A computer-based plant/soil-aeration bibliography

Numerous reviews of the general topic of plant and soil aeration have appeared in the past generation. Two comprehensive recent examples are Kozlowski (1984) and Glinaki and Stepniewski (1985). Each is excellently documented and thoroughly covers its subject matter, though perhaps from somewhat divergent perspectives. As might be expected the source of citations contained in each volume's bibliography largely reflects the geographical orientation and principal area of expertise of the contributors. In each case, undoubtedly, the authors compiled large collections of reprints and second-source citations which were summarized and synthesized into reviews. In the process, the authors characterized the citations of which they were aware, eliminated some of these from final use in the reviews, and probably missed some citations in the literature. The nature of review writing, until only recently, has demanded that these efforts be largely individual, uncoordinated, tedious, and transitory (the work of collecting and compiling the information is usually lost with the author's shift of interest, retirement, or other activity-influencing career changes). Occasionally such a bibliography may be handed down from major professor to student. Even in these cases, however, the bibliographies are not widely available. The advent of computer-based information storage and retrieval has created new opportunities. Commercial literature retrieval services exist that scan organized data bases (e.g. SCI SEARCH* and DIALOG). Even with the continued expansion of the data bases of these systems they have certain shortcomings. For the unfamiliar users of these systems there is usually difficulty in limiting the searches sufficiently to retrieve only desired citations without excluding elusive citations that may be unconventionally titled or that may not contain certain specific keywords needed to retrieve the desired citations. Commercial literature retrieval can also prove to be expensive for some users, particularly if a comprehensive retrospective search is desired. If a subject matter area were sufficiently limited in scope it could be possible for a few interested researchers cooperatively to compile a highly comprehensive listing of the relevant literature. A familiar example of such effort was the compilation of a bibliography on the topic of 15N by Hauck and Bystrom (1970). Their bibliography, published as a book, provided an excellent fixed resource, but one which lacked the capacity to grow or be manipulated. The advent of powerful microcomputers and inexpensive data-base software now enables the compilation of highly specific manipulable bibliographies. These bibliographies offer the advantage of being indexed by author, date, keywords, etc., of being sorted by subcategories, and of being copied and shared in a compact format (e.g. on floppy disk, tape, EPROM), and easily updated and expanded

Sorting Signals, N-Terminal Modifications and Abundance of the Chloroplast Proteome

Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that ‘spectral counting’ can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models

Confirmatory factor analysis of the Beck Depression inventory in obese individuals seeking surgery

Background : The Beck Depression Inventory (BDI) is frequently employed as measure of depression in studies of obesity. The aim of the study was to assess the factorial structure of the BDI in obese patients prior to bariatric surgery. Methods : Confirmatory factor analysis was conducted on the current published factor analyses of the BDI. Three published models were initially analysed with two additional modified models subsequently included. A sample of 285 patients presenting for Lap-Band® surgery was used. Results : The published bariatric model by Munoz et al. was not an adequate fit to the data. The general model by Shafer et al. was a good fit to the data but had substantial limitations. The weight loss item did not significantly load on any factor in either model. A modified Shafer model and a proposed model were tested, and both were found to be a good fit to the data with minimal differences between the two. A proposed model, in which two items, weight loss and appetite, were omitted, was suggested to be the better model with good reliability. Conclusions : The previously published factor analysis in bariatric candidates by Munoz et al. was a poor fit to the data, and use of this factor structure should be seriously reconsidered within the obese population. The hypothesised model was the best fit to the data. The findings of the study suggest that the existing published models are not adequate for investigating depression in obese patients seeking surgery