Wyniki wyszukiwania - BazTech

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Aminokwasy, glikany, peptydy i białka w ścieżkach diagnostycznych i terapeutycznych chorób cywilizacyjnych XXI wieku : projektowanie i charakterystyka fizykochemiczna oraz strukturalna

Bylińska Irena, Dzierżyńska Maria, Giżyńska Małgorzata, Guzow Katarzyna, Jankowska Elżbieta, Jurczak Przemysław, Kaczyński Zbigniew, Karska Natalia, Kowalczyk Agnieszka, Kuncewicz Katarzyna, Orlikowska Marta, Sawicka Justyna, Spodzieja Marta, Szpakowska Nikola, Szymańska Aneta, Wieczerzak Ewa, Witkowska Julia, Rodziewicz-Motowidło Sylwia

Wiadomości Chemiczne

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2022

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[Z] 76, 5-6

393--431

EN

The civilization diseases of the 21st century are non-infectious disorders, affecting a large part of modern society. They are associated with the significant development of industry and technology, and hence with environmental pollution and an unhealthy lifestyle. These factors have led to the development of many civilization diseases, which currently include: cardiovascular diseases, respiratory diseases, diabetes, obesity, malignant tumors, gastrointestinal diseases, mental disorders and allergic diseases. The development of technologies, including modern therapies and new drugs, resulted in increase in life expectancy. This creates a global problem of an aging population with an increasing number of diseases of the old age, i.e. dementias. In addition, sedentary lifestyles and changing diets are the reasons why more and more people develop metabolic diseases, as well as neurological and cognitive disorders characterized by progressive damage to nerve cells and dementia. Currently, problem on a global scale is also the growing resistance to existing antimicrobial drugs. Therefore, the scientists face many challenges related to searching for the causes of these diseases, their diagnosis and treatment. Scientific research conducted at the Department of Biomedical Chemistry at the Faculty of Chemistry of the University of Gdańsk is part of this research trend. In this publication, we discuss various research topics with the long-term aim of solving the problems associated with the diseases mentioned above. The following chapters are dedicated to (i) looking for new effective fluorophores with diagnostic and anti-cancer activity; (ii) designing of new compounds with antibacterial and antiviral activity and their synthesis; (iii) investigating the mechanisms of amyloid deposit formation by human cystatin C and possibilities of inhibition of this process; (iv) designing and studies of compounds activating the proteasome with the potential to suppress the development of neurodegenerative diseases; (v) designing peptide fibrils and hydrogels as drug carriers; (vi) searching for peptide inhibitors of immune checkpoint as potential drugs for immunotherapy; (vii) studying the mechanism of action of selected herpesviruses by determining the structure of viral proteins and (viii) studying the composition of natural glycans and glycoconjugates in order to better understand the mechanisms of interaction of bacteria with the environment or with the host.

2

The selection of wart treatment method based on Synthetic Minority Over-sampling Technique and Axiomatic Fuzzy Set theory

Jia Wenjuan, Xia Hao, Jia Lijuan, Deng Yingjie, Liu Xiaodong

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

517--526

EN

Wart disease is a kind of skin illness that is caused by Human Papillomavirus (HPV). Many medical studies are being carried out with the aid of machine learning and data mining techniques to find the most appropriate and effective treatment for a specific wart patient. However, the imbalanced distribution of medical data may lead to misclassification in this field. The purpose of this paper is to propose a algorithm to predict the response of the patients towards a specific treatment and choose an appropriate treatment method. In this paper, Synthetic Minority Over-sampling (SMOTE) method is adopted to deal with the unbalanced data and combined with Axiomatic Fuzzy Set (AFS) theory to predict whether patients can respond to treatment or not. Compared with other existing approaches, the proposed approach can provide descriptive information of the patients which can help to predict the response towards the treatment with an average prediction accuracy of 97.63% and 92.33% for cryotherapy and immunotherapy data, respectively. Furthermore, the ex-perimental results demonstrate that it can assist doctors in treatment, save medical resources and improve the quality of treatment.

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Deep learning of the role of interleukin IL-17 and its action in promoting cancer

