Recurrent joint infection caused by a multidrug-resistant capnophilic ST131 O25H4 strain.

We report a case of a native knee septic arthritis and subsequent osteomyelitis due to a CO-dependent (capnophilic) multidrug-resistant ST131 O25:H4 strain. Capnophilic phenotype made microbiology investigation challenging; susceptibility testing could not be performed and the organism did not grow in the urine culture using standard method. The combination of unique virotype and capnophilia may have contributed to the aggressiveness of this organism and the initial unsuccessful carbapenem course, leading to recurrent infection.

MMR Deficiency Defines Distinct Molecular Subtype of Breast Cancer with Histone Proteomic Networks.

Mismatch repair (MMR) alterations are important prognostic and predictive biomarkers in a variety of cancer subtypes, including colorectal and endometrial. However, in breast cancer (BC), the distinction and clinical significance of MMR are largely unknown. This may be due in part to the fact that genetic alterations in MMR genes are rare and only seen to occur in around 3% of BCs.

Clinical features of patients with -deleted bladder cancer.

Advanced urothelial carcinoma continues to have a dismal prognosis despite several new therapies in the last 5 years. and mutations and fusions, PD-L1 expression, tumor mutational burden, and microsatellite instability are established predictive biomarkers in advanced urothelial carcinoma. Novel biomarkers can optimize the sequencing of available treatments and improve outcomes.

Assessing spatial, temporal, and analytical variation of groundwater chemistry in a large nuclear complex, USA.

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a 'pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s2, which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided.

Optimizing liquid effluent monitoring at a large nuclear complex.

Effluent monitoring typically requires a large number of analytes and samples during the initial or startup phase of a facility. Once a baseline is established, the analyte list and sampling frequency may be reduced. Although there is a large body of literature relevant to the initial design, few, if any, published papers exist on updating established effluent monitoring programs.