Incomplete Labeling Research Articles

A fast marine sewage detection method for remote-sensing image

This paper presents an effective method for marine sewage detection from a remote-sensing image. It is inspired by the Grab-Cut mechanism that iterative estimation and incomplete labeling allow a considerably reduced degree of user interaction for a given quality of result. By establishing the relationship between the color feature and the object seeds, we first model object and background with Gaussian mixture model, respectively, followed by iteratively updating the parameter of model to decline the energy function. To improve the computation efficiency, we propose to extend the region of interest as background. The proposed method accounts for not only the effect of color feature, but also the geographical information. The experimental results demonstrate that the proposed method is more reliable in marine sewage detection compared to other state-of-the-art methods.

Peptidoglycan Compositional Analysis of Enterococcus faecalis Biofilm by Stable Isotope Labeling by Amino Acids in a Bacterial Culture.

Peptidoglycan (PG) is a major component of the cell wall in Enterococcus faecalis. Accurate analysis of PG composition provides crucial insights into the bacterium's cellular functions and responses to external stimuli, but this analysis remains challenging because of various chemical modifications to PG-repeat subunits. We characterized changes to the PG composition of E. faecalis grown as planktonic bacteria and biofilm by developing "stable isotope labeling by amino acids in bacterial culture" (SILAB), optimized for bacterial cultures with incomplete amino acid labeling. This comparative analysis by mass spectrometry was performed by labeling E. faecalis in biofilm with heavy Lys (l-[13C6,2D9,15N2]Lys) and planktonic bacteria with natural abundance l-Lys, then mixing equal amounts of bacteria from each condition, and performing cell wall isolation and mutanolysin digestion necessary for liquid chromatography and mass spectrometry. An analytical method was developed to determine muropeptide abundances using correction factors to compensate for incomplete heavy Lys isotopic enrichment (98.33 ± 0.05%) and incorporation (83.23 ± 1.16%). Forty-seven pairs of PG fragment ions from isolated cell walls of planktonic and biofilm samples were selected for SILAB analysis. We found that the PG in biofilm showed an increased level of PG cross-linking, an increased level of N-deacetylation of GlcNAc, a decreased level of O-acetylation of MurNAc, and an increased number of stem modifications by d,d- and l,d-carboxypeptidases.

Generative Adversarial Networks for Open Set Historical Chinese Character Recognition

Historical Chinese character recognition has been suffering from the problem of samples labeling, not only the problem of lacking sufficient labeled training samples, but also of sample classes. So the scenario for Historical Chinese character recognition is "open set" recognition, where incomplete labeling of sample classes is present at training time, and unknown classes can be submitted to the system during testing. This paper proposes a method for open set Historical Chinese Character Recognition. For open set recognition, the features available in the training data cannot effectively characterize different kinds of unknown classes. We assume that the features which characterize unknown classes can be derived or learned from other similar data sets. We utilize an auxiliary data set combined with the open set training data set to learn good features to represent historical Chinese characters. The auxiliary data set is translated using Generative Adversarial Networks (GAN) to make sure that the translated data set is as close to the historical Chinese character dataset as possible. Then we construct a neural network for features extraction. The neural network is trained using an alternative training method with the translated auxiliary dataset and incomplete labeled historical Chinese character data set. Last, features are extracted from certain layer of the trained neural network. Unknown samples are detected using statistical modelling of the Euclidean metric between samples. Experimental results show that the proposed method is effective.

Automatic Segmentation of Ultrasound Tomography Image.

Ultrasound tomography (UST) image segmentation is fundamental in breast density estimation, medicine response analysis, and anatomical change quantification. Existing methods are time consuming and require massive manual interaction. To address these issues, an automatic algorithm based on GrabCut (AUGC) is proposed in this paper. The presented method designs automated GrabCut initialization for incomplete labeling and is sped up with multicore parallel programming. To verify performance, AUGC is applied to segment thirty-two in vivo UST volumetric images. The performance of AUGC is validated with breast overlapping metrics (Dice coefficient (D), Jaccard (J), and False positive (FP)) and time cost (TC). Furthermore, AUGC is compared to other methods, including Confidence Connected Region Growing (CCRG), watershed, and Active Contour based Curve Delineation (ACCD). Experimental results indicate that AUGC achieves the highest accuracy (D = 0.9275 and J = 0.8660 and FP = 0.0077) and takes on average about 4 seconds to process a volumetric image. It was said that AUGC benefits large-scale studies by using UST images for breast cancer screening and pathological quantification.

