Estimation of Mortalities

If a linear regression is fit to log-transformed mortalities and the estimate is back-transformed according to the formula Ee^Y = e^{\mu + \sigma^2/2} a systematic bias occurs unless the error distribution is normal and the scale estimate is gauged to normal variance. This result is a consequence of the uniqueness theorem for the Laplace transform. We determine the systematic bias of minimum-L_2 and minimum-L_1 estimation with sample variance and interquartile range of the residuals as scale estimates under a uniform and four contaminated normal error distributions. Already under innocent looking contaminations the true mortalities may be underestimated by 50% in the long run. Moreover, the logarithmic transformation introduces an instability into the model that results in a large discrepancy between rg_Huber estimates as the tuning constant regulating the degree of robustness varies. Contrary to the logarithm the square root stabilizes variance, diminishes the influence of outliers, automatically copes with observed zeros, allows the `nonparametric' back-transformation formula E Y^2 = \mue^2 + \sigma^2, and in the homoskedastic case avoids a systematic bias of minimum-L_2 estimation with sample variance. For the company-specific table 3 of [Loeb94], in the age range of 20-65 years, we fit a parabola to root mortalities by minimum-L_2 , minimum-L_1, and robust rg_Huber regression estimates, and a cubic and exponential by least squares. The fits thus obtained in the original model are excellent and practically indistinguishable by a \chi^2 goodness-of-fit test. Finally , dispensing with the transformation of observations, we employ a Poisson generalized linear model and fit an exponential and a cubic by maximum likelihood

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

Discourses of student orientation to medical education programs

Background: Although medical students’ initial orientation is an important point of transition in medical education, there is a paucity of literature on the subject and major variations in the ways that different institutions orient incoming medical students to their programs. Methods: We conducted a discourse analysis of medical education orientation in the literature and on data from a survey of peer institutions’ approaches to orientation. Results: These two discourses of orientation had clear similarities, in particular, the critical role of ceremony and symbols, and the focus on developing professionalism and physician identities. There were also differences between them, in particular, in the way that the discourse in the literature focused on the symbolic and professional aspects of orientation; something we have called ‘cultural orientation’. Meanwhile, those who were responsible for orientation in their own institutions tended to focus on the practical and social dimensions. Conclusion: By examining how orientation has been described and discussed, we identify three domains of orientation: cultural, social, and practical. These domains are relatively distinct in terms of the activities associated with them, and in terms of who is involved in organizing and running these activities. We also describe orientation as a liminal activity system on the threshold of medical school where incoming students initially cross into the profession. Interestingly, this state of ambiguity also extends to the scholarship of orientation with only some of its aspects attracting formal enquiry, even though there is a growing interest in transitions in medical education as a whole. We hope, therefore, that this study can help to legitimize enquiry into orientation in all its forms and that it can begin to situate the role of orientation more firmly within the firmament of medical education practice and research

Analyzing ChIP-chip Data Using Bioconductor

Analyzing ChIP-chip Data Using Bioconducto

Designed Azolopyridinium Salts Block Protective Antigen Pores In Vitro and Protect Cells from Anthrax Toxin

Background:Several intracellular acting bacterial protein toxins of the AB-type, which are known to enter cells by endocytosis, are shown to produce channels. This holds true for protective antigen (PA), the binding component of the tripartite anthrax-toxin of Bacillus anthracis. Evidence has been presented that translocation of the enzymatic components of anthrax-toxin across the endosomal membrane of target cells and channel formation by the heptameric/octameric PA63 binding/translocation component are related phenomena. Chloroquine and some 4-aminoquinolones, known as potent drugs against Plasmodium falciparium infection of humans, block efficiently the PA63-channel in a dose dependent way.Methodology/Principal Findings:Here we demonstrate that related positively charged heterocyclic azolopyridinium salts block the PA63-channel in the μM range, when both, inhibitor and PA63 are added to the same side of the membrane, the cis-side, which corresponds to the lumen of acidified endosomal vesicles of target cells. Noise-analysis allowed the study of the kinetics of the plug formation by the heterocycles. In vivo experiments using J774A.1 macrophages demonstrated that the inhibitors of PA63-channel function also efficiently block intoxication of the cells by the combination lethal factor and PA63 in the same concentration range as they block the channels in vitro.Conclusions/Significance:These results strongly argue in favor of a transport of lethal factor through the PA63-channel and suggest that the heterocycles used in this study could represent attractive candidates for development of novel therapeutic strategies against anthrax. © 2013 Beitzinger et al

NeuriteQuant: An open source toolkit for high content screens of neuronal Morphogenesis

<p>Abstract</p> <p>Background</p> <p>To date, some of the most useful and physiologically relevant neuronal cell culture systems, such as high density co-cultures of astrocytes and primary hippocampal neurons, or differentiated stem cell-derived cultures, are characterized by high cell density and partially overlapping cellular structures. Efficient analytical strategies are required to enable rapid, reliable, quantitative analysis of neuronal morphology in these valuable model systems.</p> <p>Results</p> <p>Here we present the development and validation of a novel bioinformatics pipeline called NeuriteQuant. This tool enables fully automated morphological analysis of large-scale image data from neuronal cultures or brain sections that display a high degree of complexity and overlap of neuronal outgrowths. It also provides an efficient web-based tool to review and evaluate the analysis process. In addition to its built-in functionality, NeuriteQuant can be readily extended based on the rich toolset offered by ImageJ and its associated community of developers. As proof of concept we performed automated screens for modulators of neuronal development in cultures of primary neurons and neuronally differentiated P19 stem cells, which demonstrated specific dose-dependent effects on neuronal morphology.</p> <p>Conclusions</p> <p>NeuriteQuant is a freely available open-source tool for the automated analysis and effective review of large-scale high-content screens. It is especially well suited to quantify the effect of experimental manipulations on physiologically relevant neuronal cultures or brain sections that display a high degree of complexity and overlap among neurites or other cellular structures.</p

