Problems with studying wolf predation on small prey in summer via global positioning system collars

We attempted to study predation on various-sized prey by a male and female wolf (Canis lupus) with global positioning system (GPS) collars programmed to acquire locations every 10 min in the Superior National Forest of Minnesota. During May to August 2007, we investigated 147 clusters of locations (31% of the total) and found evidence of predation on a white-tailed deer (Odocoileus virginianus) fawn and yearling, a beaver (Castor canadensis), ruffed grouse (Bonasa umbellus), and fisher (Martes pennanti) and scavenging on a road-killed deer and other carrion. However, we missed finding many prey items and discuss the problems associated with trying to conduct such a study

Integrated population models poorly estimate the demographic contribution of immigration

Estimating the contribution of demographic parameters to changes in population growth is essential for understanding why populations fluctuate. Integrated population models (IPMs) offer a possibility to estimate the contributions of additional demographic parameters, for which no data have been explicitly collected—typically immigration. Such parameters are often subsequently highlighted as important drivers of population growth. Yet, accuracy in estimating their temporal variation, and consequently their contribution to changes in population growth rate, has not been investigated. To quantify the magnitude and cause of potential biases when estimating the contribution of immigration using IPMs, we simulated data (using northern wheatear Oenanthe oenanthe population estimates) from controlled scenarios to examine potential biases and how they depend on IPM parameterization, formulation of priors, the level of temporal variation in immigration and sample size. We also used empirical data on populations with known rates of immigration: Soay sheep Ovis aries and Mauritius kestrel Falco punctatus with zero immigration and grey wolf Canis lupus in Scandinavia with near-zero immigration. IPMs strongly overestimated the contribution of immigration to changes in population growth in scenarios when immigration was simulated with zero temporal variation (proportion of variance attributed to immigration = 63% for the more constrained formulation and real sample size) and in the wild populations, where the true number of immigrants was zero or near-zero (kestrel 19.1%–98.2%, sheep 4.2%–36.1% and wolf 84.0%–99.2%). Although the estimation of the contribution of immigration in the simulation study became more accurate with increasing temporal variation and sample size, it was often not possible to distinguish between an accurate estimation from data with high temporal variation versus an overestimation from data with low temporal variation. Unrealistically, large sample sizes may be required to estimate the contribution of immigration well. To minimize the risk of overestimating the contribution of immigration (or any additional parameter) in IPMs, we recommend to: (a) look for evidence of variation in immigration before investigating its contribution to population growth, (b) simulate and model data for comparison to the real data and (c) use explicit data on immigration when possible

Patient information leaflets (PILs) for UK randomised controlled trials : a feasibility study exploring whether they contain information to support decision making about trial participation

Peer reviewedPublisher PD

Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: a secondary analysis of a multicentre, prospective, observational cohort

BACKGROUND: Idiopathic pulmonary fibrosis is a progressive fibrotic lung disease with a variable clinical trajectory. Decline in forced vital capacity (FVC) is the main indicator of progression; however, missingness prevents long-term analysis of patterns in lung function. We aimed to identify distinct clusters of lung function trajectory among patients with idiopathic pulmonary fibrosis using machine learning techniques. METHODS: We did a secondary analysis of longitudinal data on FVC collected from a cohort of patients with idiopathic pulmonary fibrosis from the PROFILE study; a multicentre, prospective, observational cohort study. We evaluated the imputation performance of conventional and machine learning techniques to impute missing data and then analysed the fully imputed dataset by unsupervised clustering using self-organising maps. We compared anthropometric features, genomic associations, serum biomarkers, and clinical outcomes between clusters. We also performed a replication of the analysis on data from a cohort of patients with idiopathic pulmonary fibrosis from an independent dataset, obtained from the Chicago Consortium. FINDINGS: 415 (71%) of 581 participants recruited into the PROFILE study were eligible for further analysis. An unsupervised machine learning algorithm had the lowest imputation error among tested methods, and self-organising maps identified four distinct clusters (1-4), which was confirmed by sensitivity analysis. Cluster 1 comprised 140 (34%) participants and was associated with a disease trajectory showing a linear decline in FVC over 3 years. Cluster 2 comprised 100 (24%) participants and was associated with a trajectory showing an initial improvement in FVC before subsequently decreasing. Cluster 3 comprised 113 (27%) participants and was associated with a trajectory showing an initial decline in FVC before subsequent stabilisation. Cluster 4 comprised 62 (15%) participants and was associated with a trajectory showing stable lung function. Median survival was shortest in cluster 1 (2·87 years [IQR 2·29-3·40]) and cluster 3 (2·23 years [1·75-3·84]), followed by cluster 2 (4·74 years [3·96-5·73]), and was longest in cluster 4 (5·56 years [5·18-6·62]). Baseline FEV1 to FVC ratio and concentrations of the biomarker SP-D were significantly higher in clusters 1 and 3. Similar lung function clusters with some shared anthropometric features were identified in the replication cohort. INTERPRETATION: Using a data-driven unsupervised approach, we identified four clusters of lung function trajectory with distinct clinical and biochemical features. Enriching or stratifying longitudinal spirometric data into clusters might optimise evaluation of intervention efficacy during clinical trials and patient management. FUNDING: National Institute for Health and Care Research, Medical Research Council, and GlaxoSmithKline

