7 resultados para SKIN DISEASES

em Universidade do Minho


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Cell/cell-extracellular matrix (ECM) dynamic interactions appear to have a major role in regulating communication through soluble signaling, directing cell binding and activating substrates that participate in the highly organized wound healing process. Moreover, these interactions are also crucial for in vitro mimicking cutaneous physiology. Herein we explore cell sheet (CS) engineering to create cellular constructs formed by keratinocytes (hKC), fibroblasts (hDFB) and dermal microvascular endothelial cells (hDMEC), to target skin wound healing but also the in vitro recreation of relevant models. Taking advantage of temperature-responsive culture surfaces, which allow harvesting cultured cells as intact sheets along with the deposited native ECM, varied combinations of homotypic and heterotypic three-dimensional (3-D) CS-based constructs were developed. Constructs combining one CS of keratinocytes as an epidermis-like layer plus a vascularized dermis composed by hDFB and hDMECs were assembled as skin analogues for advancing in vitro testing. Simultaneously both hKC and hDMEC were shown to significantly contribute to the re-epithelialization of full-thickness mice skin wounds by promoting an early epithelial coverage, while hDMEC significantly lead to increased vessels density, incorporating the neovasculature. Thus, although determined by the cellular nature of the constructs, these outcomes demonstrated that CS engineering appear as an unique technology that open the possibility to create numerous combinations of 3D constructs to target defective wound healing as well as the construction of in vitro models to further mimic cutaneous functions crucial for drug screening and cosmetic testing assays.

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Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

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Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

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Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.

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BACKGROUND: An autoimmune disease is characterized by tissue damage, caused by self-reactivity of different effector mechanisms of the immune system, namely antibodies and T cells. All autoimmune diseases, to some extent, have implications for fertility and obstetrics. Currently, due to available treatments and specialised care for pregnant women with autoimmune disease, the prognosis for both mother and child has improved significantly. However these pregnancies are always high risk. The purpose of this study is to analyse the fertility/pregnancy process of women with systemic and organ-specific autoimmune diseases and assess pathological and treatment implications. METHODS: The authors performed an analysis of the clinical records and relevant obstetric history of five patients representing five distinct autoimmune pathological scenarios, selected from Autoimmune Disease Consultation at the Hospital of Braga, and reviewed the literature. RESULTS: The five clinical cases are the following: Case 1-28 years old with systemic lupus erythematosus, and clinical remission of the disease, under medication with hydroxychloroquine, prednisolone and acetylsalicylic acid, with incomplete miscarriage at 7 weeks of gestation without signs of thrombosis. Case 2-44 years old with history of two late miscarriages, a single preterm delivery (33 weeks) and multiple thrombotic events over the years, was diagnosed with antiphospholipid syndrome after acute myocardial infarction. Case 3-31 years old with polymyositis, treated with azathioprine for 3 years with complete remission of the disease, took the informed decision to get pregnant after medical consultation and full weaning from azathioprine, and gave birth to a healthy term new-born. Case 4-38 years old pregnant woman developed Behcet's syndrome during the final 15 weeks of gestation and with disease exacerbation after delivery. Case 5-36 years old with autoimmune thyroiditis diagnosed during her first pregnancy, with difficult control over the thyroid function over the years and first trimester miscarriage, suffered a second miscarriage despite clinical stability and antibody regression. CONCLUSIONS: As described in literature, the authors found a strong association between autoimmune disease and obstetric complications, especially with systemic lupus erythematosus, antiphospholipid syndrome and autoimmune thyroiditis.

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The blood brain barrier (BBB) and the blood cerebrospinal fluid barrier (BCSFB) form the barriers of the brain. These barriers are essential not only for the protection of the brain, but also in regulating the exchange of cells and molecules in and out of the brain. The choroid plexus (CP) epithelial cells and the arachnoid membrane form the BCSFB. The CP is structurally divided into two independent compartments: one formed by a unique and continuous line of epithelial cells that rest upon a basal lamina; and, a second consisting of a central core formed by connective and highly vascularized tissue populated by diverse cell types (fibroblasts, macrophages and dendritic cells). Here, we review how the CP transcriptome and secretome vary depending on the nature and duration of the stimuli to which the CP is exposed. Specifically, when the peripheral stimulation is acute the CP response is rapid, strong and transient, whereas if the stimulation is sustained in time the CP response persists but it is weaker. Furthermore, not all of the epithelium responds at the same time to peripheral stimulation, suggesting the existence of a synchrony system between individual CP epithelial cells.

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Mutations or amplification of the MET proto-oncogene are involved in the pathogenesis of several tumours, which rely on the constitutive engagement of this pathway for their growth and survival. However, MET is expressed not only by cancer cells but also by tumour-associated stromal cells, although its precise role in this compartment is not well characterized. Here we show that MET is required for neutrophil chemoattraction and cytotoxicity in response to its ligand hepatocyte growth factor (HGF). Met deletion in mouse neutrophils enhances tumour growth and metastasis. This phenotype correlates with reduced neutrophil infiltration to both the primary tumour and metastatic sites. Similarly, Met is necessary for neutrophil transudation during colitis, skin rash or peritonitis. Mechanistically, Met is induced by tumour-derived tumour necrosis factor (TNF)-a or other inflammatory stimuli in both mouse and human neutrophils. This induction is instrumental for neutrophil transmigration across an activated endothelium and for inducible nitric oxide synthase production upon HGF stimulation. Consequently, HGF/MET-dependent nitric oxide release by neutrophils promotes cancer cell killing, which abates tumour growth and metastasis. After systemic administration of a MET kinase inhibitor, we prove that the therapeutic benefit of MET targeting in cancer cells is partly countered by the pro-tumoural effect arising from MET blockade in neutrophils. Our work identifies an unprecedented role of MET in neutrophils, suggests a potential 'Achilles' heel' of MET-targeted therapies in cancer, and supports the rationale for evaluating anti-MET drugs in certain inflammatory diseases.