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Machine learning for analysis of gene expression data in fast- and slow-progressing amyotrophic lateral sclerosis murine models

Iadanza Ernesto, Fabbri Rachele, Goretti Francesco, Nardo Giovanni, Niccolai Elena, Bendotti Caterina, Amedei Amedeo

Biocybernetics and Biomedical Engineering

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2022

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Vol. 42, no. 1

273--284

EN

Amyotrophic lateral sclerosis is a fatal motor neuron disease characterised by degenerative changes in both upper and lower motor neurons. Current treatment options in the general cohort of ALS patients have only a minimal impact on survival. Only two approved medications are available today, just addressing the management of symptoms and supporting the respiration. In this work, gene expression data from genetically modified murine motor neurons have been analysed with machine learning techniques, with the scope of distinguishing between mice developing a fast progression of the disease, and mice showing a slower progression. Results showed high accuracy (above 80%) in all tasks, with peaks of accuracy for specific ones – such as distinguishing between fast and slow progression. In the above mentioned task the best performing algorithm reached an accuracy of 100%. This research group is currently working on three more investigations on data from mice, using similar approaches and methodology, focusing on thoracic and lumbar metabolomic data as well as microbiome data. We believe that, based on the findings in the murine models, machine learning could be used to discover ALS progression markers in humans by looking at features related to the immune response. This could pave the path for the discovery of druggable targets and disease biomarkers for homogeneous ALS patient subgroups.

2

A Detailed Study of EEG based Brain Computer Interface

Sharma G., Sharma N., Singh T., Agrawal R.

Annals of Computer Science and Information Systems

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2018

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Vol. 14

137--143

EN

Brain Computer Interface (BCI) generate a direct method to communicate with the outside world. Many patients are not able to communicate. For example:- the patient who are suffered with the several disease like post stroke - the process of thinking, remembering \& recognizing can be challenging. Because of spinal cord injuries or brain stem stroke the patient loss the monitoring power. EEG based brain computer interface (BCI) feature is beneficial to scale the brain movement \& convert them into a instruction for monitoring. In this paper our objective is to study about various applications of EEG based signal of the different disease like spinal cord injury, post stroke and ALS (amyotrophic lateral sclerosis) etc.

3

NMR-based metabonomics of cerebrospinal fluid applied to amyotrophic lateral sclerosis

Toczyłowska B., Jamrozik Z., Liebert A., Kwieciński H.

Biocybernetics and Biomedical Engineering

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2013

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Vol. 33, no. 1

21--32

EN

The aim of this study was applications of cerebrospinal fluid (CSF) NMR-based metabolic fingerprinting to amyotrophic lateral sclerosis (ALS) as possible early diagnostic tool. Two CSF sample categories were collected: 9 ALS patients and 13 age-matched control patients (without neurological disease). Metabolic profile of the CSF was determined by high resolution proton NMR spectroscopy. For statistical analysis magnitudes of 33 signals of the NMR spectrum were selected. Partial least square discriminant analysis (PLS-DA) and orthogonal PLS-DA (OPLS-DA) modeling were used to find potential biomarkers of the disease. Those analyses showed that it was possible to distinguish the ALS patients from the control ones on the basis of the CSF metabolic profile. Significantly higher levels of metabolites observed in the patients with ALS may represent the state of anaerobic metabolism and excitotoxicity.

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The pair-wise linear classifier and the k-NN rule in application to ALS progression differentiation

Sokołowska B., Jóźwik A., Niebroj-Dobosz I., Janik P.