The effects of quercetin on SW480 human colon carcinoma cells: a proteomic study

BACKGROUND: High fruit and vegetable intake is known to reduce the risk of colon cancer. To improve understanding of this phenomenon the action of different phytochemicals on colon cells has been examined. One such compound is quercetin that belongs to the group known as flavonoids. The purpose of this study was to determine the influence of quercetin on the proteome of the SW480 human colon adenocarcinoma cell line, specifically to identify proteins that could be the molecular targets of quercetin in its amelioration of the progression of colon cancer. To this end, two-dimensional gel electrophoresis and mass spectrometry were used to identify proteins that underwent a change in expression following treatment of the cells with 20 μM quercetin. This could elucidate how quercetin may reduce the progression of colon cancer. RESULTS: Quercetin treatment of the SW480 human colon cancer cells was found to result in the decreased expression of three proteins and the increased expression of one protein. The identified proteins with decreased expression were type II cytoskeletal 8 keratin and NADH dehydrogenase Fe-S protein 3. The other protein with decreased expression was not identified. The protein with increased expression belonged to the annexin family. CONCLUSION: Several proteins were determined to have altered expression following treatment with quercetin. Such changes in the levels of these particular proteins could underlie the chemo-protective action of quercetin towards colon cancer

The Emergence and Early Evolution of Biological Carbon-Fixation

The fixation of into living matter sustains all life on Earth, and embeds the biosphere within geochemistry. The six known chemical pathways used by extant organisms for this function are recognized to have overlaps, but their evolution is incompletely understood. Here we reconstruct the complete early evolutionary history of biological carbon-fixation, relating all modern pathways to a single ancestral form. We find that innovations in carbon-fixation were the foundation for most major early divergences in the tree of life. These findings are based on a novel method that fully integrates metabolic and phylogenetic constraints. Comparing gene-profiles across the metabolic cores of deep-branching organisms and requiring that they are capable of synthesizing all their biomass components leads to the surprising conclusion that the most common form for deep-branching autotrophic carbon-fixation combines two disconnected sub-networks, each supplying carbon to distinct biomass components. One of these is a linear folate-based pathway of reduction previously only recognized as a fixation route in the complete Wood-Ljungdahl pathway, but which more generally may exclude the final step of synthesizing acetyl-CoA. Using metabolic constraints we then reconstruct a “phylometabolic” tree with a high degree of parsimony that traces the evolution of complete carbon-fixation pathways, and has a clear structure down to the root. This tree requires few instances of lateral gene transfer or convergence, and instead suggests a simple evolutionary dynamic in which all divergences have primary environmental causes. Energy optimization and oxygen toxicity are the two strongest forces of selection. The root of this tree combines the reductive citric acid cycle and the Wood-Ljungdahl pathway into a single connected network. This linked network lacks the selective optimization of modern fixation pathways but its redundancy leads to a more robust topology, making it more plausible than any modern pathway as a primitive universal ancestral form

The Effects of Biting and Pulling on the Forces Generated during Feeding in the Komodo Dragon (Varanus komodoensis)

In addition to biting, it has been speculated that the forces resulting from pulling on food items may also contribute to feeding success in carnivorous vertebrates. We present an in vivo analysis of both bite and pulling forces in Varanus komodoensis, the Komodo dragon, to determine how they contribute to feeding behavior. Observations of cranial modeling and behavior suggest that V. komodoensis feeds using bite force supplemented by pulling in the caudal/ventrocaudal direction. We tested these observations using force gauges/transducers to measure biting and pulling forces. Maximum bite force correlates with both body mass and total body length, likely due to increased muscle mass. Individuals showed consistent behaviors when biting, including the typical medial-caudal head rotation. Pull force correlates best with total body length, longer limbs and larger postcranial motions. None of these forces correlated well with head dimensions. When pulling, V. komodoensis use neck and limb movements that are associated with increased caudal and ventral oriented force. Measured bite force in Varanus komodoensis is similar to several previous estimations based on 3D models, but is low for its body mass relative to other vertebrates. Pull force, especially in the ventrocaudal direction, would allow individuals to hunt and deflesh with high success without the need of strong jaw adductors. In future studies, pull forces need to be considered for a complete understanding of vertebrate carnivore feeding dynamics

The genetic architecture of the MHC class II region in British Texel sheep

Understanding the structure of the major histocompatibility complex, especially the number and frequency of alleles, loci and haplotypes, is crucial for efficient investigation of the way in which the MHC influences susceptibility to disease. Nematode infection is one of the most important diseases suffered by sheep, and the class II region has been repeatedly associated with differences in susceptibility and resistance to infection. Texel sheep are widely used in many different countries and are relatively resistant to infection. This study determined the number and frequency of MHC class II genes in a small flock of Texel sheep. There were 18 alleles at DRB1, 9 alleles at DQA1, 13 alleles at DQB1, 8 alleles at DQA2 and 16 alleles at DQB2. Several haplotypes had no detectable gene products at DQA1, DQB1 or DQB2, and these were defined as null alleles. Despite the large numbers of alleles, there were only 21 distinct haplotypes in the population. The relatively small number of observed haplotypes will simplify finding disease associations because common haplotypes provide more statistical power but complicate the discrimination of causative mutations from linked marker loci