Assessment of transcript reconstruction methods for RNA-seq.

We evaluated 25 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression-level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete transcript components with high success rates but that assembly of complete isoform structures poses a major challenge even when all constituent elements are identified. Expression-level estimates also varied widely across methods, even when based on similar transcript models. Consequently, the complexity of higher eukaryotic genomes imposes severe limitations on transcript recall and splice product discrimination that are likely to remain limiting factors for the analysis of current-generation RNA-seq data.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.

Causal explanations and scientific realism in particle physics

Particle physics studies highly complex processes which cannot be directly observed. Scientific realism claims that we are nevertheless warranted in believing that these processes really occur and that the objects involved in them really exist. This dissertation defends a version of scientific realism, called causal realism, in the context of particle physics. I start by introducing the central theses and arguments in the recent philosophical debate on scientific realism (chapter 1), with a special focus on an important presupposition of the debate, namely common sense realism. Chapter 2 then discusses entity realism, which introduces a crucial element into the debate by emphasizing the importance of experiments in defending scientific realism. Most of the chapter is concerned with Ian Hacking's position, but I also argue that Nancy Cartwright's version of entity realism is ultimately preferable as a basis for further development. In chapter 3,1 take a step back and consider the question whether the realism debate is worth pursuing at all. Arthur Fine has given a negative answer to that question, proposing his natural ontologica! attitude as an alternative to both realism and antirealism. I argue that the debate (in particular the realist side of it) is in fact less vicious than Fine presents it. The second part of my work (chapters 4-6) develops, illustrates and defends causal realism. The key idea is that inference to the best explanation is reliable in some cases, but not in others. Chapter 4 characterizes the difference between these two kinds of cases in terms of three criteria which distinguish causal from theoretical warrant. In order to flesh out this distinction, chapter 5 then applies it to a concrete case from the history of particle physics, the discovery of the neutrino. This case study shows that the distinction between causal and theoretical warrant is crucial for understanding what it means to "directly detect" a new particle. But the distinction is also an effective tool against what I take to be the presently most powerful objection to scientific realism: Kyle Stanford's argument from unconceived alternatives. I respond to this argument in chapter 6, and I illustrate my response with a discussion of Jean Perrin's experimental work concerning the atomic hypothesis. In the final part of the dissertation, I turn to the specific challenges posed to realism by quantum theories. One of these challenges comes from the experimental violations of Bell's inequalities, which indicate a failure of locality in the quantum domain. I show in chapter 7 how causal realism can further our understanding of quantum non-locality by taking account of some recent experimental results. Another challenge to realism in quantum mechanics comes from delayed-choice experiments, which seem to imply that certain aspects of what happens in an experiment can be influenced by later choices of the experimenter. Chapter 8 analyzes these experiments and argues that they do not warrant the antirealist conclusions which some commentators draw from them. It pays particular attention to the case of delayed-choice entanglement swapping and the corresponding question whether entanglement is a real physical relation. In chapter 9,1 finally address relativistic quantum theories. It is often claimed that these theories are incompatible with a particle ontology, and this calls into question causal realism's commitment to localizable and countable entities. I defend the commitments of causal realism against these objections, and I conclude with some remarks connecting the interpretation of quantum field theory to more general metaphysical issues confronting causal realism.

Wear of two artificial tooth materials in vivo: a 12-month pilot study.

STATEMENT OF PROBLEM: Wear of methacrylate artificial teeth resulting in vertical loss is a problem for both dentists and patients. PURPOSE: The purpose of this study was to quantify wear of artificial teeth in vivo and to relate it to subject and tooth variables. MATERIAL AND METHODS: Twenty-eight subjects treated with complete dentures received 2 artificial tooth materials (polymethyl methacrylate (PMMA)/double-cross linked PMMA fillers; 35%/59% (SR Antaris DCL, SR Postaris DCL); experimental 48%/46%). At baseline and after 12 months, impressions of the dentures were poured with improved stone. After laser scanning, the casts were superimposed and matched. Maximal vertical loss (mm) and volumetric loss (mm(3)) were calculated for each tooth and log-transformed to reduce variability. Volumetric loss was related to the occlusally active surface area. Linear mixed models were used to study the influence of the factors jaw, tooth, and material on adjusted (residual) wear values (alpha=.05). RESULTS: Due to drop outs (n=5) and unmatchable casts (n=3), 69% of all teeth were analyzed. Volumetric loss had a strong linear relationship to surface area (P<.001); this was less pronounced for vertical loss (P=.004). The factor showing the highest influence was the subject. Wear was tooth dependent (increasing from incisors to molars). However, these differences diminished once the wear rates were adjusted for occlusal area, and only a few remained significant (anterior versus posterior maxillary teeth). Another influencing factor was the age of the subject. CONCLUSIONS: Clinical wear of artificial teeth is higher than previously measured or expected. The presented method of analyzing wear of artificial teeth using a laser-scanning device seemed suitable.

