Seeking Clarity within Cloudy Effluents: Differentiating Fungal from Bacterial Peritonitis in Peritoneal Dialysis Patients

Fungal peritonitis is a serious complication of peritoneal dialysis (PD) therapy with the majority of patients ceasing PD permanently. The aims of this study were to identify risk factors and clinical associations that may discriminate between fungal from bacterial peritonitis.We retrospectively identified episodes of fungal peritonitis from 2001-2010 in PD patients at Liverpool and Westmead Hospitals (Australia). Fungal peritonitis cases were matched in a 1:2 ratio with patients with bacterial peritonitis from each institution's dialysis registry, occurring closest in time to the fungal episode. Patient demographic, clinical and outcome data were obtained from the medical records.Thirty-nine episodes of fungal peritonitis (rate of 0.02 episodes per patient-year of dialysis) were matched with 78 episodes of bacterial peritonitis. Candida species were the commonest pathogens (35/39; 90% episodes) with Candida albicans (37%), Candida parapsilosis (32%) and Candida glabrata (13%) the most frequently isolated species. Compared to bacterial peritonitis, fungal peritonitis patients had received PD for significantly longer (1133 vs. 775 catheter-days; p = 0.016), were more likely to have had previous episodes of bacterial peritonitis (51% vs. 10%; p = 0.01), and to have received prior antibacterial therapy (51% vs. 10%; p = 0.01). Patients with fungal peritonitis were less likely to have fever and abdominal pain on presentation, but had higher rates of PD catheter removal (79% vs. 22%; p<0.005), and permanent transfer to haemodialysis (87% vs. 24%; p<0.005). Hospital length of stay was significantly longer in patients with fungal peritonitis (26.1 days vs. 12.6 days; p = 0.017), but the all-cause 30-day mortality rate was similar in both groups. Fluconazole was a suitable empiric antifungal agent; with no Candida resistance detected.Prompt recognition of clinical risk factors, initiation of antifungal therapy and removal of PD catheters are key considerations in optimising outcomes

Randomised double-blind trial of megestrol acetate vs placebo in treatment-naive advanced hepatocellular carcinoma

10.1038/bjc.2011.333British Journal of Cancer1057945-952BJCA

Local Network Topology in Human Protein Interaction Data Predicts Functional Association

The use of high-throughput techniques to generate large volumes of protein-protein interaction (PPI) data has increased the need for methods that systematically and automatically suggest functional relationships among proteins. In a yeast PPI network, previous work has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional association. In this study we improved the prediction scheme by developing a new algorithm and applied it on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting function-associated protein pairs. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as benchmarks to compare and evaluate the function relevance. The application of our algorithms to human PPI data yielded 4,233 significant functional associations among 1,754 proteins. Further functional comparisons between them allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made functional inferences from detailed analysis on one subcluster highly enriched in the TGF-β signaling pathway (P<10−50). Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotation in this post-genomic era

A Semi-Physiologically Based Pharmacokinetic Model Describing the Altered Metabolism of Midazolam Due to Inflammation in Mice

This is the author's accepted manuscript.Purpose To investigate influence of inflammation on metabolism and pharmacokinetics (PK) of midazolam (MDZ) and construct a semi-physiologically based pharmacokinetic (PBPK) model to predict PK in mice with inflammatory disease. Methods Glucose-6-phosphate isomerase (GPI)-mediated inflammation was used as a preclinical model of arthritis in DBA/1 mice. CYP3A substrate MDZ was selected to study changes in metabolism and PK during the inflammation. The semi-PBPK model was constructed using mouse physiological parameters, liver microsome metabolism, and healthy animal PK data. In addition, serum cytokine, and liver-CYP (cytochrome P450 enzymes) mRNA levels were examined. Results The in vitro metabolite formation rate was suppressed in liver microsomes prepared from the GPI-treated mice as compared to the healthy mice. Further, clearance of MDZ was reduced during inflammation as compared to the healthy group. Finally, the semi-PBPK model was used to predict PK of MDZ after GPI-mediated inflammation. IL-6 and TNF-α levels were elevated and liver-cyp3a11 mRNA was reduced after GPI treatment. Conclusion The semi-PBPK model successfully predicted PK parameters of MDZ in the disease state. The model may be applied to predict PK of other drugs under disease conditions using healthy animal PK and liver microsomal data as inputs

Using classification and regression tree modelling to investigate response shift patterns in dentine hypersensitivity

BACKGROUND: Dentine hypersensitivity (DH) affects people's quality of life (QoL). However changes in the internal meaning of QoL, known as Response shift (RS) may undermine longitudinal assessment of QoL. This study aimed to describe patterns of RS in people with DH using Classification and Regression Trees (CRT) and to explore the convergent validity of CRT with the then-test and ideals approaches. METHODS: Data from an 8-week clinical trial of mouthwashes for dentine hypersensitivity (n = 75) using the Dentine Hypersensitivity Experience Questionnaire (DHEQ) as the outcome measure, were analysed. CRT was used to examine 8-week changes in DHEQ total score as a dependent variable with clinical status for DH and each DHEQ subscale score (restrictions, coping, social, emotional and identity) as independent variables. Recalibration was inferred when the clinical change was not consistent with the DHEQ change score using a minimally important difference for DHEQ of 22 points. Reprioritization was inferred by changes in the relative importance of each subscale to the model over time. RESULTS: Overall, 50.7% of participants experienced a clinical improvement in their DH after treatment and 22.7% experienced an important improvement in their quality of life. Thirty-six per cent shifted their internal standards downward and 14.7% upwards, suggesting recalibration. Reprioritization occurred over time among the social and emotional impacts of DH. CONCLUSIONS: CRT was a useful method to reveal both, the types and nature of RS in people with a mild health condition and demonstrated convergent validity with design based approaches to detect RS