907 research outputs found

    Investigating the impact of lung cancer cell-of-origin on tumour metabolic phenotype and heterogeneity

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    Non-small-cell lung cancer has been described as highly heterogenous which results in different metabolic phenotypes. There are multiple factors which contribute to this heterogeneity, one of which is the tumour cell-of-origin. In the lung, there are five cell types reported to be cells-of-origin: alveolar epithelial type 2, club, basal, neuroendocrine and bronchioalveolar stem cells. This project focuses on the interaction between the cell-of-origin and the metabolic phenotype of lung cancer, and we aim to assess the contribution of the cell-of-origin to lung cancer metabolic resultant phenotype and heterogeneity. To accomplish this, we have established two complementary model systems, one in vitro and one in vivo. In our in vitro model, we isolated specific lung cell types, including AT2 cells, basal cells, and club cells, utilising their unique cell surface markers. By introducing oncogenic KRAS mutations and deleting the P53 gene, we are creating lineage-restricted organoids. These organoids will serve as valuable tools for characterizing the metabolic aspects of tumours arising from different cell-of-origin backgrounds within an in vitro setting. In our in vivo model, we induced NSCLC tumours in mice with genetic modifications using viral vectors, namely Ad5-mSPC-Cre, Ad5-CC10-Cre, and Ad5- bk5-Cre. These vectors are selectively expressed in AT2, club, and basal cells, respectively. To ensure the validity of our comparisons, we have carefully monitored tumour growth dynamics and burden in these mouse models. Our comprehensive analysis has revealed three distinct transcriptomic subtypes (S1, S2, and Acetate) within these NSCLC tumours. Notably, S1 and Acetate subtypes are enriched in tumours originating from specific cell types. Positron emission tomography (PET) imaging has unveiled metabolic variations, with S1 tumours displaying heightened [18F]FDG uptake and the Acetate subtype exhibiting increased [11C]acetate uptake. Furthermore, our multi-omics approach, encompassing transcriptomics, proteomics, and metabolomics, has exposed disparities in critical metabolic pathways, such as glycolysis, hypoxia response, and apoptosis. In summary, our research provides a comprehensive examination of the metabolic heterogeneity of NSCLC based on the cell-of-origin independently of genomic alterations

    Clinical, immunological and genetic features of histiocytic disorders

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    Clinical, immunological and genetic features of histiocytic disorders

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    An extracellular receptor tyrosine kinase motif orchestrating intracellular STAT activation

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    The ErbB4 receptor isoforms JM-a and JM-b differ within their extracellular juxtamembrane (eJM) domains. Here, ErbB4 isoforms are used as a model to address the effect of structural variation in the eJM domain of receptor tyrosine kinases (RTK) on downstream signaling. A specific JM-a-like sequence motif is discovered, and its presence or absence (in JM-b-like RTKs) in the eJM domains of several RTKs is demonstrated to dictate selective STAT activation. STAT5a activation by RTKs including the JM-a like motif is shown to involve interaction with oligosaccharides of N-glycosylated cell surface proteins such as β1 integrin, whereas STAT5b activation by JM-b is dependent on TYK2. ErbB4 JM-a- and JM-b-like RTKs are shown to associate with specific signaling complexes at different cell surface compartments using analyses of RTK interactomes and super-resolution imaging. These findings provide evidence for a conserved mechanism linking a ubiquitous extracellular motif in RTKs with selective intracellular STAT signaling

    On the path integration system of insects: there and back again

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    Navigation is an essential capability of animate organisms and robots. Among animate organisms of particular interest are insects because they are capable of a variety of navigation competencies solving challenging problems with limited resources, thereby providing inspiration for robot navigation. Ants, bees and other insects are able to return to their nest using a navigation strategy known as path integration. During path integration, the animal maintains a running estimate of the distance and direction to its nest as it travels. This estimate, known as the `home vector', enables the animal to return to its nest. Path integration was the technique used by sea navigators to cross the open seas in the past. To perform path integration, both sailors and insects need access to two pieces of information, their direction and their speed of motion over time. Neurons encoding the heading and speed have been found to converge on a highly conserved region of the insect brain, the central complex. It is, therefore, believed that the central complex is key to the computations pertaining to path integration. However, several questions remain about the exact structure of the neuronal circuit that tracks the animal's heading, how it differs between insect species, and how the speed and direction are integrated into a home vector and maintained in memory. In this thesis, I have combined behavioural, anatomical, and physiological data with computational modelling and agent simulations to tackle these questions. Analysis of the internal compass circuit of two insect species with highly divergent ecologies, the fruit fly Drosophila melanogaster and the desert locust Schistocerca gregaria, revealed that despite 400 million years of evolutionary divergence, both species share a fundamentally common internal compass circuit that keeps track of the animal's heading. However, subtle differences in the neuronal morphologies result in distinct circuit dynamics adapted to the ecology of each species, thereby providing insights into how neural circuits evolved to accommodate species-specific behaviours. The fast-moving insects need to update their home vector memory continuously as they move, yet they can remember it for several hours. This conjunction of fast updating and long persistence of the home vector does not directly map to current short, mid, and long-term memory accounts. An extensive literature review revealed a lack of available memory models that could support the home vector memory requirements. A comparison of existing behavioural data with the homing behaviour of simulated robot agents illustrated that the prevalent hypothesis, which posits that the neural substrate of the path integration memory is a bump attractor network, is contradicted by behavioural evidence. An investigation of the type of memory utilised during path integration revealed that cold-induced anaesthesia disrupts the ability of ants to return to their nest, but it does not eliminate their ability to move in the correct homing direction. Using computational modelling and simulated agents, I argue that the best explanation for this phenomenon is not two separate memories differently affected by temperature but a shared memory that encodes both the direction and distance. The results presented in this thesis shed some more light on the labyrinth that researchers of animal navigation have been exploring in their attempts to unravel a few more rounds of Ariadne's thread back to its origin. The findings provide valuable insights into the path integration system of insects and inspiration for future memory research, advancing path integration techniques in robotics, and developing novel neuromorphic solutions to computational problems

