46,218 research outputs found

    Assessment of the impact of early life trauma, changes in estrogen signaling, and neurotoxic molecules in a mouse model of multiple sclerosis

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    Multiple sclerosis (MS) is the most common neurological disease that affect young adults that causes the accumulation of disability over time due to irreversible neurodegeneration. Disease presentations vary significantly from person to person in terms of who gets the disease, who develops the more severe types of MS, the type of central nervous system injury that the disease inflicts, molecular signatures on disease driving immune cells, and one’s sensitivity to prescribed treatment. While it is a deeply heterogenous disease, MS is widely accepted to be driven by an autoimmune response characterized by the infiltration of peripheral immune cells and activation of CNS-resident glial cells which results in demyelination, loss of oligodendrocytes, neuron atrophy. The etiology of MS is undetermined. Several genetic and non-genetic (a.k.a. environmental) factors have been identified to have significant impact on disease activity and its underlying mechanism. Importantly, evidence suggest that non-genetic environmental factors play a significant role in disease modification by acting on cellular drivers of the disease. Herein, using a MS model of experimental autoimmune encephalomyelitis (EAE) in four independent projects, I report that non-genetic environmental factors of early life stress, changes in estrogen level, immune cell expression of neurotoxic molecule contribute to disease heterogeneity. The studies also highlight the identity of membrane lymphotoxin-lymphotoxin receptor beta receptor signaling and CXCR2 signaling as potential biomarkers for neurodegenerative and interferon-beta resistant MS and EAE.LimitedAuthor requested closed access (OA after 2yrs) in Vireo ETD syste

    Nursing and Multiple Sclerosis : The invisible symptoms

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    La Esclerosis Múltiple (EM) es una enfermedad crónica y degenerativa, sin cura, que afecta al sistema nervioso central. Los medios y elementos que desarrollan y originan dicha enfermedad son autoinmunes, es decir, el sistema inmunitario ataca las células del sistema nervioso que, a su vez, dificulta la transmisión de los impulsos nerviosos que salen y llegan del cerebro, sin saber cuál es el factor especifico que lo origina dentro de los factores causales. La EM comienza a principios de la edad adulta por lo que limitará a las personas en el momento más activo de sus vidas. Provoca en el paciente una variedad de síntomas. Entre ellos, los que no se observan a simple vista se denominan, síntomas invisibles, entre los que se incluye, la fatiga, la depresión, el dolor y la disfunción sexual. Estos síntomas, a menudo, son pasados por alto en las etapas de la enfermedad. Desde el momento inicial y, tras el diagnóstico es donde enfermería tiene un papel relevante en la enfermedad ya que tiene acceso al paciente y, a su familia, a través de los Servicios de Urgencias de los hospitales y de Atención Primaria, para proporcionar apoyo tanto físico como psicológico. Si el paciente refiere síntomas característicos, la enfermería puede detectarlos y comunicárselo al médico, para realizar las pruebas cuanto antes, y obtener un diagnóstico precoz. Una vez, instaurada la enfermedad, puede explicar a los pacientes en que tratamientos pueden hacer más hincapié cuando surge un brote, cómo actuar en el día a día, o cómo ayudar a sus familias y/o cuidadores.Grado en Enfermerí

    Relatório de estágio realizado no Instituto de Saúde Pública da Universidade do Porto (ISPUP)

