Identification of histone modifications in biomedical text for supporting epigenomic research

Corinna K, Klinger R, Hofmann-Apitius M. Identification of Histone Modifications in Biomedical Text for Supporting Epigenomic Research. BMC Bioinformatics. 2009;10(Suppl 1):S28

Combining active learning and semi-supervised learning techniques to extract protein interaction sentences

Background: Protein-protein interaction (PPI) extraction has been a focal point of many biomedical research and database curation tools. Both Active Learning and Semi-supervised SVMs have recently been applied to extract PPI automatically. In this paper, we explore combining the AL with the SSL to improve the performance of the PPI task. Methods: We propose a novel PPI extraction technique called PPISpotter by combining Deterministic Annealing-based SSL and an AL technique to extract protein-protein interaction. In addition, we extract a comprehensive set of features from MEDLINE records by Natural Language Processing (NLP) techniques, which further improve the SVM classifiers. In our feature selection technique, syntactic, semantic, and lexical properties of text are incorporated into feature selection that boosts the system performance significantly. Results: By conducting experiments with three different PPI corpuses, we show that PPISpotter is superior to the other techniques incorporated into semi-supervised SVMs such as Random Sampling, Clustering, and Transductive SVMs by precision, recall, and F-measure. Conclusions: Our system is a novel, state-of-the-art technique for efficiently extracting protein-protein interaction pairs.X116sciescopu

Identifying the Age Cohort Responsible for Transmission in a Natural Outbreak of Bordetella bronchiseptica

Identifying the major routes of disease transmission and reservoirs of infection are needed to increase our understanding of disease dynamics and improve disease control. Despite this, transmission events are rarely observed directly. Here we had the unique opportunity to study natural transmission of Bordetella bronchiseptica – a directly transmitted respiratory pathogen with a wide mammalian host range, including sporadic infection of humans – within a commercial rabbitry to evaluate the relative effects of sex and age on the transmission dynamics therein. We did this by developing an a priori set of hypotheses outlining how natural B. bronchiseptica infections may be transmitted between rabbits. We discriminated between these hypotheses by using force-of-infection estimates coupled with random effects binomial regression analysis of B. bronchiseptica age-prevalence data from within our rabbit population. Force-of-infection analysis allowed us to quantify the apparent prevalence of B. bronchiseptica while correcting for age structure. To determine whether transmission is largely within social groups (in this case litter), or from an external group, we used random-effect binomial regression to evaluate the importance of social mixing in disease spread. Between these two approaches our results support young weanlings – as opposed to, for example, breeder or maternal cohorts – as the age cohort primarily responsible for B. bronchiseptica transmission. Thus age-prevalence data, which is relatively easy to gather in clinical or agricultural settings, can be used to evaluate contact patterns and infer the likely age-cohort responsible for transmission of directly transmitted infections. These insights shed light on the dynamics of disease spread and allow an assessment to be made of the best methods for effective long-term disease control

Ce-Duox1/BLI-3 Generated Reactive Oxygen Species Trigger Protective SKN-1 Activity via p38 MAPK Signaling during Infection in C. elegans

Infected animals will produce reactive oxygen species (ROS) and other inflammatory molecules that help fight pathogens, but can inadvertently damage host tissue. Therefore specific responses, which protect and repair against the collateral damage caused by the immune response, are critical for successfully surviving pathogen attack. We previously demonstrated that ROS are generated during infection in the model host Caenorhabditis elegans by the dual oxidase Ce-Duox1/BLI-3. Herein, an important connection between ROS generation by Ce-Duox1/BLI-3 and upregulation of a protective transcriptional response by SKN-1 is established in the context of infection. SKN-1 is an ortholog of the mammalian Nrf transcription factors and has previously been documented to promote survival, following oxidative stress, by upregulating genes involved in the detoxification of ROS and other reactive compounds. Using qRT-PCR, transcriptional reporter fusions, and a translational fusion, SKN-1 is shown to become highly active in the C. elegans intestine upon exposure to the human bacterial pathogens, Enterococcus faecalis and Pseudomonas aeruginosa. Activation is dependent on the overall pathogenicity of the bacterium, demonstrated by a weakened response observed in attenuated mutants of these pathogens. Previous work demonstrated a role for p38 MAPK signaling both in pathogen resistance and in activating SKN-1 upon exposure to chemically induced oxidative stress. We show that NSY-1, SEK-1 and PMK-1 are also required for SKN-1 activity during infection. Evidence is also presented that the ROS produced by Ce-Duox1/BLI-3 is the source of SKN-1 activation via p38 MAPK signaling during infection. Finally, for the first time, SKN-1 activity is shown to be protective during infection; loss of skn-1 decreases resistance, whereas increasing SKN-1 activity augments resistance to pathogen. Overall, a model is presented in which ROS generation by Ce-Duox1/BLI-3 activates a protective SKN-1 response via p38 MAPK signaling

