Automated localisation and boundary identification of superficial femoral artery on MRI sequences

In this paper, an automated method to localise the right superficial femoral artery (SFA) and identify its boundary on magnetic resonance imaging (MRI) sequences without contrast medium injection is proposed. Some anatomical knowledge combined with the mathematical morphology is used to distinguish SFA from other vessels. Afterwards, the directional gradient, continuity and the local contrast are applied as features to identify the artery's boundary using dynamic programming. The accuracy analysis shows that the system has average unsigned errors 3.1 ± 3.1% on five sequences compared to experts' manual tracings.     

Electrocardiogram data mining based on frame classification by dynamic time warping matching

This paper presents an electrocardiogram (ECG) data mining scheme based on the ECG frame classification realised by a dynamic time warping (DTW) matching technique, which has been used successfully in speech recognition. We use the DTW to classify ECG frames because ECG and speech signals have similar non-stationary characteristics. The DTW mapping function is obtained by searching the frame from its end to start. A threshold is setup for DTW matching residual either to classify an ECG frame or to add a new class. Classification and establishment of a template set are carried out simultaneously. A frame is classified into a category with a minimal residual and satisfying a threshold requirement. A classification residual of 1.33% is achieved by the DTW for a 10-min ECG recording.     

Proteomics in translational cancer research: biomarker discovery for clinical applications

This special focus issue of Expert Review of Proteomics invites key opinion leaders to report their recent findings and views on the important topic of translating potential proteomic biomarkers to clinically useful, regulator-approved biomarkers: a challenging journey. The issue also highlights the difficulties associated with and the way forward in the discovery of proteomic cancer biomarkers for clinical applications, as well as presenting recent original research in the field.     

Development and Application of Microsatellites in Candidate Genes Related to Wood Properties in the Chinese White Poplar (Populus tomentosa Carr.)

Gene-derived simple sequence repeats (genic SSRs), also known as functional markers, are often preferred over random genomic markers because they represent variation in gene coding and/or regulatory regions. We characterized 544 genic SSR loci derived from 138 candidate genes involved in wood formation, distributed throughout the genome of Populus tomentosa, a key ecological and cultivated wood production species. Of these SSRs, three-quarters were located in the promoter or intron regions, and dinucleotide (59.7%) and trinucleotide repeat motifs (26.5%) predominated. By screening 15 wild P. tomentosa ecotypes, we identified 188 polymorphic genic SSRs with 861 alleles, 2–7 alleles for each marker. Transferability analysis of 30 random genic SSRs, testing whether these SSRs work in 26 genotypes of five genus Populus sections (outgroup, Salix matsudana), showed that 72% of the SSRs could be amplified in Turanga and 100% could be amplified in Leuce. Based on genotyping of these 26 genotypes, a neighbour-joining analysis showed the expected six phylogenetic groupings. In silico analysis of SSR variation in 220 sequences that are homologous between P. tomentosa and Populus trichocarpa suggested that genic SSR variations between relatives were predominantly affected by repeat motif variations or flanking sequence mutations. Inheritance tests and single-marker associations demonstrated the power of genic SSRs in family-based linkage mapping and candidate gene-based association studies, as well as marker-assisted selection and comparative genomic studies of P. tomentosa and related species.     

Mitochondria and Familial Predisposition to Breast Cancer

Mitochondrial genome and functional alterations are related to various diseases including cancer. In all cases, the role of these organelles is associated with defects in oxidative energy metabolism and control of tumor-induced oxidative stress. The present study examines the involvement of mitochondrial DNA in cancer and in particular in breast cancer. Furthermore, since mitochondrial DNA is maternally inherited, hereditary breast cancer has been focused on.     

Reconstruction of major maternal and paternal lineages of the Cape Muslim population

The earliest Cape Muslims were brought to the Cape (Cape Town - South Africa) from Africa and Asia from 1652 to 1834. They were part of an involuntary migration of slaves, political prisoners and convicts, and they contributed to the ethnic diversity of the present Cape Muslim population of South Africa. The history of the Cape Muslims has been well documented and researched however no in-depth genetic studies have been undertaken. The aim of the present study was to determine the respective African, Asian and European contributions to the mtDNA (maternal) and Y-chromosomal (paternal) gene pool of the Cape Muslim population, by analyzing DNA samples of 100 unrelated Muslim males born in the Cape Metropolitan area. A panel of six mtDNA and eight Y-chromosome SNP markers were screened using polymerase chain reaction-restriction fragment length polymorphisms (PCR-RFLP). Overall admixture estimates for the maternal line indicated Asian (0.4168) and African mtDNA (0.4005) as the main contributors. The admixture estimates for the paternal line, however, showed a predominance of the Asian contribution (0.7852). The findings are in accordance with historical data on the origins of the early Cape Muslims.     

Apolar distal pocket mutants of yeast cytochrome c peroxidase: Hydrogen peroxide reactivity and cyanide binding of the TriAla,TriVal, and TriLeu variants

Three yeast cytochrome c peroxidase (CcP) variants with apolar distal heme pockets have been constructed. The CcP variants have Arg48, Trp51, and His52 mutated to either all alanines, CcP(triAla), all valines, CcP(triVal), or all leucines, CcP(triLeu). The triple mutants have detectable enzymatic activity at pH 6 but the activity is less than 0.02% that of wild-type CcP. The activity loss is primarily due to the decreased rate of reaction between the triple mutants and H₂O₂ compared to wild-type CcP. Spectroscopic properties and cyanide binding characteristics of the triple mutants have been investigated over the pH stability region of CcP, pH 4 to 8. The absorption spectra indicate that the CcP triple mutants have hemes that are predominantly five-coordinate, high-spin at pH 5 and six-coordinate, low-spin at pH 8. Cyanide binding to the triple mutants is biphasic indicating that the triple mutants have two slowly-exchanging conformational states with different cyanide affinities. The binding affinity for cyanide is reduced at least two orders of magnitude in the triple mutants compared to wild-type CcP and the rate of cyanide binding is reduced by four to five orders of magnitude. Correlation of the reaction rates of CcP and 12 distal pocket mutants with H₂O₂ and HCN suggests that both reactions require ionization of the reactants within the distal heme pocket allowing the anion to bind the heme iron. Distal pocket features that promote substrate ionization (basic residues involved in base-catalyzed substrate ionization or polar residues that can stabilize substrate anions) increase the overall rate of reaction with H₂O₂ and HCN while features that inhibit substrate ionization slow the reactions.     

Validation of discrete time-to-event prediction models in the presence of competing risks

Clinical prediction models play a key role in risk stratification, therapy assignment and many other fields of medical decision making. Before they can enter clinical practice, their usefulness has to be demonstrated using systematic validation. Methods to assess their predictive performance have been proposed for continuous, binary, and time-to-event outcomes, but the literature on validation methods for discrete time-to-event models with competing risks is sparse. The present paper tries to fill this gap and proposes new methodology to quantify discrimination, calibration, and prediction error (PE) for discrete time-to-event outcomes in the presence of competing risks. In our case study, the goal was to predict the risk of ventilator-associated pneumonia (VAP) attributed to Pseudomonas aeruginosa in intensive care units (ICUs). Competing events are extubation, death, and VAP due to other bacteria. The aim of this application is to validate complex prediction models developed in previous work on more recently available validation data.