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    Este relatório tem por objetivo descrever o estágio no Instituto de Saúde Pública da Universidade do Porto (ISPUP), realizado no âmbito do segundo ano curricular do Mestrado em Estatística Médica da Universidade de Aveiro (UA). Este estágio de 6 meses no ISPUP incluiu diferentes atividades, todas elas incluídas no projeto “Tracking cognitive decline in Multiple Sclerosis”, onde se pretendeu, fundamentalmente, avaliar a capacidade de uma ferramenta de avaliação da performance cognitiva (“Brain on Track” – BoT) distinguir pessoas com esclerose múltipla consoante o seu défice cognitivo. Neste sentido, foram aplicados conhecimentos adquiridos ao longo do Mestrado e no decorrer do presente estágio, tendo sido feita uma análise descritiva da amostra em estudo, construídos modelos lineares de efeitos mistos e utilizado a regressão logística para avaliar a capacidade de discriminação dos modelos. As pontuações totais do BoT apresentaram uma trajetória quadrática e a ferramenta apresentou capacidade de discriminar pacientes com esclerose múltipla e défice cognitivo de pacientes com a performance cognitiva preservada, tendo uma das principais limitações sido o tamanho amostral. A ferramenta BoT apresenta-se como verdadeiramente promissora uma vez que mantém a sua capacidade de discriminação e vai de encontro às recomendações de alguns profissionais de ser necessário efetuar um diagnóstico de forma longitudinal.This report aims to describe the traineeship held at Instituto de Saúde Pública da Universidade do Porto (ISPUP), carried out within the second curricular year of the Master's Degree in Medical Statistics of the University of Aveiro (UA). This 6-month traineeship at ISPUP included different activities, all within the scope of the project "Tracking cognitive decline in Multiple Sclerosis", where the main objective was to assess the ability of a tool for cognitive assessment (“Brain on Track” – BoT) to distinguish people with multiple sclerosis according to their cognitive impairment. For this, the knowledge acquired throughout the Master's degree and during the present traineeship was applied, a descriptive analysis of the sample under study was carried out, linear mixed-effects models were built and a logistic regression was also used to assess the discrimination ability of the models. BoT total scores showed a quadratic trajectory and the tool was able to discriminate patients with multiple sclerosis and cognitive impairment from patients with preserved cognitive performance, despite one of the main limitations identified being the sample size. The BoT tool presents itself as truly promising as it maintains its ability to discriminate patients and meets the recommendations of some professionals that it is necessary to carry out a longitudinal diagnosis.Mestrado em Estatística Médic

    Diferentes estratégias para promover diferenciação neuronal usando a proteína BRI2

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    BRI2 is a type 2 transmembrane protein associated with pathologies such as Alzheimer's Disease, British Familial Dementia, Danish Familial Dementia, and Multiple Sclerosis. It is a widely express protein that undergoes regulated intramembrane proteolysis from which results a few proteolytic fragments, BRI2BRICHOS, BRI2NTF (N-terminal fragment), BRI2ICD (intracellular domain), and BRI2CTF (C-terminal fragment). Recently, an association between BRI2 and a putative role in neuronal differentiation was established, however little is known, and further studies are required. To this end, in this work was studied the effect of BRI2 and the proteolytic fragments, on SH-SY5Y cells by transfection and incubation methods. The results obtained for the transfection were inconclusive. However, the results obtained from the incubation were very promising since the neurites showed a statistically significant increase after only 24h of incubation which reinforces the possible role of BRI2 in neuronal differentiation. Thus, the results obtained are relevant since point to both BRI2 and its proteolytic fragments as neuronal differentiation modulators.BRI2 é uma proteína transmembranar do tipo 2 associada a patologias tais como a Doença de Alzheimer, Demência Familiar Britânica, Demência Familiar Dinamarquesa e Esclerose Múltipla. É uma proteína amplamente expressa que sofre proteólise intramembranar regulada de onde resultam vários fragmentos nomeadamente, BRI2-BRICHOS, BRI2NTF (fragmento N-terminal), BRI2CTF (fragmento C-terminal) e BRI2ICD (domínio intracelular). Recentemente, uma associação entre a BRI2 e um possível papel na da diferenciação neuronal foi estabelecido, no entanto, pouco se sabe sendo necessários mais estudos. Para este fim, neste trabalho foi estudado o efeito de dois fragmentos proteolíticos da BRI2, em células SH-SY5Y por métodos de transfecção e incubação. Os resultados obtidos para a transfecção foram inconclusivos. No entanto, os resultados da incubação foram bastante promissores, uma vez que, as neurites apresentaram um aumento estatisticamente significativo após apenas 24h de incubação o que reforça o possível papel da BRI2 na diferenciação neuronal. Assim, os resultados obtidos são relevantes uma vez que apontam a BRI2 e os seus fragmentos proteolíticos como moduladores da diferenciação neuronal.Mestrado em Biomedicina Molecula

