progenitors cells, AGC1 down regulation has been related to early arrest proliferation and premature differentiation (Petralla et al., 2019). Additionally, in vivo AGC1 deficiency models i.e., heterozygous mice for AGC1 knock-out and neurospheres from their subventricular zone, respectively, showed a global decrease in cells proliferation and a switch in neural stem cells (NSCs) commitment, with specific reduction in OPCs number and increase in neural and astrocytic pools (Petralla et al., 2019). Therefore, the present study aims to investigate the transcriptional and epigenetic regulation underlying the alterations observed in OPCs and NSCs biological mechanisms, in either AGC1 deficiency models of Oli-neu cells (murine immortalized oligodendrocytes precursors cells), partially silenced by a shRNA for SLC25A12 gene, and SVZ-derived neurospheres from AGC1+/- mice. Western blot and immunofluorescence analysis revealed significant variations in the expression of transcription factors involved in brain cells’ proliferation and differentiation, in association with altered histone post-translational modifications, as well as histone acetylases (HATs) and deacetylases (HDACs) activity/expression, suggesting an improper transcriptional and epigenetic regulation affecting both AGC1 deficiency in vitro models. Furthermore, given the large role of acetylation in controlling in specific time-windows OPC maturation (Hernandez and Casaccia; 2015), pharmacological HATs/HDACs inhibitions were performed, confirming the involvement of chromatin remodelling enzymes in the altered proliferation and early differentiation observed in the AGC1 deficiency models of siAGC1 Oli-neu cells and AGC1+/- mice-derived neurospheres.

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This PhD project has been mainly focused on the synthesis of novel organic compounds containing heterocyclic and/or carbocyclic scaffold and on the study of stearic acid derivatives and their applications in biological field. The synthesis of novel derivatives of 9-hydroxystearic acid (9-HSA) evidenced how the presence of substituents on C9, able to make hydrogen bonds is of crucial importance for the biological activity. Also the position of the hydroxy group along the chain of hydroxystearic acids was investigated: regioisomers with the hydroxy group bound to odd carbons resulted more active than those bearing the hydroxy group on even carbons. Further, the insertion of (R)-9-HSA in magnetic nanoparticles gave a novel material which characterization remarked its suitability for drug delivery. Structural hybrids between amino aza-heterocycles and azelaic acid have been synthesized and some of them showed a selective activity towards osteosarcoma cell line U2OS. Several Apcin analogues bearing indole, benzothiazole, benzofurazan moieties connected to tryptaminyl-, amino pyridinyl-, pyrimidinyl- and pyrazinyl ring through a 1,1,1-trichloroethyl group were synthesized. Biological tests showed the importance of both the tryptaminyl and the pyrimidinyl moieties, confirming the effectiveness against acute leukemia models. The SNAr between 2-aminothiazole derivatives and 7-chlorodinitrobenzofuroxan revealed different behaviour depending from amino substituent of the thiazole. The reaction with 2-N-piperidinyl-, 2-N-morpholinyl-, or 2-N-pyrrolidinyl thiazole gave two isomeric species derived from the attack on C-5 of thiazole ring. Thiazoles substituted with primary- or not-cyclic secondary amines reacted with the exocyclic amino nitrogen atom giving a series of compounds whose biological activity have highlighted as they might be promising candidates for further development of antitumor agents. A series of 9-fluorenylidene derivatives, of interest in medical and optoelectronic field as organic scintillators, was synthesized through Wittig or Suzuky reaction and will be analyzed to test their potential scintillatory properties.

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In recent years, 3D bioprinting has emerged as an innovative and versatile technology able to produce in vitro models that resemble the native spatial organization of organ tissues, by employing or more bioinks composed of various types of cells suspended in hydrogels. Natural and semi-synthetic hydrogels are extensively used for 3D bioprinting models since they can mimic the natural composition of the tissues, they are biocompatible and bioactive with customizable mechanical properties, allowing to support cell growth. The possibility to tailor hydrogels mechanical properties by modifying the chemical structures to obtain photo-crosslinkable materials, while maintaining their biocompatibility and biomimicry, make their use versatile and suitable to simulate a broad spectrum of physiological features. In this PhD Thesis, 3D bioprinted in vitro models with tailored mechanical properties and physiologically-like features were fabricated. AlgMa-based bioinks were employed to produce a living platform with gradient stiffness, with the aim to create an easy to handle and accessible biological tool to evaluate mechanobiology. In addition, GelMa, collagen and IPN of GelMa and collagen were used as bioinks to fabricate a proof-of-concept of 3D intestinal barrier, which include multiple cell components and multi-layered structure. A useful rheological guide to drive users to the selection of the suitable bioinks for 3D bioprinting and to correlate the model’s mechanical stability after crosslinking is proposed. In conclusion, a platform capable to reproduce models with physiological gradient stiffness was developed and the fabrication of 3D bioprinted intestinal models displaying a good hierarchical structure and cells composition was fully reported and successfully achieved. The good biological results obtained demonstrated that 3D bioprinting can be used for the fabrications of 3D models and that the mechanical properties of the external environment plays a key role on the cell pathways, viability and morphology.