ASTRAL: genome-scale coalescent-based species tree estimation.

MOTIVATION: Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions. RESULTS: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy-improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods. ASTRAL is often more accurate than concatenation using maximum likelihood, except when ILS levels are low or there are too few gene trees. AVAILABILITY AND IMPLEMENTATION: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Spatial variability of total dissolved copper and copper speciation in the inshore waters of Bermuda.

Total dissolved copper (Cu) and Cu speciation were examined from inshore waters of Bermuda, in October 2009 and July-August 2010, to determine the relationship between total dissolved Cu, Cu-binding ligands and bioavailable, free, hydrated Cu(2+) concentrations. Speciation was performed using competitive ligand exchange-adsorptive cathodic stripping voltammetry (CLE-ACSV). Mean total dissolved Cu concentrations ranged from 1.4 nM to 19.2 nM, with lowest concentrations at sites further from shore, consistent with previous measurements in the Sargasso Sea, and localized Cu enrichment inshore in enclosed harbors. Ligand concentrations exceeded dissolved [Cu] at most sites, and [Cu(2+)] were correspondingly low at those sites, typically <10(-13) M. One site, Hamilton Harbour, was found to have [Cu] in excess of ligands, resulting in [Cu(2+)] of 10(-10.7) M, and indicating that Cu may be toxic to phytoplankton here.

Evaluating the accuracy of SHAPE-directed RNA secondary structure predictions.

Recent advances in RNA structure determination include using data from high-throughput probing experiments to improve thermodynamic prediction accuracy. We evaluate the extent and nature of improvements in data-directed predictions for a diverse set of 16S/18S ribosomal sequences using a stochastic model of experimental SHAPE data. The average accuracy for 1000 data-directed predictions always improves over the original minimum free energy (MFE) structure. However, the amount of improvement varies with the sequence, exhibiting a correlation with MFE accuracy. Further analysis of this correlation shows that accurate MFE base pairs are typically preserved in a data-directed prediction, whereas inaccurate ones are not. Thus, the positive predictive value of common base pairs is consistently higher than the directed prediction accuracy. Finally, we confirm sequence dependencies in the directability of thermodynamic predictions and investigate the potential for greater accuracy improvements in the worst performing test sequence.

GTfold: enabling parallel RNA secondary structure prediction on multi-core desktops.

BACKGROUND: Accurate and efficient RNA secondary structure prediction remains an important open problem in computational molecular biology. Historically, advances in computing technology have enabled faster and more accurate RNA secondary structure predictions. Previous parallelized prediction programs achieved significant improvements in runtime, but their implementations were not portable from niche high-performance computers or easily accessible to most RNA researchers. With the increasing prevalence of multi-core desktop machines, a new parallel prediction program is needed to take full advantage of today's computing technology. FINDINGS: We present here the first implementation of RNA secondary structure prediction by thermodynamic optimization for modern multi-core computers. We show that GTfold predicts secondary structure in less time than UNAfold and RNAfold, without sacrificing accuracy, on machines with four or more cores. CONCLUSIONS: GTfold supports advances in RNA structural biology by reducing the timescales for secondary structure prediction. The difference will be particularly valuable to researchers working with lengthy RNA sequences, such as RNA viral genomes.

SuperFine: fast and accurate supertree estimation.

Many research groups are estimating trees containing anywhere from a few thousands to hundreds of thousands of species, toward the eventual goal of the estimation of a Tree of Life, containing perhaps as many as several million leaves. These phylogenetic estimations present enormous computational challenges, and current computational methods are likely to fail to run even on data sets in the low end of this range. One approach to estimate a large species tree is to use phylogenetic estimation methods (such as maximum likelihood) on a supermatrix produced by concatenating multiple sequence alignments for a collection of markers; however, the most accurate of these phylogenetic estimation methods are extremely computationally intensive for data sets with more than a few thousand sequences. Supertree methods, which assemble phylogenetic trees from a collection of trees on subsets of the taxa, are important tools for phylogeny estimation where phylogenetic analyses based upon maximum likelihood (ML) are infeasible. In this paper, we introduce SuperFine, a meta-method that utilizes a novel two-step procedure in order to improve the accuracy and scalability of supertree methods. Our study, using both simulated and empirical data, shows that SuperFine-boosted supertree methods produce more accurate trees than standard supertree methods, and run quickly on very large data sets with thousands of sequences. Furthermore, SuperFine-boosted matrix representation with parsimony (MRP, the most well-known supertree method) approaches the accuracy of ML methods on supermatrix data sets under realistic conditions.

