High levels of genetic structure and striking phenotypic variability in a sexually dimorphic suckermouth catfish from the African Highveld

© 2015 The Linnean Society of London. Uncovering biological diversity to more accurately understand diversity patterns, and ultimately the processes driving diversification, is important not only from an evolutionary perspective but also a conservation perspective. This is particularly pertinent in Africa's rivers in which overall diversity, as well as how it arose, is poorly understood in comparison with lacustrine environments. Here we investigate population divergence in the sexually dimorphic suckermouth catfish species Chiloglanis anoterus (Crass, 1960) from the African Highveld, in which we observe striking variability in exaggerated male caudal fins across its range. As this trait is likely to be indirect evidence for sexual selection by female choice, a mechanism that has been shown to increase species diversity in different taxa, we used an integrated approach to test if current diversity in this species is underestimated. Results based on phylogenetic inference, population genetics and geometric morphometrics indicate that the recognized species C. anoterus represents five distinct lineages that may be considered confirmed candidate species. We suggest that diversification in these highland catfish has been facilitated through geographical isolation in upper river catchments, and that sexual selection through female choice has probably driven variation in male caudal fin morphology. In contrast to the relatively large range size of the currently recognized species (C. anoterus), our findings highlight highly restricted ranges of the lineages identified here, indicating that these highland habitats may harbour higher levels of endemic diversity than previously thought

MRI for assessment of anal fistula

Magnetic resonance imaging (MRI) is the best imaging modality for preoperative assessment of patients with anal fistula. MRI helps to accurately demonstrate disease extension and predict prognosis. This in turn helps make therapy decisions and monitor therapy. The pertinent anatomy, fistula classification and MRI findings will be discussed

Fragment reattachment, reproductive status, and health indicators of the invasive colonial tunicate Didemnum vexillum with implications for dispersal

This manuscript is not subject to U.S. copyright. The definitive version was published in Biological Invasions 14 (2012): 2133-2140, doi:10.1007/s10530-012-0219-8.The invasive colonial tunicate Didemnum vexillum is now widespread in coastal and offshore waters of New England, USA. D. vexillum can inflict ecological and economic damage through biofouling and habitat modification. Natural and anthropogenic processes that fragment colonies of D. vexillum may be accelerating the spread of this invader. Reattachment success and fragment viability were confirmed in the laboratory after four weeks of suspension in experimental aquaria. The shape of suspended D. vexillum fragments progressed from flattened to globular spheres and then flattened again after reattachment to the substrate. Reproductive activity, confirmed by the presence of eggs and larvae, was observed for fragments suspended up to three weeks suggesting that D. vexillum is capable of reproducing while in a fragmented, suspended state. An index of colony health was used to monitor change in D. vexillum health while in suspension. Overall, colony health declined with time in suspension although colonies that appeared dead (black and gray in overall color) still contained a substantial number of healthy live zooids. These results suggest that activities that cause fragmentation can significantly facilitate the spread of D. vexillum. Coastal managers should consider reducing or eliminating, when practical, activities that return fragmented colonies of D. vexillum to the water. In-water cleaning of biofouling and dredging are likely expediting the spread of this invasive species unless biofouling can be contained and removed from the water.This research was funded by the NOAA Aquatic Invasive Species Program

The second data release of the INT Photometric Ha Survey of the Northern Galactic Plane (IPHAS DR2)

The INT/WFC Photometric Hα Survey of the Northern Galactic Plane (IPHAS) is a 1800 deg2 imaging survey covering Galactic latitudes |b| < 5° and longitudes ℓ = 30°–215° in the r, i, and Hα filters using the Wide Field Camera (WFC) on the 2.5-m Isaac Newton Telescope (INT) in La Palma. We present the first quality-controlled and globally calibrated source catalogue derived from the survey, providing single-epoch photometry for 219 million unique sources across 92 per cent of the footprint. The observations were carried out between 2003 and 2012 at a median seeing of 1.1 arcsec (sampled at 0.33 arcsec pixel−1) and to a mean 5σ depth of 21.2 (r), 20.0 (i), and 20.3 (Hα) in the Vega magnitude system. We explain the data reduction and quality control procedures, describe and test the global re-calibration, and detail the construction of the new catalogue. We show that the new calibration is accurate to 0.03 mag (root mean square) and recommend a series of quality criteria to select accurate data from the catalogue. Finally, we demonstrate the ability of the catalogue's unique (r − Hα, r − i) diagram to (i) characterize stellar populations and extinction regimes towards different Galactic sightlines and (ii) select and quantify Hα emission-line objects. IPHAS is the first survey to offer comprehensive CCD photometry of point sources across the Galactic plane at visible wavelengths, providing the much-needed counterpart to recent infrared surveys