Characterization of Metabolic Response to AG-348, an Allosteric Activator of Red Cell Pyruvate Kinase, in Healthy Volunteers and Pyruvate Kinase Deficiency Patients

Pyruvate kinase (PK) deficiency is a glycolytic enzymopathy that causes lifelong chronic hemolytic anemia. AG-348 is an allosteric activator of the red cell isoform of pyruvate kinase (PK-R) that is in clinical development to treat PK deficiency. Phase 1 studies of AG-348 in healthy volunteers (NCT02108106, NCT02149966) have been completed, and a phase 2 study in patients with PK deficiency is in progress (DRIVE PK, NCT02476916). We have previously reported that in the healthy volunteer studies, AG-348 induced changes in levels of the metabolites adenosine triphosphate (ATP) and 2,3-diphosphoglycerate (2,3-DPG) that are consistent with PK-R activation. A preliminary analysis of data showed that nine out of 18 DRIVE PK patients achieved a maximal increase in hemoglobin (Hb) levels of >1.0 g/dL.In this study, we characterize whole blood metabolism of healthy human subjects (from the multiple-ascending dose study NCT02149966) as well as PK-deficient patients (from DRIVE PK), before and after administration of AG-348, with a focus on the flux through the PK-R reaction. Whole blood taken from healthy subjects/DRIVE PK patients on each respective study was incubated with a stable isotope tracer, [U-13C6]-glucose. Glycolytic flux through PK-R was estimated by kinetic flux profiling based on the isotope labeling, as well as by the specific lactate production rate, with the two methods giving consistent results.Blood cells from healthy subjects exhibited classic red blood cell (RBC) metabolism, with the majority of glucose catabolized through glycolysis. AG-348 was shown to significantly increase the maximal PK-R protein activity in these subjects, and also to have metabolic effects consistent with PK-R activation, marked by decreased concentrations of glycolytic intermediates such as 2,3-DPG and phosphoenolpyruvate (PEP). Increases in ATP concentrations were also observed, with the magnitude and kinetics of the increase strongly suggesting enhanced adenosine salvage or synthesis. The overall glycolytic rates, however, did not change significantly after two weeks of AG-348 dosing, revealing the homeostatic regulation of RBC glycolysis in healthy blood.Five of the first 18 DRIVE PK patients underwent an extensive sampling protocol for metabolic analysis. This analysis revealed a number of distinct metabolic qualities in PK-deficient patients at baseline compared with healthy subjects. These included significantly reduced rates of lactate production and high concentrations of nucleotides, amino acids, and Krebs cycle intermediates. 13C labeling was observed in Krebs cycle intermediates, demonstrating significant respiratory metabolism in whole blood cells from PK-deficient patients, while incomplete labeling of glycolytic intermediates suggested the presence of a metabolically inactive cell subpopulation. These observations are most consistent with the hypothesis that PK-deficient whole blood is dominated metabolically by immature erythrocytes that retain residual mitochondrial activity.With AG-348 treatment, three of the five DRIVE PK patients had increases in Hb of >1.0 g/dL. In those three patients, we observed increased incorporation of 13C label into glycolytic intermediates such as 2,3-DPG, suggesting an increase in metabolically active erythrocytes. First order flux estimates based on either 2,3-DPG labeling kinetics or lactate production rates showed a >0.1 mmol/L/hr (>50%) increase in glycolytic flux. Neither of the two DRIVE PK patients that did not have an Hb increase of >1.0 g/dL showed significant metabolic changes.In conclusion, metabolic profiling and stable isotope tracing experiments in blood from healthy subjects treated with AG-348 revealed strong homeostatic regulation of glycolysis even in the presence of activated PK-R. Analysis of data from a small number (n=5) of PK-deficient patients treated with AG-348 for two weeks showed that the three patients with Hb increases >1.0 g/dL also had increased glycolytic flux. While the small number of patients makes these results preliminary, it is the first demonstration of a direct link between increased red cell glycolysis induced by the PK-R activator AG-348 and the resulting hematological response as assessed by increases in Hb levels. Updated analyses including additional patients will be presented as more data are collected in the ongoing study. DisclosuresChubukov:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Johnson:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Kosinski:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Clasquin:Agios Pharmaceuticals, Inc.: Other: former employee and stock holder; Pfizer, Inc.: Employment. Jha:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Kim:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Roddy:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Merica:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Barbier:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Dang:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Silverman:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership. Kung:Agios Pharmaceuticals, Inc.: Employment, Equity Ownership.

