Synthesis of a Zirconium Complex of an N,O-type p-tert-Butylcalix[4]arene and Its Application in Some Multicomponent Reactions.

The synthesis and characterization of a new octahedral Zr(IV) complex of oxygen-depleted N,O-type calixarene ligand comprising two distal-functionalized pyrazole rings have been reported. The cone shape and structure of the prepared complex were confirmed univocally by single-crystal X-ray diffraction and NMR studies. The Zr metal lies at 2.091 Å from the plane of the calixarene ring. This complex has been utilized as an efficient catalyst for the synthesis of Biginelli adducts, bis(indolyl)methanes, and coumarins. This complex (Cl2Zr-calixarene) showed superior activity for these multicomponent reactions in comparison to the corresponding Ti(IV) and Zn(II) analogues. Ferrocene-appended bis(indolyl)methane, prepared using this catalyst, was also evaluated for its anticancer activity against the A-172 cell line.

A platform for processing expression of short time series (PESTS).

BACKGROUND: Time course microarray profiles examine the expression of genes over a time domain. They are necessary in order to determine the complete set of genes that are dynamically expressed under given conditions, and to determine the interaction between these genes. Because of cost and resource issues, most time series datasets contain less than 9 points and there are few tools available geared towards the analysis of this type of data. RESULTS: To this end, we introduce a platform for Processing Expression of Short Time Series (PESTS). It was designed with a focus on usability and interpretability of analyses for the researcher. As such, it implements several standard techniques for comparability as well as visualization functions. However, it is designed specifically for the unique methods we have developed for significance analysis, multiple test correction and clustering of short time series data. The central tenet of these methods is the use of biologically relevant features for analysis. Features summarize short gene expression profiles, inherently incorporate dependence across time, and allow for both full description of the examined curve and missing data points. CONCLUSIONS: PESTS is fully generalizable to other types of time series analyses. PESTS implements novel methods as well as several standard techniques for comparability and visualization functions. These features and functionality make PESTS a valuable resource for a researcher's toolkit. PESTS is available to download for free to academic and non-profit users at http://www.mailman.columbia.edu/academic-departments/biostatistics/research-service/software-development.

Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation.

Technological development led to an increased interest in systems biological approaches to characterize disease mechanisms and candidate genes relevant to specific diseases. We suggested that the human peripheral blood mononuclear cells (PBMC) network can be delineated by cellular reconstruction to guide identification of candidate genes. Based on 285 microarrays (7370 genes) from 98 heart transplant patients enrolled in the Cardiac Allograft Rejection Gene Expression Observational study, we used an information-theoretic, reverse-engineering algorithm called ARACNe (algorithm for the reconstruction of accurate cellular networks) and chromatin immunoprecipitation assay to reconstruct and validate a putative gene PBMC interaction network. We focused our analysis on transcription factor (TF) genes and developed a priority score to incorporate aspects of network dynamics and information from published literature to supervise gene discovery. ARACNe generated a cellular network and predicted interactions for each TF during rejection and quiescence. Genes ranked highest by priority score included those related to apoptosis, humoural and cellular immune response such as GA binding protein transcription factor (GABP), nuclear factor of κ light polypeptide gene enhancer in B-cells (NFκB), Fas (TNFRSF6)-associated via death domain (FADD) and c-AMP response element binding protein. We used the TF CREB to validate our network. ARACNe predicted 29 putative first-neighbour genes of CREB. Eleven of these (37%) were previously reported. Out of the 18 unknown predicted interactions, 14 primers were identified and 11 could be immunoprecipitated (78.6%). Overall, 75% (n= 22) inferred CREB targets were validated, a significantly higher fraction than randomly expected (P < 0.001, Fisher's exact test). Our results confirm the accuracy of ARACNe to reconstruct the PBMC transcriptional network and show the utility of systems biological approaches to identify possible molecular targets and biomarkers.

Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering.

BACKGROUND: The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after α-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA), a new clustering method suitable for sparse time series, to identify signaling modules that act in concert in the response to direct irradiation and bystander signaling. We compared our results with those of an alternate clustering method, Short Time series Expression Miner (STEM). RESULTS: While computational evaluations of both clustering results were similar, FBPA provided more biological insight. After irradiation, gene clusters were enriched for signal transduction, cell cycle/cell death and inflammation/immunity processes; but only FBPA separated clusters by function. In bystanders, gene clusters were enriched for cell communication/motility, signal transduction and inflammation processes; but biological functions did not separate as clearly with either clustering method as they did in irradiated samples. Network analysis confirmed p53 and NF-κB transcription factor-regulated gene clusters in irradiated and bystander cells and suggested novel regulators, such as KDM5B/JARID1B (lysine (K)-specific demethylase 5B) and HDACs (histone deacetylases), which could epigenetically coordinate gene expression after irradiation. CONCLUSIONS: In this study, we have shown that a new time series clustering method, FBPA, can provide new leads to the mechanisms regulating the dynamic cellular response to radiation. The findings implicate epigenetic control of gene expression in addition to transcription factor networks.

