Search tips
Search criteria

Results 1-25 (32)

Clipboard (0)
Year of Publication
more »
1.  Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry 
BMJ Open  2014;4(3):e004007.
Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes.
A regional cancer centre in Australia.
Disease-specific data from a purpose-built cancer registry (Evaluation of Cancer Outcomes (ECO)) from 869 patients were used to predict survival at 6, 12 and 24 months. The model was validated with data from a further 94 patients, and results compared to the assessment of five specialist oncologists. Machine-learning prediction using ECO data was compared with that using EAR and a model combining ECO and EAR data.
Primary and secondary outcome measures
Survival prediction accuracy in terms of the area under the receiver operating characteristic curve (AUC).
The ECO model yielded AUCs of 0.87 (95% CI 0.848 to 0.890) at 6 months, 0.796 (95% CI 0.774 to 0.823) at 12 months and 0.764 (95% CI 0.737 to 0.789) at 24 months. Each was slightly better than the performance of the clinician panel. The model performed consistently across a range of cancers, including rare cancers. Combining ECO and EAR data yielded better prediction than the ECO-based model (AUCs ranging from 0.757 to 0.997 for 6 months, AUCs from 0.689 to 0.988 for 12 months and AUCs from 0.713 to 0.973 for 24 months). The best prediction was for genitourinary, head and neck, lung, skin, and upper gastrointestinal tumours.
Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes. Importantly, the approach described made use of digital data that is already routinely collected but underexploited by clinical health systems.
PMCID: PMC3963101  PMID: 24643167
Cancer; Survival; Prediction; Machine Learning; Electronic Medical Record
2.  Protein associated with SMAD1 (PAWS1/FAM83G) is a substrate for type I bone morphogenetic protein receptors and modulates bone morphogenetic protein signalling 
Open Biology  2014;4(2):130210.
Bone morphogenetic proteins (BMPs) control multiple cellular processes in embryos and adult tissues. BMPs signal through the activation of type I BMP receptor kinases, which then phosphorylate SMADs 1/5/8. In the canonical pathway, this triggers the association of these SMADs with SMAD4 and their translocation to the nucleus, where they regulate gene expression. BMPs can also signal independently of SMAD4, but this pathway is poorly understood. Here, we report the discovery and characterization of PAWS1/FAM83G as a novel SMAD1 interactor. PAWS1 forms a complex with SMAD1 in a SMAD4-independent manner, and BMP signalling induces the phosphorylation of PAWS1 through BMPR1A. The phosphorylation of PAWS1 in response to BMP is essential for activation of the SMAD4-independent BMP target genes NEDD9 and ASNS. Our findings identify PAWS1 as the first non-SMAD substrate for type I BMP receptor kinases and as a novel player in the BMP pathway. We also demonstrate that PAWS1 regulates the expression of several non-BMP target genes, suggesting roles for PAWS1 beyond the BMP pathway.
PMCID: PMC3938053  PMID: 24554596
bone morphogenetic protein; SMAD1; FAM83G; PAWS1; ALK3; BMPR1
3.  Economic Rationality in Choosing between Short-Term Bad-Health Choices and Longer-Term Good-Health Choices 
Non-contagious, chronic disease has been identified as a global health risk. Poor lifestyle choices, such as smoking, alcohol, drug and solvent abuse, physical inactivity, and unhealthy diet have been identified as important factors affecting the increasing incidence of chronic disease. The following focuses on the circumstance affecting the lifestyle or behavioral choices of Aboriginal and Torres Strait Islander peoples in remote-/very remote Australia. Poor behavioral choices are the result of endogenous characteristics that are influenced by a range of stressful exogenous variables making up the psychosocial determinants including social disenfranchisement, cultural loss, insurmountable tasks, the loss of volitional control and resource constraints. It is shown that poor behavioral choices can be economically rational; especially under highly stressful conditions. Stressful circumstances erode individual capacity to commit to long-term positive health alternatives such as self-investment in education. Policies directed at removing the impediments and providing incentives to behaviors involving better health choices can lead to reductions in smoking and alcohol consumption and improved health outcomes. Multijurisdictional culturally acceptable policies directed at distal variables relating to the psychosocial determinants of health and personal mastery and control can be cost effective. While the content of this paper is focused on the conditions of colonized peoples, it has broader relevance.
