Statistical methods for automated drug susceptibility testing: Bayesian minimum inhibitory concentration prediction from growth curves

Determination of the minimum inhibitory concentration (MIC) of a drug that prevents microbial growth is an important step for managing patients with infections. In this paper we present a novel probabilistic approach that accurately estimates MICs based on a panel of multiple curves reflecting features of bacterial growth. We develop a probabilistic model for determining whether a given dilution of an antimicrobial agent is the MIC given features of the growth curves over time. Because of the potentially large collection of features, we utilize Bayesian model selection to narrow the collection of predictors to the most important variables. In addition to point estimates of MICs, we are able to provide posterior probabilities that each dilution is the MIC based on the observed growth curves. The methods are easily automated and have been incorporated into the Becton--Dickinson PHOENIX automated susceptibility system that rapidly and accurately classifies the resistance of a large number of microorganisms in clinical samples. Over seventy-five studies to date have shown this new method provides improved estimation of MICs over existing approaches.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS217 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Gurnis, McComas receive Macelwane Medals

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95077/1/eost9813.pd

Cervicitis as a Clinical Indicator of Gonococcal and Chlamydial Infections in Pregnancy

Objective: We undertook the present study to attempt to apply clinical indicators predictive of cervical infection in nongravid populations with either Neisseria gonorrhoeae or Chlamydia trachomatis to our pregnant population and to determine the significance of the clinical diagnosis of “cervicitis.

Designing hollow nano gold golf balls.

Hollow/porous nanoparticles, including nanocarriers, nanoshells, and mesoporous materials have applications in catalysis, photonics, biosensing, and delivery of theranostic agents. Using a hierarchical template synthesis scheme, we have synthesized a nanocarrier mimicking a golf ball, consisting of (i) solid silica core with a pitted gold surface and (ii) a hollow/porous gold shell without silica. The template consisted of 100 nm polystyrene beads attached to a larger silica core. Selective gold plating of the core followed by removal of the polystyrene beads produced a golf ball-like nanostructure with 100 nm pits. Dissolution of the silica core produced a hollow/porous golf ball-like nanostructure

Sloan Digital Sky Survey III Photometric Quasar Clustering: Probing the Initial Conditions of the Universe using the Largest Volume

The Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z = 0.5 and z = 2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans ~11,000 square degrees and probes a volume of 80(Gpc/h)^3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometrically classified quasars using an optimal quadratic estimator in four redshift slices with an accuracy of ~25% over a bin width of l ~10 - 15 on scales corresponding to matter-radiation equality and larger (l ~ 2 - 30). Observational systematics can strongly bias clustering measurements on large scales, which can mimic cosmologically relevant signals such as deviations from Gaussianity in the spectrum of primordial perturbations. We account for systematics by employing a new method recently proposed by Agarwal et al. (2014) to the clustering of photometrically classified quasars. We carefully apply our methodology to mitigate known observational systematics and further remove angular bins that are contaminated by unknown systematics. Combining quasar data with the photometric luminous red galaxy (LRG) sample of Ross et al. (2011) and Ho et al. (2012), and marginalizing over all bias and shot noise-like parameters, we obtain a constraint on local primordial non-Gaussianity of fNL = -113+/-154 (1\sigma error). [Abridged]Comment: 35 pages, 15 figure

Radiologic imaging in cystic fibrosis: cumulative effective dose and changing trends over 2 decades

