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      Endogenous Bioelectric Signaling Networks: Exploiting Voltage Gradients for Control of Growth and Form

      Author(s): , ,
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      Journal: Annual Review of Biomedical Engineering
      Publisher: Annual Reviews

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          Identification of selective inhibitors of cancer stem cells by high-throughput screening.

          Piyush B Gupta, Tamer Onder, Guozhi Jiang … (2009)
          Screens for agents that specifically kill epithelial cancer stem cells (CSCs) have not been possible due to the rarity of these cells within tumor cell populations and their relative instability in culture. We describe here an approach to screening for agents with epithelial CSC-specific toxicity. We implemented this method in a chemical screen and discovered compounds showing selective toxicity for breast CSCs. One compound, salinomycin, reduces the proportion of CSCs by >100-fold relative to paclitaxel, a commonly used breast cancer chemotherapeutic drug. Treatment of mice with salinomycin inhibits mammary tumor growth in vivo and induces increased epithelial differentiation of tumor cells. In addition, global gene expression analyses show that salinomycin treatment results in the loss of expression of breast CSC genes previously identified by analyses of breast tissues isolated directly from patients. This study demonstrates the ability to identify agents with specific toxicity for epithelial CSCs.
          Article 0 comments Cited 819 times – based on 0 reviews     Review now
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            Sparse coding with an overcomplete basis set: A strategy employed by V1?

            Bruno Olshausen, David J Field (1997)
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              Dimensionality reduction for large-scale neural recordings.

              John Cunningham, Byron M Yu (2014)
              Most sensory, cognitive and motor functions depend on the interactions of many neurons. In recent years, there has been rapid development and increasing use of technologies for recording from large numbers of neurons, either sequentially or simultaneously. A key question is what scientific insight can be gained by studying a population of recorded neurons beyond studying each neuron individually. Here, we examine three important motivations for population studies: single-trial hypotheses requiring statistical power, hypotheses of population response structure and exploratory analyses of large data sets. Many recent studies have adopted dimensionality reduction to analyze these populations and to find features that are not apparent at the level of individual neurons. We describe the dimensionality reduction methods commonly applied to population activity and offer practical advice about selecting methods and interpreting their outputs. This review is intended for experimental and computational researchers who seek to understand the role dimensionality reduction has had and can have in systems neuroscience, and who seek to apply these methods to their own data.
              Article 0 comments Cited 382 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Title: Annual Review of Biomedical Engineering
                Abbreviated Title: Annu. Rev. Biomed. Eng.
                Publisher: Annual Reviews
                ISSN (Print): 1523-9829
                ISSN (Electronic): 1545-4274
                Publication date Created: June 21 2017
                Publication date (Print): June 21 2017
                Volume: 19
                Issue: 1
                Pages: 353-387
                Article
                DOI: 10.1146/annurev-bioeng-071114-040647
                PubMed ID: 28633567
                SO-VID: 07bd2a7b-660d-4247-8122-88fc40443e03
                Copyright © © 2017
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