57 research outputs found
Growing gold nanostructures for shape-selective cellular uptake.
With development in the synthesis of shape- and size-dependent gold (Au) nanostructures (NSs) and their applications in nanomedicine, one of the biggest challenges is to understand the interaction of these shapes with cancer cells. Herein, we study the interaction of Au NSs of five different shapes with glioblastoma-astrocytoma cells. Three different shapes (nanorods, tetrahexahedra, and bipyramids), possessing tunable optical properties, have been synthesized by a single-step seed-mediated growth approach employing binary surfactant mixtures of CTAB and a secondary surfactant. By the use of two-step seed-mediated approach, we obtained new NSs, named nanomakura (Makura is a Japanese word used for pillow) which is reported for the first time here. Spherical Au nanoparticles were prepared by the Turkevich method. To study NS-cell interactions, we functionalized the NSs using thiolated PEG followed by 11-Mercaptoundecanoic acid. The influence of shape and concentration of NSs on the cytotoxicity were assessed with a LIVE/DEAD assay in glioblastoma-astrocytoma cells. Furthermore, the time-dependent uptake of nanomakura was studied with TEM. Our results indicate that unlike the other shapes studied here, the nanomakura were taken up both via receptor-mediated endocytosis and macropinocytosis. Thus, from our library of different NSs with similar surface functionality, the shape is found to be an important parameter for cellular uptake
A general representation of dynamical systems for reservoir computing
Dynamical systems are capable of performing computation in a reservoir
computing paradigm. This paper presents a general representation of these
systems as an artificial neural network (ANN). Initially, we implement the
simplest dynamical system, a cellular automaton. The mathematical fundamentals
behind an ANN are maintained, but the weights of the connections and the
activation function are adjusted to work as an update rule in the context of
cellular automata. The advantages of such implementation are its usage on
specialized and optimized deep learning libraries, the capabilities to
generalize it to other types of networks and the possibility to evolve cellular
automata and other dynamical systems in terms of connectivity, update and
learning rules. Our implementation of cellular automata constitutes an initial
step towards a general framework for dynamical systems. It aims to evolve such
systems to optimize their usage in reservoir computing and to model physical
computing substrates.Comment: 5 pages, 3 figures, accepted workshop paper at Workshop on Novel
Substrates and Models for the Emergence of Developmental, Learning and
Cognitive Capabilities at IEEE ICDL-EPIROB 201
Effects of Neural Stem Cell and Olfactory Ensheathing Cell Co-transplants on Tissue Remodelling After Transient Focal Cerebral Ischemia in the Adult Rat
Connectomics of morphogenetically engineered neurons as a predictor of functional integration in the ischemic brain
Recent advances in cell reprogramming technologies enable the in vitro generation of theoretically unlimited numbers of cells, including cells of neural lineage and specific neuronal subtypes from human, including patient-specific, somatic cells. Similarly, as demonstrated in recent animal studies, by applying morphogenetic neuroengineering principles in situ, it is possible to reprogram resident brain cells to the desired phenotype. These developments open new exciting possibilities for cell replacement therapy in stroke, albeit not without caveats. Main challenges include the successful integration of engineered cells in the ischemic brain to promote functional restoration as well as the fact that the underlying mechanisms of action are not fully understood. In this review, we aim to provide new insights to the above in the context of connectomics of morphogenetically engineered neural networks. Specifically, we discuss the relevance of combining advanced interdisciplinary approaches to: validate the functionality of engineered neurons by studying their self-organizing behavior into neural networks as well as responses to stroke-related pathology in vitro; derive structural and functional connectomes from these networks in healthy and perturbed conditions; and identify and extract key elements regulating neural network dynamics, which might predict the behavior of grafted engineered neurons post-transplantation in the stroke-injured brain
Editorial : Criticality in neural network behavior and its implications for computational processing in healthy and perturbed conditions
Connectomics of Morphogenetically Engineered Neurons as a Predictor of Functional Integration in the Ischemic Brain
