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Öğe Standardization of pediatric cardiovascular anomaly anatomy reconstructions(2024) Alzaeim, Mohamad Humam; Köse, Kevser Banu; Pişkin, Şenol; Basha, Wael Shamsi; Güngören, Fatma Zeynep; Şahin, Ömer Faruk; Femilda, JosephinIn the realm of congenital cardiovascular diseases, the understanding, modeling, and visualization of such diseases as they develop during the neonatal growth period continues to be a challenge despite the current technological advancements. Moreover, such diseases as vascular abnormalities pose further risks due to their implications for a proper standardized method for three-dimensional visualization for planning and growth monitoring. This study uses imaging and computational techniques to create multiple models that relate the diseases as they progress from the initial phase toward the late growth stage for newborns’ cardiovascular systems. Three-dimensional modeling of patients would be created from patient-specific scans coupled with image processing algorithms. This study also aims to use the working principles of already existing tools for diagnosing aortic & brain aneurysms and pulmonary hypertension for cardiovascular development. To comprehensively understand such diseases and how their physical morphology may be standardized.Öğe Computational modeling approaches for palliative care in infants with ductal dependent pulmonary flow(2024) Köse, Kevser Banu; Alzaeim, Mohamad Humam; Basha, Wael Shamsi; Mulla, SelmaThe purpose of this biomedical engineering study is to examine interventional and surgical approaches for complex and palliative solutions in infants with patent ductus arteriosus and pulmonary artesia diagnosis with mathematical modeling and computational fluid mechanics methods. In the study, we visualized hemodynamically using patient-specific preoperative cross-sectional image data and computer-aided design techniques and discussed the differences between repair methods through mathematical models and virtual repairs. We discussed the significance of blood flow analysis in the treatment planning of infants with ductal-dependent pulmonary flow.Öğe Global levodopa dose equivalency calculator(2024) Mersin, Osman; Şahinkaya, Nermin; Zırh, Tahsin Ali; Kenangil, GülayIn medical treatment of Parkinson's Disease, there is standard conversion formulas available between Levodopa and calculated equivalent dose amount of other antiparkinsonian drugs. Although there are calculation systems in the literature that include these formulas, the accuracy and stability of the currently available programs are highly questionable. For this reason, an interface was designed using the Python Tkinter library and an algorithm that included accepted formulations in the literature was designed to create the most accurate and stable calculator design. Aim of designed LED calculation program is to systematically reach the standard results by selecting the active ingredients of the drugs prescribed, both the commercial names and active pharmaceutical ingredient of the drugs. LED program can also be used in clinical research studies which can help to prevent Levodopa therapy calculation errors and provide efficient time management.Öğe Smart polymeric nanocarriers for miRNA delivery against triple negative breast cancer(2024) Yumuk, Kübra; Hamurcu, Zuhal; Ercan Ayra, Merve; Yüksel Durmaz, Yasemin; Aydın, ÖmerThe most typical malignancy in women is breast cancer. This translates to almost 2.3 million women who have been diagnosed with the illness, which, according to the World Health Organization (WHO), resulted in more than 685,000 fatalities globally in 2020. Additionally, 8 million women have received a breast cancer diagnosis in the past five years, making breast cancer the most prevalent cancer worldwide [1]. Additionally, triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks the human epidermal growth factor receptor 2, progesterone receptor, and oestrogen receptor. Furthermore, TNBC is known for its drug resistance, aggressiveness, and metastatic properties [2]. Even though radiotherapy and chemotherapy are two therapeutic modalities for the treatment of breast cancer, they have had limited effectiveness in clinics due to a number of limitations, such as the emergence of drug resistance throughout therapy. Gene therapy offers a promising avenue to overcome these challenges. MicroRNAs (miRNAs) are significant factors in the development, metastasis, and advancement of breast cancer [3]. The oncogenic transcription factor Forkhead Box M1 (FOXM1) is engaged in processes that are thought to be cancer hallmarks [4]. In a previous study Zuhal Hamurcu et.al claimed that the results of the miRNA expression profile in two distinct TNBC cells, miRNA was downregulated after FOXM1 was knocked down. Also, they conducted