Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo

<p>Abstract</p> <p>Background</p> <p>Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tracking the expression of individual <it>C. elegans </it>genes was developed that collects image samples of a developing embryo by 3-D time lapse microscopy. In this protocol, a program called StarryNite performs the automatic recognition of fluorescently labeled cells and traces their lineage. However, due to the amount of noise present in the data and due to the challenges introduced by increasing number of cells in later stages of development, this program is not error free. In the current version, the error correction (<it>i.e</it>., editing) is performed manually using a graphical interface tool named AceTree, which is specifically developed for this task. For a single experiment, this manual annotation task takes several hours.</p> <p>Results</p> <p>In this paper, we reduce the time required to correct errors made by StarryNite. We target one of the most frequent error types (movements annotated as divisions) and train a support vector machine (SVM) classifier to decide whether a division call made by StarryNite is correct or not. We show, via cross-validation experiments on several benchmark data sets, that the SVM successfully identifies this type of error significantly. A new version of StarryNite that includes the trained SVM classifier is available at <url>http://starrynite.sourceforge.net</url>.</p> <p>Conclusions</p> <p>We demonstrate the utility of a machine learning approach to error annotation for StarryNite. In the process, we also provide some general methodologies for developing and validating a classifier with respect to a given pattern recognition task.</p

A One Health Framework for the Evaluation of Rabies Control Programmes: A Case Study from Colombo City, Sri Lanka

<div><p>Background</p><p>One Health addresses complex challenges to promote the health of all species and the environment by integrating relevant sciences at systems level. Its application to zoonotic diseases is recommended, but few coherent frameworks exist that combine approaches from multiple disciplines. Rabies requires an interdisciplinary approach for effective and efficient management.</p><p>Methodology/Principal Findings</p><p>A framework is proposed to assess the value of rabies interventions holistically. The economic assessment compares additional monetary and non-monetary costs and benefits of an intervention taking into account epidemiological, animal welfare, societal impact and cost data. It is complemented by an ethical assessment. The framework is applied to Colombo City, Sri Lanka, where modified dog rabies intervention measures were implemented in 2007. The two options included for analysis were the control measures in place until 2006 (“baseline scenario”) and the new comprehensive intervention measures (“intervention”) for a four-year duration. Differences in control cost; monetary human health costs after exposure; Disability-Adjusted Life Years (DALYs) lost due to human rabies deaths and the psychological burden following a bite; negative impact on animal welfare; epidemiological indicators; social acceptance of dogs; and ethical considerations were estimated using a mixed method approach including primary and secondary data. Over the four years analysed, the intervention cost US $1.03 million more than the baseline scenario in 2011 prices (adjusted for inflation) and caused a reduction in dog rabies cases; 738 DALYs averted; an increase in acceptability among non-dog owners; a perception of positive changes in society including a decrease in the number of roaming dogs; and a net reduction in the impact on animal welfare from intermediate-high to low-intermediate.</p><p>Conclusions</p><p>The findings illustrate the multiple outcomes relevant to stakeholders and allow greater understanding of the value of the implemented rabies control measures, thereby providing a solid foundation for informed decision-making and sustainable control.</p></div

Estimating the Under-Five Mortality Rate Using a Bayesian Hierarchical Time Series Model

Background: Millennium Development Goal 4 calls for a reduction in the under-five mortality rate by two-thirds between 1990 and 2015, which corresponds to an annual rate of decline of 4.4%. The United Nations Inter-Agency Group for Child Mortality Estimation estimates under-five mortality in every country to measure progress. For the majority of countries, the estimates within a country are based on the assumption of a piece-wise constant rate of decline. Methods and Findings: This paper proposes an alternative method to estimate under-five mortality, such that the underlying rate of change is allowed to vary smoothly over time using a time series model. Information about the average rate of decline and changes therein is exchanged between countries using a Bayesian hierarchical model. Cross-validation exercises suggest that the proposed model provides credible bounds for the under-five mortality rate that are reasonably well calibrated during the observation period. The alternative estimates suggest smoother trends in under-five mortality and give new insights into changes in the rate of decline within countries. Conclusions: The proposed model offers an alternative modeling approach for obtaining estimates of under-five mortality which removes the restriction of a piece-wise linear rate of decline and introduces hierarchy to exchange information between countries. The newly proposed estimates of the rate of decline in under-5 mortality and the uncertaint

