Correlation dimension and entropy in the assessment of sex differences based on human gait data.

Introduction: It is proved that there are differences between gait performed by females and males, which appear in movements of selected body parts. Despite numerous state-of-the-art studies related to the discriminative analysis of motion capture data, the question of whether measures of signal complexity and uncertainty can extract valuable features for the problem of sex distinction still remains open. It is the subject of the paper.

The mutation profile of differentiated thyroid cancer coexisting with undifferentiated anaplastic cancer resembles that of anaplastic thyroid cancer but not that of archetypal differentiated thyroid cancer.

Differentiated thyroid cancer (DTC) has one of the lowest cancer mutational burdens, while anaplastic thyroid cancer (ATC) has a much higher mutation frequency. A fraction of ATC has an associated differentiated component, which suggests the coevolution of both cancers. Here, we aimed to compare mutation frequency in coexisting ATC and DTC diagnosed concurrently in the same thyroid gland (3 cases) as well as in archetypal DTC and ATC alone (5 cases each).

Application of Crowd Simulations in the Evaluation of Tracking Algorithms.

Tracking and action-recognition algorithms are currently widely used in video surveillance, monitoring urban activities and in many other areas. Their development highly relies on benchmarking scenarios, which enable reliable evaluations/improvements of their efficiencies. Presently, benchmarking methods for tracking and action-recognition algorithms rely on manual annotation of video databases, prone to human errors, limited in size and time-consuming.

Application of high field magnetic resonance microimaging in polymer gel dosimetry.

Purpose: The purpose of this work was to examine the suitability of VIPAR polymer gel-9.4 T magnetic resonance microimaging system for high spatial resolution dose distribution measurements.

Methods: The VIPAR samples (3 cm in outside diameter and 12 cm in height) were exposed to ionizing radiation by using a linear accelerator (Varian TrueBeam, USA; 6 MV x-ray beam).

BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm.

Motivation: In contemporary biological experiments, bias, which interferes with the measurements, requires attentive processing. Important sources of bias in high-throughput biological experiments are batch effects and diverse methods towards removal of batch effects have been established. These include various normalization techniques, yet many require knowledge on the number of batches and assignment of samples to batches.

GaMRed-Adaptive Filtering of High-Throughput Biological Data.

Data filtering based on removing non-informative features, with unchanged signal between compared experimental conditions, can significantly increase sensitivity of methods used to detect differentially expressed genes or other molecular components measured in high-throughput biological experiments. Criteria for data filtering can be stated on the basis of averages or variances of signal levels across samples. The crucial parts of feature filtering are selection of filter type and cut-off threshold, which are specific to the particular dataset.

Quality Control Procedure Based on Partitioning of NMR Time Series.

The quality of the magnetic resonance spectroscopy (MRS) depends on the stability of magnetic resonance (MR) system performance and optimal hardware functioning, which ensure adequate levels of signal-to-noise ratios (SNR) as well as good spectral resolution and minimal artifacts in the spectral data. MRS quality control (QC) protocols and methodologies are based on phantom measurements that are repeated regularly. In this work, a signal partitioning algorithm based on a dynamic programming (DP) method for QC assessment of the spectral data is described.

Inertial Motion Capture Costume Design Study.

The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system.

Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers.

Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes.

Coalescence computations for large samples drawn from populations of time-varying sizes.

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset.

Inter-population Differences in Retrogene Loss and Expression in Humans.

Gene retroposition leads to considerable genetic variation between individuals. Recent studies revealed the presence of at least 208 retroduplication variations (RDVs), a class of polymorphisms, in which a retrocopy is present or absent from individual genomes. Most of these RDVs resulted from recent retroduplications.

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry.

Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not allow for automated analyses of whole spectra. Therefore, despite highlighting potential advantages of mixture modeling of mass spectra of peptide/protein mixtures and some preliminary results presented in several papers, the mixture modeling approach was so far not developed to the stage enabling systematic comparisons with existing software packages for proteomic mass spectra analyses.

Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition.