Acidithiobacillus thiooxidans secretome containing a newly described lipoprotein Licanantase enhances chalcopyrite bioleaching rate

The nature of the mineral–bacteria interphase where electron and mass transfer processes occur is a key element of the bioleaching processes of sulfide minerals. This interphase is composed of proteins, metabolites, and other compounds embedded in extracellular polymeric substances mainly consisting of sugars and lipids (Gehrke et al., Appl Environ Microbiol 64(7):2743–2747, 1998). On this respect, despite Acidithiobacilli—a ubiquitous bacterial genera in bioleaching processes (Rawlings, Microb Cell Fact 4(1):13, 2005)—has long been recognized as secreting bacteria (Jones and Starkey, J Bacteriol 82:788–789, 1961; Schaeffer and Umbreit, J Bacteriol 85:492–493, 1963), few studies have been carried out in order to clarify the nature and the role of the secreted protein component: the secretome. This work characterizes for the first time the sulfur (meta)secretome of Acidithiobacillus thiooxidans strain DSM 17318 in pure and mixed cultures with Acidithiobacillus ferrooxidans DSM 16786, identifying the major component of these secreted fractions as a single lipoprotein named here as Licanantase. Bioleaching assays with the addition of Licanantase-enriched concentrated secretome fractions show that this newly found lipoprotein as an active protein additive exerts an increasing effect on chalcopyrite bioleaching rate

Comparison of (18)F SPECT with PET in myocardial imaging: A realistic thorax-cardiac phantom study

BACKGROUND: Positron emission tomography (PET) imaging with fluorine-18 ((18)F) Fluorodeoxyglucose (FDG) and flow tracer such as Rubidium-82 ((82)Rb) is an established method for evaluating an ischemic but viable myocardium. However, the high cost of PET imaging restricts its wider clinical use. Therefore, less expensive (18)F FDG single photon emission computed tomography (SPECT) imaging has been considered as an alternative to (18)F FDG PET imaging. The purpose of the work is to compare SPECT with PET in myocardial perfusion/viability imaging. METHODS: A nonuniform RH-2 thorax-heart phantom was used in the SPECT and PET acquisitions. Three inserts, 3 cm, 2 cm and 1 cm in diameter, were placed in the left ventricular (LV) wall to simulate infarcts. The phantom acquisition was performed sequentially with 7.4 MBq of (18)F and 22.2 MBq of Technetium-99m ((99m)Tc) in the SPECT study and with 7.4 MBq of (18)F and 370 MBq of (82)Rb in the PET study. SPECT and PET data were processed using standard reconstruction software provided by vendors. Circumferential profiles of the short-axis slices, the contrast and viability of the inserts were used to evaluate the SPECT and PET images. RESULTS: The contrast for 3 cm, 2 cm and 1 cm inserts were for (18)F PET data, 1.0 ± 0.01, 0.67 ± 0.02 and 0.25 ± 0.01, respectively. For (82)Rb PET data, the corresponding contrast values were 0.61 ± 0.02, 0.37 ± 0.02 and 0.19 ± 0.01, respectively. For (18)F SPECT the contrast values were, 0.31 ± 0.03 and 0.20 ± 0.05 for 3 cm and 2 cm inserts, respectively. For (99m)Tc SPECT the contrast values were, 0.63 ± 0.04 and 0.24 ± 0.05 for 3 cm and 2 cm inserts respectively. In SPECT, the 1 cm insert was not detectable. In the SPECT study, all three inserts were falsely diagnosed as "viable", while in the PET study, only the 1 cm insert was diagnosed falsely "viable". CONCLUSION: For smaller defects the (99m)Tc/(18)F SPECT imaging cannot entirely replace the more expensive (82)Rb/(18)F PET for myocardial perfusion/viability imaging, due to poorer image spatial resolution and poorer defect contrast

