@article{nokey,

title = {On the Dependence of Prion and Amyloid Structure on the Folding Environment},

author = {Irena Roterman and Katarzyna Stapor and Krzysztof G\k{a}dek and Tomasz Guba\la and Piotr Nowakowski and Piotr Fabian and Leszek Konieczny

},

url = {https://www.mdpi.com/1422-0067/22/24/13494},

doi = {https://www.mdpi.com/1422-0067/22/24/13494},

year  = {2021},

date = {2021-12-16},

urldate = {2021-12-16},

journal = {International Journal of Molecule Sciences},

abstract = {Currently available analyses of amyloid proteins reveal the necessity of the existence of radical structural changes in amyloid transformation processes. The analysis carried out in this paper based on the model called fuzzy oil drop (FOD) and its modified form (FOD-M) allows quantifying the role of the environment, particularly including the aquatic environment. The starting point and basis for the present presentation is the statement about the presence of two fundamentally different methods of organizing polypeptides into ordered conformations\textemdashglobular proteins and amyloids. The present study shows the source of the differences between these two paths resulting from the specificity of the external force field coming from the environment, including the aquatic and hydrophobic one. The water environment expressed in the fuzzy oil drop model using the 3D Gauss function directs the folding process towards the construction of a micelle-like system with a hydrophobic core in the central part and the exposure of polarity on the surface. The hydrophobicity distribution of membrane proteins has the opposite characteristic: Exposure of hydrophobicity at the surface of the membrane protein with an often polar center (as in the case of ion channels) is expected. The structure of most proteins is influenced by a more or less modified force field generated by water through the appropriate presence of a non-polar (membrane-like) environment. The determination of the proportion of a factor different from polar water enables the assessment of the protein status by indicating factors favoring the structure it represents. View Full-Text

},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Current Trends in Software Engineering Bachelor Theses},

author = {Jacek Dajda and Micha\l Idzik and Jakub Sroka and Miko\laj Sikora Wiktor Paw\lowski and Maciej Smo lka and Przemys\law Jab\lecki and Filip \'{S}lazyk and Maciej Malawski and Emilia Majerz and Aleksandra Pasternak and Witold Dzwinel

},

url = {https://doi.org/10.31577/cai_2021_4_930

},

doi = {https://doi.org/10.31577/cai_2021_4_930},

year  = {2021},

date = {2021-12-14},

journal = {Computing and Informatics},

abstract = {This article presents short analysis and observations on current trends and directions in conducting engineering theses in the field of computer science. This report is based on collected bachelor theses in AGH Computer Science Department for academic year 2020/2021 as well as the conducted competition for the best engineering theses held during XXII KKIO 2021 Software Engineering Conference. The awarded works are briefly presented as an illustration to the drawn conclusions.



},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Preface to the Special Issue on Software Engineering},

author = {Bubak, M. and Malawski, M. and S\lota, R. G. },

url = {https://www.cai.sk/ojs/index.php/cai/article/view/2021_4_729/1101},

doi = {https://doi.org/10.31577/cai_2021_4_729},

year  = {2021},

date = {2021-12-14},

journal = {Vol. 40 No. 4 (2021): Computing and Informatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Context in medical imaging: the case of focal liver lesion classification},

author = {Moshe Raboh and Dana Levanony and Paul Dufort and Arkadiusz Sitek},

url = {https://spie.org/medical-imaging/presentation/Context-in-medical-imaging--the-case-of-focal-liver/12032-21},

year  = {2021},

date = {2021-10-28},

urldate = {2021-10-28},

journal = {Physics of Medical Imaging},

abstract = {There are many different sources of information beyond the actual images that serve to inform radiologists when they are making diagnoses. To better utilize and explore the power of context in medical imaging we developed a classification algorithm based on convolutional neural networks with various contexts to classify liver lesions in multi-phase computed tomography. We designed an algorithm, to efficiently handle 3D context, clinical context, and co-occurrences context considering the presence or absence of other lesions in the volume to inform classification of a lesion under consideration. Our evaluation demonstrates that this novel algorithm substantially improves classification results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Licho\lai2021,

title = {MiR-191 as a Key Molecule in Aneurysmal Aortic Remodeling },

author = {Sabina Licho\lai and Dorota Studzi\'{n}ska and Hanna Plutecka and Tomasz Guba\la and Wojciech Szczeklik and Marek Sanak},

url = {https://doi.org/10.3390/biom11111611

},

doi = {https://doi.org/10.3390/biom11111611},

year  = {2021},

date = {2021-08-17},

urldate = {2021-08-17},

journal = {Biomolecules},

abstract = {Abdominal aortic aneurysms (AAA) are a complex disease with an unclear pathomechanism. A positive family history is emphasized as a significant risk factor, and a nonspecific model of inheritance suggests participation of epigenetic regulation in the pathogenesis of this disease. Past studies have implicated microRNAs in the development of AAA; therefore in this project, we measured miR-191 levels in AAA patients and compared them with a control group. We found that miR-191 levels were significantly elevated in aneurysmal patients, although this did not correlate with the available clinical data. We then developed an in vitro model where, using cells with an endothelial phenotype, we determined the effect of miR-191 on the transcriptome using RNA sequencing. Subsequent pathway analysis established that some of the perturbations mediated by miR-191 can be explained by several processes which have long been observed and described in literature as accompanying the development of abdominal aortic aneurysms. View Full-Text

