6,045 research outputs found

    Platelet-activating factor receptor in health and disease.

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    Background Platelet-activating factor receptor (PAFR) expression has been linked to anthropogenic particulate matter (PM). Traffic-related air pollution (TRAP) now accounts for the majority of this PM. PAFR expression has also been linked to an increased risk of infection from Streptococcus pneumoniae (S. pneumoniae). Children with asthma and sickle cell disease (SCD) have a significantly increased risk of morbidity and mortality from invasive pneumococcal disease (IPD). PAFR expression has not yet been investigated in relation to TRAP-generated PM, nor has constitutive expression been investigated in these children at increased risk of IPD. Methods PM10 was collected from roadside traffic using the Cyclone device. A549 cells were exposed to the collected PM10 and flow cytometry was undertaken to measure PAFR expression by median fluorescence intensity (MFI). Exposed A549 cells also underwent assays to determine bacterial adhesion (colony-forming units, CFU) using D39 S. pneumoniae species. In both experiments, Dulbecco’s phosphate buffered saline (DPBS) was used as a control. In a separate study, children aged 1 – 17 years were recruited into 4 groups: 2 disease groups (children with asthma, and those with SCD); and 2 control groups (healthy children, and children with atopy but not asthma). Nasal epithelial cells were collected and PAFR expression (MFI) measured by flow cytometry. 24-hour PM10 pollution (μg/m3) data were also collected for each participant. Results TRAP-related PM caused a significant increase in PAFR expression in A549 cells when exposed to a concentration of 10 ug/ml (p < 0.05). Bacterial adhesion (CFU) was significantly raised in A549 cells exposed to TRAP PM verses the control wells (p < 0.05). In children, PAFR expression in SCD was notably raised when compared to all other groups (p < 0.001). There was no 7 significant difference in the PAFR expression in those with asthma versus the control groups. 24% of the children within the study demonstrated exposure to PM10 levels above the WHO daily safety limit. Conclusion PAFR expression and subsequent bacterial adhesion is increased following exposure to TRAP. PAFR is shown to be constitutively raised in those with SCD and this may explain some of the reported risk from IPD. Air pollution levels in London remain above safe limits despite public health initiatives trying to decrease them

    Aged lipid-laden microglia display impaired responses to stroke

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    Microglial cells of the aged brain manifest signs of dysfunction that could contribute to the worse neurological outcome of stroke in the elderly. Treatment with colony-stimulating factor 1 receptor antagonists enables transient microglia depletion that is followed by microglia repopulation after treatment interruption, causing no known harm to mice. We tested whether this strategy restored microglia function and ameliorated stroke outcome in old mice. Cerebral ischemia/reperfusion induced innate immune responses in microglia highlighted by type I interferon and metabolic changes involving lipid droplet biogenesis. Old microglia accumulated lipids under steady state and displayed exacerbated innate immune responses to stroke. Microglia repopulation in old mice reduced lipid-laden microglia, and the cells exhibited reduced inflammatory responses to ischemia. Moreover, old mice with renewed microglia showed improved motor function 2 weeks after stroke. We conclude that lipid deposits in aged microglia impair the cellular responses to ischemia and worsen functional recovery in old mice.© 2022 The Authors. Published under the terms of the CC BY 4.0 license

    Characterising the neck motor system of the blowfly

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    Flying insects use visual, mechanosensory, and proprioceptive information to control their movements, both when on the ground and when airborne. Exploiting visual information for motor control is significantly simplified if the eyes remain aligned with the external horizon. In fast flying insects, head rotations relative to the body enable gaze stabilisation during highspeed manoeuvres or externally caused attitude changes due to turbulent air. Previous behavioural studies into gaze stabilisation suffered from the dynamic properties of the supplying sensor systems and those of the neck motor system being convolved. Specifically, stabilisation of the head in Dipteran flies responding to induced thorax roll involves feed forward information from the mechanosensory halteres, as well as feedback information from the visual systems. To fully understand the functional design of the blowfly gaze stabilisation system as a whole, the neck motor system needs to be investigated independently. Through X-ray micro-computed tomography (μCT), high resolution 3D data has become available, and using staining techniques developed in collaboration with the Natural History Museum London, detailed anatomical data can be extracted. This resulted in a full 3- dimensional anatomical representation of the 21 neck muscle pairs and neighbouring cuticula structures which comprise the blowfly neck motor system. Currently, on the work presented in my PhD thesis, μCT data are being used to infer function from structure by creating a biomechanical model of the neck motor system. This effort aims to determine the specific function of each muscle individually, and is likely to inform the design of artificial gaze stabilisation systems. Any such design would incorporate both sensory and motor systems as well as the control architecture converting sensor signals into motor commands under the given physical constraints of the system as a whole.Open Acces