A post-labeling method for multiplexed and multicolored genotyping analysis of SSR, indel and SNP markers in single tube with bar-coded split tag (BStag)

<p>Abstract</p> <p>Background</p> <p>Genotyping analysis using capillary DNA sequencing with fluorescently labeled primer pairs obtained by polymerase chain reaction (PCR) is widely used, but is expensive. The post-PCR labeling method using fluorescently labeled short oligonucleotides and nested PCR of the amplified product obtained from unlabeled primer pairs is a simple and inexpensive alternative. However, previously reported protocols often produced spurious peaks or inconsistent amplification under multiplexed analysis as a result of simultaneous progress of both the amplification and labeling reactions and local homology of the attached tag sequence.</p> <p>Results</p> <p>A set of 16 bp-long oligonucleotide sequences termed bar-coded split tag (BStag), comprising a common basal region, a three-nucleotide 'bar-code' sequence, and a mismatched nucleotide at the middle position were designed for selective post-PCR labeling. The BStag was attached at the 5' end of the forward primer of interest. The melting temperature of the BStag was low enough to separate the labeling reaction from initial PCR amplification, and each sequence was minimally divergent but maintained maximum selectivity. Post-PCR labeling of the amplified product was achieved by extending for three cycles at a lower annealing temperature after the conventional amplification program with the appropriate fluorescently labeled BStag primer. No amplification was confirmed with BStag primers for 12 plant species. The electropherogram of the labeled product obtained using this method was consistent with that of prelabeled primer, except for their apparent size.</p> <p>Conclusions</p> <p>BStag enabled multiplexed post-PCR labeling of simple sequence repeat or insertion/deletion markers with different dyes in a single tube. BStag in conjunction with locus specific oligo and allele specific oligo was also useful for single nucleotide polymorphism analysis. The labeling protocol was simple and no additional operation was required. Single-tube multiplexed post-PCR labeling is useful for a wide variety of genotyping studies with maximal flexibility and minimal costs.</p

Dusty Planetary Systems

Extensive photometric stellar surveys show that many main sequence stars show emission at infrared and longer wavelengths that is in excess of the stellar photosphere; this emission is thought to arise from circumstellar dust. The presence of dust disks is confirmed by spatially resolved imaging at infrared to millimeter wavelengths (tracing the dust thermal emission), and at optical to near infrared wavelengths (tracing the dust scattered light). Because the expected lifetime of these dust particles is much shorter than the age of the stars (>10 Myr), it is inferred that this solid material not primordial, i.e. the remaining from the placental cloud of gas and dust where the star was born, but instead is replenished by dust-producing planetesimals. These planetesimals are analogous to the asteroids, comets and Kuiper Belt objects (KBOs) in our Solar system that produce the interplanetary dust that gives rise to the zodiacal light (tracing the inner component of the Solar system debris disk). The presence of these "debris disks" around stars with a wide range of masses, luminosities, and metallicities, with and without binary companions, is evidence that planetesimal formation is a robust process that can take place under a wide range of conditions. This chapter is divided in two parts. Part I discusses how the study of the Solar system debris disk and the study of debris disks around other stars can help us learn about the formation, evolution and diversity of planetary systems by shedding light on the frequency and timing of planetesimal formation, the location and physical properties of the planetesimals, the presence of long-period planets, and the dynamical and collisional evolution of the system. Part II reviews the physical processes that affect dust particles in the gas-free environment of a debris disk and their effect on the dust particle size and spatial distribution.Comment: 68 pages, 25 figures. To be published in "Solar and Planetary Systems" (P. Kalas and L. French, Eds.), Volume 3 of the series "Planets, Stars and Stellar Systems" (T.D. Oswalt, Editor-in-chief), Springer 201

Whether to report diabetes as the underlying cause-of-death? a survey of internists of different sub-specialties