Objective: With the increasing life expectancy for patients with cystic fibrosis (CF), and a known predisposition to certain cancers, cumulative radiation exposure from radiologic imaging is of increasing significance. This study explores the estimated cumulative effective radiation dose over a 17-year period from radiologic procedures and changing trends of imaging modalities over this period. Methods: Estimated cumulative effective dose (CED) from all thoracic and extrathoracic imaging modalities and interventional radiology procedures for both adult and pediatric patients with CF, exclusively attending a nationally designated CF center between 1992-2009 for > 1 year, was determined. The study period was divided into three equal tertiles, and estimated CED attributable to all radiologic procedures was estimated for each tertile. Results: Two hundred thirty patients met inclusion criteria (2,240 person-years of follow-up; 5,596 radiologic procedures). CED was > 75 mSv for one patient (0.43%), 36 patients (15.6%) had a CED between 20 and 75 mSv, 56 patients (24.3%) had a CED between 5 and 20 mSv, and in 138 patients (60%) the CED was estimated to be between 0 and 5 mSv over the study period. The mean annual CED per patient increased consecutively from 0.39 mSv/y to 0.47 mSv/y to 1.67 mSv/y over the tertiles one to three of the study period, respectively (P < .001). Thoracic imaging accounted for 46.9% of the total CED and abdominopelvic imaging accounted for 42.9% of the CED, respectively. There was an associated 5.9-fold increase in the use of all CT scanning per patient (P < .001). Conclusions: This study highlights the increasing exposure to ionizing radiation to patients with CF as a result of diagnostic imaging, primarily attributable to CT scanning. Increased awareness of CED and strategies to reduce this exposure are needed

Inadvertent paralog inclusion drives artifactual topologies and timetree estimates in phylogenomics

Increasingly, large phylogenomic datasets include transcriptomic data from non-model organisms. This has allowed controversial and unexplored evolutionary relationships in the tree of life to be addressed but also increases the risk of inadvertent inclusion of paralogs in the analysis. While this may be expected to result in decreased phylogenetic support it is not clear if it could also drive highly supported artefactual relationships. Many groups, including the hyper-diverse Lissamphibia, are especially susceptible to these issues due to ancient gene duplication events, small numbers of sequenced genomes and because transcriptomes are increasingly applied to resolve historically conflicting taxonomic hypotheses. We tested the potential impact of paralog inclusion on the topologies and timetree estimates of the Lissamphibia using published and de novo sequencing data including 18 amphibian species, from which 2,656 single-copy gene families were identified. A novel paralog filtering approach resulted in four differently curated datasets, which were used for phylogenetic reconstructions using Bayesian inference, maximum likelihood and quartet-based supertrees. We found that paralogs drive strongly supported conflicting hypotheses within the Lissamphibia (Batrachia and Procera) and older divergence time estimates even within groups where no variation in topology was observed. All investigated methods, except Bayesian inference with the CAT-GTR model, were found to be sensitive to paralogs, but with filtering convergence to the same answer (Batrachia) was observed. This is the first large-scale study to address the impact of orthology selection using transcriptomic data and emphasises the importance of quality over quantity particularly for understanding relationships of poorly sampled taxa

Rates and predictors of risk of stroke and its subtypes in diabetes: a prospective observational study

Background Small vessel disease is reported to be a more common cause of ischaemic stroke in people with diabetes than in others. However, population based studies have shown no difference between those with and those without diabetes in the subtypes of stroke. We determined the rates and predictors of risk of stroke and its subtypes in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial. Methods 9795 patients aged 50–75 years with type 2 diabetes were followed up for a median of 5 years. Annual rates were derived by the Kaplan–Meier method and independent predictors of risk by Cox proportional hazards regression analyses. Results The annual rate of stroke was 6.7 per 1000 person years; 82% were ischaemic and caused by small artery disease (36%), large artery disease (17%) and embolism from the heart (13%); 10% were haemorrhagic. Among the strongest baseline predictors of ischaemic or unknown stroke were age (60–65 years, HR 1.98; >65 years, HR 2.35) and a history of stroke or transient ischaemic attack (TIA) (HR 2.06). Other independent baseline predictors were male sex, smoking, history of hypertension, ischaemic heart disease, nephropathy, systolic blood pressure and blood low density lipoprotein (LDL) cholesterol, HbA1c and fibrinogen. A history of peripheral vascular disease, low high density lipoprotein, age and history of hypertension were associated with large artery ischaemic stroke. A history of diabetic retinopathy, LDL cholesterol, male sex, systolic blood pressure, smoking, diabetes duration and a history of stroke or TIA were associated with small artery ischaemic stroke. Conclusions Older people with a history of stroke were at highest risk of stroke, but the prognosis and prognostic factors of subtypes were heterogeneous. The results will help clinicians quantify the absolute risk of stroke and its subtypes for typical diabetes patients.FIELD trial sponsored by Laboratoires Fournier SA, Dijon, France (part of Abbott