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Öğe Modeling tumor growth using fractal calculus: Insights into tumor dynamics(Elsevier Ireland Ltd, 2024) Golmankhaneh, Amirreza Khalili; Tunç, Sümeyye; Schlichtinger, Agnieszka Matylda; Asanza, Dachel Martinez; Golmankhaneh, Alireza KhaliliImportant concepts like fractal calculus and fractal analysis, the sum of squared residuals, and Aikaike's information criterion must be thoroughly understood in order to correctly fit cancer-related data using the proposed models. The fractal growth models employed in this work are classified in three main categories: Sigmoidal growth models (Logistic, Gompertz, and Richards models), Power Law growth model, and Exponential growth models (Exponential and Exponential-Lineal models)”. We fitted the data, computed the sum of squared residuals, and determined Aikaike's information criteria using Matlab and the web tool WebPlotDigitizer. In addition, the research investigates “double-size cancer” in the fractal temporal dimension with respect to various mathematical models.Öğe Furin and the adaptive mutation of SARS-COV2: A computational framework(Springer Heidelberg, 2022) Sohail, Ayesha; Tunç, Sümeyye; Nutini, Alessandro; Arif, RobiaSARS-2 virus has reached its most harmful mutated form and has damaged the world's economy, integrity, health system and peace to a limit. An open problem is to address the release of antibodies after the infection and after getting the individuals vaccinated against the virus. The viral fusion process is linked with the furin enzyme and the adaptation is linked with the mutation, called D614G mutation. The cell-protein studies are extremely challenging. We have developed a mathematical model to address the process at the cell-protein level and the delay is linked with this biological process. Genetic algorithm is used to approximate the parametric values. The mathematical model proposed during this research consists of virus concentration, the infected cells count at different stages and the effect of interferon. To improve the understanding of this model of SARS-CoV2 infection process, the action of interferon (IFN) is quantified using a variable for the non-linear mathematical model, that is based on a degradation parameter gamma. This parameter is responsible for the delay in the dynamics of this viral action. We emphasize that this delay responds to the evasion by SARS-CoV2 via antagonizing IFN production, inhibiting IFN signaling and improving viral IFN resistance. We have provided videos to explain the modeling scheme.Öğe Forecasting the action of CAR-T cells against SARS-corona virus-II infection with branching process(Springer Heidelberg, 2022) Al-Utaibi, Khaled A.; Nutini, Alessandro; Sohail, Ayesha; Arif, Robia; Tunç, Sümeyye; Sait, Sadiq M.The CAR-T cells are the genetically engineered T cells, designed to work specifically for the virus antigens (or other antigens, such as tumour specific antigens). The CAR-T cells work as the living drug and thus provides an adoptive immunotherapy strategy. The novel corona virus treatment and control designs are still under clinical trials. One of such techniques is the injection of CAR-T cells to fight against the COVID-19 infection. In this manuscript, the hypothesis is based on the CAR-T cells, that are suitably engineered towards SARS-2 viral antigen, by the N protein. The N protein binds to the SARS-2 viral RNA and is found in abundance in this virus, thus for the engineered cell research, this protein sequence is chosen as a potential target. The use of the sub-population of T-reg cells is also outlined. Mathematical modeling of such complex line of action can help to understand the dynamics. The modeling approach is inspired from the probabilistic rules, including the branching process, the Moran process and kinetic models. The Moran processes are well recognized in the fields of artificial intelligence and data science. The model depicts the infectious axis “virus—CAR-T cells—memory cells”. The theoretical analysis provides a positive therapeutic action; the delay in viral production may have a significant impact on the early stages of infection. Although it is necessary to carefully evaluate the possible side effects of therapy. This work introduces the possibility of hypothesizing an antiviral use by CAR-T cells.