Bioanalytical Method Development and Validation of Memantine in Human Plasma by High Performance Liquid Chromatography with Tandem Mass Spectrometry: Application to Bioequivalence Study

A simple, sensitive, and rapid HPLC-MS/MS method was developed and validated for quantitative estimation of memantine in human plasma. Chromatography was performed on Zorbax SB-C18 (4.6 × 75 mm, 3.5 μm) column. Memantine (ME) and internal standard Memantine-d6(MED6) were extracted by using liquid-liquid extraction and analyzed by LC-ESI-MS/MS using multiple-reaction monitoring (MRM) mode. The assay exhibited a linear dynamic range of 50.00–50000.00 pg/ml for ME in human plasma. This method demonstrated an intra- and interday precision within the range of 2.1–3.7 and 1.4–7.8%, respectively. Further intra- and interday accuracy was within the range of 95.6–99.8 and 95.7–99.1% correspondingly. The mean recovery of ME and MED6 was 86.07 ± 6.87 and 80.31 ± 5.70%, respectively. The described method was successfully employed in bioequivalence study of ME in Indian male healthy human volunteers under fasting conditions

Local algorithms : Self-stabilization on speed

Non peer reviewe

Suppression of magnetic order in CaCo 1.86 As 2 with Fe substitution: Magnetization, neutron diffraction, and x-ray diffraction studies of Ca ( Co 1 − x Fe x ) y As 2

Magnetization, neutron diffraction, and high-energy x-ray diffraction results for Sn-flux grown single-crystal samples of Ca(Co$_{1-x}$Fe$_{x}$)$_{y}$As$_{2}$, $0\leq x\leq1$, $1.86\leq y \leq 2$, are presented and reveal that A-type antiferromagnetic order, with ordered moments lying along the $c$ axis, persists for $x\lesssim0.12(1)$. The antiferromagnetic order is smoothly suppressed with increasing $x$, with both the ordered moment and N\'{e}el temperature linearly decreasing. Stripe-type antiferromagnetic order does not occur for $x\leq0.25$, nor does ferromagnetic order for $x$ up to at least $x=0.104$, and a smooth crossover from the collapsed-tetragonal (cT) phase of CaCo$_{1.86}$As$_{2}$ to the tetragonal (T) phase of CaFe$_{2}$As$_{2}$ occurs. These results suggest that hole doping CaCo$_{1.86}$As$_{2}$ has a less dramatic effect on the magnetism and structure than steric effects due to substituting Sr for Ca.Comment: 12 pages, 16 Figure

Cross-Platform Comparison of Microarray-Based Multiple-Class Prediction

High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets

Cross-platform expression profiling demonstrates that SV40 small tumor antigen activates Notch, Hedgehog, and Wnt signaling in human cells

BACKGROUND: We previously analyzed human embryonic kidney (HEK) cell lines for the effects that simian virus 40 (SV40) small tumor antigen (ST) has on gene expression using Affymetrix U133 GeneChips. To cross-validate and extend our initial findings, we sought to compare the expression profiles of these cell lines using an alternative microarray platform. METHODS: We have analyzed matched cell lines with and without expression of SV40 ST using an Applied Biosystems (AB) microarray platform that uses single 60-mer oligonucleotides and single-color quantitative chemiluminescence for detection. RESULTS: While we were able to previously identify only 456 genes affected by ST with the Affymetrix platform, we identified 1927 individual genes with the AB platform. Additional technical replicates increased the number of identified genes to 3478 genes and confirmed the changes in 278 (61%) of our original set of 456 genes. Among the 3200 genes newly identified as affected by SV40 ST, we confirmed 20 by QRTPCR including several components of the Wnt, Notch, and Hedgehog signaling pathways, consistent with SV40 ST activation of these developmental pathways. While inhibitors of Notch activation had no effect on cell survival, cyclopamine had a potent killing effect on cells expressing SV40 ST. CONCLUSIONS: These data show that SV40 ST expression alters cell survival pathways to sensitize cells to the killing effect of Hedgehog pathway inhibitors

Origin of Co-Expression Patterns in E.coli and S.cerevisiae Emerging from Reverse Engineering Algorithms

BACKGROUND: The concept of reverse engineering a gene network, i.e., of inferring a genome-wide graph of putative gene-gene interactions from compendia of high throughput microarray data has been extensively used in the last few years to deduce/integrate/validate various types of "physical" networks of interactions among genes or gene products. RESULTS: This paper gives a comprehensive overview of which of these networks emerge significantly when reverse engineering large collections of gene expression data for two model organisms, E. coli and S. cerevisiae, without any prior information. For the first organism the pattern of co-expression is shown to reflect in fine detail both the operonal structure of the DNA and the regulatory effects exerted by the gene products when co-participating in a protein complex. For the second organism we find that direct transcriptional control (e.g., transcription factor-binding site interactions) has little statistical significance in comparison to the other regulatory mechanisms (such as co-sharing a protein complex, co-localization on a metabolic pathway or compartment), which are however resolved at a lower level of detail than in E. coli. CONCLUSION: The gene co-expression patterns deduced from compendia of profiling experiments tend to unveil functional categories that are mainly associated to stable bindings rather than transient interactions. The inference power of this systematic analysis is substantially reduced when passing from E. coli to S. cerevisiae. This extensive analysis provides a way to describe the different complexity between the two organisms and discusses the critical limitations affecting this type of methodologies

