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Background: Autoimmune diseases encompass a diverse array of disorders that disturb the optimal functioning of the immune system, which is to eliminate the 'foreign or/and dangerous' to mistakenly target the body's own tissues. Objective: The aim of this research is to evaluate the most effective approach to managing autoimmune diseases within the framework of pregnancy. Methods: The exact causes and etiologies of these diseases are multifactorial and mostly still unclear. Ro/SSA autoantibodies and La/SSB, could be found in Sjögren's disease (SJ), systemic lupus (SLE) and other autoimmune disorders. Smoking, stress, UV exposure, vitamin D deficiency, and other genetic and environmental factors have been identified as risk factors for rheumatic diseases. Results: Over the years, an ever-increasing incidence of these diseases has been observed in the general population, with the female sex being at increased risk for their occurrence. This fact raises the question of what should be the management of these pathological entities during pregnancy. Taking into account the very significant impact on the quality of paitients'daily life and the seemingly augmented prevalence of autoimmune diseases, as well as their preference in the female population, the reasonable question arises as to what should be the optimal management of these diseases in the context of pregnancy. Conclusion: Given the limited data of the global medical community regarding the etiological factors and mechanisms that trigger the onset of rheumatic diseases, the management of pregnant women is a complex conundrum that health professionals are challenged to face and solve.
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This review delves into the possible connection between periodontitis and negative pregnancy outcomes, such as preeclampsia and preterm birth. It highlights the potential influence of an unidentified microbial factor on preeclampsia and the effects of inflammatory responses on the rate of preterm births. Furthermore, it underscores the prevalent occurrence of oral ailments within the populace and their significant repercussions on quality of life. Hormonal fluctuations during pregnancy may exacerbate oral conditions such as pregnancy gingivitis and periodontitis, necessitating bespoke therapeutic approaches that take into account potential fetal ramifications. Periodontal disease, characterized by microbial attack and inflammatory response, results in tissue destruction and tooth loss. The oral cavity's susceptibility to bacterial colonization, which is primarily due to its role as a site for food intake, is highlighted. Furthermore, research indicates a correlation between inflammatory responses and factors such as prostaglandin E2 and IL-1ß, and preterm birth. Therapeutic interventions are a focus of international research, with efforts being aimed at optimizing outcomes through larger studies involving pregnant women.
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Uterine artery embolization (UAE) for the treatment of symptomatic uterine fibroids and non-controllable adenomyosis symptoms is a relatively new procedure for organ-preserving therapy. These benign conditions can become symptomatic in about 30% of women between the ages of 35 and 50. The purpose of the UAE either for fibroids or adenomyosis is the elimination of blood loss, the reduction in pain, and bulky or rectal pressure symptoms. The purpose of this study is to present our experience in UAE with the use of hydrogel-coated tris acryl microspheres for the treatment of symptomatic uterine fibroids and adenomyosis.
RESUMEN
Single-channel patch-clamp recordings allow observing the action of a single protein complex in real time and hence the deduction of the underlying conformational changes in the ion-channel protein. Commonly, recordings are modeled using hidden Markov chains, connecting open and closed states in the experimental data with protein conformations. The rates between states denote transition probabilities that could be modified by membrane voltage or ligand binding. Modeling algorithms have to deal with limited recording bandwidth and a very noisy background. It was previously shown that the fit of two-dimensional (2D)-dwell-time histograms with simulations is very robust in that regard. Errors introduced by the low-pass filter or noise cancel out to a certain degree when comparing experimental and simulated data. In addition, the topology of models (that is, the chain of open and closed states) could be inferred from 2D-histograms. However, the 2D-fit was never applied to its full potential. A major reason may be the extremely time-consuming and often unreliable fitting process, due to the stochastic variability in the simulations. We have now solved these issues by introducing a message-passing interface (MPI) allowing massive parallel computing on a high-performance computing (HPC) cluster and obtaining ensemble solutions. With ensembles, we have demonstrated how important ranked solutions are for difficult tasks related to a noisy background, fast gating events beyond the corner frequency of the low-pass filter, and topology estimation of the underlying Markov model. Finally, we have shown that, by combining the objective function of the 2D-fit with the deviation of the current amplitude distributions, automatic determination of the current level of the conducting state is possible, even with an apparent current reduction due to low-pass filtering. Making use of an HPC cluster, the power of 2D-dwell-time analysis can be used to its fullest with minor input of the experimenter.