Relationship between a validated molecular cardiac transplant rejection classifier and routine organ function parameters.

BACKGROUND: As acute cellular cardiac allograft rejection is a systemic process affecting the entire organism, we hypothesized that scores of a peripheral blood mononuclear cell gene expression profiling (GEP) test developed and validated to rule out International Society of Heart and Lung Transplantation (ISHLT) grade > or = 3A/2R acute cellular cardiac allograft rejection also reflects biologically plausible changes of the routinely assessed clinical parameters. METHODS: We retrospectively analyzed 76 patients who underwent GEP testing, at the time of their routine clinical follow-up in our Institution between February 1, 2006 and January 31, 2007. Data were analyzed with t-test, nonparametric tests, bivariate Spearman's correlation, and multivariate linear regression modeling. RESULTS: More activated GEP-score correlated with longer corrected QT (QTc)-interval (r = 0.377, p = 0.001, n = 63), longer QRS duration (r = 0.231, p = 0.03, n = 66), higher heart rate (r = 0.221, p = 0.037, n = 66), higher serum creatinine (r = 0.26, p = 0.01, n = 75), higher gamma-glutamyl transferase (GGT) GGT (r = 0.266, p = 0.037, n = 46), lower pulmonary artery oxygen saturation (r = -0.313, p = 0.003, n = 76), lower platelet count (r = -0.372, p = 0.001, n = 74), lower monocyte count (r = -0.208, p = 0.040, n = 72), and lower high-density lipoprotein (HDL) HDL level (r = -0.242, p = 0.041, n = 53). Multivariate analysis showed a significant amount of variance in the GEP score independently explained by the variability of QTc-interval (beta = 1.998, p = 0.001) and platelet count (beta = -1.540, p = 0.017). Post hoc analysis of the 11 individual GEP-classifier genes showed WDRA40 (p = 0.02) and ras homolog gene family, member U (RHOU) RHOU (p = 0.01) independently related to mixed venous O(2)Sat%. CONCLUSION: A GEP test developed and validated to detect the absence of cardiac rejection correlates with electrocardiographic and hemodynamic cardiac parameters as well as renal, hepatic, bone marrow, and lipid metabolism parameters suggesting a complex relationship between rejection, leukocytes, and organ function within the continuum between alloimmunological quiescence and rejection.

Additivity of pilocarpine to bimatoprost in ocular hypertension and early glaucoma.

PURPOSE: To determine if the intraocular pressure (IOP) effect of pilocarpine at various concentrations is additive to that of bimatoprost and to assess the tolerability of this combination. METHODS: This was a randomized, prospective trial of patients with IOP > 21 mm Hg following appropriate medication washout. For all visits IOP was measured at 9:00 AM and 11:00 AM. Following baseline visit (#1), bimatoprost 0.03% was instilled qhs OU through visit 6. Following visits 2, 3, and 4 pilocarpine (2%, 4%, 6%) was instilled qid in one randomly selected eye. Pilocarpine was discontinued after visit 5 and bimatoprost after visit 6. Two-tailed, paired t test was used to compare treated and contralateral eyes for their IOP, IOP change, percentage IOP change from baseline, and to compare IOP in the same eye at 9:00 AM and 11:00 AM (before and after pilocarpine administration). IOPs using bimatoprost alone or in combination with various pilocarpine concentrations were compared using single variant Analysis of Variance (ANOVA). RESULTS: Seventeen patients were enrolled and 13 patients completed the study. Bimatoprost reduced IOP 28.7% to 30.5% (P < 0.0001) from baseline to visit 2. IOPs in eyes treated with bimatoprost alone or with bimatoprost and various pilocarpine concentrations were similar (P > 0.81, ANOVA). The IOP (P > 0.17) and percentage IOP change from baseline (P > 0.10) was similar in treated and contralateral eyes with all three strengths of pilocarpine. IOP values at 9:00 AM and 11:00 AM, before and after pilocarpine administration, were similar (P > 0.22). CONCLUSION: Bimatoprost alone reduces IOP substantially. Pilocarpine added to bimatoprost at concentrations of 2%, 4%, or 6% was neither additive nor antagonistic to the ocular hypotensive efficacy of bimatoprost.

New-onset graft dysfunction after heart transplantation--incidence and mechanism-related outcomes.

