Citations

Objective To test the association between hospital type and performance of candidate quality measures for treatment of muscle‐invasive bladder cancer ( MIBC ) using a large national tumour registry. Proposed quality measures include receipt of neoadjuvant chemotherapy, timely treatment, adequate lymph node dissection, and continent urinary diversion. Patients and Methods Using the N ational C ancer D atabase, patients with stage ≥ II urothelial carcinoma treated with radical cystectomy ( RC ) from 2003 to 2010 were identified. Hospitals were grouped by type and annual RC volume: community, comprehensive low volume ( CLV ), comprehensive high volume ( CHV ), academic low volume ( ALV ), and academic high volume ( AHV ) groups. Logistic regression models were used to test the association between hospital group and performance of quality measures, adjusting for year, demographic, and clinical/pathological characteristics; generalised estimating equations were fitted to the models to adjust for clustering at the hospital level. Results In all, 23 279 patients underwent RC at community (12.4%), comprehensive ( CLV 38%, CHV 5%), and academic ( ALV 17%, AHV 28%) hospitals. While only 0.8% (175) of patients met all four quality criteria, 61% of patients treated at AHV hospitals met two or more quality metric indicators compared with ALV (45%), CHV (44%), CLV (38%), and community (37%) hospitals ( P < 0.001). After adjustment, patients were more likely to receive two or more quality measures when treated at AHV (odds ratio [ OR ] 2.4, confidence interval [ CI ] 2.0–2.9), ALV ( OR 1.3, CI 1.1–1.6), and CHV ( OR 1.3, CI 1.03–1.7) hospitals compared with community hospitals. Conclusions Patients undergoing RC at AHV hospitals were more likely to meet quality criteria. However, performance remains low across hospital types, highlighting the opportunity to improve quality of care for MIBC .

Abstract This study examined habitat variables associated with 53 active bald eagle Haliaeetus leucocephalus nest sites in the Winona District of the Upper Mississippi River National Wildlife and Fish Refuge, Minnesota and Wisconsin. The Refuge is the most heavily visited refuge in the United States, where breeding eagle populations have been increasing dramatically. During February–April 2009, nest trees were identified and measured, nest heights were determined, distances to nearest water bodies were assessed, and forest inventories were conducted for the standing timber surrounding the nest trees. Nest densities and spacing were assessed within each navigation pool, and land cover types were examined within 100- and 1,000-m radii around known eagle nest sites and random points within the Refuge. Ninety-three percent of nest sites had supercanopy eastern cottonwoods Populus deltoides and silver maples Acer saccharinum as the nest trees. Potential human disturbances from highways, railroads, and commercial barge and recreational boat traffic were present within 400 m of 90% of known nest sites. Eagle nest sites were located an average of 1.52 km from the next nearest nest, with nest densities ranging from 0.32 to 9.72 nests/100 km2 among the four navigation pools of the Winona District. Land cover types around known nest sites and random points differed significantly at both 100- and 1,000 m scales, with wet forest and open water significantly more abundant and agricultural and developed lands significantly less abundant than around randomly selected points. Successful nests that fledged at least one young were spaced significantly further away from other active nests and were located in areas with lower tree density than were unsuccessful nests. Floodplain-nesting bald eagles tended to select the tallest, dominant trees for nest sites, placing nests near the height of the surrounding canopy. Human presence within the Refuge does not appear to be limiting the expansion of nesting bald eagles in this riverine habitat.

Key Points Imatinib improves outcomes for adults with Ph+ ALL at least in part by facilitating allogeneic stem cell transplant. Allogeneic hematopoietic stem cell transplant is not dispensible in Ph+ ALL in the imatinib era.

ABSTRACTGenes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene‐environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P‐values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.

Abstract Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70 917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46 450 breast cancer cases and 42 461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P &lt; 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P &lt; 10−4) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P &lt; 10−8. Results from the second analytic approach were consistent with those from the first (P &gt; 10−10). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Summary A low‐diversity microbial community, dominated by the γ ‐proteobacterium H alomonas sulfidaeris , was detected in samples of warm saline formation porewater collected from the C ambrian Mt. S imon S andstone in the I llinois B asin of the N orth A merican M idcontinent (1.8 km/5872 ft burial depth, 50° C , pH 8, 181 bars pressure). These highly porous and permeable quartz arenite sandstones are directly analogous to reservoirs around the world targeted for large‐scale hydrocarbon extraction, as well as subsurface gas and carbon storage. A new downhole low‐contamination subsurface sampling probe was used to collect in situ formation water samples for microbial environmental metagenomic analyses. Multiple lines of evidence suggest that this H . sulfidaeris ‐dominated subsurface microbial community is indigenous and not derived from drilling mud microbial contamination. Data to support this includes V 1‐ V 3 pyrosequencing of formation water and drilling mud, as well as comparison with previously published microbial analyses of drilling muds in other sites. Metabolic pathway reconstruction, constrained by the geology, geochemistry and present‐day environmental conditions of the Mt . S imon S andstone, implies that H . sulfidaeris ‐dominated subsurface microbial community may utilize iron and nitrogen metabolisms and extensively recycle indigenous nutrients and substrates. The presence of aromatic compound metabolic pathways suggests this microbial community can readily adapt to and survive subsurface hydrocarbon migration.

Abstract Integrative genomics has the potential to uncover relevant loci, as clinical outcome and response to chemotherapies are most likely not due to a single gene (or data type) but rather a complex relationship involving genetic variation, mRNA, DNA methylation, and copy number variation. In addition to this complexity, many complex phenotypes are thought to be controlled by the interplay of multiple genes within the same molecular pathway or gene set (GS). To address these two challenges, we propose an integrative gene set analysis approach and apply this strategy to a cisplatin (CDDP) pharmacogenomics study involving lymphoblastoid cell lines for which genome-wide SNP and mRNA expression data was collected. Application of the integrative GS analysis implicated the role of the RNA binding and cytoskeletal part GSs. The genes LMNB1 and CENPF, within the cytoskeletal part GS, were functionally validated with siRNA knockdown experiments, where the knockdown of LMNB1 and CENPF resulted in CDDP resistance in multiple cancer cell lines. This study demonstrates the utility of an integrative GS analysis strategy for detecting novel genes associated with response to cancer therapies, moving closer to tailored therapy decisions for cancer patients.

In this paper, we present recent developments in the characterization of anisotropic, biological media utilizing displacements measured with dynamic MRE. In one approach, a waveguide constrained analysis is applied to physical structures (such as muscle), which evaluates the velocities of wave propagation along arbitrarily oriented fibers or fiber bundles in a local fashion, utilizing a spectral filter and a sliding window, spatial Fourier transform. In a second approach, the anisotropic equations of elasticity, in variational form, are inverted for a determination of the complex moduli comprising the medium. Issues concerning ill-conditioning, the effects of boundary conditions, and multiaspect excitation requirements will be addressed, as well as a discussion concerning the models which are appropriate for various physical situations. These two complementary methods of analysis will be demonstrated utilizing both phantom as well as in vivo dynamic displacement measurements.