PMCID: PMC3863881  PMID: 24217181
smoking; alcohol abuse; health; behavioral choice; psychosocial determinants; human capital
4.  Development of a Community-Sensitive Strategy to Increase Availability of Fresh Fruits and Vegetables in Nashville’s Urban Food Deserts, 2010–2012 
Food deserts, areas that lack full-service grocery stores, may contribute to rising rates of obesity and chronic diseases among low-income and racial/ethnic minority residents. Our corner store project, part of the Centers for Disease Control and Prevention’s Communities Putting Prevention to Work initiative, aimed to increase availability of healthful foods in food deserts in Nashville, Tennessee.
Community Context
We identified 4 food deserts in which most residents are low-income and racially and ethnically diverse. Our objectives were to develop an approach to increase availability of fresh fruits and vegetables, low-fat or nonfat milk, and 100% whole-wheat bread in Nashville’s food deserts and to engage community members to inform our strategy.
Five corner stores located in food deserts met inclusion criteria for our intervention. We then conducted community listening sessions, proprietor surveys, store audits, and customer-intercept surveys to identify needs, challenges to retailing the products, and potential intervention strategies.
Few stores offered fresh fruits, fresh vegetables, low-fat or nonfat milk, or 100% whole-wheat bread, and none stocked items from all 4 categories. Major barriers to retailing healthful options identified by community members are mistrust of store owners, history of poor-quality produce, and limited familiarity with healthful options. Store owners identified neighborhood crime as the major barrier. We used community input to develop strategies.
Engaging community residents and understanding neighborhood context is critical to developing strategies that increase access to healthful foods in corner stores.
PMCID: PMC3725846  PMID: 23886044
5.  Distribution, genetic analysis and conservation priorities for rare Texas freshwater molluscs in the genera Fusconaia and Pleurobema (Bivalvia: Unionidae) 
Aquatic Biosystems  2012;8:12.
Freshwater bivalves in the order Unionoida are considered to be one of the most endangered groups of animals in North America. In Texas, where over 60% of unionids are rare or very rare, 15 species have been recently added to the state’s list of threatened species, and 11 are under consideration for federal listing. Due to insufficient survey efforts in the past decades, however, primary data on current distribution and habitat requirement for most of these rare species are lacking, thus challenging their protection and management. Taxonomic identification of endemic species based on shell morphology is challenging and complicates conservation efforts. In this paper we present historic and current distributional data for three rare Texas species, Fusconaia askewi, F. lananensis, and Pleurobema riddellii, collected during our 2003–2011 state-wide surveys and suggest appropriate conservation measures. In addition, we tested the genetic affinities of Fusconaia and similar species collected from eastern Texas and western Louisiana using cox1 and nad1 sequences.
We found that F. askewi still inhabits four river basins in eastern and northeastern Texas and can be locally abundant, while P. riddellii was found only in one river basin. Pleurobema riddellii was well-separated from F. askewi and grouped with the P. sintoxia clade. The sequences for F. lananensis were very similar to those for F. askewi, with a maximum difference of just over 1% for nad1 and only 0.7% for cox1, similar to the variation between F. askewi alleles. Except for one low difference (1.55%) with the partial cox1 sequence for F. burkei, all other Fusconaia populations, including those from the Calcasieu drainage, differed by over 2.3% for both genes.
Our study suggested that F. lananensis is not a valid species, and it is likely that only one Fusconaia species (F. askewi or its probable senior synonym F. chunii) is currently present in East Texas, thus simplifying conservation efforts. Distribution range of both these regional endemics (F. askewi and P. riddellii) has been reduced in the last 80 years.
PMCID: PMC3422191  PMID: 22731520
Freshwater molluscs; Fusconaia askewi; Fusconaia lananensis; Pleurobema riddellii; Molecular identification; Taxonomy; Distribution; Habitat requirements; Conservation priorities
6.  Morbidity of the Arterial Switch Operation 
The Annals of Thoracic Surgery  2012;93(6):1977-1983.