Confocal Imaging and Tissue-Specific Fluorescent Probes for Real-Time In Vivo Immunohistochemistry. Proof of the Concept in a Gastric Lymph Node Metastasis Model.

Tumor-specific fluorescent antibodies, which can be recognized at a cellular or tissue level using optical imaging such as confocal laser endomicroscopy (CLE), could provide a means for rapid and accurate tumor diagnosis and staging. The aim of this study was to evaluate the ability of CLE to detect the presence of tagged cells within lymph nodes in an original simulated metastatic model. A solution of indocyanine green containing a suspension of porcine hepatocytes, marked with carboxy-fluorescein-succinimidyl-ester (CFSE), was injected endoscopically in the gastric submucosa of 10 pigs. Fluorescence lymphography using a near-infrared laparoscope was used to identify sentinel and secondary drainage nodes. Additionally, a nonfluorescent gastric and a mesenteric node were identified. Every 5-10min, those nodes were scanned using probe-based or needle-based CLE (pCLE or nCLE). Immunohistochemistry (IHC) using anti-cytokeratin 18 antibodies was subsequently performed to confirm the presence of hepatocytes in the lymph nodes. A total of 36 lymph nodes were analyzed with both CLE probes. Hepatocyte penetration in lymph nodes, as assessed by repeated CLE scanning, took 10-40min after submucosal injection. Concordance between CLE and IHC was 84 and 72% for pCLE and nCLE, respectively. False negatives were partly due to incomplete CFSE labeling of hepatocytes, which could not be recognized by CLE, but were detected with IHC. Real-time CLE analysis effectively recognized the presence in perigastric nodes of marked hepatic cells that had been injected endoscopically in the stomach. Validation studies on tumor-bearing animals using tumor-specific antibodies should be performed.

Image annotation with incomplete labelling by modelling image specific structured loss

In this paper, we address the problem of image annotation with incomplete labeling, where multiple objects in each training image are not fully labeled. The conventional one‐versus‐all support vector machine (OVA‐SVM), which performs fairly well on full labeling, decays drastically under the setting of incompleteness. Recently, a structured output learning method termed OVA‐SSVM was proposed to boost the performance of OVA‐SVM by modeling the structured associations of labels and show efficiency under the setting of incompleteness. OVA‐SSVM assumes that each training sample includes a single label and adopts an loss measure of classification style where, as long as one of the predicted label is correct, the overall prediction should be considered correct. However, this may not be appropriate for the multilabel annotation task. Therefore, we extend the OVA‐SSVM method to the multilabel situation and design a novel image‐specific structured loss to account for the dependences between predicted labels relying on image label associations. The superiority of the proposed image‐specific structured loss is that it can directly learn the semantic relationships of labels from training data without predefined semantic hierarchy. Extensive empirical results on a variety of benchmark datasets show that the proposed method performs significantly better than OVA‐SSVM on image annotation tasks with incomplete labeling and achieves competitive performance compared to other state‐of‐the‐art methods. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

When One Plus One Does Not Equal Two: Fluorescence Anisotropy in Aggregates and Multiply Labeled Proteins

