Band 11, Heft 1

The Protein Data Bank (PDB) undergoes an exponential expansion in terms of the number of macromolecular structures deposited every year. A pivotal question is how this rapid growth of structural information improves the quality of three-dimensional models constructed by contemporary bioinformatics approaches. To address this problem, we performed a retrospective analysis of the structural coverage of a representative set of proteins using remote homology detected by COMPASS and HHpred. We show that the number of proteins whose structures can be confidently predicted increased during a 9-year period between 2005 and 2014 on account of the PDB growth alone. Nevertheless, this encouraging trend slowed down noticeably around the year 2008 and has yielded insignificant improvements ever since. At the current pace, it is unlikely that the protein structure prediction problem will be solved in the near future using existing template-based modeling techniques. Therefore, further advances in experimental structure determination, qualitatively better approaches in fold recognition, and more accurate template-free structure prediction methods are desperately needed.

Congo red (CR) and other self-assembling compounds creating supramolecular structures of rod- or ribbon-like architecture form specific complexes with cellulose and also with many proteins, including antibodies bound to the antigen and amyloids in particular. The mechanism of complexation and structure of these complexes are still poorly recognized despite the importance of the problem for medicine. This work proposes the progress in electron microscopy studies of amyloid-dye complexes by labeling supramolecular ligand CR with silver ions as a marker. Silver ions are introduced to CR carried by the strongly binding silver dye Titan yellow, which in addition form comicellar structures with CR. Silver carried by self-assembled dye molecules forms in the resulting metal nanoparticles, making the specific amyloid ligand CR perceptible in EM studies.

Toxicity of the prion molecule is a result of transmission of conformational change by direct contact with malignant misfolded molecule. The aim of this study is analyze the role of D278N mutation in promoting preferential oligomerization modes. Proteins exist as ensembles in equilibrium between different structural and dynamic states, including functionally relevant conformers as the most populated states as well as malfunctioning conformers as less populated states. Furthermore, the existence of different conformations allows protein oligomerization with condition-specific affinities. The maintenance of a particular role requires specific conversion between multiple stable states. Protein-protein binding may facilitate or may be a necessary condition of structural adaptation. In the case of prion disease, protein-protein interactions, resulting in prion agglomeration, have toxic effect. How exactly increased concentrations of prion oligomers trigger mechanisms leading to neuronal death is not known. Nevertheless, first oligomerization and second aggregate recognition are likely sequence of events that have to happen before any pathological condition may arise. Here, we carry out structural and dynamic analyses of the effect of disease-causing mutations on the dimerization and tetramerization of prion molecule as the first step in aggregate formation. D178N mutation has almost no effect on the monomeric structure but helps to stabilize the dimer, which consequently facilitates tetramer formation and stability.

This article deals with the AORTA software system providing support for research activities to find molecular basis for further assessment of individual predisposition to atherosclerosis. These studies are aimed at finding a relationship between somatic mutations of the mitochondrial genome in the aortic wall cells and the extent of atherosclerotic lesions of the aorta. A morphologist selects these areas on an aortic tissue sample and describes them, so that within each area, deviation of the quantitative indicator of atherosclerosis severity (phenotypic marker) from the area average should be sufficiently small. Next, the frequency and severity indicators of somatic mutations of the mitochondrial genome (genetic markers) are measured for each area and then entered into the AORTA system.

In this paper, we presented the problem of predicting response to recombinant human growth hormone (GH) treatment in GH-deficient children. Such a prediction can be done by techniques of mathematical modelling and is important because the therapy consists of daily injections and is expensive; thus, it should be administered only to those patients who will, with high probability, benefit from it. Until now, the leading methodological approach to this problem was multiple regression analysis. Several authors demonstrated that it is possible to derive useful models by this method; however, it has some obvious limitations that can be avoided with the use of the proposed neural network approach.

In this paper, two image processing methods for use in medical image processing based on the level set method are described. The theoretical bases are described and the methods are applied to a set of sample computed tomography images. The results are then compared. The results indicate that the Chan-Vese method is more useful for image segmentation in medicine than the distance-regulated method owing to both the significant differences in calculation time and the quality of results obtained for noisy images.

Skin cancer is the most commonly diagnosed type of cancer in humans regardless of age, gender, or race. One of the most common malignant skin cancers is melanoma, which is a dangerous proliferation of melanocytes. In the last several years, an increasing melanoma incidence has been observed worldwide, and the incidence rate is increasing faster than those of any other skin cancer. The correct identification and diagnosis of moles still creates problems to inexperienced dermatologists and family physicians. In this paper, we present a new approach to the problem of assessing difficult cases in dermatology. We propose a teledermatology system to support the consultation process between family physicians and experts in the field of dermoscopic images. The system consists of a desktop monitoring application and a special smartphone application implemented for experts. If necessary, the physician can send the dermoscopic image to two dermatologists for further examination. This cloud-based architecture provides an interesting system for a fast and efficient exchange of dermatological information. Initial results and assessment of doctors are promising and indicate that the application can be used as a decision support system for dermoscopic images.

Background: This article presents an example application of an e-learning tool for presenting cases with the aim of acquainting medical students with the procedures performed by a court expert in assessing causes and effects of an accident at work. Methods: The present publication is based on medico-legal expertise dealing with the case of a 51-year-old manual worker of a carpentry company who, due to lack of proper training in handling the machine, severely injured his hand. The main advantage of this publication is the presentation of a series of cause-effect events at every stage of the patient’s treatment that led to minor and major complications and adverse effects. Their starting point was the employer’s evident error, i.e., failure to provide the worker with proper training in handling the machine. Results and conclusions: The discussed orthopedic case has been implemented in the CASUS base (mainly using the program “Virtual Patients” as tool for case presentation) in the form of a description of a properly carried out diagnostic procedure and equipped with the expert’s opinion and explanation of possible inappropriate decisions.

This paper reviews the available e-learning applications used in teaching medicine and presents the functionalities of the Web application developed to support classes conducted with the problem-based learning (PBL) method. The application is a form of e-learning platform that allows posting as well as archiving content stored during PBL sessions; it is made up of three modules: the administration module, the teacher module, and the student module. The presented Web application is flexible in operation; it allows designing the number of groups and PBL sessions. The user, apart from using the system during PBL sessions, can access it at any place and time to supplement and update the content. The materials collected during individual PBL sessions constitute sets of content unique for each group because the learning objectives are different for them. With this approach, students can study considerably larger batches of material than it would be possible during classes conducted with other methods.