},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kara2021,

title = {An integrated genomic approach to dissect the genetic landscape regulating the cell-to-cell transfer of α-synuclein},

author = {Eleanna Kara and Alessandro Crimi and Anne Wiedmer and John Hardy and Bradley T. Hyman and Adriano Aguzzi},

doi = {https://doi.org/10.1016/j.celrep.2021.109189},

year  = {2021},

date = {2021-06-08},

urldate = {2021-06-08},

abstract = {Neuropathological and experimental evidence suggests that the cell-to-cell transfer of α-synuclein has an important role in the pathogenesis of Parkinson’s disease (PD). However, the mechanism underlying this phenomenon is not fully understood. We undertook a small interfering RNA (siRNA), genome-wide screen to identify genes regulating the cell-to-cell transfer of α-synuclein. A genetically encoded reporter, GFP-2A-αSynuclein-RFP, suitable for separating donor and recipient cells, was transiently transfected into HEK cells stably overexpressing α-synuclein. We find that 38 genes regulate the transfer of α-synuclein-RFP, one of which is ITGA8, a candidate gene identified through a recent PD genome-wide association study (GWAS). Weighted gene co-expression network analysis (WGCNA) and weighted protein-protein network interaction analysis (WPPNIA) show that those hits cluster in networks that include known PD genes more frequently than expected by random chance. The findings expand our understanding of the mechanism of α-synuclein spread.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bubak2021,

title = {The EurValve model execution environment},

author = {M Bubak and K Czechowicz and T Guba\la and D R Hose and M Kasztelnik and M Malawski and J Meizner and P Nowakowski and S Wood},

url = {https://royalsocietypublishing.org/doi/10.1098/rsfs.2020.0006},

doi = {10.1098/rsfs.2020.0006},

issn = {2042-8898},

year  = {2021},

date = {2021-02-01},

urldate = {2021-02-01},

journal = {Interface Focus},

volume = {11},

number = {1},

pages = {20200006},

abstract = {The goal of this paper is to present a dedicated high-performance computing (HPC) infrastructure which is used in the development of a so-called reduced-order model (ROM) for simulating the outcomes of interventional procedures which are contemplated in the treatment of valvular heart conditions. Following a brief introduction to the problem, the paper presents the design of a model execution environment, in which representative cases can be simulated and the parameters of the ROM fine-tuned to enable subsequent deployment of a decision support system without further need for HPC. The presentation of the system is followed by information concerning its use in processing specific patient cases in the context of the EurValve international collaboration.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {AI \& COVID-19},

author = {Davide Bacciu and Emanuela Girardi and Marco Maratea and Jose Sousa

},

url = {https://content.iospress.com/download/intelligenza-artificiale/ia210121?id=intelligenza-artificiale%2Fia210121},

doi = {DOI 10.3233/IA-210121},

year  = {2021},

date = {2021-01-21},

journal = {Intelligenza Artificiale},

abstract = {The COVID-19 pandemic has influenced our lives significantly since March 2020, and a number of initiatives have

been put forward in order to tackle its effects, including those focused on technological solutions. In this paper, we present

one of such initiatives, i.e. the CLAIRE’s taskforce on AI and COVID-19, in which Artificial Intelligence methodologies and

tools are being developed to help the society contrasting the pandemic. We present the different lines of development within

the taskforce, some fields in which they are used, and draw few recommendations},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sitek2021artificial,

title = {Artificial Intelligence in PET: an Industry Perspective},

author = {Arkadiusz Sitek and Sangtae Ahn and Evren Asma and Adam Chandler and Alvin Ihsani and Sven Prevrhal and Arman Rahmim and Babak Saboury and Kris Thielemans},

url = {https://arxiv.org/abs/2107.06747},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {PET Clinics},

abstract = {Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has the ability to enhance and optimize all aspects of the PET imaging chain from patient scheduling, patient setup, protocoling, data acquisition, detector signal processing, reconstruction, image processing and interpretation. AI poses industry-specific challenges which will need to be addressed and overcome to maximize the future potentials of AI in PET. This paper provides an overview of these industry-specific challenges for the development, standardization, commercialization, and clinical adoption of AI, and explores the potential enhancements to PET imaging brought on by AI in the near future. In particular, the combination of on-demand image reconstruction, AI, and custom designed data processing workflows may open new possibilities for innovation which would positively impact the industry and ultimately patients.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}