scholarly journals 45698 Molecular Signatures of Cocaine Neurotoxicity in Human Brain Models

Author(s):  
Emily Mendez ◽  
Laura Stertz ◽  
Gabriel Fries ◽  
Ruifeng Hu ◽  
Thomas Meyer ◽  
...  
IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 111303-111315 ◽  
Author(s):  
Jaakko Hakala ◽  
Joni Kilpijarvi ◽  
Mariella Sarestoniemi ◽  
Matti Hamalainen ◽  
Sami Myllymaki ◽  
...  

Author(s):  
Estela Suarez ◽  
Susanne Kunkel ◽  
Anne Küsters ◽  
Hans Ekkehard Plesser ◽  
Thomas Lippert

AbstractThe precise simulation of the human brain requires coupling different models in order to cover the different physiological and functional aspects of this extremely complex organ. Each of this brain models is implemented following specific mathematical and programming approaches, potentially leading to diverging computational behaviour and requirements. Such situation is the typical use case that can benefit from the Modular Supercomputing Architecture (MSA), which organizes heterogeneous computing resources at system level. This architecture and its corresponding software environment enable to run each part of an application or a workflow on the best suited hardware.This paper presents the MSA concept covering current hardware and software implementations, and describes how the neuroscientific workflow resulting of coupling the codes NEST and Arbor is being prepared to exploit the MSA.


Author(s):  
J. Sebastian Giudice ◽  
Ahmed Alshareef ◽  
Taotao Wu ◽  
Andrew K. Knutsen ◽  
Lucy V. Hiscox ◽  
...  

Central to the investigation of the biomechanics of traumatic brain injury (TBI) and the assessment of injury risk from head impact are finite element (FE) models of the human brain. However, many existing FE human brain models have been developed with simplified representations of the parenchyma, which may limit their applicability as an injury prediction tool. Recent advances in neuroimaging techniques and brain biomechanics provide new and necessary experimental data that can improve the biofidelity of FE brain models. In this study, the CAB-20MSym template model was developed, calibrated, and extensively verified. To implement material heterogeneity, a magnetic resonance elastography (MRE) template image was leveraged to define the relative stiffness gradient of the brain model. A multi-stage inverse FE (iFE) approach was used to calibrate the material parameters that defined the underlying non-linear deviatoric response by minimizing the error between model-predicted brain displacements and experimental displacement data. This process involved calibrating the infinitesimal shear modulus of the material using low-severity, low-deformation impact cases and the material non-linearity using high-severity, high-deformation cases from a dataset of in situ brain displacements obtained from cadaveric specimens. To minimize the geometric discrepancy between the FE models used in the iFE calibration and the cadaveric specimens from which the experimental data were obtained, subject-specific models of these cadaveric brain specimens were developed and used in the calibration process. Finally, the calibrated material parameters were extensively verified using independent brain displacement data from 33 rotational head impacts, spanning multiple loading directions (sagittal, coronal, axial), magnitudes (20–40 rad/s), durations (30–60 ms), and severity. Overall, the heterogeneous CAB-20MSym template model demonstrated good biofidelity with a mean overall CORA score of 0.63 ± 0.06 when compared to in situ brain displacement data. Strains predicted by the calibrated model under non-injurious rotational impacts in human volunteers (N = 6) also demonstrated similar biofidelity compared to in vivo measurements obtained from tagged magnetic resonance imaging studies. In addition to serving as an anatomically accurate model for further investigations of TBI biomechanics, the MRE-based framework for implementing material heterogeneity could serve as a foundation for incorporating subject-specific material properties in future models.


2021 ◽  
Vol 53 ◽  
pp. S199-S200
Author(s):  
P. Lukow ◽  
D. Martins ◽  
M. Veronese ◽  
P. McGuire ◽  
F.E. Turkheimer ◽  
...  

Cells ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 106
Author(s):  
Anssi Pelkonen ◽  
Cristiana Pistono ◽  
Pamela Klecki ◽  
Mireia Gómez-Budia ◽  
Antonios Dougalis ◽  
...  

Human pluripotent stem cell (hPSC)-derived neuron cultures have emerged as models of electrical activity in the human brain. Microelectrode arrays (MEAs) measure changes in the extracellular electric potential of cell cultures or tissues and enable the recording of neuronal network activity. MEAs have been applied to both human subjects and hPSC-derived brain models. Here, we review the literature on the functional characterization of hPSC-derived two- and three-dimensional brain models with MEAs and examine their network function in physiological and pathological contexts. We also summarize MEA results from the human brain and compare them to the literature on MEA recordings of hPSC-derived brain models. MEA recordings have shown network activity in two-dimensional hPSC-derived brain models that is comparable to the human brain and revealed pathology-associated changes in disease models. Three-dimensional hPSC-derived models such as brain organoids possess a more relevant microenvironment, tissue architecture and potential for modeling the network activity with more complexity than two-dimensional models. hPSC-derived brain models recapitulate many aspects of network function in the human brain and provide valid disease models, but certain advancements in differentiation methods, bioengineering and available MEA technology are needed for these approaches to reach their full potential.


2021 ◽  
pp. 2101251
Author(s):  
You Jung Kang ◽  
Hsih‐Yin Tan ◽  
Charles Y. Lee ◽  
Hansang Cho

2021 ◽  
Vol 13 (1) ◽  
pp. 011001 ◽  
Author(s):  
Theresa S P Rothenbücher ◽  
Hakan Gürbüz ◽  
Marta P Pereira ◽  
Arto Heiskanen ◽  
Jenny Emneus ◽  
...  

2021 ◽  
Vol 8 (21) ◽  
pp. 2170145
Author(s):  
You Jung Kang ◽  
Hsih‐Yin Tan ◽  
Charles Y. Lee ◽  
Hansang Cho

2021 ◽  
Author(s):  
Maria Mavrikaki ◽  
Jonathan D. Lee ◽  
Isaac H. Solomon ◽  
Frank J. Slack

Coronavirus disease 2019 (COVID-19) is predominantly an acute respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and remains a significant threat to public health. COVID-19 is accompanied by neurological symptoms and cognitive decline, but the molecular mechanisms underlying this effect remain unclear. As aging induces distinct molecular signatures in the brain associated with cognitive decline in healthy populations, we hypothesized that COVID-19 may induce molecular signatures of aging. Here, we performed whole transcriptomic analysis of human frontal cortex, a critical area for cognitive function, in 12 COVID-19 cases and age- and sex-matched uninfected controls. COVID-19 induces profound changes in gene expression, despite the absence of detectable virus in brain tissue. Pathway analysis shows downregulation of genes involved in synaptic function and cognition and upregulation of genes involved in immune processes. Comparison with five independent transcriptomic datasets of aging human frontal cortex reveals striking similarities between aged individuals and severe COVID-19 patients. Critically, individuals below 65 years of age exhibit profound transcriptomic changes not observed among older individuals in our patient cohort. Our data indicate that severe COVID-19 induces molecular signatures of aging in the human brain and emphasize the value of neurological follow-up in recovered individuals.


Neuron ◽  
2021 ◽  
Author(s):  
Matthew N. Tran ◽  
Kristen R. Maynard ◽  
Abby Spangler ◽  
Louise A. Huuki ◽  
Kelsey D. Montgomery ◽  
...  

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