    The Expedition PS129 of the Research Vessel POLARSTERN to the Weddell Sea in 2022

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    Machine Learning Approaches for Semantic Segmentation on Partly-Annotated Medical Images

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    Semantic segmentation of medical images plays a crucial role in assisting medical practitioners in providing accurate and swift diagnoses; nevertheless, deep neural networks require extensive labelled data to learn and generalise appropriately. This is a major issue in medical imagery because most of the datasets are not fully annotated. Training models with partly-annotated datasets generate plenty of predictions that belong to correct unannotated areas that are categorised as false positives; as a result, standard segmentation metrics and objective functions do not work correctly, affecting the overall performance of the models. In this thesis, the semantic segmentation of partly-annotated medical datasets is extensively and thoroughly studied. The general objective is to improve the segmentation results of medical images via innovative supervised and semi-supervised approaches. The main contributions of this work are the following. Firstly, a new metric, specifically designed for this kind of dataset, can provide a reliable score to partly-annotated datasets with positive expert feedback in their generated predictions by exploiting all the confusion matrix values except the false positives. Secondly, an innovative approach to generating better pseudo-labels when applying co-training with the disagreement selection strategy. This method expands the pixels in disagreement utilising the combined predictions as a guide. Thirdly, original attention mechanisms based on disagreement are designed for two cases: intra-model and inter-model. These attention modules leverage the disagreement between layers (from the same or different model instances) to enhance the overall learning process and generalisation of the models. Lastly, innovative deep supervision methods improve the segmentation results by training neural networks one subnetwork at a time following the order of the supervision branches. The methods are thoroughly evaluated on several histopathological datasets showing significant improvements

    Analysis of the retina and visual pathway by OCT, OCTA and psychophysical tests in asymptomatic subjects at high genetic risk for the development of Alzheimer's disease

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    Tesis inédita de la Universidad Complutense de Madrid, Facultad de Medicina, leída el 15-07-2022La Enfermedad de Alzheimer (EA) es una enfermedad neurodegenerativa progresiva que se caracteriza: por una atrofia cortical difusa, declive de las funciones cognitivas, así como la agregación anormal de proteínas como la beta amiloide fibrilar (Aß) y tau hiperfosforilada (p-Tau).El factor de riesgo prevalente es la edad avanzada, tras el cual destaca la herencia genética. Elmayor factor de riesgo genético conocido es ser portador de al menos un alelo 4 del gen de la apoliproteina E (ApoE). Otro de los factores que incrementa el riesgo para desarrollar la EA, es la historia familiar de primer grado. Los signos cerebrales de la EA aparecen décadas antes del inicio clínico de la enfermedad. Dado que la relación entre cerebro y retina se establece ya desde la etapa embrionaria, los cambios retinianos detectados con técnicas de diagnóstico oftalmológico en sujetos con alto riesgo genético para el desarrollo de EA posibilitan la identificación de potenciales pacientes de EA en etapas muy tempranas...Alzheimer's disease (AD) is a progressive neurodegenerative disease characterised by: diffuse cortical atrophy, decline in cognitive functions, as well as abnormal aggregation of proteins such as fibrillar amyloid Beta (Aβ) and hyperphosphorylated tau(p-Tau).The prevalent risk factor is older age, after which genetic inheritance is the most important. The major known genetic risk factor is carrying at least one 4 allele of the apoliprotein E (ApoE 4)gene. Another factor that increases the risk of developing AD is a first-degree family history. Brain signs of AD appear decades before clinical onset of the disease. Since the relationship between brain and retina is established as early as the embryonic stage, retinal changes detected with ophthalmological diagnostic techniques in subjects at high genetic risk for developing AD make it possible to identify potential AD patients at very early stages..Fac. de MedicinaTRUEunpu

    Optical and hyperspectral image analysis for image-guided surgery

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