KEGG pathway analysis and GO enrichment analysis for miRNA, and these analyses revealed that this miRNA is connected to the cell cycle, AMPK, p53, and NF-kB signalling pathways, as well as the formation and progression of cancer [5]. However, a few barriers, including miRNA instability, unfavourable offtarget effects, and non-specific activation of the immune system's natural defences, prevent RNAi-based techniques from operating to their full potential. Delivery of miRNA into cells is further restricted by endothelial cell resistance, inability to achieve endosomal escape, which prevents the miRNA from reaching the location of cytosolic action. The development of nanocarriers addresses almost all these problems. To make complex and transport miRNA to breast cancer cells, we developed “smart” polymeric nanocarriers. Also, smart polymeric nanoparticles provide a protective shield, shielding miRNAs from enzymatic degradation and enhancing their bioavailability. Inhibitor miRNA and smart nanocarriers are complex at a 2/1 N/P ratio. Additionally, mimic miRNA and negative miRNA form an 8/1 complex with smart nanocarriers. Finally, with a 16/1 N/P ratio, FAM-labelled negative miRNA and smart nanocarriers are complex. Furthermore, the percentage of cells encapsulating miRNAs in cells analysed using flow cytometry was determined. Accordingly, the import percentages of BT-549 and MDA-MB-231 cells are over 35% and 55%, respectively. The fluorescence microscopy results obtained show that our FAM-labelled miRNAs reach the inside of the cell within 4 hours. As a result of this experiment, it was observed that miRNA could be transported to the cell without any enzymatic digestion. Our results demonstrated the potential of polymeric miRNA delivery systems showcasing promising outcomes in preclinical for triple-negative breast cancer treatment. These advances hold immense promise in improving the precision, efficacy, and safety of breast cancer treatments. To enable efficient delivery and controlled release of miRNA, the physicochemical characteristics of the smart nanocarriers, including size, charge on the surface, and stability, are optimized.Öğe rs-fMRI analysis using spatio-temporal sparse convolutional neural networks(Institute of Electrical and Electronics Engineers Inc., 2022) Yener, Fatma Muberr; Yıldız, Sultan; Hafeez, Muhammad Adeel; Kayasandık, Cihan Bilge; Doğan, Merve YüsraNeuropsychiatric diseases such as Autism Spectrum Disorder (ASD) and Schizophrenia cause various behavioral and communication dysfunctions in human life. Resting state functional magnetic resonance imaging (rs-fMRI) is used to detect and characterize functional changes in the brain associated with these disorders. Machine learning methods are known to perform well in classifying fMRI images and have proven to have great potential in the field of computer aided diagnosis. In most of the previous studies, hand-crafted features have been used in fMRI analyzes and classifications to date. This prevents the system from being end-to-end and causes spatial or temporal information to be lost due to dimension reduction. The method presented in this study works end-to-end as well as being fed with an entire 4-dimensional fMRI sequence. It is faster than traditional convolutions and recurrent neural networks of the same size, thanks to the sparse convolutional layers that are the building blocks of the network. Experiments with schizophrenia and ASD fMRIs have shown similar performance to those in the literature, despite limited resources.Öğe Brain tumor classification using MRI images and convolutional neural networks(Institute of Electrical and Electronics Engineers Inc., 2022) Hafeez, Muhammad Adeel; Kayasandık, Cihan Bilge; Doğan, Merve YüşraThe brain tumor has become one of the most prominent types of cancers affecting a huge population across the globe every year. It has the lowest life expectancy rate and the risk of death is highly associated with the type, shape, and location of the tumor. The Magnetic Resonance Imaging (MRI) is a strong tool to detect different brain lesions and is extensively used by radiologists and physicians. For the early and accurate diagnosis of the brain tumor using MRI, it is important to consider automated computer-assisted diagnosis which is more flexible and efficient. In this paper, we have proposed a Convolutional Neural Network (CNN) based approach for the classification of three types of brain tumors (meningiomas, gliomas, and pituitary tumors). A publicly available dataset that contains 3064 T1-weighted brain CE-MRI images collected from 233 patients has been used in the study. We propose a 15 layers CNN model for the classification of three types of brain tumors from the mentioned dataset. We obtained an accuracy, precision, recall, and f1-score of 98.6%, 99%, 98.3%, and 98.6% from our proposed model which is higher than previously reported results.