The arterial switch operation (ASO) has become a safe, reproducible surgical procedure with low mortality in experienced centers. We examined morbidity, which remains significant, particularly for complex ASO.
From 2003 to 2011, 101 consecutive patients underwent ASO, arbitrarily classified as “simple” (n = 52) or “complex” (n = 49). Morbidity was measured in selected complications and postoperative hospitalization. Three outcomes were analyzed: ventilation time, postextubation hospital length of stay, and a composite morbidity index, defined as ventilation time + postextubation hospital length of stay + occurrence of selected major complications. Complexity was measured with the comprehensive Aristotle score.
The operative mortality was zero. Twenty-five major complications occurred in 23 patients: 6 of 25 (12%) in simple ASO and 19 of 49 (39%) in complex ASO (p = 0.002). The most frequent complication was unplanned reoperation (15 vs 6, p = 0.03). No patients required permanent pacing. The complex group had a significantly higher morbidity index and longer ventilation time and postextubation hospital length of stay. In multivariate analysis, factors independently predicting higher morbidity were the comprehensive Aristotle score, arch repair, bypass time, and malaligned commissures. Myocardial infarction caused one sudden late death at 3 months. Late coronary failure was 2%. Overall survival was 99% at a mean follow-up of 49 ± 27 months.
In this consecutive series without operative mortality, morbidity was significantly higher in complex ASO. The only anatomic incremental risk factors for morbidity were aortic arch repair and malaligned commissures, but not primary diagnosis, weight less than 2.5 kg, or coronary patterns.
PMCID: PMC3381339  PMID: 22365263
7.  Early migration characteristics of a hydroxyapatite-coated femoral stem: an RSA study 
International Orthopaedics  2009;35(4):483-488.
Measurement of early stem subsidence can be used to predict the likelihood of long-term femoral component loosening and clinical failure. Data that examines the early migration pattern of clinically proven stems will provide clinicians with useful baseline data with which to compare new stem designs. This study was performed to evaluate the early migration pattern of a hydroxyapatite-coated press-fit femoral component that has been in use for over ten years. We enrolled 30 patients who underwent THA for osteoarthritis. The median age was 70 years (range, 55–80 years). Patients were clinically assessed using the Harris hip score. Radiostereometric analysis was used to evaluate stem migration at three to four days, six months, one year and two years. We observed a mean subsidence of 0.73 mm at six months, 0.62 mm at one year and 0.58 mm at two years and a mean retroversion of 1.82° at six months, 1.90° at one year and 1.59° at two years. This data suggests that subsidence is confined to the first six months after which there was no further subsidence. The results from this study can be compared with those from novel cementless stem designs to help predict the long-term outcome one may expect from new cementless stem designs.
PMCID: PMC3066322  PMID: 20012862
8.  Heparin-Induced Thrombocytopenia Associated with Massive Intracardiac Thrombosis: A Case Report 
Case Reports in Hematology  2012;2012:257023.
A 60-years old patient was admitted to a community hospital with septic arthritis. He was treated with antibiotics and subcutaneous unfractionated heparin (UH) was used for venous thromboprophylaxis. After three days, he developed leg deep venous thrombosis and was treated with IV heparin. One day later, the patient developed pulmonary emboli, which was found using ventilation/perfusion scan. He was transferred to the University Hospital for further management. Upon arrival, antibiotic and intravenous UH were continued. Trans-Esophageal Echocardiogram showed a thrombus in the right atrium, a small portion of which extended to the left atrium through a patent foramen ovale. Another large thrombus was noted in the right ventricle, which extended to the pulmonary artery. Review of the patient's medical records revealed a halving of his platelet count three days following the heparin administration. Therefore, HIT seemed very likely. Intravenous UH was stopped and an emergency thrombectomy was performed. ELISA testing of HIT antibodies came negative. This made HIT diagnosis unlikely and the patient received dalteparin. A week later, as the platelet count declined again, HIT antibodies' testing using ELISA and C-14 serotonin release was repeated, and both assays were positive. Argatroban was restarted and the platelet count normalized.
PMCID: PMC3420555  PMID: 22937322
9.  Medication compliance aids: a qualitative study of users' views 
Despite the rapid rise in the use of multicompartmental compliance aids (MCAs), little is known about the role they play in self-management of medication.