The behavior of fluorescence anisotropy and polarization in systems with multiple dyes is well known. Homo-FRET and its consequent energy migration cause the fluorescence anisotropy to decrease as the number of like fluorophores within energy transfer distance increases. This behavior is well understood when all subunits within a cluster are saturated with fluorophores. However, incomplete labeling as might occur from a mixture of endogenous and labeled monomer units, incomplete saturation of binding sites, or photobleaching produces stochastic mixtures. Models in widespread and longstanding use that describe these mixtures apply an assumption of equal fluorescence efficiency for all sites first stated by Weber and Daniel in 1966. The assumption states that fluorophores have the same brightness when free in solution as they do in close proximity to each other in a cluster. The assumption simplifies descriptions of anisotropy trends as the fractional labeling of the cluster changes. However, fluorophores in close proximity often exhibit nonadditivity due to such things as self-quenching behavior or exciplex formation. Therefore, the anisotropy of stochastic mixtures of fluorophore clusters of a particular size will depend on the behavior of those fluorophores in clusters. We present analytical expressions for fractionally labeled clusters exhibiting a range of behaviors, and experimental results from two systems: an assembled tetrameric cluster of fluorescent proteins and stochastically labeled bovine serum albumin containing up to 24 fluorophores. The experimental results indicate that clustered species do not follow the assumption of equal fluorescence efficiency in the systems studied with clustered fluorophores showing reduced fluorescence intensity. Application of the assumption of equal fluorescence efficiency will underpredict anisotropy and consequently underestimate cluster size in these two cases. The theoretical results indicate that careful selection of the fractional labeling in strongly quenched systems will enhance opportunities to determine cluster sizes, making accessible larger clusters than are currently considered possible.

CoreFlow: A computational platform for integration, analysis and modeling of complex biological data

A major challenge in mass spectrometry and other large-scale applications is how to handle, integrate, and model the data that is produced. Given the speed at which technology advances and the need to keep pace with biological experiments, we designed a computational platform, CoreFlow, which provides programmers with a framework to manage data in real-time. It allows users to upload data into a relational database (MySQL), and to create custom scripts in high-level languages such as R, Python, or Perl for processing, correcting and modeling this data. CoreFlow organizes these scripts into project-specific pipelines, tracks interdependencies between related tasks, and enables the generation of summary reports as well as publication-quality images. As a result, the gap between experimental and computational components of a typical large-scale biology project is reduced, decreasing the time between data generation, analysis and manuscript writing. CoreFlow is being released to the scientific community as an open-sourced software package complete with proteomics-specific examples, which include corrections for incomplete isotopic labeling of peptides (SILAC) or arginine-to-proline conversion, and modeling of multiple/selected reaction monitoring (MRM/SRM) results. CoreFlow was purposely designed as an environment for programmers to rapidly perform data analysis. These analyses are assembled into project-specific workflows that are readily shared with biologists to guide the next stages of experimentation. Its simple yet powerful interface provides a structure where scripts can be written and tested virtually simultaneously to shorten the life cycle of code development for a particular task. The scripts are exposed at every step so that a user can quickly see the relationships between the data, the assumptions that have been made, and the manipulations that have been performed. Since the scripts use commonly available programming languages, they can easily be transferred to and from other computational environments for debugging or faster processing. This focus on 'on the fly' analysis sets CoreFlow apart from other workflow applications that require wrapping of scripts into particular formats and development of specific user interfaces. Importantly, current and future releases of data analysis scripts in CoreFlow format will be of widespread benefit to the proteomics community, not only for uptake and use in individual labs, but to enable full scrutiny of all analysis steps, thus increasing experimental reproducibility and decreasing errors. This article is part of a Special Issue entitled: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

Constructions en changement: hommage à Paul Hirschbühler ed. by Monique Dufresne

Dufresne, Monique, éd. Constructions en changement: hommage à Paul Hirschbühler. Québec: PU de Laval, 2012. ISBN 978-2-7637-8936-1. Pp. 209. $30 Can. This volume serves a dual purpose: to present four papers on French historical grammar from the ongoing corpus and research project Modéliser le changement: les voies du français (Martineau and others), and to honor Hirschbühler—himself a participant in the project—on his retirement. Dufresne opens the volume with a heartfelt dedication and an introduction. The first paper, by Alexandra Simonenko and Hirschbühler, exemplifies Hirschbühler’s characteristically detailed consideration of new data and careful attention to the previous literature. The authors analyze fifteen thousand examples of proclisis and enclisis of object pronouns in verb-initial clauses, examining four clause types over five centuries. They meticulously compare two previous analyses against the new data, concluding convincingly that Labelle and Hirschbühler’s 2005 account of functional-projection loss over time for some subtypes is superior to Rouveret’s 2004 analysis, in which the number of projections generally increases. The second paper (Dufresne and Fernande Dupuis) lays to rest the traditional assumption that the choice of auxiliary with verbs of motion and change-of-state in Old French was random. Rather, activities viewed as telic require BE in Old French, while atelic activities require HAVE. In this first large-scale investigation of unaccusativity in the history of French, over two thousand clauses (twelfth through sixteenth century) with verbs identified as syntactically unaccusative are examined. Although the preliminary character of some of the data on postverbal subjects (for example, incomplete labeling or discussion of some of the graphs) makes parts of the theoretical analysis difficult to evaluate, many fascinating questions for continuing research are raised. In the third of these admirably data-intensive studies, Christiane Marchello-Nizia and Magali Rouquier provide an extensive description of the order and expression of subjects and objects in two complete very early texts, the Passion de Clermont and the Vie de Saint Alexis. Adding these texts to two previously examined later texts, the authors obtain a more precise picture of the evolution of medieval French syntax. Object-verb order loses ground between the two early texts; there is a continual, intriguing preference for expressing either the subject or the object, but not both. (A question: Are verb-object versus object-verb orders for nonfinite verbs treated separately or not?) The final paper presents a follow-up by Lene Schøsler on her previous work with semantically bleached verbs such as faire or prendre and their nominal objects. She establishes tests for distinguishing such constructions, containing a fixed number and type of complements and modification relationships, from syntactically free verb phrases, maintaining that they represent a sub-type of grammaticalization . Overall, for those interested in French and Romance syntax and the lexicon, this volume will provoke new insights into the relevance of diachronic corpus studies to issues of more general concern. Indiana University, Bloomington Barbara Vance 228 FRENCH REVIEW 87.3 ...