<p>Abstract</p> <p>Background</p> <p>Cause-specific mortality is a commonly used endpoint of clinical trials or prospective studies. However, it is sometimes difficult for physician to determine the underlying-cause-of-death (UCD), especially for diabetic patients coexisted with cardiovascular diseases (CVD). The aim of this survey was to examine whether internists with different specialties have different opinions on the reporting of diabetes as the UCD.</p> <p>Methods</p> <p>A total of 549 physicians completed the questionnaire in Taiwan, which comprised seven hypothetical case scenarios, each indicating a different level of contribution of diabetes in initiating the chain of events leading to death.</p> <p>Results</p> <p>As a whole, endocrinologists were more likely than cardiologists and nephrologists to report diabetes as the UCD. The differences were more prominent when the diabetic patient had a coexisting CVD. In scenario 3 (a diabetic patient with hypertension who died from acute myocardial infarction), the percentage was 56% in endocrinologists, which was significantly higher than in cardiologists (42%) and nephrologists (41%). In scenario 4 (a diabetic patient with hypertension who died from cerebrovascular infarction), the percentage was 45% in endocrinologists, and only 31% in cardiologists and 36% in nephrologists.</p> <p>Conclusions</p> <p>Internists of different sub-specialties do have different opinions on the reporting of diabetes as the UCD, especially when the diabetic patient has a coexisting CVD.</p

Mechanical Systems with Symmetry, Variational Principles, and Integration Algorithms

This paper studies variational principles for mechanical systems with symmetry and their applications to integration algorithms. We recall some general features of how to reduce variational principles in the presence of a symmetry group along with general features of integration algorithms for mechanical systems. Then we describe some integration algorithms based directly on variational principles using a discretization technique of Veselov. The general idea for these variational integrators is to directly discretize Hamilton’s principle rather than the equations of motion in a way that preserves the original systems invariants, notably the symplectic form and, via a discrete version of Noether’s theorem, the momentum map. The resulting mechanical integrators are second-order accurate, implicit, symplectic-momentum algorithms. We apply these integrators to the rigid body and the double spherical pendulum to show that the techniques are competitive with existing integrators

Modulation of the virus-receptor interaction by mutations in the V5 loop of feline immunodeficiency virus (FIV) following in vivo escape from neutralising antibody

&lt;b&gt;BACKGROUND:&lt;/b&gt; In the acute phase of infection with feline immunodeficiency virus (FIV), the virus targets activated CD4+ T cells by utilising CD134 (OX40) as a primary attachment receptor and CXCR4 as a co-receptor. The nature of the virus-receptor interaction varies between isolates; strains such as GL8 and CPGammer recognise a "complex" determinant on CD134 formed by cysteine-rich domains (CRDs) 1 and 2 of the molecule while strains such as PPR and B2542 require a more "simple" determinant comprising CRD1 only for infection. These differences in receptor recognition manifest as variations in sensitivity to receptor antagonists. In this study, we ask whether the nature of the virus-receptor interaction evolves in vivo.&lt;p&gt;&lt;/p&gt; &lt;b&gt;RESULTS:&lt;/b&gt; Following infection with a homogeneous viral population derived from a pathogenic molecular clone, a quasispecies emerged comprising variants with distinct sensitivities to neutralising antibody and displaying evidence of conversion from a "complex" to a "simple" interaction with CD134. Escape from neutralising antibody was mediated primarily by length and sequence polymorphisms in the V5 region of Env, and these alterations in V5 modulated the virus-receptor interaction as indicated by altered sensitivities to antagonism by both anti-CD134 antibody and soluble CD134.&lt;p&gt;&lt;/p&gt; &lt;b&gt;CONCLUSIONS:&lt;/b&gt; The FIV-receptor interaction evolves under the selective pressure of the host humoral immune response, and the V5 loop contributes to the virus-receptor interaction. Our data are consistent with a model whereby viruses with distinct biological properties are present in early versus late infection and with a shift from a "complex" to a "simple" interaction with CD134 with time post-infection.&lt;p&gt;&lt;/p&gt

A genome-wide association study identifies protein quantitative trait loci (pQTLs)

There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10 -57), CCL4L1 (p = 3.9×10-21), IL18 (p = 6.8×10-13), LPA (p = 4.4×10-10), GGT1 (p = 1.5×10-7), SHBG (p = 3.1×10-7), CRP (p = 6.4×10-6) and IL1RN (p = 7.3×10-6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10-40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. © 2008 Melzer et al

Measuring Under-Five Mortality: Validation of New Low-Cost Methods

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