Professional Reading

The History of the Joint Chiefs of Staff In World War II: The War Against Japa

The Teleost Retina as a Model for Developmental and Regeneration Biology

Retinal development in teleosts can broadly be divided into three epochs. The first is the specification of cellular domains in the larval forebrain that give rise to the retinal primordia and undergo early morphogenetic movements. The second is the neurogenic events within the retina proper—proliferation, cell fate determination, and pattern formation—that establish neuronal identities and form retinal laminae and cellular mosaics. The third, which is unique to teleosts and occurs in the functioning eye, is stretching of the retina and persistent neurogenesis that allows the growth of the retina to keep pace with the growth of the eye and other tissues. The first two events are rapid, complete by about 3 days postfertilization in the zebrafish embryo. The third is life-long and accounts for the bulk of retinal growth and the vast majority of adult retinal neurons. In addition, but clearly related to the retina's developmental history, lesions that kill retinal neurons elicit robust neuronal regeneration that originates from cells intrinsic to the retina. This paper reviews recent studies of retinal development in teleosts, focusing on those that shed light on the genetic and molecular regulation of retinal specification and morphogenesis in the embryo, retinal neurogenesis in larvae and adults, and injury-induced neuronal regeneration.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63365/1/zeb.2004.1.257.pd

The APEX Quantitative Proteomics Tool: Generating protein quantitation estimates from LC-MS/MS proteomics results

Mass spectrometry (MS) based label-free protein quantitation has mainly focused on analysis of ion peak heights and peptide spectral counts. Most analyses of tandem mass spectrometry (MS/MS) data begin with an enzymatic digestion of a complex protein mixture to generate smaller peptides that can be separated and identified by an MS/MS instrument. Peptide spectral counting techniques attempt to quantify protein abundance by counting the number of detected tryptic peptides and their corresponding MS spectra. However, spectral counting is confounded by the fact that peptide physicochemical properties severely affect MS detection resulting in each peptide having a different detection probability. Lu et al. (2007) described a modified spectral counting technique, Absolute Protein Expression (APEX), which improves on basic spectral counting methods by including a correction factor for each protein (called O(i) value) that accounts for variable peptide detection by MS techniques. The technique uses machine learning classification to derive peptide detection probabilities that are used to predict the number of tryptic peptides expected to be detected for one molecule of a particular protein (O(i)). This predicted spectral count is compared to the protein's observed MS total spectral count during APEX computation of protein abundances. Results: The APEX Quantitative Proteomics Tool, introduced here, is a free open source Java application that supports the APEX protein quantitation technique. The APEX tool uses data from standard tandem mass spectrometry proteomics experiments and provides computational support for APEX protein abundance quantitation through a set of graphical user interfaces that partition thparameter controls for the various processing tasks. The tool also provides a Z-score analysis for identification of significant differential protein expression, a utility to assess APEX classifier performance via cross validation, and a utility to merge multiple APEX results into a standardized format in preparation for further statistical analysis. Conclusion: The APEX Quantitative Proteomics Tool provides a simple means to quickly derive hundreds to thousands of protein abundance values from standard liquid chromatography-tandem mass spectrometry proteomics datasets. The APEX tool provides a straightforward intuitive interface design overlaying a highly customizable computational workflow to produce protein abundance values from LC-MS/MS datasets.National Institute of Allergy and Infectious Diseases (NIAID) N01-AI15447National Institutes of HealthNational Science Foundation, the Welsh and Packard FoundationsInternational Human Frontier Science ProgramCenter for Systems and Synthetic Biolog