Background: DNA microarrays are used for discovery of genes expressed differentially between various biological conditions. In microarray experiments the number of analyzed samples is often much lower than the number of genes (probe sets) which leads to many false discoveries. Multiple testing correction methods control the number of false discoveries but decrease the sensitivity of discovering differentially expressed genes.

Comparison of peptide cancer signatures identified by mass spectrometry in serum of patients with head and neck, lung and colorectal cancers: association with tumor progression.

Mass spectrometry-based analyses of the low-molecular-weight fraction of serum proteome allow identifying proteome profiles (signatures) that are potentially useful in detection and diagnostics of cancer. Here we compared serum proteome profiles of healthy donors and patients with three different types of cancer aiming to identify peptide signatures that were either common for all cancer samples or specific for cancer type. Blood samples were collected before start of the therapy from patients with head and neck squamous cell cancer, colorectal adenocarcinoma and non-small cell lung cancer, and from a corresponding group of healthy volunteers.

Radiation-related changes in serum proteome profiles detected by mass spectrometry in blood of patients treated with radiotherapy due to larynx cancer.

The study aimed to detect features of human serum proteome that were associated with exposure to ionizing radiation. The analyzed group consisted of 46 patients treated with radical radiotherapy for larynx cancer; patients were irradiated with total doses in a range from 51 to 72 Gy. Three consecutive blood samples were collected from each patient: before the start, 2 weeks after the start, and 4-6 weeks after the end of radiotherapy.

RuleGO: a logical rules-based tool for description of gene groups by means of Gene Ontology.

Genome-wide expression profiles obtained with the use of DNA microarray technology provide abundance of experimental data on biological and molecular processes. Such amount of data need to be further analyzed and interpreted in order to obtain biological conclusions on the basis of experimental results. The analysis requires a lot of experience and is usually time-consuming process.

Association between plasma proteome profiles analysed by mass spectrometry, a lymphocyte-based DNA-break repair assay and radiotherapy-induced acute mucosal reaction in head and neck cancer patients.

Purpose: The plasma proteome was analysed as a potential source of markers of radiosensitivity in patients treated with definitive radiotherapy for head and neck cancer.

Materials And Methods: Acute mucosal reactions that developed during radiotherapy were assessed in 55 patients. Blood samples were collected from each patient before the treatment and also from 50 healthy donors.

BWtrs: A tool for searching for tandem repeats in DNA sequences based on the Burrows-Wheeler transform.

Genomes of organisms contain a variety of repeated structures of various length and type, interspersed or tandem. Tandem repeats play important role in molecular biology as they are related to genetic backgrounds of inherited diseases, and also they can serve as markers for DNA mapping and DNA fingerprinting. Improving the efficiency of algorithms for searching for tandem repeats in DNA sequences can lead to many useful applications in the area of genomics.

Mass spectrometry-based analysis of therapy-related changes in serum proteome patterns of patients with early-stage breast cancer.

Background: The proteomics approach termed proteome pattern analysis has been shown previously to have potential in the detection and classification of breast cancer. Here we aimed to identify changes in serum proteome patterns related to therapy of breast cancer patients.

Methods: Blood samples were collected before the start of therapy, after the surgical resection of tumors and one year after the end of therapy in a group of 70 patients diagnosed at early stages of the disease.

First report on the patient database for the identification of the genetic pathways involved in patients over-reacting to radiotherapy: GENEPI-II.

Background: Identifying the most radiosensitive patient group would have huge clinical implications.

Methods: A tissue bank containing skin fibroblasts, whole blood, lymphocytes, plasma and lymphoblastoid cell lines from clinically radiation hypersensitive patients was established from patients in Europe and Canada. Over-reacting individuals had CTCAE3.

Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer.

Background: Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints) detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry.

Does social-economical transformation influence the incidence of type 1 diabetes mellitus? A Polish example.

Background: The dramatic increase in the incidence of diabetes mellitus type 1 (DMT1) in all countries of Central and Eastern Europe seems to be correlated with the rapid transformations of the political, economical, and social conditions. The aim of this study was to analyze the increase of DMT1 incidence vs. changes of parameters describing economical conditions, medical care standards, and level of hygiene.