Rapid affinity purification of erythropoietin from biological samples using disposable monoliths.

Identification of post-translational modifications of proteins in biological samples often requires access to preanalytical purification and concentration methods. In the purification step high or low molecular weight substances can be removed by size exclusion filters, and high abundant proteins can be removed, or low abundant proteins can be enriched, by specific capturing tools. In this paper is described the experience and results obtained with a recently emerged and easy-to-use affinity purification kit for enrichment of the low amounts of EPO found in urine and plasma specimens. The kit can be used as a pre-step in the EPO doping control procedure, as an alternative to the commonly used ultrafiltration, for detecting aberrantly glycosylated isoforms. The commercially available affinity purification kit contains small disposable anti-EPO monolith columns (6 ?L volume, Ø7 mm, length 0.15 mm) together with all required buffers. A 24-channel vacuum manifold was used for simultaneous processing of samples. The column concentrated EPO from 20 mL urine down to 55 ?L eluate with a concentration factor of 240 times, while roughly 99.7% of non-relevant urine proteins were removed. The recoveries of Neorecormon (epoetin beta), and the EPO analogues Aranesp and Mircera applied to buffer were high, 76%, 67% and 57%, respectively. The recovery of endogenous EPO from human urine was 65%. High recoveries were also obtained when purifying human, mouse and equine EPO from serum, and human EPO from cerebrospinal fluid. Evaluation with the accredited EPO doping control method based on isoelectric focusing (IEF) showed that the affinity purification procedure did not change the isoform distribution for rhEPO, Aranesp, Mircera or endogenous EPO. The kit should be particularly useful for applications in which it is essential to avoid carry-over effects, a problem commonly encountered with conventional particle-based affinity columns. The encouraging results with EPO propose that similar affinity monoliths, with the appropriate antibodies, should constitute useful tools for general applications in sample preparation, not only for doping control of EPO and other hormones such as growth hormone and insulin but also for the study of post-translational modifications of other low abundance proteins in biological and clinical research, and for sample preparation prior to in vitro diagnostics.

Use of flow cytometric methods for single-cell analysis in environmental microbiology

Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

The molecular basis of social behavior: models, methods and advances.

Elucidating the molecular and neural basis of complex social behaviors such as communal living, division of labor and warfare requires model organisms that exhibit these multi-faceted behavioral phenotypes. Social insects, such as ants, bees, wasps and termites, are attractive models to address this problem, with rich ecological and ethological foundations. However, their atypical systems of reproduction have hindered application of classical genetic approaches. In this review, we discuss how recent advances in social insect genomics, transcriptomics, and functional manipulations have enhanced our ability to observe and perturb gene expression, physiology and behavior in these species. Such developments begin to provide an integrated view of the molecular and cellular underpinnings of complex social behavior.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

Comparison of different methods for thin section EM analysis of Mycobacterium smegmatis.

Bacteria are generally difficult specimens to prepare for conventional resin section electron microscopy and mycobacteria, with their thick and complex cell envelope layers being especially prone to artefacts. Here we made a systematic comparison of different methods for preparing Mycobacterium smegmatis for thin section electron microscopy analysis. These methods were: (1) conventional preparation by fixatives and epoxy resins at ambient temperature. (2) Tokuyasu cryo-section of chemically fixed bacteria. (3) rapid freezing followed by freeze substitution and embedding in epoxy resin at room temperature or (4) combined with Lowicryl HM20 embedding and ultraviolet (UV) polymerization at low temperature and (5) CEMOVIS, or cryo electron microscopy of vitreous sections. The best preservation of bacteria was obtained with the cryo electron microscopy of vitreous sections method, as expected, especially with respect to the preservation of the cell envelope and lipid bodies. By comparison with cryo electron microscopy of vitreous sections both the conventional and Tokuyasu methods produced different, undesirable artefacts. The two different types of freeze-substitution protocols showed variable preservation of the cell envelope but gave acceptable preservation of the cytoplasm, but not lipid bodies, and bacterial DNA. In conclusion although cryo electron microscopy of vitreous sections must be considered the 'gold standard' among sectioning methods for electron microscopy, because it avoids solvents and stains, the use of optimally prepared freeze substitution also offers some advantages for ultrastructural analysis of bacteria.

Methods for integration site distribution analyses in animal cell genomes.

The question of where retroviral DNA becomes integrated in chromosomes is important for understanding (i) the mechanisms of viral growth, (ii) devising new anti-retroviral therapy, (iii) understanding how genomes evolve, and (iv) developing safer methods for gene therapy. With the completion of genome sequences for many organisms, it has become possible to study integration targeting by cloning and sequencing large numbers of host-virus DNA junctions, then mapping the host DNA segments back onto the genomic sequence. This allows statistical analysis of the distribution of integration sites relative to the myriad types of genomic features that are also being mapped onto the sequence scaffold. Here we present methods for recovering and analyzing integration site sequences.