To explore the perceived benefits of MCAs for people using them to manage their own or a relative's medication.
Design of study
Qualitative study using in-depth interviews.
West Northumberland.
Recruitment was via posters and leaflets in general practices and community pharmacies. In-depth interviews were conducted using a topic guide.
Nineteen people were interviewed. Three overarching themes emerged in relation to medicine taking: disruption, organisation, and adherence, which impacted on control. The medication regime had caused disruption to their lives and this had led to the purchase of an MCA. The MCA enabled them to organise their medication, which they believed had improved the efficiency of medicine taking and saved time. Although the MCA did not prompt them to take their medication, they could see whether they had actually taken it or not, which alleviated their anxiety. To meet their individual needs and lifestyles, some had developed broader systems of medication management, incorporating the MCA. For a small cost – the initial outlay for the MCA and time spent loading it – they gained control over the management of their medication and their condition.
This group found the use of an MCA to be beneficial, but advice and support regarding how best to manage their medication and on the most appropriate design to suit their needs would be helpful.
PMCID: PMC3026148  PMID: 21276336
medication adherence; medication systems; qualitative research
10.  VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics 
Nucleic Acids Research  2011;40(Database issue):D729-D734.
VectorBase ( is a NIAID-supported bioinformatics resource for invertebrate vectors of human pathogens. It hosts data for nine genomes: mosquitoes (three Anopheles gambiae genomes, Aedes aegypti and Culex quinquefasciatus), tick (Ixodes scapularis), body louse (Pediculus humanus), kissing bug (Rhodnius prolixus) and tsetse fly (Glossina morsitans). Hosted data range from genomic features and expression data to population genetics and ontologies. We describe improvements and integration of new data that expand our taxonomic coverage. Releases are bi-monthly and include the delivery of preliminary data for emerging genomes. Frequent updates of the genome browser provide VectorBase users with increasing options for visualizing their own high-throughput data. One major development is a new population biology resource for storing genomic variations, insecticide resistance data and their associated metadata. It takes advantage of improved ontologies and controlled vocabularies. Combined, these new features ensure timely release of multiple types of data in the public domain while helping overcome the bottlenecks of bioinformatics and annotation by engaging with our user community.
PMCID: PMC3245112  PMID: 22135296
11.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry 
The developed, directed mass spectrometry workflow allows to generate consistent and system-wide quantitative maps of microbial proteomes in a single analysis. Application to the human pathogen L. interrogans revealed mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense, and new insights about the regulation of absolute protein abundances within operons.
The developed, directed proteomic approach allowed consistent detection and absolute quantification of 1680 proteins of the human pathogen L. interrogans in a single LC–MS/MS experiment.The comparison of 25 extensive, consistent and quantitative proteome maps revealed new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans, and about the regulation of protein abundances within operons.The generated time-resolved data sets are compatible with pattern analysis algorithms developed for transcriptomics, including hierarchical clustering and functional enrichment analysis of the detected profile clusters.This is the first study that describes the absolute quantitative behavior of any proteome over multiple states and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
Over the last decade, mass spectrometry (MS)-based proteomics has evolved as the method of choice for system-wide proteome studies and now allows for the characterization of several thousands of proteins in a single sample. Despite these great advances, redundant monitoring of protein levels over large sample numbers in a high-throughput manner remains a challenging task. New directed MS strategies have shown to overcome some of the current limitations, thereby enabling the acquisition of consistent and system-wide data sets of proteomes with low-to-moderate complexity at high throughput.
In this study, we applied this integrated, two-stage MS strategy to investigate global proteome changes in the human pathogen L. interrogans. In the initial discovery phase, 1680 proteins (out of around 3600 gene products) could be identified (Schmidt et al, 2008) and, by focusing precious MS-sequencing time on the most dominant, specific peptides per protein, all proteins could be accurately and consistently monitored over 25 different samples within a few days of instrument time in the following scoring phase (Figure 1). Additionally, the co-analysis of heavy reference peptides enabled us to obtain absolute protein concentration estimates for all identified proteins in each perturbation (Malmström et al, 2009). The detected proteins did not show any biases against functional groups or protein classes, including membrane proteins, and span an abundance range of more than three orders of magnitude, a range that is expected to cover most of the L. interrogans proteome (Malmström et al, 2009).