Öğe Total internal reflection holographic microscopy for cellular imaging(SPIE, 2022) Gürcan, Tolga; Toy, Muhammed FatihThe study of interfacial structures is of utmost importance not only for various research fields such as cell biology and display systems but also their sub-disciplines. One of the traditional means of imaging buried structures rely on the use optical sectioning with superresolution microscopy. Although it exceeds diffraction limit in resolution, there are various shortcomings to utilize this methodology such as its reliance on fluorescent markers, long exposure times to high cost of the imaging system. Ultimately, these limitations position the existing technologies unideal for live cell imaging, including the imaging of surface proteins of a living cell. A label free quantitative phase imaging method is realized in this project to enable imaging of an interface between different media. This system is based on an off-axis holographic microscope and uses a high numerical aperture (NA) microscope objective to achieve total internal reflection (TIR). Existing literature on total internal reflection holographic microscopy utilizes prism to achieve TIR which limits the working distance of objective hence magnification. Our system relies on a 100x objective with 1.49 NA to improve resolution and magnification. Complex field which is reflected from the sample can be recovered by using digital holography principles. The resolution of the system can further be enhanced by combining several illumination angles and utilizing synthetic aperture reconstruction.Öğe An integrated top-stage incubator and lens free holographic imaging system for culture monitoring applications(SPIE, 2022) Özbilgin, Zeynep; Akşit, Sevdenur; Toy, Muhammed FatihLens free inline holographic microscopy was shown to be a potent approach for many applications relying on cellular imaging. Applications requiring a large field of view at moderate resolution are the ones that are most suitable for this platform. Besides, the simplicity of the overall imaging system, which requires only a light source and a camera, positions this approach as an easily accessible one. Acquired holograms from such a system are processed to recover phase images. As an additional advantage on top of the simplicity, phase imaging enables the imaging of otherwise transparent cell samples without any need for labeling or staining. Eventually, such a system can be used for long term imaging of live cell cultures with wide field of view. Up to now, two alternatives were explored for the imaging of live cell cultures for extended duration. In one approach, a portable imaging system was placed inside a standard incubator with cell cultures on top. A stage top incubator was used on a modified microscope in the other approach. In both approaches, the cost of the system grows due to commercial systems, and the overall footprint of the system with incubator is too large to be classified as portable. Here, an integrated portable system is presented that can maintain cell cultures at desired temperature in a 3D printed enclosure while imaging them in lens free inline holographic microscopy modality. Such a system is well suited for tissue culturing and monitoring at limited resources settings.Öğe Maskless lithography with holographic feedback for the fabrication of optical elements(SPIE, 2022) Gürcan, Tolga; Toy, Muhammed FatihPhotolithography has become a powerful tool in the fabrication of micro-optical elements following the advancements in grayscale approaches. However, hitting tight design tolerance goals require precise control of all parameters such as temperature, resist nonlinearity or preventing vignetting. In this work we took an alternative route to these problems by combining maskless lithography with digital holography. Addition of digital holography enables the use of feedback by measuring the quantitative phase of specimen near real time and in situ nondestructively. After each near UV exposure, phase retardation map of exposed photopolymer is measured with digital holography part of the system. Any deviation from target phase is corrected by changing the pattern displayed on the mask. We showed that the proposed method reduces the standard deviation of resulting phase compared to traditional one-shot grayscale lithography. It also does not require any precalibration of photoresist and relaxes the constraints for uniform UV illumination in sample plane.