An experimental study of Quartets MaxCut and other supertree methods.

BACKGROUND: Supertree methods represent one of the major ways by which the Tree of Life can be estimated, but despite many recent algorithmic innovations, matrix representation with parsimony (MRP) remains the main algorithmic supertree method. RESULTS: We evaluated the performance of several supertree methods based upon the Quartets MaxCut (QMC) method of Snir and Rao and showed that two of these methods usually outperform MRP and five other supertree methods that we studied, under many realistic model conditions. However, the QMC-based methods have scalability issues that may limit their utility on large datasets. We also observed that taxon sampling impacted supertree accuracy, with poor results obtained when all of the source trees were only sparsely sampled. Finally, we showed that the popular optimality criterion of minimizing the total topological distance of the supertree to the source trees is only weakly correlated with supertree topological accuracy. Therefore evaluating supertree methods on biological datasets is problematic. CONCLUSIONS: Our results show that supertree methods that improve upon MRP are possible, and that an effort should be made to produce scalable and robust implementations of the most accurate supertree methods. Also, because topological accuracy depends upon taxon sampling strategies, attempts to construct very large phylogenetic trees using supertree methods should consider the selection of source tree datasets, as well as supertree methods. Finally, since supertree topological error is only weakly correlated with the supertree's topological distance to its source trees, development and testing of supertree methods presents methodological challenges.

A simulation study comparing supertree and combined analysis methods using SMIDGen.

BACKGROUND: Supertree methods comprise one approach to reconstructing large molecular phylogenies given multi-marker datasets: trees are estimated on each marker and then combined into a tree (the "supertree") on the entire set of taxa. Supertrees can be constructed using various algorithmic techniques, with the most common being matrix representation with parsimony (MRP). When the data allow, the competing approach is a combined analysis (also known as a "supermatrix" or "total evidence" approach) whereby the different sequence data matrices for each of the different subsets of taxa are concatenated into a single supermatrix, and a tree is estimated on that supermatrix. RESULTS: In this paper, we describe an extensive simulation study we performed comparing two supertree methods, MRP and weighted MRP, to combined analysis methods on large model trees. A key contribution of this study is our novel simulation methodology (Super-Method Input Data Generator, or SMIDGen) that better reflects biological processes and the practices of systematists than earlier simulations. We show that combined analysis based upon maximum likelihood outperforms MRP and weighted MRP, giving especially big improvements when the largest subtree does not contain most of the taxa. CONCLUSIONS: This study demonstrates that MRP and weighted MRP produce distinctly less accurate trees than combined analyses for a given base method (maximum parsimony or maximum likelihood). Since there are situations in which combined analyses are not feasible, there is a clear need for better supertree methods. The source tree and combined datasets used in this study can be used to test other supertree and combined analysis methods.

Closure operations in phylogenetics.

Closure operations are a useful device in both the theory and practice of tree reconstruction in biology and other areas of classification. These operations take a collection of trees (rooted or unrooted) that classify overlapping sets of objects at their leaves, and infer further tree-like relationships. In this paper we investigate closure operations on phylogenetic trees; both rooted and unrooted; as well as on X-splits, and in a general abstract setting. We derive a number of new results, particularly concerning the completeness (and incompleteness) and complexity of various types of closure rules.

Comparison of botulinum toxin serotypes A and B for the treatment of cervical dystonia.