To elucidate mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense of L. interrogans, we generated time-resolved proteome maps of cells perturbed with serum and three different antibiotics at sublethal concentrations that are currently used to treat Leptospirosis. This yielded an information-rich proteomic data set that describes, for the first time, the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date. Using this unique property of the data set, we could quantify protein components of entire pathways across several time points and subject the data sets to cluster analysis, a tool that was previously limited to the transcript level due to incomplete sampling on protein level (Figure 4). Based on these analyses, we could demonstrate that Leptospira cells adjust the cellular abundance of a certain subset of proteins and pathways as a general response to stress while other parts of the proteome respond highly specific. The cells furthermore react to individual treatments by ‘fine tuning' the abundance of certain proteins and pathways in order to cope with the specific cause of stress. Intriguingly, the most specific and significant expression changes were observed for proteins involved in motility, tissue penetration and virulence after serum treatment where we tried to simulate the host environment. While many of the detected protein changes demonstrate good agreement with available transcriptomics data, most proteins showed a poor correlation. This includes potential virulence factors, like Loa22 or OmpL1, with confirmed expression in vivo that were significantly up-regulated on the protein level, but not on the mRNA level, strengthening the importance of proteomic studies. The high resolution and coverage of the proteome data set enabled us to further investigate protein abundance changes of co-regulated genes within operons. This suggests that although most proteins within an operon respond to regulation synchronously, bacterial cells seem to have subtle means to adjust the levels of individual proteins or protein groups outside of the general trend, a phenomena that was recently also observed on the transcript level of other bacteria (Güell et al, 2009).
The method can be implemented with standard high-resolution mass spectrometers and software tools that are readily available in the majority of proteomics laboratories. It is scalable to any proteome of low-to-medium complexity and can be extended to post-translational modifications or peptide-labeling strategies for quantification. We therefore expect the approach outlined here to become a cornerstone for microbial systems biology.
Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
PMCID: PMC3159967  PMID: 21772258
absolute quantification; directed mass spectrometry; Leptospira interrogans; microbiology; proteomics
12.  Phosphoproteomic Analysis Reveals Interconnected System-Wide Responses to Perturbations of Kinases and Phosphatases in Yeast 
Science signaling  2010;3(153):rs4.
The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules, and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery, and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.
PMCID: PMC3072779  PMID: 21177495
13.  ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry 
BMC Bioinformatics  2011;12:78.
Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.
We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.
This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.
Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in
PMCID: PMC3213215  PMID: 21414234
14.  Case Report: Cementless Stem Stabilization after Intraoperative Fracture: A Radiostereometric Analysis 
We present the case of a patient with intraoperative femoral fracture during THA, which was repaired using cerclage fixation and insertion of an hydroxyapatite-coated cementless stem. The patient was evaluated postoperatively using radiostereometry during a 2-year course, and despite a large amount of subsidence and rotation, stabilization occurred and was maintained by 6 months. By evaluating the pattern of stem migration after intraoperative fracture, this case shows, even in the presence of instability, a successful clinical outcome can be achieved using an hydroxyapatite-coated cementless stem.
PMCID: PMC2816748  PMID: 19760467
15.  Systematic investigation of lycopene effects in LNCaP cells by use of novel large-scale proteomic analysis software 
Lycopene, the red pigment of tomatoes, is a carotenoid with potent antioxidant properties. Although lycopene might function as a prostate cancer chemoprevention agent, little is known about its effects at the cellular level. To define general changes induced by treatment of cells with lycopene, and to gain insights into the possible chemoprevention properties of lycopene, we investigated changes in protein expression after lycopene treatment in human LNCaP cells. The high throughput proteomics data were then visualized and analyzed by novel biological protein pathway modeling software. Differentially expressed proteins were identified, and the data were analyzed by protein pathway simulation software without need for specialized programming by importing pathway models from a number of sources or creating their own. One notable outcome was the identification of a group of upregulated proteins involved in detoxification of reactive oxygen species. This finding suggests that a possible mechanism of lycopene chemoprevention is the stimulation of detoxification enzymes associated with the antioxidant response element. Novel biological pathway modeling software enhances analysis of large proteomics data. When applied to the analysis of proteins differentially expressed in prostate cancer cells upon treatment with lycopene, the upregulation of detoxification enzymes was identified.
