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Assessment of Thyroid Functions in Multiple Sclerosis Patients Treated with Disease Modifying Therapies: Thyroid Functions in Multiple Sclerosis
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Background:

Multiple sclerosis is a chronic disease believed to be the result of autoimmune disorders of the central nervous system, characterised by inflammation, demyelination, and axonal transection, affecting primarily young adults. Disease modifying therapies have become widely used, and the rapid development of these drugs highlighted the need to update our knowledge on their short- and long-term safety profile.

Objective:

The study aim is to evaluate the impact of disease-modifying treatments on thyroid functions and thyroid autoantibodies with subsequent effects on the outcome of the disease.

Materials and Methods:

A retro prospective study enrolled 45 patients who were registered and diagnosed in the Multiple Sclerosis Clinic according to the revised McDonald criteria (2017). Blood samples for thyroid functions and thyroid autoantibody tests were taken before, 3 months and after 6 months from the start of disease modifying therapy. The Expanded Disability Status Scale was used to assess the severity of the disease before and after 6 months of receiving treatment.

Results:

45 patients with the mean age of 33.3 years, a standard deviation (SD) of ± 9.5 years were enrolled in this study. (64.4%) patients’ age was between 20 - 39 years.

The mean free T3 decreased significantly, while the mean anti-TPO and anti-TG increased after three months compared to its baseline level.

After six months of treatment, the mean free T4 decreased significantly, while the mean TSH increased compared to its baseline level. There were no statistically significant correlations between the baseline (EDSS) score and after 6 months of therapy.

Conclusion

Thyroid hormone dysfunction and thyroid autoimmune antibody levels that changed in response to interferon beta therapy in patients with multiple sclerosis may be temporary and not associated with poor outcomes.

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Publication Date
Sat May 28 2022
Journal Name
Abstract And Applied Analysis
Discretization Fractional-Order Biological Model with Optimal Harvesting
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In this paper, a discretization of a three-dimensional fractional-order prey-predator model has been investigated with Holling type III functional response. All its fixed points are determined; also, their local stability is investigated. We extend the discretized system to an optimal control problem to get the optimal harvesting amount. For this, the discrete-time Pontryagin’s maximum principle is used. Finally, numerical simulation results are given to confirm the theoretical outputs as well as to solve the optimality problem.

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Publication Date
Wed Oct 07 2020
Journal Name
Journal Of Interdisciplinary Mathematics
Discrete an SIS model with immigrants and treatment
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In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior

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Publication Date
Thu Nov 01 2012
Journal Name
Journal Of Craniofacial Surgery
Inferior Alveolar Nerve Injuries Associated With Mandibular Fractures
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The study evaluates the incidence of inferior alveolar nerve injuries in mandibular fractures, the duration of their recovery, and the factors associated with them. Fifty-two patients with mandibular fractures involving the ramus, angle, and body regions were included in this study; the inferior alveolar nerve was examined for neurological deficit posttraumatically using sharp/blunt differentiation method, and during the follow-up period the progression of neural recovery was assessed. The incidence of neural injury of the inferior alveolar nerve was 42.3%, comminuted and displaced linear fractures were associated with higher incidence of inferior alveolar nerve injury and prolonged recovery time, and recovery of inferior alveolar nerve fun

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
On New Weibull Inverse Lomax Distribution with Applications
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In this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data  sets

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Constructing fuzzy linear programming model with practical application
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This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB )  to find the optimal solution

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Publication Date
Wed Jan 01 2020
Journal Name
Proceedings Of The 2020 2nd International Conference On Sustainable Manufacturing, Materials And Technologies
The food web prey-predator model with toxin
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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Craniofacial Surgery
Is Orbital Floor Reconstruction With Titanium Mesh Safe?
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Publication Date
Fri Mar 18 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Detecting Deepfakes with Deep Learning and Gabor Filters
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The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

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Publication Date
Sat Jan 01 2022
Journal Name
Intelligent Automation & Soft Computing
A Novel Classification Method with Cubic Spline Interpolation
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Publication Date
Sat Jan 01 2022
Journal Name
Food Science And Technology
Analyzing food production risk with Monte Carlo simulation
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