Multilevel Parallelization of AutoDock 4.2

<p>Abstract</p> <p>Background</p> <p>Virtual (computational) screening is an increasingly important tool for drug discovery. AutoDock is a popular open-source application for performing molecular docking, the prediction of ligand-receptor interactions. AutoDock is a serial application, though several previous efforts have parallelized various aspects of the program. In this paper, we report on a multi-level parallelization of AutoDock 4.2 (mpAD4).</p> <p>Results</p> <p>Using MPI and OpenMP, AutoDock 4.2 was parallelized for use on MPI-enabled systems and to multithread the execution of individual docking jobs. In addition, code was implemented to reduce input/output (I/O) traffic by reusing grid maps at each node from docking to docking. Performance of mpAD4 was examined on two multiprocessor computers.</p> <p>Conclusions</p> <p>Using MPI with OpenMP multithreading, mpAD4 scales with near linearity on the multiprocessor systems tested. In situations where I/O is limiting, reuse of grid maps reduces both system I/O and overall screening time. Multithreading of AutoDock's Lamarkian Genetic Algorithm with OpenMP increases the speed of execution of individual docking jobs, and when combined with MPI parallelization can significantly reduce the execution time of virtual screens. This work is significant in that mpAD4 speeds the execution of certain molecular docking workloads and allows the user to optimize the degree of system-level (MPI) and node-level (OpenMP) parallelization to best fit both workloads and computational resources.</p

The incidence of liver injury in Uyghur patients treated for TB in Xinjiang Uyghur autonomous region, China, and its association with hepatic enzyme polymorphisms nat2, cyp2e1, gstm1 and gstt1.

BACKGROUND AND OBJECTIVE: Of three first-line anti-tuberculosis (anti-TB) drugs, isoniazid is most commonly associated with hepatotoxicity. Differences in INH-induced toxicity have been attributed to genetic variability at several loci, NAT2, CYP2E1, GSTM1and GSTT1, that code for drug-metabolizing enzymes. This study evaluated whether the polymorphisms in these enzymes were associated with an increased risk of anti-TB drug-induced hepatitis in patients and could potentially be used to identify patients at risk of liver injury. METHODS AND DESIGN: In a cross-sectional study, 2244 tuberculosis patients were assessed two months after the start of treatment. Anti-TB drug-induced liver injury (ATLI) was defined as an ALT, AST or bilirubin value more than twice the upper limit of normal. NAT2, CYP2E1, GSTM1 and GSTT1 genotypes were determined using the PCR/ligase detection reaction assays. RESULTS: 2244 patients were evaluated, there were 89 cases of ATLI, a prevalence of 4% 9 patients (0.4%) had ALT levels more than 5 times the upper limit of normal. The prevalence of ATLI was greater among men than women, and there was a weak association with NAT2*5 genotypes, with ATLI more common among patients with the NAT2*5*CT genotype. The sensitivity of the CT genotype for identifying patients with ATLI was 42% and the positive predictive value 5.9%. CT ATLI was more common among slow acetylators (prevalence ratio 2.0 (95% CI 0.95,4.20) )compared to rapid acetylators. There was no evidence that ATLI was associated with CYP2E1 RsaIc1/c1genotype, CYP2E1 RsaIc1/c2 or c2/c2 genotypes, or GSTM1/GSTT1 null genotypes. CONCLUSIONS: In Xinjiang Uyghur TB patients, liver injury was associated with the genetic variant NAT2*5, however the genetic markers studied are unlikely to be useful for screening patients due to the low sensitivity and low positive predictive values for identifying persons at risk of liver injury

Multicenter Evaluation of a Novel Surveillance Paradigm for Complications of Mechanical Ventilation