PMCID: PMC2926987  PMID: 20740054
detoxification enzymes; ICAT; LNCaP; lycopene; teranode
16.  Differential Plasma Glycoproteome of p19ARF Skin Cancer Mouse Model Using the Corra Label-Free LC-MS Proteomics Platform 
Clinical proteomics  2008;4(3-4):105.
A proof-of-concept demonstration of the use of label-free quantitative glycoproteomics for biomarker discovery workflow is presented here, using a mouse model for skin cancer as an example. Blood plasma was collected from 10 control mice, and 10 mice having a mutation in the p19ARF gene, conferring them high propensity to develop skin cancer after carcinogen exposure. We enriched for N-glycosylated plasma proteins, ultimately generating deglycosylated forms of the modified tryptic peptides for liquid chromatography mass spectrometry (LC-MS) analyses. LC-MS runs for each sample were then performed with a view to identifying proteins that were differentially abundant between the two mouse populations. We then used a recently developed computational framework, Corra, to perform peak picking and alignment, and to compute the statistical significance of any observed changes in individual peptide abundances. Once determined, the most discriminating peptide features were then fragmented and identified by tandem mass spectrometry with the use of inclusion lists. We next assessed the identified proteins to see if there were sets of proteins indicative of specific biological processes that correlate with the presence of disease, and specifically cancer, according to their functional annotations. As expected for such sick animals, many of the proteins identified were related to host immune response. However, a significant number of proteins also directly associated with processes linked to cancer development, including proteins related to the cell cycle, localisation, trasport, and cell death. Additional analysis of the same samples in profiling mode, and in triplicate, confirmed that replicate MS analysis of the same plasma sample generated less variation than that observed between plasma samples from different individuals, demonstrating that the reproducibility of the LC-MS platform was sufficient for this application. These results thus show that an LC-MS-based workflow can be a useful tool for the generation of candidate proteins of interest as part of a disease biomarker discovery effort.
PMCID: PMC2821048  PMID: 20157627
Skin cancer; LC-MS; Label-free protein quantification; Biomarker discovery; Systems biology; Targeted peptide sequencing; Glycoproteomics; Plasma
19.  Detailed Characterization and Profiles of Crankcase and Diesel Particular Matter Exhaust Emissions Using Speciated Organics 
Environmental science & technology  2008;42(15):5661-5666.
A monitoring campaign was conducted in August-September 2005 to compare different experimental approaches quantifying school bus self-pollution. As part of this monitoring campaign, a detailed characterization of PM2.5 diesel engine emissions from the tailpipe and crankcase emissions from the road draft tubes was performed. To distinguish between tailpipe and crankcase vent emissions, a deuterated alkane, n-hexatriacontane-d74 (n-C36D74) was added to the engine oil to serve as intentional quantitative tracers for lubricating oil PM emissions. This paper focuses on the detailed chemical speciation of crankcase and tailpipe PM emissions from two school buses used in this study. We found that organic carbon emission rates were generally higher from the crankcase than from the tailpipe for these two school buses, while elemental carbon contributed significantly only in the tailpipe emissions. The n-C36D74 that was added to the engine oil was emitted at higher rates from the crankcase than the tailpipe. Tracers of engine oil (hopanes, and steranes) were present in much higher proportion in crankcase emissions. Particle-associated PAH emission rates were generally very low (< 1 μg/km), but more PAH species were present in crankcase than in tailpipe emissions. The speciation of samples collected in the bus cabins was consistent with most of the bus self-pollution originating from crankcase emissions.
PMCID: PMC2614383  PMID: 18754490
School bus self-pollution; tailpipe and crankcase emissions; organic speciation; tracers
20.  Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics 
BMC Bioinformatics  2008;9:542.
Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics.
We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling.
The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field.
