Relapsing remitting multiple sclerosis in an Iranian patient with neurofibromatosis type I

Neurofibromatosis type 1 (NF-1) is a common hereditary neurocutaneous disease, with known gene mutations, that mainly involves the skin and nervous system. Multiple sclerosis (MS) is an acquired inflammatory disease in which the myelin of nerve cells in the brain and spinal cord is damaged. These two disease do not share any apparent pathological similarities. We herein present a 32-year-old woman with definite NF-1, who has recently been diagnosed with MS, which to the best of our knowledge is a rare co-occurrence. Though there are often neurologic sign and symptoms in patients with NF-1, they should not always be considered as the natural history of the disease, and other overlapped pathologies should be kept in mind, in order to not miss or postpone the efficient treatment. © N. Mohebi et al., 2015

Opsoclonus-myoclonus syndrome, a post-infectious neurologic complication of COVID-19: case series and review of literature

Opsoclonus-myoclonus-ataxia syndrome is a heterogeneous constellation of symptoms ranging from full combination of these three neurological findings to varying degrees of isolated individual sign. Since the emergence of coronavirus disease 2019 (COVID-19), neurological symptoms, syndromes, and complications associated with this multi-organ viral infection have been reported and the various aspects of neurological involvement are increasingly uncovered. As a neuro-inflammatory disorder, one would expect to observe opsoclonus-myoclonus syndrome after a prevalent viral infection in a pandemic scale, as it has been the case for many other neuro-inflammatory syndromes. We report seven cases of opsoclonus-myoclonus syndrome presumably parainfectious in nature and discuss their phenomenology, their possible pathophysiological relationship to COVID-19, and diagnostic and treatment strategy in each case. Finally, we review the relevant data in the literature regarding the opsoclonus-myoclonus syndrome and possible similar cases associated with COVID-19 and its diagnostic importance for clinicians in various fields of medicine encountering COVID-19 patients and its complications. © 2021, Journal of NeuroVirology, Inc

A novel homozygous variation in the PANK2 gene in two Persian siblings with atypical pantothenate kinase associated neurodegeneration

Pantothenate Kinase-associated Neurodegeneration (PKAN) is an autosomal recessive disorder that is caused by variation in pantothenate kinase-2 gene (PANK2) gene on chromosome 20. The common presentation of this disease includes progressive dystonia, Parkinsonism, retinopathy, cognitive impairment, and spasticity. The typical magnetic resonance imaging finding is eye of the tiger sign in globus pallidus and not pathogenic and not found in all patients. In the present study, we describe two siblings who have a novel variation of the PANK2 gene. These patients with the same genotype, have different ages at the onset of disease and also the various severity of the disease. The description of these cases helps to understand this disease, its symptoms, pathogenesis, and its treatment. © A.H. Habibi et al., 2019

Improving the Performance of a Fuzzy Logic Model in Seismic Damage Prediction using a Guided Adaptive Search-based Particle Swarm Optimization ALGORITHM

This paper proposes a fuzzy logic model to improve the accuracy of seismic damageability simulations for buildings. The Rapid Visual Screening (RVS) method is often used to evaluate seismic damages in buildings due to its speed and simplicity, but it can be subject to human error and other uncertainties. The proposed model uses fuzzy logic to address these uncertainties and build a more robust simulator for estimating the seismic damage state. To fine-tune the hyperparameters of the fuzzy model, the Guided Adaptive Search-based Particle Swarm Optimization (GuASPSO) algorithm is used, which has been shown to be efficient and effective. The model is applied to simulate the damageability of reinforced concrete buildings damaged in the 2017 Sar-Pol-Zahab earthquake in Iran, and the results are compared to those obtained using two popular meta-heuristic optimizers, the PSO and GWO algorithms. The results demonstrate that the GuASPSO algorithm outperforms the other two in terms of performance metrics in the training, validation, and total data sets. The proposed model is a significant step toward more accurate and practical seismic damageability simulations