Implementing COOL: Comparative welfare effects of different labeling schemes

Country-of-origin labeling (COOL) is being implemented in different forms and degrees in the United States and other countries across the world. The first implementation of mandatory country of origin labeling (MCOOL) in the United States was for seafood in 2005. This is an example of partial MCOOL because it exempts the foodservice sector and excludes processed seafood from labeling. Using a conceptual framework, we analyze the welfare impacts of partial MCOOL when compared to no, voluntary, and total mandatory COOL, taking into account imperfect competition in the downstream markets, information asymmetry, and diversion of low-quality product to the unlabeled market. The model is general enough to apply to any incomplete regulation for which the perceived low-quality product is required to be labeled, such as the labeling of genetically modified food in the European Union. Our results show that when consumers have a strong enough preference for domestic relative to imported product, regulators can overestimate the gain in consumer welfare from partial mandatory labeling if they ignore the diversion of lower quality imports to the unlabeled sector. We show that if the preference for domestic product is large enough, total MCOOL benefits the home market the most overall, including domestic consumers and producers, but not the imperfectly competitive downstream agents. However, if total MCOOL is too costly to implement, partial MCOOL is the second-best solution, but only if consumers falsely believe the unlabeled product to be of higher quality than it truly is. Our results suggest more research is needed to determine the extent to which consumers value the information provided by MCOOL and to enable regulators to consider the welfare impact of diversion in evaluating incomplete mandatory labeling regulations.

Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness.

Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug’s efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File – Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug interaction claims linked to the Drug Interactions section for a drug were potentially novel. The baseline performance characteristics of the proof-of-concept will enable further technical and user-centered research on robust methods for scaling the approach to the many thousands of product labels currently on the market.

Three-dimensional reconstruction and quantitative morphometric analysis of pyramidal and giant neurons of the rat dorsal cochlear nucleus

Correct interpretation of functional data obtained from various cell types of the cochlear nucleus (CN), a structure involved in auditory information processing, necessitates reliable cell identification. Our aim was to perform a quantitative morphological characterization of giant and pyramidal cells of the rat CN and identify parameters that are suitable for their adequate classification. Neurons were labeled with biocytin, visualized with a fluorescent marker, and three-dimensionally reconstructed from confocal images. The size and shape of the soma and dendritic tree of each neuron were characterized by 17 morphometric parameters. The variables were subjected to multivariate statistical analysis to determine their importance while discriminating between giant and pyramidal cells. Our results provide a new battery of morphometric data, which could not be obtained earlier, improve the chances of correct cell identification, make modeling experiments easier and more reliable, and help us to understand both the functions of individual CN neurons and the network properties of this nucleus. In addition, we demonstrate that even partial labeling and/or incomplete reconstruction of neurons may be enough for their correct identification if selected parameters describing the cell bodies and the proximal portions of the dendritic trees are utilized. We propose that our findings have specific relevance to studies which attempt cell identification after functional experiments resulting in incomplete labeling of the investigated neurons.

