Biological and physicochemical stability of ceftazidime and aminophylline on glucose parenteral solution

Ceftazidime is a broad spectrum antibiotic administered mainly by the parenteral route, and it is especially effective against Pseudomonas aeruginosa. The period of time in which serum levels exceed the Minimum Inhibitory Concentration (MIC) is an important pharmacodynamic parameter for its efficacy. One of the forms to extend this period is to administer the antibiotic by continuous infusion, after prior dilution in a Parenteral Solution (PS). The present work assessed the stability of ceftazidime in 5% glucose PS for 24 hours, combined or not with aminophylline, through High Performance Liquid Chromatography (HPLC). The physicochemical evaluation was accompanied by in vitro antimicrobial activity compared MIC test in the 24-hour period. Escherichia coli and Pseudomonas aeruginosa were the microorganisms chosen for the MIC comparison. The HPLC analysis confirmed ceftazidime and aminophylline individual stability on PS, while the MIC values were slightly higher than the mean described in the literature. When both drugs were associated in the same PS, the ceftazidime concentration by HPLC decreased 25% after 24 hours. Not only did the MIC values show high loss of antibiotic activity within the same period, but also altered MIC values immediately after the preparation, which was not detected by HPLC. Our results indicate that this drug combination is not compatible, even if used right away, and that PS might not be the best vehicle for ceftazidime, emphasizing the importance of the MIC evaluation for drug interactions.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations

Abstract Background Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC Methods Microarray experiments were performed with custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary RCC tumors and 11 nontumor adjacent matched tissues were analyzed. Meta-analyses were performed with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. Results A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). A signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 22% were significantly (p <0.05) cis correlated with the expression of the mRNA in the same locus across RCC and three other human tissues. Gene Ontology (GO) analysis of those loci pointed to 'regulation of biological processes’ as the main enriched category. A module map analysis of the protein-coding genes significantly (p <0.05) trans correlated with the 20% most abundant lncRNAs, identified 51 enriched GO terms (p <0.05). We determined that 60% of the expressed lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands, RNA Pol II binding and histones methylation and acetylation. Conclusion Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation.

Biological and physicochemical stability of ceftazidime and aminophylline on glucose parenteral solution

Ceftazidime is a broad spectrum antibiotic administered mainly by the parenteral route, and it is especially effective against Pseudomonas aeruginosa. The period of time in which serum levels exceed the Minimum Inhibitory Concentration (MIC) is an important pharmacodynamic parameter for its efficacy. One of the forms to extend this period is to administer the antibiotic by continuous infusion, after prior dilution in a Parenteral Solution (PS). The present work assessed the stability of ceftazidime in 5% glucose PS for 24 hours, combined or not with aminophylline, through High Performance Liquid Chromatography (HPLC). The physicochemical evaluation was accompanied by in vitro antimicrobial activity compared MIC test in the 24-hour period. Escherichia coli and Pseudomonas aeruginosa were the microorganisms chosen for the MIC comparison. The HPLC analysis confirmed ceftazidime and aminophylline individual stability on PS, while the MIC values were slightly higher than the mean described in the literature. When both drugs were associated in the same PS, the ceftazidime concentration by HPLC decreased 25% after 24 hours. Not only did the MIC values show high loss of antibiotic activity within the same period, but also altered MIC values immediately after the preparation, which was not detected by HPLC. Our results indicate that this drug combination is not compatible, even if used right away, and that PS might not be the best vehicle for ceftazidime, emphasizing the importance of the MIC evaluation for drug interactions.