Implementation of a Risk-Stratified Opioid and Benzodiazepine Weaning Protocol in a Pediatric Cardiac ICU.

OBJECTIVES: Opioids and benzodiazepines are commonly used to provide analgesia and sedation for critically ill children with cardiac disease. These medications have been associated with adverse effects including delirium, dependence, withdrawal, bowel dysfunction, and potential neurodevelopmental abnormalities. Our objective was to implement a risk-stratified opioid and benzodiazepine weaning protocol to reduce the exposure to opioids and benzodiazepines in pediatric patients with cardiac disease. DESIGN: A prospective pre- and postinterventional study. PATIENTS: Critically ill patients less than or equal to 21 years old with acquired or congenital cardiac disease exposed to greater than or equal to 7 days of scheduled opioids ± scheduled benzodiazepines between January 2013 and February 2015. SETTING: A 24-bed pediatric cardiac ICU and 21-bed cardiovascular acute ward of an urban stand-alone children's hospital. INTERVENTION: We implemented an evidence-based opioid and benzodiazepine weaning protocol using educational and quality improvement methodology. MEASUREMENTS AND MAIN RESULTS: One-hundred nineteen critically ill children met the inclusion criteria (64 post intervention, 55 pre intervention). Demographics and risk factors did not differ between groups. Patients in the postintervention period had shorter duration of opioids (19.0 vs 30.0 d; p < 0.01) and duration of benzodiazepines (5.3 vs 22.7 d; p < 0.01). Despite the shorter duration of wean, there was a decrease in withdrawal occurrence (% Withdrawal Assessment Tool score ≥ 4, 4.9% vs 14.1%; p < 0.01). There was an 8-day reduction in hospital length of stay (34 vs 42 d; p < 0.01). There was a decrease in clonidine use (14% vs 32%; p = 0.02) and no change in dexmedetomidine exposure (59% vs 75%; p = 0.08) in the postintervention period. CONCLUSIONS: We implemented a risk-stratified opioid and benzodiazepine weaning protocol for critically ill cardiac children that resulted in reduction in opioid and benzodiazepine duration and dose exposure, a decrease in symptoms of withdrawal, and a reduction in hospital length of stay.

Implementation of a risk-stratified opioid weaning protocol in a pediatric intensive care unit.

PURPOSE: Opioids are important in the care of critically ill children. However, their use is associated with complications including delirium, dependence, withdrawal, and bowel dysfunction. Our aim was to implement a risk-stratified opioid weaning protocol to reduce the duration of opioids without increasing the incidence of withdrawal. METHODS: A pre- and post-interventional prospective study was undertaken in a large children's hospital pediatric ICU where we implemented a risk-stratified opioid weaning protocol. Patients were included if exposed to ≥7days of scheduled opioids. The primary outcome was duration of opioids and secondary outcome was hospital LOS. RESULTS: One hundred seven critically ill children met the inclusion criteria (68 pre-, 39 post-intervention). Demographics, risk factors, and confounders did not differ between groups. Patients in the post-intervention group had shorter duration of opioids (17 vs. 22.5days, p=0.01) and opioid wean (12 vs. 18days, p=0.01). Despite the shorter duration of opioid wean, there was no increase in withdrawal incidence. There was no difference in the LOS (29 vs. 33days, p=0.06). CONCLUSIONS: We implemented a risk-stratified opioid weaning protocol for critically ill children that resulted in reduction in opioid exposure without an increase in withdrawal. There was no difference in the LOS.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease.

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease.

A yeast phenomic model for the gene interaction network modulating CFTR-ΔF508 protein biogenesis.

BACKGROUND: The overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-[increment]F508) accounts for most of the disease. In cell models, CFTR-[increment]F508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-[increment]F508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-[increment]F would manifest phenotypically. METHODS: To gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC-transporter, we employed yeast genetics to develop a "phenomic" model, in which the CFTR-[increment]F508-equivalent residue of a yeast homolog is mutated (Yor1-[increment]F670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-[increment]F undergoes protein misfolding and has reduced half-life, analogous to CFTR-[increment]F. Gene interaction was then assessed quantitatively by growth curves for all ~5000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1. RESULTS: From a comparative genomic perspective, yeast gene interaction influencing Yor1-[increment]F biogenesis was representative of human homologs previously found to modulate processing of CFTR-[increment]F in mammalian cells. Additional evolutionarily conserved pathways were implicated by the study, and a [increment]F-specific pro-biogenesis function of the recently discovered ER Membrane Complex (EMC) was evident from the yeast screen. This novel function was validated biochemically by siRNA of an EMC ortholog in a human cell line expressing CFTR-[increment]F508. The precision and accuracy of quantitative high throughput cell array phenotyping (Q-HTCP), which captures tens of thousands of growth curves simultaneously, provided powerful resolution to measure gene interaction on a phenomic scale, based on discrete cell proliferation parameters. CONCLUSION: We propose phenomic analysis of Yor1-[increment]F as a model for investigating gene interaction networks that can modulate cystic fibrosis disease severity. Although the clinical relevance of the Yor1-[increment]F gene interaction network for cystic fibrosis remains to be defined, the model appears to be informative with respect to human cell models of CFTR-[increment]F. Moreover, the general strategy of yeast phenomics can be employed in a systematic manner to model gene interaction for other diseases relating to pathologies that result from protein misfolding or potentially any disease involving evolutionarily conserved genetic pathways.

A screen to identify small molecule inhibitors of protein-protein interactions in mycobacteria.