Öğe Mechanistic insight into impact of phosphorylation on dynamics of farnesyltransferase: Targeting the protein under hyperinsulinemia(Cell Press, 2022) Pekel, Hanife; Güzel, Mustafa; Şensoy, Özge[Abstract Not Available]Öğe Combining multiple clustering and network analysis for discoveries in gene expression data(Association for Computing Machinery, Inc, 2021) Alhajj, Sleiman; Alhajj, Aya; Tarıyan Özyer, SibelClustering is a challenging research task which could benefit a wide range of practical applications, including bioinformatics. It targets success by optimizing a number of objectives, a characteristic mostly ignored by clustering approaches. This paper describes a synthetic clustering algorithm which first applies multi-objective based approach to produce the alternative clustering solutions. Then the best clusters from each solution are selected and combined into a seed for a compact and effective solution which is expected to be better than all the individual solutions because it combines the best of each. This way, the developed algorithm may be classified as a fuzzy clustering approach because each object may belong to more than one cluster in the synthesized solution with a degree of membership in each cluster. Another interesting aspect of the algorithm is that it identifies the outliers. Further, a network is built from the relationships of the objects within the various clusters. The network is analyzed to reveal interesting discoveries not clearly reflected in the clustering outcome. The validity and applicability of the presented methodology has been assessed using synthetic and real data from the cancer.Öğe A python code for maximum likelihood estimation of the location and scale parameters of the truncated normal distribution(Institute of Electrical and Electronics Engineers Inc., 2021) Ögütcen, Melih Yılmaz; Kocatürk, Mehmet; Okatan, MuratExtracellular neural recordings obtained from chronically implanted microelectrode arrays are widely used in behavioral neurophysiology and invasive brain-machine interfaces. After the raw recordings are band-pass filtered within a frequency band suitable for spike detection, spikes are often detected by amplitude thresholding. Developing principled methods for computing amplitude thresholds is an active research area. 'Truncation thresholds' are a pair of amplitude thresholds that are computed using a recently proposed algorithm. As part of an effort that aims to integrate this algorithm into a real-Time data acquisition and spike detection system, here we present a Python code for maximum likelihood estimation of the location and scale parameters of the truncated Normal distribution, which is one of the steps involved in the computation of truncation thresholds.Öğe Using Johnson's SU distribution for modeling the background activity in extracellular neural recordings(Institute of Electrical and Electronics Engineers Inc., 2021) Ögütcen, Melih Yılmaz; Kocatürk, Mehmet; Okatan, MuratExtracellular neural recordings obtained from awake behaving subjects through chronically implanted microelectrode arrays provide information about the functioning of the brain with sub-millisecond temporal resolution at the level of individual neurons. After bandpass filtering in a frequency range suitable for spike detection, these recordings consist of spikes and background activity. Methods exist to segment the background activity automatically using truncation thresholds and Otsu-based methods. In previous work, truncation thresholds have been computed using the truncated Normal distribution. Here, we use the truncated Johnson's SU distribution instead to examine whether it segments the background activity better. We also find that the truncated Johnson's SU distribution explains the background activity segmented by Otsu-based thresholds. These results are useful for developing invasive brain-computer-interfaces that automatically extract information from extracellular neural recordings in real time.Öğe Öğrenci mikroskobunda epifloresan görüntüleme(Institute of Electrical and Electronics Engineers Inc., 2020) Gökduman, Selcen NecibeFluorescence microscopy is used as an important tool for research and education in the biological sciences. Fluorescence microscopes allow fluorescent signal to be obtained by stimulating markers in biological samples using light at a certain wavelength. The high cost of fluorescence microscopes has limited its use to academic laboratories and wealthy research institutions. In this project, a low-cost and accessible epifluorescence imaging device has been produced. A plug-in device has been designed to be used to achieve fluorescence imaging without changing the optical elements of the existing standard student microscope. The built device is designed to be mounted on the eyepiece of a monocular student microscope to obtain an epifluorescence image. In this way, it is aimed to make fluorescence imaging accessible for many laboratories with a device that can be mounted as needed on an easily available student microscope.