Diurnal variability of C-reactive protein in obstructive sleep apnea

OBJECTIVE: The objective of this study is to examine the diurnal variability of C-reactive protein (CRP) in obstructive sleep apnea (OSA). METHODS AND MEASUREMENTS: Participants included 44 women and men with untreated OSA (mean apnea/hypopnea index = 37.5, SD +/- 28) and 23 healthy adults with no OSA. Sleep was monitored with polysomnography in the University of California San Diego General Clinical Research Center. Over a 24-h period, blood was collected every 2 h, and CRP levels were determined. RESULTS: Adjusting for age, gender, and body mass index, a significant group by time interaction showed that patients with OSA had higher CRP levels during the daytime (8:00 a.m.-8:00 p.m.) versus the nighttime (10:00 p.m. until 6:00 p.m.; p < 0.001). Non-apneics showed no significant change in CRP levels during the 24 h. CONCLUSIONS: The findings indicate that sleep apnea patients have disproportionately elevated CRP levels in the day versus the nighttime, possibly as a result of carryover effects of nighttime arousal into the daytime.

Classification of the taxon 2 and taxon 3 complex of Bisgaard within Gallibacterium and description of Gallibacterium melopsittaci sp. nov., Gallibacterium trehalosifermentans sp. nov. and Gallibacterium salpingitidis sp. nov

This investigation was based on 23 isolates from several European countries collected over the past 30 years, and included characterization of all isolates. Published data on amplified fragment length polymorphism typing of isolates representing all biovars as well as protein profiles were used to select strains that were then further characterized by polyamine profiling and sequencing of 16S rRNA, infB, rpoB and recN genes. Comparison of 16S rRNA gene sequences revealed a monophyletic group within the avian 16S rRNA group of the Pasteurellaceae, which currently includes the genera Avibacterium, Gallibacterium and Volucribacter. Five monophyletic subgroups related to Gallibacterium anatis were recognized by 16S rRNA, rpoB, infB and recN gene sequence comparisons. Whole-genome similarity between strains of the five subgroups and the type strain of G. anatis calculated from recN sequences allowed us to classify them within the genus Gallibacterium. In addition, phenotypic data including biochemical traits, protein profiling and polyamine patterns clearly indicated that these taxa are related. Major phenotypic diversity was observed for 16S rRNA gene sequence groups. Furthermore, comparison of whole-genome similarities, phenotypic data and published data on amplified fragment length polymorphism and protein profiling revealed that each of the five groups present unique properties that allow the proposal of three novel species of Gallibacterium, for which we propose the names Gallibacterium melopsittaci sp. nov. (type strain F450(T) =CCUG 36331(T) =CCM 7538(T)), Gallibacterium trehalosifermentans sp. nov. (type strain 52/S3/90(T) =CCUG 55631(T) =CCM 7539(T)) and Gallibacterium salpingitidis sp. nov. (type strain F150(T) =CCUG 15564(T) =CCUG 36325(T) =NCTC 11414(T)), a novel genomospecies 3 of Gallibacterium and an unnamed taxon (group V). An emended description of the genus Gallibacterium is also presented.

IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival

BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.

Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.