    Leukemia inhibitory factor: recent advances and implications in biotechnology

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    "In Press, Journal Pre-proof"Leukemia inhibitory factor (LIF) is a pleiotropic cytokine with several functions in health and disease ranging from inflammation to cancer. LIF is also a potential target and/or therapeutic agent for diseases such as multiple sclerosis, stroke and even psychological disorders, where the function of LIF as a neurotrophic factor has only recently been explored. In recent years, a limited number of LIF clinical trials have been completed, which partially explains the shortage of effective applications as a therapeutic agent. With the increasing interest from biotechnology companies producing recombinant LIF, this status quo will certainly change, and the potential impact of LIF in terms of disease diagnosis, treatment and management will be realized.This work was supported by national funds through the fct i.p. and by the erdf through the compete2020 - programa operacional competitividade e internacionalização (poci) with the strategic program uid/bia/04050/2019 (poci-01-0145-feder-007569). We also acknowledge support from fct within the fun2cyt project with the grant poci-01-0145-feder-030568

    Ambiguous Medical Image Segmentation using Diffusion Models

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    Collective insights from a group of experts have always proven to outperform an individual's best diagnostic for clinical tasks. For the task of medical image segmentation, existing research on AI-based alternatives focuses more on developing models that can imitate the best individual rather than harnessing the power of expert groups. In this paper, we introduce a single diffusion model-based approach that produces multiple plausible outputs by learning a distribution over group insights. Our proposed model generates a distribution of segmentation masks by leveraging the inherent stochastic sampling process of diffusion using only minimal additional learning. We demonstrate on three different medical image modalities- CT, ultrasound, and MRI that our model is capable of producing several possible variants while capturing the frequencies of their occurrences. Comprehensive results show that our proposed approach outperforms existing state-of-the-art ambiguous segmentation networks in terms of accuracy while preserving naturally occurring variation. We also propose a new metric to evaluate the diversity as well as the accuracy of segmentation predictions that aligns with the interest of clinical practice of collective insights

    Study flow chart.

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    IntroductionThe availability of consumer-facing health technologies for chronic disease management is skyrocketing, yet most are limited by low adoption rates. Improving adoption requires a better understanding of a target population’s previous exposure to technology. We propose a low-resource approach of capturing and clustering technology exposure, as a mean to better understand patients and target health technologies.MethodsUsing Multiple Sclerosis (MS) as a case study, we applied exploratory multivariate factorial analyses to survey data from the Swiss MS Registry. We calculated individual-level factor scorings, aiming to investigate possible technology adoption clusters with similar digital behavior patterns. The resulting clusters were transformed using radar and then compared across sociodemographic and health status characteristics.ResultsOur analysis included data from 990 respondents, resulting in three clusters, which we defined as the (1) average users, (2) health-interested users, and (3) low frequency users. The average user uses consumer-facing technology regularly, mainly for daily, regular activities and less so for health-related purposes. The health-interested user also uses technology regularly, for daily activities as well as health-related purposes. The low-frequency user uses technology infrequently.ConclusionsOnly about 10% of our sample has been regularly using (adopting) consumer-facing technology for MS and health-related purposes. That might indicate that many of the current consumer-facing technologies for MS are only attractive to a small proportion of patients. The relatively low-resource exploratory analyses proposed here may allow for a better characterization of prospective user populations and ultimately, future patient-facing technologies that will be targeted to a broader audience.</div

    UniverSeg: Universal Medical Image Segmentation

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    While deep learning models have become the predominant method for medical image segmentation, they are typically not capable of generalizing to unseen segmentation tasks involving new anatomies, image modalities, or labels. Given a new segmentation task, researchers generally have to train or fine-tune models, which is time-consuming and poses a substantial barrier for clinical researchers, who often lack the resources and expertise to train neural networks. We present UniverSeg, a method for solving unseen medical segmentation tasks without additional training. Given a query image and example set of image-label pairs that define a new segmentation task, UniverSeg employs a new Cross-Block mechanism to produce accurate segmentation maps without the need for additional training. To achieve generalization to new tasks, we have gathered and standardized a collection of 53 open-access medical segmentation datasets with over 22,000 scans, which we refer to as MegaMedical. We used this collection to train UniverSeg on a diverse set of anatomies and imaging modalities. We demonstrate that UniverSeg substantially outperforms several related methods on unseen tasks, and thoroughly analyze and draw insights about important aspects of the proposed system. The UniverSeg source code and model weights are freely available at https://universeg.csail.mit.eduComment: Victor and Jose Javier contributed equally to this work. Project Website: https://universeg.csail.mit.ed

