scholarly journals Designing Patient-Specific Optimal Neurostimulation Patterns for Seizure Suppression

2018 ◽  
Vol 30 (5) ◽  
pp. 1180-1208 ◽  
Author(s):  
Roman A. Sandler ◽  
Kunling Geng ◽  
Dong Song ◽  
Robert E. Hampson ◽  
Mark R. Witcher ◽  
...  
Keyword(s):  
Global Optimization ◽  
Closed Loop ◽  
Epileptic Seizures ◽  
Patient Specific ◽  
Spontaneous Seizure ◽  
Global Optimization Algorithm ◽  
Neuron Network ◽  
Seizure State ◽  
Wide Range ◽  
Stimulation Pattern

Neurostimulation is a promising therapy for abating epileptic seizures. However, it is extremely difficult to identify optimal stimulation patterns experimentally. In this study, human recordings are used to develop a functional 24 neuron network statistical model of hippocampal connectivity and dynamics. Spontaneous seizure-like activity is induced in silico in this reconstructed neuronal network. The network is then used as a testbed to design and validate a wide range of neurostimulation patterns. Commonly used periodic trains were not able to permanently abate seizures at any frequency. A simulated annealing global optimization algorithm was then used to identify an optimal stimulation pattern, which successfully abated 92% of seizures. Finally, in a fully responsive, or closed-loop, neurostimulation paradigm, the optimal stimulation successfully prevented the network from entering the seizure state. We propose that the framework presented here for algorithmically identifying patient-specific neurostimulation patterns can greatly increase the efficacy of neurostimulation devices for seizures.

scholarly journals Rapid Motor Fluctuations Reveal Short-Timescale Neurophysiological Biomarkers of Parkinson’s Disease

2020 ◽  
Author(s):  
Minkyu Ahn ◽  
Shane Lee ◽  
Peter M. Lauro ◽  
Erin L. Schaeffer ◽  
Umer Akbar ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neural Activity ◽  
Motor Performance ◽  
Closed Loop ◽  
Oscillatory Activity ◽  
Patient Specific ◽  
Significant Information ◽  
Informative Signal ◽  
Wide Range

ABSTRACTIdentifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson’s Disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. Here, we recorded neural activity from the subthalamic nucleus (STN) of patients with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment. This approach leveraged natural motor performance variations as a basis to identify corresponding neurophysiological biomarkers. Using machine learning techniques, we show it was possible to use neural signals from the STN to decode the level of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic “β” oscillations, contributed to this decoding. While signals providing significant information about the quality of motor performance were found throughout the STN, the most informative signals tended to arise from locations in or near the dorsolateral, sensorimotor portion. Importantly, the informative patterns of neural oscillations were not fully generalizable across subjects, suggesting a patient-specific approach will be critical for optimal disease tracking and closed-loop neuromodulation.

scholarly journals Stem cell therapies and benefaction of somatic cell nuclear transfer cloning in COVID-19 era

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Birbal Singh ◽  
Gorakh Mal ◽  
Vinod Verma ◽  
Ruchi Tiwari ◽  
Muhammad Imran Khan ◽  
...  
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Regenerative Medicine ◽  
Somatic Cell ◽  
Somatic Cell Nuclear Transfer ◽  
Nuclear Transfer ◽  
Drug Testing ◽  
Human Interaction ◽  
Patient Specific ◽  
Wide Range

Abstract Background The global health emergency of COVID-19 has necessitated the development of multiple therapeutic modalities including vaccinations, antivirals, anti-inflammatory, and cytoimmunotherapies, etc. COVID-19 patients suffer from damage to various organs and vascular structures, so they present multiple health crises. Mesenchymal stem cells (MSCs) are of interest to treat acute respiratory distress syndrome (ARDS) caused by SARS-CoV-2 infection. Main body Stem cell-based therapies have been verified for prospective benefits in copious preclinical and clinical studies. MSCs confer potential benefits to develop various cell types and organoids for studying virus-human interaction, drug testing, regenerative medicine, and immunomodulatory effects in COVID-19 patients. Apart from paving the ways to augment stem cell research and therapies, somatic cell nuclear transfer (SCNT) holds unique ability for a wide range of health applications such as patient-specific or isogenic cells for regenerative medicine and breeding transgenic animals for biomedical applications. Being a potent cell genome-reprogramming tool, the SCNT has increased prominence of recombinant therapeutics and cellular medicine in the current era of COVID-19. As SCNT is used to generate patient-specific stem cells, it avoids dependence on embryos to obtain stem cells. Conclusions The nuclear transfer cloning, being an ideal tool to generate cloned embryos, and the embryonic stem cells will boost drug testing and cellular medicine in COVID-19.

