196,081 research outputs found
The immunological barriers to xenotransplantation
No full textThe availability of cells, tissues and organs from a non-human species such as the pig could, at least in theory, meet the demand of organs necessary for clinical transplantation. At this stage, the important goal of getting over the first year of survival has been reported for both cellular and solid organ xenotransplantation in relevant preclinical primate models. In addition, xenotransplantation is already in the clinic as shown by the broad use of animal-derived medical devices, such as bioprosthetic heart valves and biological materials used for surgical tissue repair. At this stage, however, prior to starting a wide-scale clinical application of xenotransplantation of viable cells and organs, the important obstacle represented by the humoral immune response will need to be overcome. Likewise, the barriers posed by the activation of the innate immune system and coagulative pathway will have to be controlled. As far as xenogeneic nonviable xenografts, increasing evidence suggests that considerable immune reactions, mediated by both innate and adaptive immunity, take place and influence the long-term outcome of xenogeneic materials in patients, possibly precluding the use of bioprosthetic heart valves in young individuals. In this context, the present article provides an overview of current knowledge on the immune processes following xenotransplantation and on the possible therapeutic interventions to overcome the immunological drawbacks involved in xenotransplantation
Immunological challenges and therapies in xenotransplantation
No full textXenotransplantation, or the transplantation of cells, tissues, or organs between different species, was proposed a long time ago as a possible solution to the worldwide shortage of human organs and tissues for transplantation. In this setting, the pig is currently seen as the most likely candidate species. In the last decade, progress in this field has been remarkable and includes a better insight into the immunological mechanisms underlying the rejection process. Several immunological hurdles nonetheless remain, such as the strong antibodymediated and innate or adaptive cellular immune responses linked to coagulation derangements, precluding indefinite xenograft survival. This article reviews our current understanding of the immunological mechanisms involved in xenograft rejection and the potential strategies that may enable xenotransplantation to become a clinical reality in the not-toodistant future. © 2014 Cold Spring Harbor Laboratory Press; all rights reserved
Inhibition of adenosine uptake by selective inhibitors of phosphodiesterases in PC12 cells.
No full textCISCA and CytoDArk0: A cell instance segmentation and classification method for histo(patho)logical image Analyses and a new, open, Nissl-stained dataset for brain cytoarchitecture studies
No full textDelineating and classifying individual cells in microscopy tissue images is inherently challenging yet remains essential for advances in medical and neuroscientific research. In this work, we propose a new deep learning framework, CISCA, for automatic cell instance segmentation and classification in histological slices. At the core of CISCA is a network architecture featuring a lightweight U-Net with three heads in the decoder. The first head classifies pixels into boundaries between neighboring cells, cell bodies, and background, while the second head regresses four distance maps along four directions. The outputs from the first and second heads are integrated through a tailored post-processing step, which ultimately produces the segmentation of individual cells. The third head enables the simultaneous classification of cells into relevant classes, if required. We demonstrate the effectiveness of our method using four datasets, including CoNIC, PanNuke, and MoNuSeg, which are publicly available H&E-stained datasets that cover diverse tissue types and magnifications. In addition, we introduce CytoDArk0, the first annotated dataset of Nissl-stained histological images of the mammalian brain, containing nearly 40,000 annotated neurons and glial cells, aimed at facilitating advancements in digital neuropathology and brain cytoarchitecture studies. We evaluate CISCA against other state-of-the-art methods, demonstrating its versatility, robustness, and accuracy in segmenting and classifying cells across diverse tissue types, magnifications, and staining techniques. This makes CISCA well suited for detailed analyses of cell morphology and efficient cell counting in both digital pathology workflows and brain cytoarchitecture research
Revealing Cortical Layers in Histological Brain Images with Self-Supervised Graph Convolutional Networks Applied to Cell-Graphs
No full textIdentifying cerebral cortex layers is crucial for comparative studies of the cytoarchitecture aiming at providing insights into the relations between brain structure and function across species. The absence of extensive annotated datasets typically limits the adoption of machine learning approaches, leading to the manual delineation of cortical layers by neuroanatomists. We introduce a self-supervised approach to detect layers in 2D Nissl-stained histological slices of the cerebral cortex. It starts with the segmentation of individual cells and the creation of an attributed cell-graph. A self-supervised graph convolutional network generates cell embeddings that encode morphological and structural traits of the cellular environment and are exploited by a community detection algorithm for the final layering. Our method, the first self-supervised of its kind with no spatial transcriptomics data involved, holds the potential to accelerate cytoarchitecture analyses, sidestepping annotation needs and advancing cross-species investigation
Experimental evaluation of the quasi-static collapse of automotive front beams made of glass fiber reinforced plastics
No full textModelli della sensibilità allo strain-rate e identificazione dei parametri caratteristici di lamiere di acciaio
No full textÈ ormai ampiamente riconosciuto che i materiali hanno un comportamento che varia con la velocità di deformazione. L'influenza della velocità sulle proprietà del materiale viene modellata tramite modelli costitutivi. I modelli che sono stati proposti sono numerosi e differenti fra di loro e non esistono dei criteri ben definiti per la loro scelta. I dati caratteristici dei vari materiali non sempre sono disponibili anche perché la loro identificazione è piuttosto difficoltosa. Scopo del lavoro è di implementare una procedura numerica per l'identificazione dei parametri di influenza rispetto alla velocità di deformazione, tramite la simulazione di una prova sperimentale. Per questo scopo sono stati considerati e confrontati diversi modelli. Di questi modelli si sono messi in evidenza i vantaggi e le principali limitazioni e si sono potuti determinare i parametri per i due materiali considerat
Cocultures of metastatic and host immune cells: selective effects of NAMI-A for tumor cells.
No full textBiochemical and morphological changes in PC12 cells after short-term exposure to inhibitors of adenosine uptake and of cyclic AMP transporter.
No full textProgettazione e sviluppo di un dispositivo per la caratterizzazione dinamica dei materiali ad elevate velocità di deformazione
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