Clusters of Conserved Beta Cell Marker Genes for Assessment of Beta Cell Phenotype

The aim of this study was to establish a gene expression blueprint of pancreatic beta cells conserved from rodents to humans and to evaluate its applicability to assess shifts in the beta cell differentiated state. Genome-wide mRNA expression profiles of isolated beta cells were compared to those of a large panel of other tissue and cell types, and transcripts with beta cell-abundant and -selective expression were identified. Iteration of this analysis in mouse, rat and human tissues generated a panel of conserved beta cell biomarkers. This panel was then used to compare isolated versus laser capture microdissected beta cells, monitor adaptations of the beta cell phenotype to fasting, and retrieve possible conserved transcriptional regulators.Journal ArticleSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Cluster Lenses

Clusters of galaxies are the most recently assembled, massive, bound structures in the Universe. As predicted by General Relativity, given their masses, clusters strongly deform space-time in their vicinity. Clusters act as some of the most powerful gravitational lenses in the Universe. Light rays traversing through clusters from distant sources are hence deflected, and the resulting images of these distant objects therefore appear distorted and magnified. Lensing by clusters occurs in two regimes, each with unique observational signatures. The strong lensing regime is characterized by effects readily seen by eye, namely, the production of giant arcs, multiple-images, and arclets. The weak lensing regime is characterized by small deformations in the shapes of background galaxies only detectable statistically. Cluster lenses have been exploited successfully to address several important current questions in cosmology: (i) the study of the lens(es) - understanding cluster mass distributions and issues pertaining to cluster formation and evolution, as well as constraining the nature of dark matter; (ii) the study of the lensed objects - probing the properties of the background lensed galaxy population - which is statistically at higher redshifts and of lower intrinsic luminosity thus enabling the probing of galaxy formation at the earliest times right up to the Dark Ages; and (iii) the study of the geometry of the Universe - as the strength of lensing depends on the ratios of angular diameter distances between the lens, source and observer, lens deflections are sensitive to the value of cosmological parameters and offer a powerful geometric tool to probe Dark Energy. In this review, we present the basics of cluster lensing and provide a current status report of the field.Comment: About 120 pages - Published in Open Access at: http://www.springerlink.com/content/j183018170485723/ . arXiv admin note: text overlap with arXiv:astro-ph/0504478 and arXiv:1003.3674 by other author

Two novel missense mutations in the myelin protein zero gene causes Charcot-Marie-Tooth type 2 and Déjérine-Sottas syndrome

<p>Abstract</p> <p>Background</p> <p>The Charcot-Marie-Tooth (CMT) phenotype caused by mutation in the <it>myelin protein zero (MPZ) </it>gene varies considerably, from early onset and severe forms to late onset and milder forms. The mechanism is not well understood. The myelin protein zero (P₀) mediates adhesion in the spiral wraps of the Schwann cell's myelin sheath. The crystalline structure of the extracellular domain of the myelin protein zero (P₀ex) is known, while the transmembrane and intracellular structure is unknown.</p> <p>Findings</p> <p>One novel missense mutation caused a milder late onset CMT type 2, while the second missense mutation caused a severe early onset phenotype compatible with Déjérine-Sottas syndrome.</p> <p>Conclusions</p> <p>The phenotypic variation caused by different missense mutations in the <it>MPZ </it>gene is likely caused by different conformational changes of the MPZ protein which affects the functional tetramers. Severe changes of the MPZ protein cause dysfunctional tetramers and predominantly uncompacted myelin, i.e. the severe phenotypes congenital hypomyelinating neuropathy and Déjérine-Sottas syndrome, while milder changes cause the phenotypes CMT type 1 and 2.</p