Regeneration of begonia plantlets by direct organogenesis

The economic importance of ornamentals worldwide suggests a bright future for ornamental breeding. Rapid progress in plant molecular biology has great potentials to contribute to the breeding of novel ornamental plants utilizing recombinant DNA technology. The plant cell, tissue or organ culture of many ornamental species and their regeneration are essential for providing the material and systems for their genetic manipulation, and this is therefore the first requirement of genetic engineering. In this research, different concentration of BA (0.0, 0.5, 1.0, 2.0 mgl(-1) with NAA ( 0.0, 0.5, 1.0 mgl(-1)) and BA (0.0, 0.5, 1.0, 2.0 mgl(-1)) with IAA ( 0.0, 0.5, 1.0, mgl(-1)) were investigated to optimize regeneration of Begonia elatior cv. Toran orange. The best regeneration and growth were obtained from the media containing 2.0 mgl(-1) BA and 1.0 mgl(-1) NAA (70%) followed by 1.0 mgl(-1) BA and 0.5 mgl(-1) NAA (50%), 1.0 mgl(-1) BA and 1.0 mgl(-1) NAA (20%) in BA - NAA combination. The media with BA - IAA combination showed that the best regeneration was 0.5 mgl(-1) BA and 0.5 mgl(-1) IAA (43%) followed by 0.5 mgl(-1) BA and 1.0 mgl(-1) IAA (23%)

Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization

Abstract Background Patients with schizophrenia have difficulty managing their medical healthcare needs, possibly resulting in delayed treatment and poor outcomes. We analyzed whether patients reduced primary care use over time, differentially by diagnosis with schizophrenia, diabetes, or both schizophrenia and diabetes. We also assessed whether such patterns of primary care use were a significant predictor of mortality over a 4-year period. Methods The Veterans Healthcare Administration (VA) is the largest integrated healthcare system in the United States. Administrative extracts of the VA's all-electronic medical records were studied. Patients over age 50 and diagnosed with schizophrenia in 2002 were age-matched 1:4 to diabetes patients. All patients were followed through 2005. Cluster analysis explored trajectories of primary care use. Proportional hazards regression modelled the impact of these primary care utilization trajectories on survival, controlling for demographic and clinical covariates. Results Patients comprised three diagnostic groups: diabetes only (n = 188,332), schizophrenia only (n = 40,109), and schizophrenia with diabetes (Scz-DM, n = 13,025). Cluster analysis revealed four distinct trajectories of primary care use: consistent over time, increasing over time, high and decreasing, low and decreasing. Patients with schizophrenia only were likely to have low-decreasing use (73% schizophrenia-only vs 54% Scz-DM vs 52% diabetes). Increasing use was least common among schizophrenia patients (4% vs 8% Scz-DM vs 7% diabetes) and was associated with improved survival. Low-decreasing primary care, compared to consistent use, was associated with shorter survival controlling for demographics and case-mix. The observational study was limited by reliance on administrative data. Conclusion Regular primary care and high levels of primary care were associated with better survival for patients with chronic illness, whether psychiatric or medical. For schizophrenia patients, with or without comorbid diabetes, primary care offers a survival benefit, suggesting that innovations in treatment retention targeting at-risk groups can offer significant promise of improving outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/78274/1/1472-6963-9-127.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78274/2/1472-6963-9-127.pdfPeer Reviewe

Comparative Genome-Wide Screening Identifies a Conserved Doxorubicin Repair Network That Is Diploid Specific in Saccharomyces cerevisiae

The chemotherapeutic doxorubicin (DOX) induces DNA double-strand break (DSB) damage. In order to identify conserved genes that mediate DOX resistance, we screened the Saccharomyces cerevisiae diploid deletion collection and identified 376 deletion strains in which exposure to DOX was lethal or severely reduced growth fitness. This diploid screen identified 5-fold more DOX resistance genes than a comparable screen using the isogenic haploid derivative. Since DSB damage is repaired primarily by homologous recombination in yeast, and haploid cells lack an available DNA homolog in G1 and early S phase, this suggests that our diploid screen may have detected the loss of repair functions in G1 or early S phase prior to complete DNA replication. To test this, we compared the relative DOX sensitivity of 30 diploid deletion mutants identified under our screening conditions to their isogenic haploid counterpart, most of which (n = 26) were not detected in the haploid screen. For six mutants (bem1Δ, ctf4Δ, ctk1Δ, hfi1Δ,nup133Δ, tho2Δ) DOX-induced lethality was absent or greatly reduced in the haploid as compared to the isogenic diploid derivative. Moreover, unlike WT, all six diploid mutants displayed severe G1/S phase cell cycle progression defects when exposed to DOX and some were significantly enhanced (ctk1Δ and hfi1Δ) or deficient (tho2Δ) for recombination. Using these and other “THO2-like” hypo-recombinogenic, diploid-specific DOX sensitive mutants (mft1Δ, thp1Δ, thp2Δ) we utilized known genetic/proteomic interactions to construct an interactive functional genomic network which predicted additional DOX resistance genes not detected in the primary screen. Most (76%) of the DOX resistance genes detected in this diploid yeast screen are evolutionarily conserved suggesting the human orthologs are candidates for mediating DOX resistance by impacting on checkpoint and recombination functions in G1 and/or early S phases

Effects of Proteins from Culture Medium on Surface Property of Silanes- Functionalized Magnetic Nanoparticles

Monodisperse magnetic nanoparticles (MNPs) were synthesized by thermal decomposition of iron-oleate and functionalized with silanes bearing various functional groups such as amino group (NH2), short-chain poly(ethylene glycol) (PEG), and carboxylic group (COOH). Then, silanes-functionalized magnetic nanoparticles (silanes-MNPs) were incubated in cell culture medium plus fetal calf serum to investigate the effects of proteins from culture medium on surface property of MNPs. Zeta potential measurements showed that although surface charges of silanes-MNPs were different, they exhibited negative charges at neutral pH and approximate isoelectric points after they were incubated in cell culture medium. The reason was that silanes-MNPs could easily adsorb proteins from culture medium via non-covalent binding, resulting in the formation of protein-silanes-MNPs conjugates. Moreover, silanes-MNPs with various functional groups had different adsorption capacity to proteins, as confirmed by Coomassie blue fast staining method. The in vitro cell experiments showed that protein-silanes-MNPs had higher cellular uptake by cancer cells than silanes-MNPs

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196