BACKGROUND: Graft dysfunction (GD) after heart transplantation (HTx) is a major cause of morbidity and mortality. The impact of different pathophysiologic mechanisms on outcome is unknown. In this large, single-center study we aimed to assess the incidence of GD and compare the outcomes with different histopathologic mechanisms of rejection. METHODS: We analyzed a data set of 1,099 consecutive patients after their HTx at Columbia University Medical Center between January 1994 and March 2008, and identified all patients hospitalized with new-onset GD. Based on the histopathologic data, patients were divided into GD-unexplained (Group-GD-U), GD-antibody-mediated rejection (Group-GD-AMR), GD-cardiac allograft vasculopathy (Group-GD-CAV) and GD-acute cellular rejection (Group-GD-ACR) groups. We compared the in-hospital and 3-, 6- and 12-month mortality across these groups using the chi-square test. We also compared the 3-, 6- and 12-month survival curves across groups using the log-rank test. RESULTS: Of 126 patients (12%) identified with GD, complete histology data were available for 100 patients. There were 21, 20, 27 and 32 patients identified in Group-GD-U, Group-GD-AMR, Group-GD-CAV and Group-GD-ACR, respectively. The in-hospital mortality rates were 52%, 20%, 15% and 6%, respectively. The in-hospital mortality rate was significantly higher in Group-GD-U compared with all other groups (p = 0.0006). The 3-, 6- and 12-month survival rate was also significantly lower in Group-GD-U compared with all other groups. CONCLUSION: A significant proportion of patients presenting with new-onset GD have unexplained histopathology. Unexplained GD is associated with a significantly higher mortality rate. New diagnostic tools are necessary to better understand and detect/predict this malignant phenotype.

Gene Expression Signatures of Peripheral Blood Mononuclear Cells during the Early Post-Transplant Period in Patients Developing Cardiac Allograft Vasculopathy.

Background. Cardiac allograft vasculopathy (CAV) is a major cause of graft loss and death after heart transplantation. Currently, no diagnostic methods are available during the early post-transplant period to accurately identify patients at risk of CAV. We hypothesized that PBMC gene expression profiles (GEP) can identify patients at risk of CAV. Methods. We retrospectively analyzed a limited set of whole-genome PBMC microarrays from 10 post-transplant patients who did (n = 3) or did not (n = 7) develop advanced grade CAV during their long-term follow-up. We used significance analysis of microarrays to identify differentially expressed genes and High-Throughput GoMiner to assess gene ontology (GO) categories. We corroborated our findings by retrospective analysis of PBMC real-time PCR data from 33 patients. Results. Over 300 genes were differentially expressed (FDR < 5%), and 18 GO-categories including "macrophage activation", "Interleukin-6 pathway", "NF-KappaB cascade", and "response to virus" were enriched by these genes (FDR < 5%). Out of 8 transcripts available for RT-PCR analysis, we confirmed 6 transcripts (75.0%) including FPRL1, S100A9, CXCL10, PRO1073, and MMP9 (P < .05). Conclusion. Our pilot data suggest that GEP of PBMC may become a valuable tool in the evaluation of patients at risk of CAV. Larger prospectively designed studies are needed to corroborate our hypothesis.

Peripheral blood mononuclear cell transcriptome profiles suggest T-cell immunosuppression after uncomplicated mechanical circulatory support device surgery.

Mechanical circulatory support device (MCSD) surgery in patients with advanced heart failure patients is often complicated by infections that are linked to altered cell-mediated immunity. Using a transcriptome-wide peripheral blood mononuclear cell (PBMC) gene expression profiling approach, we analyzed expression patterns directly before and after MCSD implantation in 11 patients who had an uncomplicated course after MCSD implantation (Day 0-24 hours before, Day 1-24 hours after, and Day 7-1 week after implantation). Data were analyzed using Significance Analysis of Microarrays (SAM) and High-Throughput GoMiner on post-implantation profiles (Day 1, Day 7) in comparison with baseline (Day 0). Day1 profiles included differential expression of 821 genes (SAM, FDR <0.1, fold change >1.5), enriching >60 Gene Ontology (GO) categories. Grouping by component genes revealed GO clusters, which we term "interleukin related" (primarily upregulated), "T-cell related" (primarily downregulated), and "apoptosis related" (both up- and down-regulated genes). Day 7 profiles included GO categories related to repair processes. In conclusion, transcriptome-wide expression profiling of PBMCs suggests a response pattern to MCSD implantation of inflammatory activation and simultaneous T-cell suppression.

Large datasets in biomedicine: a discussion of salient analytic issues.

Advances in high-throughput and mass-storage technologies have led to an information explosion in both biology and medicine, presenting novel challenges for analysis and modeling. With regards to multivariate analysis techniques such as clustering, classification, and regression, large datasets present unique and often misunderstood challenges. The authors' goal is to provide a discussion of the salient problems encountered in the analysis of large datasets as they relate to modeling and inference to inform a principled and generalizable analysis and highlight the interdisciplinary nature of these challenges. The authors present a detailed study of germane issues including high dimensionality, multiple testing, scientific significance, dependence, information measurement, and information management with a focus on appropriate methodologies available to address these concerns. A firm understanding of the challenges and statistical technology involved ultimately contributes to better science. The authors further suggest that the community consider facilitating discussion through interdisciplinary panels, invited papers and curriculum enhancement to establish guidelines for analysis and reporting.