OBJECTIVE: To directly compare two serotypes of botulinum toxin (BoNTA and BoNTB) in cervical dystonia (CD) using a randomized, double-blind, parallel-arm study design. METHODS: Subjects with CD who had a previous response from BoNTA were randomly assigned to BoNTA or BoNTB and evaluated in a blinded fashion at baseline, 4 weeks, 8 weeks, and 2-week intervals thereafter until loss of 80% of clinical effect or completion of 20 weeks of observation. CD severity was measured with the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS), and adverse events were assessed by structured interview. Statistical analysis included Wilcoxon rank sum test, log rank tests, and Kaplan-Meier survival curves for duration of effect. RESULTS: A total of 139 subjects (BoNTA, n = 74; BoNTB, n = 65) were randomized at 19 study sites. Improvement in TWSTRS score was found at 4 weeks after injection and did not differ between serotypes. Dysphagia and dry mouth were more frequent with BoNTB (dysphagia: BoNTA 19% vs BoNTB 48%, p = 0.0005; dry mouth (BoNTA 41% vs BoNTB 80%, p < 0.0001). In clinical responders, BoNT A had a modestly longer duration of benefit (BoNTA 14 weeks, BoNTB 12.1 weeks, p = 0.033). CONCLUSION: Both serotypes of botulinum toxin (BoNTA and BoNTB) had equivalent benefit in subjects with cervical dystonia at 4 weeks. BoNTA had fewer adverse events and a marginally longer duration of effect in subjects showing a clinical response.

Addressing the challenges of the global nursing community.

AIM: To describe both the initial and the subsequent impact of the 2001 Global Nursing Partnerships Conference: 'Strategies for a Sustainable Workforce', the first ever forum of its type, on the key challenges facing the global nursing community. DESIGN: Identification of short- and long-term outcomes through descriptive review of immediate post-conference evaluations and follow-up questionnaires sent out 13 months later to nursing leaders in the participating countries. METHODS: Content analysis of quantitative data from 61 immediate post-conference evaluations and 13 follow-up questionnaires, as well as qualitative data from participant comments on the evaluation forms and questionnaires. FINDINGS: Analysis indicated conference participants viewed the conference as a beneficial forum to collaboratively examine nursing workforce issues and trends, develop country-specific nursing action plans, establish and strengthen national and international partnerships, and build stronger international nursing bodies. CONCLUSION: The Global Nursing Partnerships Conference was an international success--addressing the unique challenges facing nursing leaders in developed and developing countries and the needs of nurses throughout the world.

The development, reliability, and validity of a clinical rating scale for codependency.

This investigation examined the reliability and validity of a rating scale for codependency in substance abuse treatment. The investigators developed an example-anchored rating scale to operationalize codependency as substance abuse counselors construe it in practice, and recruited 27 counselors for a counterbalanced multiple-treatment experiment. Counselors were randomly assigned to one of four continuing education workshops for rating-scale training, and asked to evaluate codependency in five videotaped cases. Semistructured case interviews were videotaped with a male and a female from five adult populations to vary the gender and codependency of cases: (1) outpatients in treatment for addiction, (2) outpatient spouses, (3) members of Codependents Anonymous, (4) United States Bureau of Land Management smoke jumpers, and (5) college students majoring in business or economics. To control for gender effects, one workshop presented male cases, one workshop presented female cases, and two workshops presented cases of both genders. To control for order effects, the assignment of videotapes to workshops was randomized to counterbalance the order in which counselors viewed them. The findings suggest that the rating scale yields reliable and valid evaluations of codependency without appreciable gender bias.

Enacting narrative pedagogy. The lived experiences of students and teachers.

Reforming nursing education to meet contemporary challenges in educational and clinical environments is needed through the development and implementation of new pedagogies. Nancy Diekelmann is advancing the science of nursing education by describing a new phenomenological pedagogy, Narrative Pedagogy, identified through interpretive research in nursing education. Narrative Pedagogy is an approach to reforming nursing education that is always site specific and not generalizable from school to school. However, the processes of Narrative Pedagogy are transferable and can be enacted in many contexts. This study describes the common experiences and shared meanings of teachers and students engaging in or enacting Narrative Pedagogy. Diekelmann gathered seven teachers and students in five schools of nursing in four midwestern states to share their experiences. Interpretive phenomenology was used to analyze the group interview. One of the findings identified during this analysis, Enacting Narrative Pedagogy, is explicated, and two themes, Decentering Skill Acquisition and Content and Attending to the Practices of Thinking, are described.

Maintenance of the long-term effectiveness of tramadol in treatment of the pain of diabetic neuropathy.