PMCID: PMC2651178  PMID: 19087345
21.  Bilateral Entorhinal Cortex Lesions Impair Acquisition of Delayed Spatial Alternation in Rats. 
Entorhinal cortex lesions induce significant reorganization of several homotypic and heterotypic inputs to the hippocampus. This investigation determined whether surviving heterotypic inputs after bilateral entorhinal lesions would support the acquisition of a learned alternation task. Rats with entorhinal lesions or sham operations were trained to acquire a spatial alternation task. Although the sham-operated rats acquired the task within about three weeks postsurgery, rats with bilateral entorhinal lesions failed to learn the task after 12 consecutive weeks of training despite heterotypic sprouting of the cholinergic septodentate pathway and the expansion of the commissural/associational fiber plexus within the dentate gyrus. Thus, heterotypic sprouting failed to ameliorate significantly the effects of bilateral entorhinal lesions. Rather, entorhinal lesions produce a persistent impairment of spatial memory, characterized by a mixture of random error production and perseverative responding.
PMCID: PMC1839929  PMID: 17049284
22.  PhosphoPep—a phosphoproteome resource for systems biology research in Drosophila Kc167 cells 
The ability to analyze and understand the mechanisms by which cells process information is a key question of systems biology research. Such mechanisms critically depend on reversible phosphorylation of cellular proteins, a process that is catalyzed by protein kinases and phosphatases. Here, we present PhosphoPep, a database containing more than 10 000 unique high-confidence phosphorylation sites mapping to nearly 3500 gene models and 4600 distinct phosphoproteins of the Drosophila melanogaster Kc167 cell line. This constitutes the most comprehensive phosphorylation map of any single source to date. To enhance the utility of PhosphoPep, we also provide an array of software tools that allow users to browse through phosphorylation sites on single proteins or pathways, to easily integrate the data with other, external data types such as protein–protein interactions and to search the database via spectral matching. Finally, all data can be readily exported, for example, for targeted proteomics approaches and the data thus generated can be again validated using PhosphoPep, supporting iterative cycles of experimentation and analysis that are typical for systems biology research.
PMCID: PMC2063582  PMID: 17940529
data integration; Drosophila; interactive database; phosphoproteomics; systems biology
23.  The skiers knee without swelling or instability, a difficult diagnosis: a case report 
Skiing as a recreational activity has increased exponentially in the last twenty-years. Similar to any sporting activity, participants can sustain various types of injury, which provides the emergency departments with a continuous supply of patients. The injury pattern from the slopes has also changed over this time period, due to alterations and improvements in ski equipment. An increased diversity in alpine skiing techniques, as well as snowboarding and cross-terrain disciplines has also influenced this change.
We present a multi-media experience of a high-speed ski fall that caused a valgus-external rotation injury to the right knee that precluded the patient from further ski activity. There was no bruising, swelling or instability demonstrated and the patient returned to ski activities 24-hours post-injury. Although this injury appeared clinically benign initially, the patient complained of persistent pain around the right knee which was causing occupational difficulties. Following normal clinical assessment, the patient returned to work but continued to complain of persistent pain at the lateral aspect of the right knee. Magnetic Resonance Imaging (MRI) demonstrated extensive bone marrow oedema (BMO), a mild depression of the articular cortex compression with a small focus of articular cartilage disruption and microfractures of the lateral tibial plateau. The patient was treated conservatively and remains well with avoidance of impact exercises 14-months post-injury.
In the presence of any high speed injury, we would stress that regardless of initial normal investigations, clinical suspicion should remain paramount and not deter the physician from further investigation in the presence of continuing symptomatology.
PMCID: PMC1865549  PMID: 17448236
24.  UniPep - a database for human N-linked glycosites: a resource for biomarker discovery 
Genome Biology  2006;7(8):R73.
UniPep, a database of human N-linked glycosites is presented as a resource for biomarker discovery
There has been considerable recent interest in proteomic analyses of plasma for the purpose of discovering biomarkers. Profiling N-linked glycopeptides is a particularly promising method because the population of N-linked glycosites represents the proteomes of plasma, the cell surface, and secreted proteins at very low redundancy and provides a compelling link between the tissue and plasma proteomes. Here, we describe UniPep - a database of human N-linked glycosites - as a resource for biomarker discovery.
PMCID: PMC1779586  PMID: 16901351

Results 1-25 (32)