Evaluating Patterns of a White-Band Disease (WBD) Outbreak in Acropora palmata Using Spatial Analysis: A Comparison of Transect and Colony Clustering

. Likewise, there is little known about the spatiality of outbreaks. We examined the spatial patterns of WBD during a 2004 outbreak at Buck Island Reef National Monument in the US Virgin Islands. colonies with and without WBD.As the search for causation continues, surveillance and proper documentation of the spatial patterns may inform etiology, and at the same time assist reef managers in allocating resources to tracking the disease. Our results indicate that the spatial scale of data collected can drastically affect the calculation of prevalence and spatial distribution of WBD outbreaks. Specifically, we illustrate that higher resolution sampling resulted in more realistic disease estimates. This should assist in selecting appropriate sampling designs for future outbreak investigations. The spatial techniques used here can be used to facilitate other coral disease studies, as well as, improve reef conservation and management

CCN3 modulates bone turnover and is a novel regulator of skeletal metastasis

The CCN family of proteins is composed of six secreted proteins (CCN1-6), which are grouped together based on their structural similarity. These matricellular proteins are involved in a large spectrum of biological processes, ranging from development to disease. In this review, we focus on CCN3, a founding member of this family, and its role in regulating cells within the bone microenvironment. CCN3 impairs normal osteoblast differentiation through multiple mechanisms, which include the neutralization of pro-osteoblastogenic stimuli such as BMP and Wnt family signals or the activation of pathways that suppress osteoblastogenesis, such as Notch. In contrast, CCN3 is known to promote chondrocyte differentiation. Given these functions, it is not surprising that CCN3 has been implicated in the progression of primary bone cancers such as osteosarcoma, Ewing’s sarcoma and chondrosarcoma. More recently, emerging evidence suggests that CCN3 may also influence the ability of metastatic cancers to colonize and grow in bone

A Serological Survey of Infectious Disease in Yellowstone National Park’s Canid Community

BACKGROUND:Gray wolves (Canis lupus) were reintroduced into Yellowstone National Park (YNP) after a >70 year absence, and as part of recovery efforts, the population has been closely monitored. In 1999 and 2005, pup survival was significantly reduced, suggestive of disease outbreaks. METHODOLOGY/PRINCIPAL FINDINGS:We analyzed sympatric wolf, coyote (Canis latrans), and red fox (Vulpes vulpes) serologic data from YNP, spanning 1991-2007, to identify long-term patterns of pathogen exposure, identify associated risk factors, and examine evidence for disease-induced mortality among wolves for which there were survival data. We found high, constant exposure to canine parvovirus (wolf seroprevalence: 100%; coyote: 94%), canine adenovirus-1 (wolf pups [0.5-0.9 yr]: 91%, adults [>or=1 yr]: 96%; coyote juveniles [0.5-1.5 yrs]: 18%, adults [>or=1.6 yrs]: 83%), and canine herpesvirus (wolf: 87%; coyote juveniles: 23%, young adults [1.6-4.9 yrs]: 51%, old adults [>or=5 yrs]: 87%) suggesting that these pathogens were enzootic within YNP wolves and coyotes. An average of 50% of wolves exhibited exposure to the protozoan parasite, Neospora caninum, although individuals' odds of exposure tended to increase with age and was temporally variable. Wolf, coyote, and fox exposure to canine distemper virus (CDV) was temporally variable, with evidence for distinct multi-host outbreaks in 1999 and 2005, and perhaps a smaller, isolated outbreak among wolves in the interior of YNP in 2002. The years of high wolf-pup mortality in 1999 and 2005 in the northern region of the park were correlated with peaks in CDV seroprevalence, suggesting that CDV contributed to the observed mortality. CONCLUSIONS/SIGNIFICANCE:Of the pathogens we examined, none appear to jeopardize the long-term population of canids in YNP. However, CDV appears capable of causing short-term population declines. Additional information on how and where CDV is maintained and the frequency with which future epizootics might be expected might be useful for future management of the Northern Rocky Mountain wolf population

Optimization Approaches to Semi-Supervised Learning

We examine mathematical models for semi-supervised support vector machines (S VM). Given a training set of labeled data and a working set of unlabeled data, S VM constructs a support vector machine using both the training and working sets. We use S VM to solve the transductive inference problem posed by Vapnik. In transduction, the task is to estimate the value of a classification function at the given points in the working set. This contrasts with inductive inference which estimates the classification function at all possible values. We propose a general S VM model that minimizes both the misclassification error and the function capacity based on all the available data. Depending on how poorly-estimated unlabeled data are penalized, different mathematical models result. We examine several practical algorithms for solving these model. The first approach utilizes the S VM model for 1-norm linear support vector machines converted to a mixedinteger program (MIP). A global solution of the ..