Recent advances in cell reprogramming technologies enable the in vitro generation of theoretically unlimited numbers of cells, including cells of neural lineage and specific neuronal subtypes from human, including patient-specific, somatic cells. Similarly, as demonstrated in recent animal studies, by applying morphogenetic neuroengineering principles in situ, it is possible to reprogram resident brain cells to the desired phenotype. These developments open new exciting possibilities for cell replacement therapy in stroke, albeit not without caveats. Main challenges include the successful integration of engineered cells in the ischemic brain to promote functional restoration as well as the fact that the underlying mechanisms of action are not fully understood. In this review, we aim to provide new insights to the above in the context of connectomics of morphogenetically engineered neural networks. Specifically, we discuss the relevance of combining advanced interdisciplinary approaches to: validate the functionality of engineered neurons by studying their self-organizing behavior into neural networks as well as responses to stroke-related pathology in vitro; derive structural and functional connectomes from these networks in healthy and perturbed conditions; and identify and extract key elements regulating neural network dynamics, which might predict the behavior of grafted engineered neurons post-transplantation in the stroke-injured brain
The role of olfactory ensheathing cells, MRI, and biomaterials in transplant-mediated CNS repair
Bruk av olfaktoriske ensheathing celler, MRI og biomaterialer i transplantasjonsmediert reparasjon av CNS skader
Den beskrevne studien har brukt en interdisiplinær tilnærming for å evaluere transplantasjons mediert CNS reparasjon i en skademodell av synsnerven. Ved å integrere forskjellige MRI metoder har vi analysert olfaktoriske ensheathing celler’s (OEC) evne til å integrere og overleve in vivo i vår skademodell. Cellenes evne til å modulere regenerasjonen av den skadede synsnerven er også dokumentert ultrastrukturelt med elektronmikroskopi (EM). Studien har også omfattet in vitro analyser av interaksjonen mellom OEC og modifiserte biopolymerer i 2-og 3-dimensjonale matriser.
Den spesifikke målsetningen med denne studien har vært: (a) Utvikle protokoller for effektiv merkning av OEC med mikron store jern partikler; (b) Kombinere cellulær MRI og mangan-forsterket MRI (MEMRI) for spatiotemporal monitorering av intravitreal (ivit) og intra-optisk nerve (iON) transplantasjon av OEC; (c) Studere celleimplantatenes evne til å promotere regenerasjon av synsbane aksoner etter skade i synsnerven både (i) longitudinelt in vivo med MRI og (ii) ultrastrukturelt med transmisjons elektron mikroskopi (TEM); (d) Produsere og teste modifiserte alginat strukturer som plattformer for kontrollert frigjøring av mangan (Mn2+) brukt som kontrastmiddel ved MEMRI; (e) Utvikle arginin-glycin-aspartat (RGD)-peptid alginater og karakterisere interaksjonen med OEC dyrket på disse modifiserte aliginat matrisene.
I avhandlingen presenteres gjennomføringen av disse målene og belyser potensialet av å integrere MRI, biomateraler og celleterapeutiske teknologier i studier av transplantasjons-mediert reparasjon av skader i CNS
Silencing of Activity During Hypoxia Improves Functional Outcomes in Motor Neuron Networks in vitro
The effects of hypoxia, or reduced oxygen supply, to brain tissue can be disastrous, leading to extensive loss of function. Deoxygenated tissue becomes unable to maintain healthy metabolism, which leads to increased production of reactive oxygen species (ROS) and loss of calcium homoeostasis, with damaging downstream effects. Neurons are a highly energy demanding cell type, and as such they are highly sensitive to reductions in oxygenation and some types of neurons such as motor neurons are even more susceptible to hypoxic damage. In addition to the immediate deleterious effects hypoxia can have on neurons, there can be delayed effects which lead to increased risk of developing neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), even if no immediate consequences are apparent. Furthermore, impairment of the function of various hypoxia-responsive factors has been shown to increase the risk of developing several neurodegenerative disorders. Longitudinal assessment of electrophysiological network activity is underutilised in assessing the effects of hypoxia on neurons and how their activity and communication change over time following a hypoxic challenge. This study utilised multielectrode arrays and motor neuron networks to study the response to hypoxia and the subsequent development of the neuronal activity over time, as well as the effect of silencing network activity during the hypoxic challenge. We found that motor neuron networks exposed to hypoxic challenge exhibited a delayed fluctuation in multiple network activity parameters compared to normoxic networks. Silencing of activity during the hypoxic challenge leads to maintained bursting activity, suggesting that functional outcomes are better maintained in these networks and that there are activity-dependent mechanisms involved in the network damage following hypoxia
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