    Multimodal Dataset Distillation for Image-Text Retrieval

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    Dataset distillation methods offer the promise of reducing a large-scale dataset down to a significantly smaller set of (potentially synthetic) training examples, which preserve sufficient information for training a new model from scratch. So far dataset distillation methods have been developed for image classification. However, with the rise in capabilities of vision-language models, and especially given the scale of datasets necessary to train these models, the time is ripe to expand dataset distillation methods beyond image classification. In this work, we take the first steps towards this goal by expanding on the idea of trajectory matching to create a distillation method for vision-language datasets. The key challenge is that vision-language datasets do not have a set of discrete classes. To overcome this, our proposed multimodal dataset distillation method jointly distill the images and their corresponding language descriptions in a contrastive formulation. Since there are no existing baselines, we compare our approach to three coreset selection methods (strategic subsampling of the training dataset), which we adapt to the vision-language setting. We demonstrate significant improvements on the challenging Flickr30K and COCO retrieval benchmark: the best coreset selection method which selects 1000 image-text pairs for training is able to achieve only 5.6% image-to-text retrieval accuracy (recall@1); in contrast, our dataset distillation approach almost doubles that with just 100 (an order of magnitude fewer) training pairs.Comment: 28 pages, 11 figure

    Modelling Perception of Large-Scale Thematic Structure in Music

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    Large-scale thematic structure—the organisation of material within a musical composition—holds an important position in the Western classical music tradition and has subsequently been incorporated into many influential models of music cognition. Whether, and if so, how, these structures may be perceived provides an interesting psychological problem, combining many aspects of memory, pattern recognition, and similarity judgement. However, strong experimental evidence supporting the perception of large-scale thematic structures remains limited, often arising from difficulties in measuring and disrupting their perception. To provide a basis for experimental research, this thesis develops a probabilistic computational model that characterises the possible cognitive processes underlying the perception of thematic structure. This modelling is founded on the hypothesis that thematic structures are perceptible through the statistical regularities they form, arising from the repetition and learning of material. Through the formalisation of this hypothesis, features were generated characterising compositions’ intra-opus predictability, stylistic predictability, and the amounts of repetition and variation of identified thematic material in both pitch and rhythmic domains. A series of behavioural experiments examined the ability of these modelled features to predict participant responses to important indicators of thematic structure. Namely, similarity between thematic elements, identification of large-scale repetitions, perceived structural unity, sensitivity to thematic continuation, and large-scale ordering. Taken together, the results of these experiments provide converging evidence that the perception of large-scale thematic structures can be accounted for by the dynamic learning of statistical regularities within musical compositions

    PLEKHS1 drives PI3Ks and remodels pathway homeostasis in PTEN-null prostate

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    The PIP3/PI3K network is a central regulator of metabolism and is frequently activated in cancer, commonly by loss of the PIP3/PI(3,4)P2 phosphatase, PTEN. Despite huge research investment, the drivers of the PI3K network in normal tissues and how they adapt to overactivation are unclear. We find that in healthy mouse prostate PI3K activity is driven by RTK/IRS signaling and constrained by pathway feedback. In the absence of PTEN, the network is dramatically remodeled. A poorly understood YXXM- and PIP3/PI(3,4)P2-binding PH domain-containing adaptor, PLEKHS1, became the dominant activator and was required to sustain PIP3, AKT phosphorylation, and growth in PTEN-null prostate. This was because PLEKHS1 evaded pathway-feedback and experienced enhanced PI3K- and Src-family kinase-dependent phosphorylation of Y258XXM, eliciting PI3K activation. hPLEKHS1 mRNA and activating Y419 phosphorylation of hSrc correlated with PI3K pathway activity in human prostate cancers. We propose that in PTEN-null cells receptor-independent, Src-dependent tyrosine phosphorylation of PLEKHS1 creates positive feedback that escapes homeostasis, drives PIP3 signaling, and supports tumor progression

    Preliminary population studies of the grassland swallowtail butterfly Euryades corethrus (Lepidoptera, Papilionidae)

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    Euryades corethrus is a Troidini butterfly (Papilionidae, Papilioninae), endemic to grasslands in southern Brazil, Uruguay, Argentina and Paraguay. Formerly abundant, nowadays it is in the Red list of endangered species for those areas. During its larval stage, it feeds on Aristolochia spp, commonly found in southern grasslands. These native grassland areas are diminishing, being converted to crops and pastures, causing habitat loss for Aristolochia and E. corethrus. This study aimed to assess the genetic diversity, population structure and demographic history of E. corethrus. We sampled eight populations from Rio Grande do Sul, Brazil and based on Cytochrome Oxidase subunit I (COI) molecular marker, our results suggest a low genetic variability between populations, presence of gene flow and, consequently, lack of population structure. A single maternally inherited-genetic marker is insufficient for population-level decisions, but barcoding is a useful tool during early stages of population investigation, bringing out genomic diversity patterns within the target species. Those populations likely faced a bottleneck followed by a rapid expansion during the last glaciation and subsequent stabilization in effective population size. Habitat loss is a threat, which might cause isolation, loss of genetic variability and, ultimately, extinction of E. corethrus if no habitat conservation policy is adopted.info:eu-repo/semantics/publishedVersio
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