    Epidemiology of neuropathic pain:an analysis of prevalence and associated factors in UK Biobank

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    Abstract. Introduction:. Previous epidemiological studies of neuropathic pain have reported a range of prevalences and factors associated with the disorder. Objectives:. This study aimed to verify these characteristics in a large UK cohort. Methods:. A cross-sectional analysis was conducted of 148,828 UK Biobank participants who completed a detailed questionnaire on chronic pain. The Douleur Neuropathique en Quatre Questions (DN4) was used to distinguish between neuropathic pain (NeuP) and non-neuropathic pain (non-NeuP) in participants with pain of at least 3 months' duration. Participants were also identified with less than 3 months' pain or without pain (NoCP). Multivariable regression was used to identify factors associated with NeuP compared with non-NeuP and NoCP, respectively. Results:. Chronic pain was present in 76,095 participants (51.1%). The overall prevalence of NeuP was 9.2%. Neuropathic pain was significantly associated with worse health-related quality of life, having a manual or personal service type occupation, and younger age compared with NoCP. As expected, NeuP was associated with diabetes and neuropathy, but also other pains (pelvic, postsurgical, and migraine) and musculoskeletal disorders (rheumatoid arthritis, osteoarthritis, and fibromyalgia). In addition, NeuP was associated with pain in the limbs and greater pain intensity and higher body mass index compared with non-NeuP. Female sex was associated with NeuP when compared with NoCP, whereas male sex was associated with NeuP when compared with non-NeuP. Conclusion:. This is the largest epidemiological study of neuropathic pain to date. The results confirm that the disorder is common in a population of middle- to older-aged people with mixed aetiologies and is associated with a higher health impact than non-neuropathic pain

    The radiologically isolated syndrome: revised diagnostic criteria

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    International audienceThe radiologically isolated syndrome (RIS) was defined in 2009 as the presence of asymptomatic, incidentally identified demyelinating-appearing white matter lesions in the central nervous system within individuals lacking symptoms typical of multiple sclerosis. The RIS criteria have been validated and predict the transition to symptomatic MS reliably. The performance of RIS criteria that require fewer MRI lesions is unknown. 2009-RIS subjects, by definition, fulfill 3-4 of 4 criteria for 2005 dissemination in space [DIS] and subjects fulfilling only 1 or 2 lesions in at least one 2017 DIS location were identified within 37 prospective databases. Univariate and multivariate Cox regression models were used to identify predictors of a first clinical event. Performances of different groups were calculated. 747 subjects (72.2% female, mean age 37.7 ± 12.3 years at the index MRI) were included. The mean clinical follow-up time was 46.8 ± 45.4 months. All subjects had focal T2 hyperintensities suggestive of inflammatory demyelination on MRI; 251 (33.6%) fulfilled 1 or 2 2017 DIS criteria (designated as Group 1 and Group 2, respectively), and 496 (66.4%) fulfilled 3 or 4 2005 DIS criteria representing 2009-RIS subjects. Group 1 and 2 subjects were younger than the 2009-RIS Group and were more likely to develop new T2 lesions over time (p < 0.001). Groups 1 and 2 were similar regarding survival distribution and risk factors for transition to multiple sclerosis. At five years, the cumulative probability for a clinical event was 29.0% for Groups 1-2 compared to 38.7% for 2009-RIS (p = 0.0241). The presence of spinal cord lesions on the index scan and CSF-restricted oligoclonal bands in Groups 1-2 increased the risk of symptomatic MS evolution at five years to 38%, comparable to the risk of development in the 2009-RIS group. The presence of new T2 or gadolinium-enhancing lesions on follow-up scans independently increased the risk of presenting with a clinical event (p < 0.001). The 2009-RIS subjects or Group 1-2 with at least 2 of the risk factors for a clinical event demonstrated better sensitivity (86.0%), negative predictive value (73.1%), accuracy (59.8%) and area under the curve (60.7%) compared to other criteria studied. This large prospective cohort brings Class I evidence that subjects with fewer lesions than required in the 2009 RIS criteria evolve directly to a first clinical event at a similar rate when additional risk factors are present. Our results provide a rationale for revisions to existing RIS diagnostic criteria
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