Empirical comparison of cross-platform normalization methods for gene expression data

<p>Abstract</p> <p>Background</p> <p>Simultaneous measurement of gene expression on a genomic scale can be accomplished using microarray technology or by sequencing based methods. Researchers who perform high throughput gene expression assays often deposit their data in public databases, but heterogeneity of measurement platforms leads to challenges for the combination and comparison of data sets. Researchers wishing to perform cross platform normalization face two major obstacles. First, a choice must be made about which method or methods to employ. Nine are currently available, and no rigorous comparison exists. Second, software for the selected method must be obtained and incorporated into a data analysis workflow.</p> <p>Results</p> <p>Using two publicly available cross-platform testing data sets, cross-platform normalization methods are compared based on inter-platform concordance and on the consistency of gene lists obtained with transformed data. Scatter and ROC-like plots are produced and new statistics based on those plots are introduced to measure the effectiveness of each method. Bootstrapping is employed to obtain distributions for those statistics. The consistency of platform effects across studies is explored theoretically and with respect to the testing data sets.</p> <p>Conclusions</p> <p>Our comparisons indicate that four methods, DWD, EB, GQ, and XPN, are generally effective, while the remaining methods do not adequately correct for platform effects. Of the four successful methods, XPN generally shows the highest inter-platform concordance when treatment groups are equally sized, while DWD is most robust to differently sized treatment groups and consistently shows the smallest loss in gene detection. We provide an R package, CONOR, capable of performing the nine cross-platform normalization methods considered. The package can be downloaded at <url>http://alborz.sdsu.edu/conor</url> and is available from CRAN.</p

Ensemble Analysis of Angiogenic Growth in Three-Dimensional Microfluidic Cell Cultures

We demonstrate ensemble three-dimensional cell cultures and quantitative analysis of angiogenic growth from uniform endothelial monolayers. Our approach combines two key elements: a micro-fluidic assay that enables parallelized angiogenic growth instances subject to common extracellular conditions, and an automated image acquisition and processing scheme enabling high-throughput, unbiased quantification of angiogenic growth. Because of the increased throughput of the assay in comparison to existing three-dimensional morphogenic assays, statistical properties of angiogenic growth can be reliably estimated. We used the assay to evaluate the combined effects of vascular endothelial growth factor (VEGF) and the signaling lipid sphingoshine-1-phosphate (S1P). Our results show the importance of S1P in amplifying the angiogenic response in the presence of VEGF gradients. Furthermore, the application of S1P with VEGF gradients resulted in angiogenic sprouts with higher aspect ratio than S1P with background levels of VEGF, despite reduced total migratory activity. This implies a synergistic effect between the growth factors in promoting angiogenic activity. Finally, the variance in the computed angiogenic metrics (as measured by ensemble standard deviation) was found to increase linearly with the ensemble mean. This finding is consistent with stochastic agent-based mathematical models of angiogenesis that represent angiogenic growth as a series of independent stochastic cell-level decisions

Broadening of Neutralization Activity to Directly Block a Dominant Antibody-Driven SARS-Coronavirus Evolution Pathway

Phylogenetic analyses have provided strong evidence that amino acid changes in spike (S) protein of animal and human SARS coronaviruses (SARS-CoVs) during and between two zoonotic transfers (2002/03 and 2003/04) are the result of positive selection. While several studies support that some amino acid changes between animal and human viruses are the result of inter-species adaptation, the role of neutralizing antibodies (nAbs) in driving SARS-CoV evolution, particularly during intra-species transmission, is unknown. A detailed examination of SARS-CoV infected animal and human convalescent sera could provide evidence of nAb pressure which, if found, may lead to strategies to effectively block virus evolution pathways by broadening the activity of nAbs. Here we show, by focusing on a dominant neutralization epitope, that contemporaneous- and cross-strain nAb responses against SARS-CoV spike protein exist during natural infection. In vitro immune pressure on this epitope using 2002/03 strain-specific nAb 80R recapitulated a dominant escape mutation that was present in all 2003/04 animal and human viruses. Strategies to block this nAb escape/naturally occurring evolution pathway by generating broad nAbs (BnAbs) with activity against 80R escape mutants and both 2002/03 and 2003/04 strains were explored. Structure-based amino acid changes in an activation-induced cytidine deaminase (AID) “hot spot” in a light chain CDR (complementarity determining region) alone, introduced through shuffling of naturally occurring non-immune human VL chain repertoire or by targeted mutagenesis, were successful in generating these BnAbs. These results demonstrate that nAb-mediated immune pressure is likely a driving force for positive selection during intra-species transmission of SARS-CoV. Somatic hypermutation (SHM) of a single VL CDR can markedly broaden the activity of a strain-specific nAb. The strategies investigated in this study, in particular the use of structural information in combination of chain-shuffling as well as hot-spot CDR mutagenesis, can be exploited to broaden neutralization activity, to improve anti-viral nAb therapies, and directly manipulate virus evolution