Öğe Modeling the crossover behavior of the bacterial infection with the COVID-19 epidemics(Elsevier B.V., 2022) Yu, Zhenhua; Sohail, Ayesha; Arif, Robia; Nutini, Alessandro; Nofal, Taher A.; Tunç, SümeyyeTo explore the crossover linkage of the bacterial infections resulting from the viral infection, within the host body, a computational framework is developed. It analyzes the additional pathogenic effect of Streptococcus pneumonia, one of the bacteria that can trigger the super-infection mechanism in the COVID-19 syndrome and the physiological effects of innate immunity for the control or eradication of this bacterial infection. The computational framework, in a novel manner, takes into account the action of pro-inflammatory and anti-inflammatory cytokines in response to the function of macrophages. A hypothetical model is created and is transformed to a system of non-dimensional mathematical equations. The dynamics of three main parameters (macrophages sensitivity ?, sensitivity to cytokines ? and bacterial sensitivity ?), analyzes a “threshold value” termed as the basic reproduction number R0 which is based on a sub-model of the inflammatory state. Piece-wise differentiation approach is used and dynamical analysis for the inflammatory response of macrophages is studied in detail. The results shows that the inflamatory response, with high probability in bacterial super-infection, is concomitant with the COVID-19 infection. The mechanism of action of the anti-inflammatory cytokines is discussed during this research and it is observed that these cytokines do not prevent inflammation chronic, but only reduce its level while increasing the activation threshold of macrophages. The results of the model quantifies the probable deficit of the biological mechanisms linked with the anti-inflammatory cytokines. The numerical results shows that for such mechanisms, a minimal action of the pathogens is strongly amplified, resulting in the “chronicity” of the inflammatory process.Öğe Exploration of the novel corona virus transition graphs with petrinet modeling(World Scientific Publishing Co Pte Ltd, 2021) Alam, Fatima; Abdel-Salam, Abdel-Salam G.; Sohail, Ayesha; Yousaf, Muhammad; Tunç, SümeyyeCorona virus (CoV) is a group of viruses with non-bifurcated, single-stranded, and positive-sense RNA genomes. Apart from infecting several economically significant vertebrates (such as pigs and chickens), it is reported in the recent literature that six main types of CoVs infect the human hosts and cause lung infections. In animals, CoVs cause several diseases, including pneumonia, gastrointestinal tract, and central nervous system diseases. In humans, the CoVs work as respiratory tract diseases, and the new CoVs can penetrate the barrier between other species and humans and can cause a high mortality rate. In the course of this study, a novel approach to networking, based on the density-dependent differential equations, is adopted for the precise explanation of the propagation of the virus and the effect of quarantine on it. An infectious disease model with a time delay is suggested based on the conventional infectious disease model. To describe the viral infection period and treatment time, the time differential is used. Using the epidemic data released in real-time, the minimum error is obtained firstly through the inversion of the numerical simulation parameter; then we simulate the development pattern of the epidemic according to the dynamics system; finally, the effectiveness of quarantine steps is compared and analyzed. With the help of a discrete model, the transformations are documented in detail that is difficult to evaluate numerically. The provided numerical results are in close agreement with the experimental findings. The modeling of Petri nets (PNs) used has proven to be a successful method. The current research strategy can help the public to gain awareness of the disease spread, which is highly desired.Öğe Computational framework to explore impact of environmental stress on epidemics(World Scientific, 2020) Sohail, Ayesha; Idrees, Muhammad; Sajjad, Maria; Iftikhar, Sahrish; Tunç, SümeyyeIn the field of epidemiology, not only the disease and the carriers, but also the surrounding environment and the associated stresses play a vital role. Environmental stresses in a novel habitat may facilitate adaptive shifts. Organisms living under environmental stresses often experience higher mutation rates and display greater phenotypic and genetic variation. There is controversial evidence available in the literature about the impact of environmental stresses on the organisms and the resulting variation in mutation rates and the immune responses. In nature, "selection"and the high energetic costs of stress usually reduce this variation. The prior knowledge of the interaction between the stress and disease epidemics may help to control the disease spread at an early stage. A mathematical model of epidemiology, specifically focusing on the vector borne diseases, with environmental stress is reported in this paper. The model is validated with the aid of stability analysis. During this research, a set of parametric values is obtained using reverse engineering. For this purpose, the parametric evaluation is reported with the help of Monte Carlo Markov Chain (MCMC) reverse engineering. Among other factors, the environmental stresses are also responsible for different dynamics of the same disease, in different continents of the world. The proposed research methodology will help in forecasting the epidemiological problems such as the current threat of coronavirus.