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BACKGROUND: Glaucoma is a leading cause of irreversible blindness worldwide and is particularly challenging to treat in its refractory forms. The Ahmed valve offers a potential solution for these difficult cases. This research aims to assess the initial clinical experience with Ahmed valve implantation in Romania, evaluating its effectiveness, associated complications, and overall patient outcomes over a five-year period. METHODS: We conducted a prospective study on 50 patients who underwent Ahmed valve implantation due to various types of glaucoma. Patients were monitored at several intervals, up to five years post-surgery. Intraocular pressure and visual acuity were the primary measures of success. RESULTS: On average, patients maintained the intraocular pressure within the targeted range, with the mean intraocular pressure being 17 mmHg 5 years post-surgery. Success, defined as maintaining target intraocular pressure without additional surgery, was achieved in 82% at 1 year, 68% at 3 years, and 60% after 5 years postoperative. CONCLUSION: Ahmed valve implantation is a viable treatment option for refractory glaucoma, demonstrating significant intraocular pressure reduction and manageable complication rates over a five-year follow-up period. Future research should focus on long-term outcomes and optimization of surgical techniques to further reduce complication rates and improve patient quality of life.
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Infectious keratitis is a severe infection of the eye, which requires urgent care in order to prevent permanent complications. Typical cases are usually diagnosed clinically, whereas severe cases also require additional tools, such as direct microscopy, corneal cultures, molecular techniques, or ophthalmic imaging. The initial treatment is empirical, based on the suspected etiology, and is later adjusted as needed. It ranges from topical administration of active substances to oral drugs, or to complex surgeries in advanced situations. A novel alternative is represented by Photoactivated Chromophore Corneal Collagen Cross-Linking (PACK-CXL), which is widely known as a minimally invasive therapy for corneal degenerations. The purpose of this review is to identify the main diagnostic and prognostic factors which further outline the indications and contraindications of PACK-CXL in infectious keratitis. Given the predominantly positive outcomes in the medical literature, we ponder whether this is a promising treatment modality, which should be further evaluated in a systematic, evidence-based manner in order to develop a clear treatment protocol for successful future results, especially in carefully selected cases.
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Infectious keratitis represents a serious concern for ophthalmologists, with a progressively growing incidence in the last few years. In this prospective comparative study, we evaluated two groups of patients with infectious keratitis or corneal ulcer resistant to antimicrobial and antifungal therapy, treated respectively with conventional and accelerated photoactivated chromophore collagen cross-linking. Eight patients were assigned to each group and they were monitored for 12 months. We investigated the differences between groups, comparing on one side the mean of the quantitative variables using the t-test and on the other side the frequencies of qualitative variables using the Fisher exact test. The time to healing for the group treated with conventional cross-linking was 2 days longer than for the group undergoing accelerated cross-linking (34.9±11.4 vs. 32.9±9.4 days), a difference that did not reach statistical significance (P=0.708). We conclude that the accelerated protocol is as safe and efficient as the classic procedure. The accelerated protocol has an important advantage, both for the doctor and the patient, of being time sparing (the time for accelerated cross-linking is 3 times shorter than in the case of the conventional protocol).
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Parameter estimation is a major challenge in computational modeling of biological processes. This is especially the case in image-based modeling where the inherently quantitative output of the model is measured against image data, which is typically noisy and non-quantitative. In addition, these models can have a high computational cost, limiting the number of feasible simulations, and therefore rendering most traditional parameter estimation methods unsuitable. In this paper, we present a pipeline that uses Gaussian process learning to estimate biological parameters from noisy, non-quantitative image data when the model has a high computational cost. This approach is first successfully tested on a parametric function with the goal of retrieving the original parameters. We then apply it to estimating parameters in a biological setting by fitting artificial in-situ hybridization (ISH) data of the developing murine limb bud. We expect that this method will be of use in a variety of modeling scenarios where quantitative data is missing and the use of standard parameter estimation approaches in biological modeling is prohibited by the computational cost of the model.
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Algoritmos , Simulação por Computador/economia , Embrião de Mamíferos/embriologia , Membro Posterior/embriologia , Processamento de Imagem Assistida por Computador/economia , Modelos Biológicos , Animais , Hibridização In Situ , CamundongosRESUMO
Morphogenesis, the process by which an adult organism emerges from a single cell, has fascinated humans for a long time. Modeling this process can provide novel insights into development and the principles that orchestrate the developmental processes. This chapter focuses on the mathematical description and numerical simulation of developmental processes. In particular, we discuss the mathematical representation of morphogen and tissue dynamics on static and growing domains, as well as the corresponding tissue mechanics. In addition, we give an overview of numerical methods that are routinely used to solve the resulting systems of partial differential equations. These include the finite element method and the Lattice Boltzmann method for the discretization as well as the arbitrary Lagrangian-Eulerian method and the Diffuse-Domain method to numerically treat deforming domains.