A closed-loop wide-range tunable mechanical resonator for energy harvesting systems

2009 ◽  
Vol 19 (9) ◽  
pp. 094004 ◽  
Author(s):  
Christian Peters ◽  
Dominic Maurath ◽  
Wolfram Schock ◽  
Florian Mezger ◽  
Yiannos Manoli
Keyword(s):  
Energy Harvesting ◽  
Closed Loop ◽  
Mechanical Resonator ◽  
Wide Range ◽  
Harvesting Systems

Implementation of Eurocode Load Cases in Optimization Problems of Steel Frames, Based on Genetic Algorithms

2013 ◽  
Vol 310 ◽  
pp. 609-613
Author(s):  
Ioana D. Balea ◽  
Radu Hulea ◽  
Georgios E. Stavroulakis
Keyword(s):  
Finite Element ◽  
Genetic Algorithms ◽  
Global Optimization ◽  
Optimal Design ◽  
Optimization Problems ◽  
Steel Frames ◽  
Global Optimization Algorithm ◽  
Planar Structures ◽  
Discrete Global Optimization ◽  
Steel Sections

This paper presents an implementation of Eurocode load cases for discrete global optimization algorithm for planar structures based on the principles of finite element methods and genetic algorithms. The final optimal design is obtained using IPE sections chosen as feasible by the algorithm, from the available steel sections from industry. The algorithm is tested on an asymmetric planar steel frame with promising results.

scholarly journals Could metabolomics drive the fate of COVID-19 pandemic? A narrative review on lights and shadows

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michele Mussap ◽  
Vassilios Fanos
Keyword(s):  
Molecular Mechanisms ◽  
Vascular Dysfunction ◽  
Asymptomatic Infection ◽  
Multiple Organ ◽  
Therapeutic Interventions ◽  
Patient Specific ◽  
Wide Range ◽  
Life Threatening ◽  
The Individual ◽  
Host Metabolism

Abstract Human Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection activates a complex interaction host/virus, leading to the reprogramming of the host metabolism aimed at the energy supply for viral replication. Alterations of the host metabolic homeostasis strongly influence the immune response to SARS-CoV-2, forming the basis of a wide range of outcomes, from the asymptomatic infection to the onset of COVID-19 and up to life-threatening acute respiratory distress syndrome, vascular dysfunction, multiple organ failure, and death. Deciphering the molecular mechanisms associated with the individual susceptibility to SARS-CoV-2 infection calls for a system biology approach; this strategy can address multiple goals, including which patients will respond effectively to the therapeutic treatment. The power of metabolomics lies in the ability to recognize endogenous and exogenous metabolites within a biological sample, measuring their concentration, and identifying perturbations of biochemical pathways associated with qualitative and quantitative metabolic changes. Over the last year, a limited number of metabolomics- and lipidomics-based clinical studies in COVID-19 patients have been published and are discussed in this review. Remarkable alterations in the lipid and amino acid metabolism depict the molecular phenotype of subjects infected by SARS-CoV-2; notably, structural and functional data on the lipids-virus interaction may open new perspectives on targeted therapeutic interventions. Several limitations affect most metabolomics-based studies, slowing the routine application of metabolomics. However, moving metabolomics from bench to bedside cannot imply the mere determination of a given metabolite panel; rather, slotting metabolomics into clinical practice requires the conversion of metabolic patient-specific data into actionable clinical applications.

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