Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 11447060

Visual prostheses.

E M Maynard
View original source ↗Export metadata ↓

Abstract

The development of man-made systems to restore functional vision in the profoundly blind has recently undergone a renaissance that has been fueled by a combination of celebrity and government interest, advances in the field of bioengineering, and successes with existing neuroprosthetic systems. This chapter presents the underlying physiologic principles of artificial vision, discusses three contemporary approaches to restoring functional vision in the blind, and concludes by presenting several relevant questions to vision prostheses. While there has been significant progress in the individual components constituting an artificial vision system, the remaining challenge of integrating these components with each other and the nervous system does not lie strictly in the realm of neuroscience, medicine, or engineering but at the interface of all three. In spite of the apparent complexity of an artificial vision system, it is not unreasonable to be optimistic about its eventual success.

Explore related subjects

Biomedical EngineeringEye, ArtificialHumansOptic NerveProsthesis DesignRetinaVision, OcularJournal ArticleReview

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

E M Maynard. 2001. Visual prostheses.. https://doi.org/10.1146/annurev.bioeng.3.1.145

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2002

Modeling and simulation: tools for metabolic engineering.

Mathematical modeling is one of the key methodologies of metabolic engineering. Based on a given metabolic model different computational tools for the simulation, data evaluation, systems analysis, prediction, design and optimization of metabolic systems have been developed. The currently used metabolic modeling approaches can be subdivided into structural models, stoichiometric models, carbon flux models, stationary and nonstationary mechanistic models and models with gene regulation. However, the power of a model strongly depends on its basic modeling assumptions, the simplifications made and the data sources used. Model validation turns out to be particularly difficult for metabolic systems. The different modeling approaches are critically reviewed with respect to their potential and benefits for the metabolic engineering cycle. Several tools that have emerged from the different modeling approaches including structural pathway synthesis, stoichiometric pathway analysis, metabolic flux analysis, metabolic control analysis, optimization of regulatory architectures and the evaluation of rapid sampling experiments are discussed.

Biomedical Engineering↗
PubMed2002

Optimizing bioconversion pathways through systems analysis and metabolic engineering.

We demonstrate a general approach for metabolic engineering of biocatalytic systems comprising the uses of a chemostat for strain improvement and radioisotopic tracers for the quantification of pathway fluxes. Flux determination allows the identification of target pathways for modification as validated by subsequent overexpression of the corresponding gene. We demonstrate this method in the indene bioconversion network of Rhodococcus modified for the overproduction of 1,2-indandiol, a key precursor for the AIDS drug Crixivan.

Biomedical Engineering↗
PubMed2002

Analysis of carbon metabolism in Escherichia coli strains with an inactive phosphotransferase system by (13)C labeling and NMR spectroscopy.

We have developed Escherichia coli strains that internalize glucose utilizing the GalP permease instead of the phosphoenolpyruvate:carbohydrate phosphotransferase system. It has been demonstrated that a strain with these modifications (PTS(-)Glc(+)) can direct more carbon flux into the aromatic pathway than the wild-type parental strain (N. Flores et al., 1996, Nat. Biotechnol. 14, 620-623; G. Gosset et al., 1996, J. Ind. Microbiol. 17, 47-52; J. L. Baéz et al., 2001, Biotechnol. Bioeng. 73, 530-535). In this study, we have determined and compared the carbon fluxes of a wild-type strain (JM101), a PTS(-)Glc(-) strain, and two isogenic PTS(-)Glc(+) derivatives named PB12 and PB13 by combining genetic, biochemical, and NMR approaches. It was determined that in these strains a functional glk gene in the chromosome is required for rapid glucose consumption; furthermore, glucokinase-specific activities were higher than in the wild-type strain. (13)C labeling and NMR analysis allowed the determination of differences in vivo which include higher glycolytic fluxes of 93.1 and 89.2% compared with the 76.6% obtained for the wild-type E. coli. In PB12 and PB13 we found a flux through the malic enzymes of 4 and 10%, respectively, compared to zero in the wild-type strain. While flux through the Pck enzyme was absent in PB12 and PB13, in the wild type it was 7.7%. Finally, it was found that in the JM101 and PB12 strains both the oxidative and the nonoxidative branches of the pentose phosphate pathway contributed to ribose 5-phosphate synthesis, whereas in PB13 this pentose was synthesized almost exclusively through the oxidative branch. The determined carbon fluxes correlate with biochemical and genetic characterizations.

Biomedical Engineering↗