Journal of Medical Informatics & Technologies

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2012

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Vol. 20

79--83

EN

The two kinds of classifier based on the k-NN rule, the standard and the parallel version, were used for recognition of severity of ALS disease. In case of the second classifier version, feature selection was done separately for each pair of classes. The error rate, estimated by the leave one out method, was used as a criterion as for determination the optimum values of k's as well as for feature selection. All features selected in this manner were used in the standard and in the parallel classifier based on k-NN rule. Furthermore, only for the verification purpose, the linear classifier was applied. For this kind of classifier the error rates were calculated by use the training set also as a testing one. The linear classifier was trained by the error correction algorithm with a modified stop condition. The data set concerned with the healthy subjects and patients with amyotrophic lateral sclerosis (ALS). The set of several biomarkers such as erythropoietin, matrix metalloproteinases and their tissue inhibitors measured in serum and cerebrospinal fluid (CSF) were treated as features. It was shown that CSF biomarkers were very sensitive for the ALS progress.

5

Assessment of human motoneuron afterhyperpolarization duration in health and disease

Piotrkiewicz M., Kudina L., Jason Chen J. J., Hausmanowa-Petrusewicz I.

Biocybernetics and Biomedical Engineering

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2012

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Vol. 32, no. 3

43-61

EN

The results of the investigatigation of afterhyperpolarization (AHP) duration in normal aging and selected neuromuscular disorders are presented. This investigation yielded unexpected results: the AHP shortening in myogenic disease (DMD) and no significant difference from control values in neurogenic disease (ALS). However, introduction of age factor revealed novel aspects of the human ALS, which can be interpreted on the basis of the results obtained in a SOD1 mice, thus confirming usefulness of this animal model of ALS. In spastic patients the AHP was prolonged and the difference from the control AHP duration decreased with age and disease duration. Our results suggest that the match between temporal characteristics of the AHP of MN and of the twitch of its muscle unit is preserved during normal aging and in spasticity, but not in the DMD.

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Analysis of matrix metalloproteinases (MMPs) in cerebrospinal fluid of patients with amyotrophic lateral sclerosis (ALS)

Sokołowska B., Jóźwik A., Niebroj-Dobosz I., Janik P., Kwieciński H.

Journal of Medical Informatics & Technologies

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2009

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Vol. 13

147--150

EN

Matrix metalloproteinases (MMPs) are implicated in the pathogenesis of motor neuron degeneration in amyotrophic lateral sclerosis (ALS) and might be potential markers of diagnosis, prognosis and monitoring treatment effects. The aim of the present study was evaluation of the MMPs significance in cerebrospinal fluid (CSF MMPs) of patients with ALS in relation to severity of the disease. Metalloproteinases MT-MMP-1, MMP-2, MMP-9 and additionally age of subjects and disease duration were analyzed. The results demonstrate that the error of differentiation between healthy subjects and ALS patients (for MMP-2 feature) as well as between mild and severe ALS states (for CSF MMPs set) equalled to 0.033. In conclusion, the pattern recognition approach may be useful for differentation of ALS progressing on the basis of CSF MMPs features.

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Progressive die-back and death of motoneurons in a transgenic mouse model of amyotrophic lateral sclerosis

Gordon T., Tam S. L., Sharp P. S., Hegedus. J.

Biocybernetics and Biomedical Engineering

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2005

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Vol. 25, no. 4

17-26

EN

Fischer et al. [1] commented that the longest and largest nerve fibers with the highest metabolic demand appear to be the most susceptible to "dying-back" in a wide variety of degenerative and toxic conditions of the central and peripheral nervous systems. In the high copy number G93AmSOD1 transgenic mouse model of familial amyotrophic lateral sclerosis (ALS) we tested the hypothesis that the largest motoneurons which have the most terminal connections are the most susceptible to the disease. In a time course study of motoneuron, muscle and motor unit properties in fast - and slow-twitch hindlimb muscles of G93A and wild type mice, we found a rapid decline in numbers of functional motor units and motoneurons that progresses from birth to a plateau after 90-100 days of life with surprisingly Iittle compensatory axonal sprouting. Fast motoneurons are the most susceptible, contrasting with the slow motoneurons. Preliminary evidence of loss of S100 reactive perisynaptic Schwann cells at the denervated endplate regions of the affected muscles indicate loss paralIeIs rapid progression of disease with consequent decline in muscle force and motor unit numbers, folIowed closely in time by motoneuron death.