Ventilator-associated pneumonia (VAP) surveillance is time consuming, subjective, inaccurate, and inconsistently predicts outcomes. Shifting surveillance from pneumonia in particular to complications in general might circumvent the VAP definition's subjectivity and inaccuracy, facilitate electronic assessment, make interfacility comparisons more meaningful, and encourage broader prevention strategies. We therefore evaluated a novel surveillance paradigm for ventilator-associated complications (VAC) defined by sustained increases in patients' ventilator settings after a period of stable or decreasing support.We assessed 600 mechanically ventilated medical and surgical patients from three hospitals. Each hospital contributed 100 randomly selected patients ventilated 2-7 days and 100 patients ventilated >7 days. All patients were independently assessed for VAP and for VAC. We compared incidence-density, duration of mechanical ventilation, intensive care and hospital lengths of stay, hospital mortality, and time required for surveillance for VAP and for VAC. A subset of patients with VAP and VAC were independently reviewed by a physician to determine possible etiology.Of 597 evaluable patients, 9.3% had VAP (8.8 per 1,000 ventilator days) and 23% had VAC (21.2 per 1,000 ventilator days). Compared to matched controls, both VAP and VAC prolonged days to extubation (5.8, 95% CI 4.2-8.0 and 6.0, 95% CI 5.1-7.1 respectively), days to intensive care discharge (5.7, 95% CI 4.2-7.7 and 5.0, 95% CI 4.1-5.9), and days to hospital discharge (4.7, 95% CI 2.6-7.5 and 3.0, 95% CI 2.1-4.0). VAC was associated with increased mortality (OR 2.0, 95% CI 1.3-3.2) but VAP was not (OR 1.1, 95% CI 0.5-2.4). VAC assessment was faster (mean 1.8 versus 39 minutes per patient). Both VAP and VAC events were predominantly attributable to pneumonia, pulmonary edema, ARDS, and atelectasis.Screening ventilator settings for VAC captures a similar set of complications to traditional VAP surveillance but is faster, more objective, and a superior predictor of outcomes

Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result.</p> <p>Results</p> <p>In this paper, we describe the first systematic comparison of a wide range of normalisation methods, using two objectives that should be met by a good method. These objectives are minimisation of inter-spectra variance and maximisation of signal with respect to class separation. The former is assessed using an estimation of the coefficient of variation, the latter using the classification performance of three types of classifiers on real-world datasets representing two-class diagnostic problems. To obtain a maximally robust evaluation of a normalisation method, both objectives are evaluated over multiple datasets and multiple configurations of baseline correction and peak detection methods. Results are assessed for statistical significance and visualised to reveal the performance of each normalisation method, in particular with respect to using no normalisation. The normalisation methods described have been implemented in the freely available MASDA R-package.</p> <p>Conclusion</p> <p>In the general case, normalisation of mass spectra is beneficial to the quality of data. The majority of methods we compared performed significantly better than the case in which no normalisation was used. We have shown that normalisation methods that scale spectra by a factor based on the dispersion (e.g., standard deviation) of the data clearly outperform those where a factor based on the central location (e.g., mean) is used. Additional improvements in performance are obtained when these factors are estimated locally, using a sliding window within spectra, instead of globally, over full spectra. The underperforming category of methods using a globally estimated factor based on the central location of the data includes the method used by the majority of SELDI users.</p

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis : A Tutorial

Cost-effectiveness analyses (CEA) of randomised controlled trials are a key source of information for health care decision makers. Missing data are, however, a common issue that can seriously undermine their validity. A major concern is that the chance of data being missing may be directly linked to the unobserved value itself [missing not at random (MNAR)]. For example, patients with poorer health may be less likely to complete quality-of-life questionnaires. However, the extent to which this occurs cannot be ascertained from the data at hand. Guidelines recommend conducting sensitivity analyses to assess the robustness of conclusions to plausible MNAR assumptions, but this is rarely done in practice, possibly because of a lack of practical guidance. This tutorial aims to address this by presenting an accessible framework and practical guidance for conducting sensitivity analysis for MNAR data in trial-based CEA. We review some of the methods for conducting sensitivity analysis, but focus on one particularly accessible approach, where the data are multiply-imputed and then modified to reflect plausible MNAR scenarios. We illustrate the implementation of this approach on a weight-loss trial, providing the software code. We then explore further issues around its use in practice