Öğe A mobile parallel manipulator for the elbow rehabilitation of parkinsonian patients(Institute of Electrical and Electronics Engineers Inc., 2020) Gül, Rabia; Şener, Şaika; Hocao?lu, ElifThis study presents a two degrees of freedom (DoF) parallel manipulator that enables Parkinsonian Patients to regularly do the assigned rhythmic tasks in order to reduce the symptoms of motor disorders. Considering the elderly patients who constitute the majority of the Parkinsonians, the robot is designed to be portable to serve people to consistently take therapy at home. Moreover, the robotic platform is designed to be adjustable for any anthropometric size of a human arm in order to allow people to ergonomically perform tasks. The kinematic analysis and control of the five-bar parallel robot are carried out to ensure that users can do upper extremity coordination on the anthropometrically compatible workspace.Öğe Hücre dışı sinirsel kayıtlarda olabilirli?e dayalı genlik eşikleme(Institute of Electrical and Electronics Engineers Inc., 2019) Dağdevir, Eda; Kocatürk, Mehmet; Okatan, MuratHücre dışı sinirsel kayıtlarda genlik eşiğinin optimizasyonu son zamanlarda beyin-makine arayüzü literatüründe etkin bir araştırma konusu haline gelmiştir. Önceki bir çalışmada, davranış değişkenlerinin sinirsel etkinlikte en yüksek işaret-gürültü oranıyla kodlanmasını sağlayan eşiğin genlik eşiği olarak makul bir seçim olduğu önerilmiştir. Bir başka makul eşik adayı ise en yüksek olabilirlikle kestirilen eşik değeridir. Bu çalışmada bu iki eşik türü iyi öğrenilmiş bir görselmotor görev sırasında iki sıçanın motor korteksinden (M1) kaydedilen hücre dışı kayıtlar kullanılarak kestirilmiştir. Kestirilen eşikler şifre çözücülerde kullanılarak başarımları karşılaştırılmıştır. İncelenen dört şifre çözücü arasından en iyi duyarlılık, özgüllük ve doğruluk ölçütlerine sahip olan yöntemin en yüksek olabilirlikle kestirilen eşiği kullanan lojistik regresyon olduğu belirlenmiştir. Bu sonuçlar beyin-makine arayüzlerinin verimliliğinin artırılması açısından önemlidir.Öğe Speckle-enhanced prism spectrometer(IEEE Computer Society, 2019) Çetindağ, Şakir Kaan; Ferhanoğlu, Onur; Toy, Muhammed Fatih; Çivitçi, FehmiWe present an improved prism spectrometer with high wavelength range and spectral resolution. The device is an upgraded prism spectrometer that utilizes an additional scattering medium leading to a wavelength-dependent speckle pattern. We demonstrate < 20 pm resolution and \sim 750 nm wavelength range with the proposed device. With the demonstrated spectral resolution, the speckle-enhanced prism could provide the means to image deep tissue layers in Optical Coherence Tomography.Öğe Hücre dışı sinirsel kayıtlarda farklı genlik eşiklerinin karşılaştırılması(The Institute of Electrical and Electronics Engineers (IEEE), 2019) Dağdevir, Eda; Kocatürk, Mehmet; Okatan, MuratHücre dışı sinirsel kayıtlardan bilgi çıkarımında genlik eşikleri kullanılmaktadır. Genlik eşiği davranış değişkenlerinin sinirsel etkinlikte en yüksek işaret-gürültü oranıyla kodlanmasını sağlayacak şekilde kestirilebildiği gibi en yüksek olabilirlikle de kestirilebilmektedir. Bu çalışmada bu iki eşik türü iyi öğrenilmiş bir görsel-motor görev sırasında iki sıçanın motor korteksinden (M1) kaydedilen hücre dışı kayıtlar kullanılarak kestirilmiştir ve kestirilen eşik değerleri karşılaştırılmıştır. Sonuçlar bu iki eşik türü arasında anlamlı bir fark bulunmadığını göstermektedir. Ayrıca en yüksek olabilirlikle kestirilen eşik değerinin güven aralığının genişliğinin şifre çözüm doğruluğu ile ilintili olduğu bulunmuştur. Bu sonuçlar beyin-makine ara yüzlerinde kullanılacak uygun genlik eşiklerinin belirlenmesi açısından önemlidir.Öğe A novel homozygous nonsense mutation (p.R516X) in the SLC5A5 gene causing congenital hypothyroidism(Nature Publishing Group, 2019) Işık, Fatma Büşra; Sözügüzel, Mavi Deniz; Kılıçoğlu Aydın, Birsen; Parlayan, Cüneyd; Yıldız, Mete; Cangül, Hakan[Abstract Not Available]Öğe Comparison of machine learning techniques on MS lesion segmentation(Institute of Electrical and Electronics Engineers Inc., 2019) Doğan, Ahsen Feyza; Göksel Duru, DilekMultiple sclerosis arises with conformational change in myelin sheath. Magnetic resonance imaging is frequently used in detection of MS. In this study, to figure out MS lesion, machine learning techniques, namely k means and support vector machine are used. K means is an unsupervised technique used to cluster data into k groups. Support vector machine is a supervised machine learning technique used as classifier. Since dataset does not contain label of images, labels are generated by pixel values adopted from original MR image. Classification results were achieved as 70.24% and 91.04% for k means and SVM respectively. According to the promising results, future research will focus on the automatization of this segmentation process via deep learning leading to medical decision support system.
