Medical University of Varna

About: Medical University of Varna is a education organization based out in Varna, Varna, Bulgaria. It is known for research contribution in the topics: Population & Medicine. The organization has 1199 authors who have published 1273 publications receiving 32940 citations. The organization is also known as: MU-Varna & Higher Medical Institute of Varna.

Perceived challenges to public health in Central and Eastern Europe: a qualitative analysis

Abstract: There is a major gradient in burden of disease between Central and Eastern Europe compared to Western Europe. Many of the underlying causes and risk factors are amenable to public health interventions. The purpose of the study was to explore perceptions of public health experts from Central and Eastern European countries on public health challenges in their countries. We invited 179 public health experts from Central and Eastern European countries to a 2-day workshop in Berlin, Germany. A total of 25 public health experts from 14 countries participated in May 2008. The workshop was structured into 8 sessions of 1.5 hours each, with the topic areas covering coronary heart disease, stroke, prevention, obesity, alcohol, tobacco, tuberculosis, and HIV/AIDS. The workshop was recorded and the proceedings transcribed verbatim. The transcripts were entered into atlas.ti for content analysis and coded according to the session headings. After analysis of the content of each session discussion, a re-coding of the discussions took place based on the themes that emerged from the analysis. Themes discussed recurred across disease entities and sessions. Major themes were the relationship between clinical medicine and public health, the need for public health funding, and the problems of proving the effectiveness of disease prevention. Areas for action identified included the need to engage with the public, to create a better scientific basis for public health interventions, to identify “best practices” of disease prevention, and to implement registries/surveillance instruments. The need for improved data collection was seen throughout all areas discussed, as was the need to harmonize data across countries. To reduce the burden of disease across Europe, closer collaboration of countries across Europe seems important in order to learn from each other. A more credible scientific basis for effective public health interventions is urgently needed. The monitoring of health trends is crucial to evaluate the impact of public health programmes.

Dataset of patient-derived digital breast phantoms for in silico studies in breast computed tomography, digital breast tomosynthesis, and digital mammography.

Abstract: PURPOSE To present a dataset of computational digital breast phantoms derived from high-resolution three-dimensional (3D) clinical breast images for the use in virtual clinical trials in two-dimensional (2D) and 3D x-ray breast imaging. ACQUISITION AND VALIDATION METHODS Uncompressed computational breast phantoms for investigations in dedicated breast CT (BCT) were derived from 150 clinical 3D breast images acquired via a BCT scanner at UC Davis (California, USA). Each image voxel was classified in one out of the four main materials presented in the field of view: fibroglandular tissue, adipose tissue, skin tissue, and air. For the image classification, a semi-automatic software was developed. The semi-automatic classification was compared via manual glandular classification performed by two researchers. A total of 60 compressed computational phantoms for virtual clinical trials in digital mammography (DM) and digital breast tomosynthesis (DBT) were obtained from the corresponding uncompressed phantoms via a software algorithm simulating the compression and the elastic deformation of the breast, using the tissue's elastic coefficient. This process was evaluated in terms of glandular fraction modification introduced by the compression procedure. The generated cohort of 150 uncompressed computational breast phantoms presented a mean value of the glandular fraction by mass of 12.3%; the average diameter of the breast evaluated at the center of mass was 105 mm. Despite the slight differences between the two manual segmentations, the resulting glandular tissue segmentation did not consistently differ from that obtained via the semi-automatic classification. The difference between the glandular fraction by mass before and after the compression was 2.1% on average. The 60 compressed phantoms presented an average glandular fraction by mass of 12.1% and an average compressed thickness of 61 mm. DATA FORMAT AND ACCESS The generated digital breast phantoms are stored in DICOM files. Image voxels can present one out of four values representing the different classified materials: 0 for the air, 1 for the adipose tissue, 2 for the glandular tissue, and 3 for the skin tissue. The generated computational phantoms datasets were stored in the Zenodo public repository for research purposes (http://doi.org/10.5281/zenodo.4529852, http://doi.org/10.5281/zenodo.4515360). POTENTIAL APPLICATIONS The dataset developed within the INFN AGATA project will be used for developing a platform for virtual clinical trials in x-ray breast imaging and dosimetry. In addition, they will represent a valid support for introducing new breast models for dose estimates in 2D and 3D x-ray breast imaging and as models for manufacturing anthropomorphic physical phantoms.

Students adaptation to the educational environment - stages and activities

Abstract: The process of adaptation to the conditions of the university education is important for the successful acquisition of a knowledge and skills for the future profession. Expansion of social behaviour between students, correct relationships with teachers and the formation of the feeling that they are a part of the academic community contribute to greater motivation and ease in the overall process about acquiring new professional competencies. This article presents the development of the understanding of adaptation of students to the educational environment, stages and activities for adaptation to the new academic way of life.

Brain-derived neurotrophic factor: a new adipokine

Abstract: Since leptin discovery in 1994, an extensive body of work has been demonstrating that adipose tissue (mainly its white phenotype) expresses not only metabolic, but also endocrine and paracrine phenotypes, particularly in adipobiology of disease. This new biology is achieved predominantly through secretion of adipokines, which include more than hundred highly active signaling proteins. However, studies on adipobiology of neurotrophins have recently emerged, nerve growth factor being one example of adipose-derived neurotrophins. Here we present data showing that brain-derived neurotrophic factor is also expressed in both white and brown adipose tissue. Biomedical Reviews 2007; 18: 85-88.