Öğe Cerrahi operasyon geçirmemiş jinekolojik onkoloji hastalarında üriner inkontinans değerlendirmesi(2019) Atak Çakır, Pınar; Atılgan, Esra; Yılmaz, SakineAmaç: Jinekolojik kanser hastalarının tedavi dönemlerinde üriner inkontinans görüldüğü literatürde belirtilmesine rağmen, tedavi öncesi dönemde üriner inkontinansı inceleyen çalışmalar sınırlı sayıdadır. Çalışmanın amacı jinekolojik kanser hastalarında tanı aldıkları dönemde üriner inkontinansın değerlendirilmesiydi. Gereç ve Yöntemler: Çalışmaya Dr. Abdurrahman Yurtaslan Ankara Onkoloji Eğitim ve Araştırma Hastanesinde jinekolojik onkoloji servisinde yatan 30 jinekolojik kanser hastası ve 30 sağlıklı kadın dahil edildi. Katılımcıların demografik bilgileri kaydedildi. Üriner inkontinans; işeme günlüğü, İnkontinans Şiddet İndeksi (İŞİ) ve Uluslararası İnkontinans Konsültasyon Sorgulama Anketi-Kısa Form ile değerlendirildi. Bulgular: Çalışmaya katılan jinekolojik kanserli kadınların ortalama yaşı 50,88±10,54 yıl, sağlıklı kadınların 48,80±8,69 yıl olarak bulundu (p=0,411). Gruplar arasında Uluslararası İnkontinans Konsültasyon Sorgulama Anketi-Kısa Form skoru açısından (p=0,008) istatistiksel olarak anlamlı fark vardı. İki grup arasında İŞİ skoru ve işeme günlüğü parametreleri arasında istatistiksel olarak anlamlı fark saptanmadı (p>0,05). Sonuç: Jinekolojik kanser grubunda sağlıklı gruba göre üriner inkontinansın daha yaygın olduğu tespit edildi. Sonuç olarak, jinekolojik kanser hastalarına tanı aldıkları dönemden itibaren ürolojik rehabilitasyonun uygulanması gerektiğini düşünmekteyiz.Öğe Rotator manşet lezyonu olan olgularda üst ekstremite ve skapular proprioseptif nöromusküler fasilitasyon tekniğinin etkisi(Turkey Assoc Physiotherapists, 2019) Tunç, Sümeyye; Atılgan, Esra; Algun, Zeliha CandanAmaç: Bu çalışma rotator manşet lezyonu tanısı alan olgularda proprioseptif nöromusküler fasilitasyon (PNF) tekniğinin ağrı, fonksiyonellik ve yaşam kalitesi üzerindeki etkisini incelemek amacıyla yapıldı. Yöntem: Çalışmaya rotator manşet lezyonu tanısı alan 40 olgu dahil edildi. Olgular randomize olarak iki gruba ayrıldı. PNF grubuna konservatif tedaviye ek olarak üst ekstremite ve skapular PNF tekniği, Kontrol grubuna ise, sadece konservatif tedavi uygulandı. Hastalar haftada üç gün altı hafta süre ile tedaviye alındı. Olguların ağrı değerlendirmesi için Vizüel Analog Skalası (VAS), normal eklem hareketi değerlendirmesi için gonyometre, fonksiyonellik ve aktivite düzeyinin değerlendirmesi için Kol, Omuz ve El Sorunları Anketi ve Constant Skoru (CS), yaşam kalitesinin değerlendirmesi için ise, SF-36 anketi kullanıldı. Değerlendirmeler başlangıçta ve altıncı haftada yapıldı. Sonuçlar: Her iki grupta da anlamlı düzeyde ağrının azaldığı ve eklem hareket açıklığının arttığı belirlendi (p<0,05). PNF grubunun aktivite (p<0,001) ve gece (p=0,013) VAS skoru ve omuz eksternal rotasyon eklem açıklığı (p=0,003) sonuçlarında, kontrol grubuna göre daha fazla iyileşme görüldü. Fonksiyonellik ve genel sağlık durumu değerlendirme sonuçlarında her iki grupta da anlamlı gelişme gözlendi (p<0,05). CS (p=0,046) ile SF-36 enerji (p=0,016) ve mental sağlık (p=0,014) alt parametreleri PNF grubu lehine anlamlıydı. Tartışma: Rotator manşet lezyonunda PNF tekniğinin ağrıyı azaltmak, fonksiyonelliği ve yaşam kalitesini iyileştirmek açısından klinikte etkin şekilde kullanılabilecek bir yöntem olduğu saptandı. Omuz rehabilitasyonunda özellikle skapular PNF patern ve tekniklerinin ihmal edilmemesi gerektiği sonucuna ulaşıldı.Öğe Analysis of trabecular bone mechanics using machine learning(Sage Publications Ltd, 2019) Sohail, Ayesha; Younas, Muhammad; Bhatti, Yousaf; Li, Zhiwu; Tunç, Sümeyye; Abid, MuhammadBone remodeling is a dynamic process, and mutliphase analysis incorporated with the forecasting algorithm can help the biologists and orthopedics to interpret the laboratory generated results and to apply them in improving applications in the fields of "drug design, treatment, and therapy" of diseased bones. The metastasized bone microenvironment has always remained a challenging puzzle for the researchers. A multiphase computational model is interfaced with the artificial intelligence algorithm in a hybrid manner during this research. Trabecular surface remodeling is presented in this article, with the aid of video graphic footage, and the associated parametric thresholds are derived from artificial intelligence and clinical data.