OBJECTIVE: The objective of this study was to evaluate the efficacy and safety of tramadol in a 6-month open extension following a 6-week double-blind randomized trial. RESEARCH DESIGN AND METHODS: Patients with painful diabetic neuropathy who completed the double-blind study were eligible for enrollment in an open extension of up to 6 months. All patients received tramadol 50-400 mg/day. Self-administered pain intensity scores (scale 0-4; none to extreme pain) and pain relief scores (scale -1-4; worse to complete relief) were recorded the first day of the open extension (last day of the double-blind phase) and at 30, 90, and 180 days. RESULTS: A total of 117 patients (56 former tramadol and 61 former placebo) entered the study. On the first day of the study, patients formerly treated with placebo had a significantly higher mean pain intensity score (2. 2+/-1.02 vs. 1.4+/-0.93, P<0.001) and a lower pain relief score (0. 9+/-1.43 vs. 2.2+/-1.27, P<0.001) than former tramadol patients. By Day 90, both groups had mean pain intensity scores of 1.4, which were maintained throughout the study. Mean pain relief scores (2. 4+/-1.09 vs. 2.2+/-1.14) were similar after 30 days in the former placebo and former tramadol groups, respectively and were maintained for the duration of the study. Four patients discontinued therapy due to ineffective pain relief; 13 patients discontinued due to adverse events. The most common adverse events were constipation, nausea, and headache. CONCLUSIONS: Tramadol provides long-term relief of the pain of diabetic neuropathy.

Current perception threshold: an adjunctive test for detection of acquired demyelinating polyneuropathies.

Current Perception Threshold (CPT) evaluation quantifies the sensory threshold to transcutaneous electrical stimulation of three sensory fiber subtypes: A-beta (2,000 Hz), A-delta (250 Hz) and C fibers (5 Hz). Demyelinating polyneuropathies tend to affect larger myelinated fibers before smaller unmyelinated fibers, and they usually begin at the proximal nerve roots or terminal axons, due to relative weakness of the blood-nerve barrier in these locations. Axonal polyneuropathies tend to affect smaller fibers before larger fibers, in a distal to proximal gradient. Ten patients with demyelinating polyneuropathy and ten patients with axonal polyneuropathy underwent CPT testing. CPT comparisons were made with regard to side-to-side asymmetries, fiber type involvement, and the ratio of fiber types involved. The C2, lateral antebrachial cutaneous, and sural distributions were examined bilaterally. Demyelinating polyneuropathies were detected with 50% sensitivity and 100% specificity. This diagnostic sensitivity is similar to that of published criteria based upon motor nerve conduction. CPT testing can distinguish demyelinating from axonal polyneuropathies. It may be particularly helpful in patients with predominantly sensory symptoms in whom EMG/NCS data may be equivocal, or in patients who decline EMG/NCS studies.

Toward a narrative-centered curriculum for nurse practitioners.

This paper discusses various alternative and nontraditional teaching strategies currently used in nurse practitioner curricula. These instructional strategies include case-study analysis (Ryan-Wenger & Lee, 1997) and problem-based learning/practice-based learning (Barrows, 1994). We suggest a further evolution, using principles and practices of a narrative pedagogy (Diekelmann, 1995) to allow convergence of these several narratively-focused inductive and interpretive approaches. This combination of ways of learning has led us toward a narrative-centered curriculum for family nurse practitioners (FNPs). Specific ways to use narrative in the FNP curriculum are presented to demonstrate how to take the curriculum beyond traditional ways of teaching and learning.

Right frontal lobe slow frequency repetitive transcranial magnetic stimulation (SF r-TMS) is an effective treatment for depression: a case-control pilot study of safety and efficacy.

Major depression may result from decreased left frontal lobe function with respect to the right. Fast frequency repetitive transcranial magnetic stimulation (FF r-TMS) excites the underlying cortex whereas slow frequency repetitive transcranial magnetic stimulation (SF r-TMS) causes cortical inhibition. Left frontal FF r-TMS attenuates major depression whereas the inhibitory effects of right frontal SF r-TMS are unknown. This study tested the hypothesis that right frontal SF r-TMS would treat depressed patients with minimal effect on controls. A psychiatrist administered the Beck depression inventory and Hamilton D depression rating scales to eight depressed patients and six controls before and after the treatment protocol. Eight sessions of 100 right frontal lobe SF r-TMS were given at motor threshold and 0.5 Hz over a 6 week period. No adverse outcomes were noted in either group. A significant antidepressant effect was noted in depressed patients on the Beck and Hamilton D depression rating scales (p<0.05). No change on either scale was noted in the controls. In conclusion right frontal lobe SF r-TMS is a safe, non-invasive treatment for major depression that deserves further investigation.