Volume 13, Issue 4

The mechanism of specific ligand binding by proteins is discussed using the PDZ domain complexing the pentapeptide. This process is critical for clustering the membrane ion channel. The traditional model based on the Beta-sheet extension by complexed pentapeptide is interpreted as a hydrophobic core extension supported by additional Beta-strand generated by complexed pentapeptide. The explanation is based on the fuzzy oil drop model applied to the crystal structure of PDZ-pentapeptide.

Heme binding by proteins and protein-protein complexation are the processes strongly related to the biological activity of proteins. The mechanism of these processes has not been still recognised. These phenomena are presented using haemoglobin as the example. Half of the mature haemoglobin (one α-chain and one β-chain) treated as a dissociation step in haemoglobin degradation reveals a specific change in heme binding after dissociation. This phenomenon is the object of analysis that interprets the structure of both complexes (tetramer and dimer) with respect to their hydrophobic core structure. The results suggest the higher stability of the complex in the form of one α-chain and one β-chain with respect to the hydrophobic core.

In this article, we describe the applicability of a signal processing method, specifically the modified S-transform (MST) method, on RNA sequences to identify periodicities between 2 and 11. MicroRNAs (miRNA) are associated with gene regulation and gene silencing and thus have wide applications in biological sciences. Also, the functionality of miRNA is highly associated with its secondary structures (stem, bulge and loop). Signal processing methods have been previously applied on genomic data to reveal the periodicities that determine a wide variety of biological functions, ranging from exon detection to microsatellite identification in DNA sequences. However, there has been less focus on RNA-based signal processing. Here, we show that the signal processing method can be successfully applied to miRNA sequences. We observed that these periodicities are highly correlated with the secondary structure of miRNA and such methods could possibly be used as indicators of secondary and tertiary structure formation.

The aim of this article was to show an Electronic Health Record for elderly patients that was prepared for tablets with Android system. The program can be used in case of collecting patient data that comes from the Comprehensive Geriatric Assessment – the multidisciplinary diagnostic tool which is performed among older adults in hospital and outpatient settings. The application was designed for devices with Android system using JellyBean, Kitkat or Lollipop system version. The app allowed to perform, save, edit, view and send survey results. Additionally, it had an option of creating an account with different permission levels. The program was created to facilitate and accelerate the work of a physician who is obliged to complete a Comprehensive Geriatric Assessment card with the patient. It was intended to replace the filling out of a paper questionnaire, in which the doctor must personally sum up all the results, with a tool that will be available on tablets and which enables to complete and evaluate the results of medical examination faster than during performing the questionnaire in a traditional way.

Background: Clinical Text Analysis and Knowledge Extraction System (cTAKES) is an open-source natural language processing (NLP) system. In recent development modules of cTAKES, a negation detection (ND) algorithm is used to improve annotation capabilities and simplify automatic identification of negative context in large clinical documents. In this research, the two types of ND algorithms used are lexicon and syntax, which are analyzed using a database made openly available by the National Center for Biomedical Computing. The aim of this analysis is to find the pros and cons of these algorithms. Methods: Patient medical reports were collected from three institutions included the 2010 i2b2/VA Clinical NLP Challenge, which is the input data for this analysis. This database includes patient discharge summaries and progress notes. The patient data is fed into five ND algorithms: NegEx, ConText, pyConTextNLP, DEEPEN and Negation Resolution (NR). NegEx, ConText and pyConTextNLP are lexicon-based, whereas DEEPEN and NR are syntax-based. The results from these five ND algorithms are post-processed and compared with the annotated data. Finally, the performance of these ND algorithms is evaluated by computing standard measures including F-measure, kappa statistics and ROC, among others, as well as the execution time of each algorithm. Results: This research is tested through practical implementation based on the accuracy of each algorithm’s results and computational time to evaluate its performance in order to find a robust and reliable ND algorithm. Conclusions: The performance of the chosen ND algorithms is analyzed based on the results produced by this research approach. The time and accuracy of each algorithm are calculated and compared to suggest the best method.

Ferroportin (Fpn) is a membrane protein representing the major cellular iron exporter, essential for metal translocation from cells into plasma. Despite its pivotal role in human iron homeostasis, many questions on Fpn structure and biology remain unanswered. In this work, we present two novel and more reliable structural models of human Fpn (hFpn; inward-facing and outward-facing conformations) obtained using as templates the recently solved crystal structures of a bacterial homologue of hFpn, Bdellovibrio bacteriovorus Fpn. In the absence of an experimentally solved structure of hFpn, the structural predictions described here allow to analyze the role of pathogenic mutations in the Fpn-linked hereditary hemochromatosis disease and represent a valuable alternative for reliable structure-based functional studies on this human iron exporter.