Nutini Alessandro, Sohail Ayesha

Bio-Algorithms and Med-Systems

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2020

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Vol. 16, no. 4

art. no. 20200052

EN

In breast cancer patients, metastasis remains a major cause of death. The metastasis formation process is given by an interaction between the cancer cells and the microenvironment that surrounds them. In this article, we develop a mathematical model that analyzes the role of interleukin IL-17 and its action in promoting cancer and in facilitating tissue metastasis in breast cancer, using a dynamic analysis based on a stochastic process that accounts for the local and global action of this molecule. The model uses the Ornstein-Uhlembeck and Markov process in continuous time. It focuses on the oncological expansion and the interaction between the interleukin IL-17 and cell populations This analysis tends to clarify the processes underlying the metastasis expansion mechanism both for a better understanding of the pathological event and for a possible better control of therapeutic strategies. IL-17 is a proinflammatory interleukin that acts when there is tissue damage or when there is a pathological situation caused by an external pathogen or by a pathological condition such as cancer. This research is focused on the role of interleukin IL-17 which, especially in the case of breast cancer, turns out to be a dominant “communication pin” since it interconnects with the activity of different cell populations affected by the oncological phenomenon. Stochastic modeling strategies, specially the Ornstein-Uhlenbeck process, with the aid of numerical algorithms are elaborated in this review. The role of IL-17 is discussed in this manuscript at all the stages of cancer. It is discussed that IL-17 also acts as “metastasis promoter” as a result of its proinflammatory nature. The stochastic nature of IL-17 is discussed based on the evidence provided by recent literature. The resulting dynamical analysis can help to select the most appropriate therapeutic strategy. Cancer cells, in the case of breast cancer, have high level of IL-17 receptors (IL-17R); therefore the interleukin itself has direct effects on these cells. Immunotherapy research, focused on this cytokine and interlinked with the stochastic modeling, seems to be a promising avenue.

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Predicting the success of wart treatment methods using decision tree based fuzzy informative images

Akben S. B.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 4

819--827

EN

Warts are small, rough, benign tumours caused by human papillomavirus (HPV). A challenge is predicting the success of wart treatment methods because success may vary depending on the patient and the features of disease. Recently, a machine learning based expert prediction system and related prediction rules were proposed. However, the success of this system is not satisfactory and should be improved. Furthermore, medical experts find it difficult to interpret the suggested rules of this system. The decision tree-based method was accordingly used in this study to determine the rules of predicting the success of wart treatment methods. According to findings, the success rate varied from 90 to 95% according to the treatment method; these rates are higher than previously reported. Furthermore, the decision tree rules that were determined can be transformed into images to visually interpret the success rates of treatment methods as a function of patient age and the time elapsed since disease appearance. This study provides a method for simple and more accurate interpretation of rules for medical experts. The success of treatment methods is now predictable as a percentage.

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Aspekty immunologiczne terapii fotodynamicznej

Kawczyk-Krupka A., Czuba Z., Latos W., Mertas A., Król W., Simon-Sieroń M., Sieroń A.

Journal of Ecology and Health

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2010

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R. 14, nr 6

284-290

PL

Terapia fotodynamiczna (photodynamic therapy - PDT) jest metodą leczenia wybranych (przede wszystkim wczesnych) nowotworów i stanów przednowotworowych. Istotą tej metody jest selektywne niszczenie zmienionych chorobowo tkanek poprzez zadziałanie na nie światła laserowego o ściśle określonej długości fali. Zjawisko to umożliwia substancja - fotouczulacz, wychwytywana przez chorobowo zmienioną tkankę. Standardowo stosowanymi fouczulaczami są porfiryny, które są komponentą hemoglobiny. Działanie fotodynamiczne wywołuje trzy typy reakcji w naświetlanej tkance: bezpośredni efekt cytotoksyczny, pośredni efekt cytotoksyczny przez okluzję naczyń krwionośnych oraz wtórne działanie immunostymulujące i prozapalne. Spośród wymienionych sposobów działania, efekt immunostymulujący wydaje się być unikalny, zważywszy, że zarówno chemio- jak i radioterapia powodują upośledzenie funkcji układu immunologicznego. Wiele prac doświadczalnych wykazało, iż w trakcie terapii fotodynamicznej dochodzi do mobilizacji komórek immunokompetentnych: nacieku limfocytów, neutrofili, makrofagów, co wskazuje na aktywację procesu zapalnego. Mediatorami tego procesu są substancje wazoaktywne, składniki C3 dopełniacza, białka ostrej fazy, proteinazy, peroksydazy, reaktywne formy tlenu, cytokiny, czynniki wzrostu oraz inne substancje biorące udział w odpowiedzi immunologicznej. Podkreśla się, iż immunomodulacyjny efekt terapii fotodynamicznej związany jest także z wpływem na angiogenezę i aktywność metastatyczną komórek nowotworowych.

EN

Photodynamic therapy (PDT) is a well-known method for the selective, non-invasive and effective treatment of precancerous and cancerous lesions due to the activation of photobiochemical processes that cause cytotoxicity. PDT is based on mutual reactions between laser irradiation and photosensitizers that accumulate in tissues and result in selective damage of pathological tissues. The anticancer effect of PDT is due to three main mechanisms. First, PDT is cytotoxic, with both necrotic and apoptotic effects. Second, PDT leads to the occlusion of blood and lymphatic vessels of the tumor. Third, PDT is associated with the modulation of immune and inflammatory responses. In addition to these mechanisms of cell death, there is a variety of events that occur during PDT that lead to and magnify the inactivation of tumor cells. Many studies have reported the infiltration of lymphocytes, neutrophils and macrophages into PDT-treated tissue, indicating activation of the immune response. The inflammatory process is mediated by factors such as vasoactive substances, components of the complement and clotting cascades, acute phase proteins, proteinases, peroxidases, reactive oxygen species, leukocyte chemoattractants, cytokines, growth factors and other immunoregulators. It is possible that immunomodulatory mechanisms of PDT could also influence angiogenesis and the invasiveness of tumor cells.