Despite extensive efforts in tuberculosis (TB) drug research, very few novel inhibitors have been discovered. This issue emphasizes the need for innovative methods to discover new anti-TB drugs. In this study, we established a new high-throughput screen (HTS) platform technology that differs from traditional TB drug screens because it utilizes Mycobacterial-Protein Fragment Complementation (M-PFC) to identify small molecule inhibitors of protein-protein interactions in mycobacteria. Several examples of protein-protein interactions were tested with M-PFC to highlight the diversity of selectable drug targets that could be used for screening. These included interactions of essential regulators (IdeR dimerization), enzymatic complexes (LeuCD), secretory antigens (Cfp10-Esat6), and signaling pathways (DevR dimerization). The feasibility of M-PFC in a HTS platform setting was tested by performing a proof-of-concept quantitative HTS of 3,600 small molecule compounds on DevR-DevR interaction, which was chosen because of its strong implications in Mycobacterium tuberculosis persistence and the need for effective drugs against latent TB. The calculated Z'-factor was consistently ≥0.8, indicating a robust and reproducible assay. Completion of the proof-of-concept screen allowed for the identification of advantages and disadvantages in the current assay design, where improvements made will further pioneer M-PFC-based applications in a large-scale HTS format.

Stringent mating-type-regulated auxotrophy increases the accuracy of systematic genetic interaction screens with Saccharomyces cerevisiae mutant arrays.

A genomic collection of haploid Saccharomyces cerevisiae deletion strains provides a unique resource for systematic analysis of gene interactions. Double-mutant haploid strains can be constructed by the synthetic genetic array (SGA) method, wherein a query mutation is introduced by mating to mutant arrays, selection of diploid double mutants, induction of meiosis, and selection of recombinant haploid double-mutant progeny. The mechanism of haploid selection is mating-type-regulated auxotrophy (MRA), by which prototrophy is restricted to a particular haploid genotype generated only as a result of meiosis. MRA escape leads to false-negative genetic interaction results because postmeiotic haploids that are supposed to be under negative selection instead proliferate and mate, forming diploids that are heterozygous at interacting loci, masking phenotypes that would be observed in a pure haploid double-mutant culture. This work identified factors that reduce MRA escape, including insertion of terminator and repressor sequences upstream of the MRA cassette, deletion of silent mating-type loci, and utilization of alpha-type instead of a-type MRA. Modifications engineered to reduce haploid MRA escape reduced false negative results in SGA-type analysis, resulting in >95% sensitivity for detecting gene-gene interactions.

Purification, crystallization and preliminary X-ray crystallographic analysis of the nucleocapsid protein of Bunyamwera virus.

Bunyamwera virus (BUNV) is the prototypic member of the Bunyaviridae family of segmented negative-sense RNA viruses. The BUNV nucleocapsid protein has been cloned and expressed in Escherichia coli. The purified protein has been crystallized and a complete data set has been collected to 3.3 angstroms resolution at a synchrotron source. Crystals of the nucleocapsid protein belong to space group C2, with unit-cell parameters a = 384.7, b = 89.8, c = 89.2 angstroms, beta = 94.4 degrees . Self-rotation function analysis of the X-ray diffraction data has provided insight into the oligomeric state of the protein as well as the orientation of the oligomers in the asymmetric unit. The structure determination of the protein is ongoing.

Identification of the Bunyamwera bunyavirus transcription termination signal.

Bunyamwera virus (BUNV) is the prototype of the family Bunyaviridae, which comprises segmented RNA viruses. Each of the BUNV negative-strand segments, small (S), medium (M) and large (L), serves as template for two distinct RNA-synthesis activities: (i) replication to generate antigenomes that are in turn replicated to yield further genomes; and (ii) transcription to generate a single species of mRNA. BUNV mRNAs are truncated at their 3' ends relative to the genome template, presumably because the BUNV transcriptase terminates transcription before reaching the 5' terminus of the genomic template. Here, identification of the transcription termination signal responsible for 3'-end truncation of BUNV S-segment mRNA was carried out. It was shown that efficient transcription termination was signalled by a 33 nt sequence within the 5' non-translated region (NTR) of the S segment. A 6 nt region (3'-GUCGAC-5') within this sequence was found to play a major role in termination signalling, with other nucleotides possessing individually minor, but collectively significant, signalling ability. By abrogating the signalling ability of these 33 nt, we identified a second, functionally independent termination signal located 32 nt downstream. This downstream signal was 9 nt in length and contained a pentanucleotide sequence, 3'-UGUCG-5', that overlapped the 6 nt major signalling component of the upstream signal. The pentanucleotide sequence was also found within the 5' NTR of the BUNV L segment and in several other members of the genus Orthobunyavirus, suggesting that the mechanism responsible for BUNV transcription termination may be common to other orthobunyaviruses.

The Bunyamwera virus mRNA transcription signal resides within both the 3' and the 5' terminal regions and allows ambisense transcription from a model RNA segment.

Bunyamwera virus (BUNV) is the prototype of the Bunyaviridae family of RNA viruses. BUNV genomic strands are templates for both replication and transcription, whereas the antigenomic RNAs serve only as templates for replication. By mutagenesis of model templates, we showed that the BUNV transcription promoter comprises elements within both the 3' and the 5' nontranslated regions. Using this information, we designed a model ambisense BUNV segment that transcribed BUNV S mRNA from the genomic strand and green fluorescent protein (GFP) mRNA from the antigenome. Demonstration of GFP expression showed that this ambisense strategy represents a viable approach for generating BUNV segments able to express additional proteins.