Targeted modification of wheat grain protein to reduce the content of celiac causing epitopes

The prolamin peptides in wheat gluten and in the homologous storage proteins of barley and rye cause painful chronic erasure of microvilli of the small intestine epithelium in celiac patients. If untreated, it can lead to chronic diarrhea, abdominal distension, osteoporosis, weight-loss due to malabsorption of nutrients, and anemia. In addition to congenital cases, life-long exposure to gluten proteins in bread and pasta can also induce development of celiac sprue in adults. To date, the only effective treatment is life-long strict abstinence from the staple food grains. Complete exclusion of dietary gluten is, however, difficult due to use of wheat in many foods, incomplete labeling and social constraints. Thus, finding alternative therapies for this most common foodborne disease remained an active area of research, which has led to many suggestions in last few years. The pros and cons associated with these therapies were reviewed in the present communication. As different celiac patients are immunogenic to different members of the undigestible proline/glutamine rich peptides of ~149 gliadins and low molecular weight glutenin subunits as well as the six high molecular weight glutenin subunits, an exhaustive digestion of the immunogenic peptides in the stomach, duodenum, jejunum, and ileum of celiacs is required. In view of the above, we evaluated the capacity of cereal grains to synthesize and store the enzymes prolyl endopeptidase from Flavobacterium meningosepticum and the barley cysteine endoprotease B2, which in combination are capable of detoxifying immunogenic gluten peptides in a novel treatment of celiac disease.

Effective correction of experimental errors in quantitative proteomics using stable isotope labeling by amino acids in cell culture (SILAC)

Accurate and reliable quantitative proteomics in cell culture has been considerably facilitated by the introduction of the stable isotope labeling by amino acids in cell culture (SILAC), combined with high resolution mass spectrometry. There are however several major sources of quantification errors that commonly occur with SILAC techniques, i.e. incomplete incorporation of isotopic amino acids, arginine-to-proline conversion, and experimental errors in final sample mixing. Dataset normalization is a widely adopted solution to such errors, however this may not completely prevent introducing incorrect expression ratios. Here we demonstrate that a label-swap replication of SILAC experiments was able to effectively correct experimental errors by averaging ratios measured in individual replicates using quantitative proteomics and phosphoproteomics of ligand treatment of neural cell cultures. Furthermore, this strategy was successfully applied to a SILAC triplet experiment, which presents a much more complicated experimental matrix, affected by both incomplete labeling and arginine-to-proline conversion. Based on our results, we suggest that SILAC experiments should be designed to incorporate label-swap replications for enhanced reliability in expression ratios.

Correcting for Artifacts from Spectral Cross-Talk and Imperfect Detection Volume Overlap in Dual-Color Fluorescence Cross-Correlation Spectroscopy

Dual-color fluorescence cross-correlation spectroscopy (dcFCCS) allows to quantitatively assess the interactions of mobile molecules labeled with distinct fluorophores.One major artifact risk in dcFCCS is a false-positive or overestimated cross-correlation amplitude arising from spectral cross-talk. Cross-talk can be reduced or prevented by fast alternating excitation, but the technology is not easily implemented in standard commercial setups. We devised an experimental strategy that does not require specialized hard- and software for recognizing and correcting for cross-talk in standard dcFCCS.Another major artifact risk in dcFCCS is a false-negative or underestimated cross-correlation amplitude arising from an imperfect detection volume overlap. Samples based on fluorophores conjugated to oligonucleotides that have been traditionally used for dcFCCS calibration typically suffer from incomplete labeling. Using these samples, it is difficult to attribute a reduced cross-correlation amplitude to the imperfection of the calibration sample or to that of the setup. We therefore developed a new cross-correlation calibration standard with a predictable degree of labeling.View Large Image | View Hi-Res Image | Download PowerPoint Slide

Study of Neurotrophin-3 Signaling in Primary Cultured Neurons using Multiplex Stable Isotope Labeling with Amino Acids in Cell Culture

Conventional stable isotope labeling with amino acids in cell culture (SILAC) requires extensive metabolic labeling of proteins and therefore is difficult to apply to cells that do not divide or are unstable in SILAC culture. Using two different sets of heavy amino acids for labeling allows for straightforward SILAC quantitation using partially labeled cells because the two cell populations are always equally labeled. Here we report the application of this labeling strategy to primary cultured neurons. We demonstrated that protein quantitation was not compromised by incomplete labeling of the neuronal proteins. We used this method to study neurotrophin-3 (NT-3) signaling in primary cultured neurons. Surprisingly our results indicate TrkB signaling is a major component of the signaling network induced by NT-3 in cortical neurons. In addition, involvement of proteins such as VAMP2, Scamp1, and Scamp3 suggests that NT-3 may lead to enhanced exocytosis of synaptic vesicles.