6

Szczepionka na raka. Czy to możliwe?

Ząbek M.

Laboratorium - Przegląd Ogólnopolski

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2007

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nr 3

50--52

PL

Wzrastająca zachorowalność i umieralność na choroby nowotworowe oraz brak satysfakcjonujących wyników stosowanych obecnie metod chemioterapii sprawia, iż nadal poszukiwane są nowe, skuteczne sposoby leczenia. Do szczególnie atrakcyjnych należy immunoterapia. Oferuje możliwość stosowania selektywnych i precyzyjnych terapeutyków, rozpoznających antygeny swoiste dla nowotworów. Obecnie trwają badania nad skutecznością wykorzystywania komórek dendrytycznych, nieswoistych limfocytów, limfocytów stymulowanych antygenami nowotworowymi, szczepionek przeciwnowotworowych , immunocytokin, przeciwciał, biologicznych modyfikatorów odpowiedzi. Wyniki terapii są niejednoznaczne, wymagają prowadzenia dalszych prac badawczych. Wobec braku wiedzy na temat uniwersalnego mechanizmu transformacji nowotworowej stworzenie jednego, idealnego leku czy szczepionki przeciwnowotworowej wydaje się jeszcze mało prawdopodobne.

EN

Continously growing incidence and mortality from malig sisease and still unsatisfying results of current standards of motherapy induce intensive research of new effective therapy. Among them immunotherapy seems to be particullary attractive using dendritic cells, T cells, cancer vaccines, immunucytokines, antibodies, biological response modifiers. It gives opportunity to create selective therapeutics working by recognizing cancer specific antigens. Since the universal mechanism of cancerogenic is still unknown, construction if ideal anticancer therapeutic vaccine hardly seems to be possible and needs further investigations.

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Nowa era przeciwciał monoklonalnych

Bednarek I.

Laboratorium - Przegląd Ogólnopolski

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2006

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nr 8-9

63--64

PL

Od czasu opracowania techniki fucji komórek tworzenie hybrydom produkujących przeciwciała monoklonalne stało się podstawowym źródłem syntezy wysocespecyficznych cząsteczek immunoglobulin, skierowanych przeciwko wybranemu antygenowi. Przeciwciała monoklonalne wprowadzono zarówno do badań podstawowych, diagnostyki, jak i terapii. Zastosowanie przeciwciał monoklonalnych w terapii wymusiło opracowanie bardziej wyszukanych metod syntezy - zadaniem stało się otrzymanie przeciwciał nie tylko specyficznych, ale maksymalnie zbliżonych strukturą do przeciwciał ludzkich. Tak powstały przeciwciała chimeryczne czy humanizowane, otrzymywane drogą inżynierii genetycznej.

EN

Starting from the day, when cell fusions technique was established, hybridoma cells producing monoclonal antibodies became main source of highly specific immunoglobulin directed against chosen antigen. Recently monoclonal antibodies are introduced into research area, diagnostic and therapy as well. Application of monoclonal antibodies into therapy demands approaching much more sophisicated methods of immunoglobulin synthesis. The aim is synthesis of monoclonal antibodies not only highly specific, but also structurally the closest to the structure of human antibodies. That is how using genetic engineering methods chimeric and humanized monoclonal antibodies were synthesized.

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Modelling Tumour-Immunity Interactions With Different Stimulation Functions

Zhivkov P., Waniewski J.

International Journal of Applied Mathematics and Computer Science

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2003

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Vol. 13, no 3

307-315

EN

Tumour immunotherapy is aimed at the stimulation of the otherwise inactive immune system to remove, or at least to restrict, the growth of the original tumour and its metastases. The tumour-immune system interactions involve the stimulation of the immune response by tumour antigens, but also the tumour induced death of lymphocytes. A system of two non-linear ordinary differential equations was used to describe the dynamic process of interaction between the immune system and the tumour. Three different types of stimulation functions were considered: (a) Lotka-Volterra interactions, (b) switching functions dependent on the tumour size in the Michaelis-Menten form, and (c) Michaelis-Menten switching functions dependent on the ratio of the tumour size to the immune capacity. The linear analysis of equilibrium points yielded several different types of asymptotic behaviour of the system: unrestricted tumour growth, elimination of tumour or stabilization of the tumour size if the initial tumour size is relatively small, otherwise unrestricted tumour growth, global stabilization of the tumour size, and global elimination of the tumour. Models with switching functions dependent on the tumour size and the tumour to the immune capacity ratio exhibited qualitatively similar asymptotic behaviour.

9

Mathematical Modeling of the Competition Between Acquired Immunity and Cancer

Kolev M.

International Journal of Applied Mathematics and Computer Science

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2003

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Vol. 13, no 3

289-296

EN

In this paper we propose and analyse a model of the competition between cancer and the acquired immune system. The model is a system of integro-differential bilinear equations. The role of the humoral response is analyzed. The simulations are related to the immunotherapy of tumors with antibodies.