Corrigendum: FRET and FCS-Friends or Foes?

Here, ′g′ refers to green molecules, ′r represents red molecules, and ′gr stands for cross-correlating or FRET active complexes with green and red labeling. The above modification in the cross-correlation function capitalizes on the incomplete labeling efficiency in the data interpretation. ηAR and ηAG are the brightness of acceptor on direct (red) excitation and green (FRET) excitation, respectively. As the above equation does not include the contribution from cross-talk, it holds good for the systems with ALEX/PIE excitations.1 Additionally, a summary of the FCS-FRET Equations are given in Table 1. Description Equation Parameters FCS with FRET 15 Si: Fraction S2/S1. τr: Relaxation time between states S2 & S1. FCCS with FRET (Kinetic) 16 Sx: Reduced fraction S2/S1 due to the brightness change as a result of FRET. τr:relaxation time between states S2 & S1. FCCS with FRET (Kinetic includes FRET efficiency) 18 β: Brightness factor of the acceptor with FRET-excitation relative to the directly-excited donor. α: Cross-talk between donor and acceptor channels. FCCS with FRET and PIE/ALEX system (Static and without cross-talk) 19 ηAR: Brightness of acceptor with direct (red) excitation. ηAG: Brightness of acceptor with green (FRET) excitation.

A Bayesian Markov-Chain-Based Heteroscedastic Regression Model for the Analysis of 18O-Labeled Mass Spectra

To reduce the influence of the between-spectra variability on the results of peptide quantification, one can consider the (18)O-labeling approach. Ideally, with such labeling technique, a mass shift of 4 Da of the isotopic distributions of peptides from the labeled sample is induced, which allows one to distinguish the two samples and to quantify the relative abundance of the peptides. It is worth noting, however, that the presence of small quantities of (16)O and (17)O atoms during the labeling step can cause incomplete labeling. In practice, ignoring incomplete labeling may result in the biased estimation of the relative abundance of the peptide in the compared samples. A Markov model was developed to address this issue (Zhu, Valkenborg, Burzykowski. J. Proteome Res. 9, 2669-2677, 2010). The model assumed that the peak intensities were normally distributed with heteroscedasticity using a power-of-the-mean variance funtion. Such a dependence has been observed in practice. Alternatively, we formulate the model within the Bayesian framework. This opens the possibility to further extend the model by the inclusion of random effects that can be used to capture the biological/technical variability of the peptide abundance. The operational characteristics of the model were investigated by applications to real-life mass-spectrometry data sets and a simulation study.

A Markov-Chain Model for the Analysis of High-Resolution Enzymatically 18O-Labeled Mass Spectra

The enzymatic 18O-labeling is a useful quantification technique to account for between-spectrum variability of the results of mass spectrometry experiments. One of the important issues related to the use of the technique is the problem of incomplete labeling of peptide molecules, which may result in biased estimates of the relative peptide abundance. In this manuscript, we propose a Markov-chain model, which takes into account the possibility of incomplete labeling in the estimation of the relative abundance from the observed data. This allows for the use of less precise but faster labeling strategies, which should better fit in the high-throughput proteomic framework. Our method does not require extra experimental steps, as proposed in the approaches developed by Mirgorodskaya et al. (2000), López-Ferrer et al. (2006) and Rao et al. (2005), while it includes the model proposed by Eckel-Passow et al. (2006) as a special case. The method estimates information about the isotopic distribution directly from the observed data and is able to account for biases induced by the different sulphur content in peptides as reported by Johnson and Muddiman (2004). The method is integrated in a statistically sound framework and allows for the calculation of the errors on the parameter estimates based on model theory. In this manuscript, we describe the methodology in a technical matter and assess the properties of the algorithm via a thorough simulation study. The method is also tested on a limited dataset; more intense validation and investigation of the operational characteristics is being scheduled.