Bioengineering / Biyomühendislik

Permanent URI for this collectionhttps://hdl.handle.net/11147/4529

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Deep Convolutional Neural Networks for Viability Analysis Directly From Cell Holograms Captured Using Lensless Holographic Microscopy
(The Chemical and Biological Microsystems Society (CBMS), 2019) Delikoyun, Kerem; Çine, Ersin; Anıl İnevi, Müge; Özçivici, Engin; Özuysal, Mustafa; Tekin, Hüseyin Cumhur
Cell viability analysis is one of the most widely used protocols in the fields of biomedical sciences. Traditional methods are prone to human error and require high-cost and bulky instrumentations. Lensless digital inline holographic microscopy (LDIHM) offers low-cost and high resolution imaging. However, recorded holograms should be digitally reconstructed to obtain real images, which requires intense computational work. We introduce a deep transfer learning-based cell viability classification method that directly processes the hologram without reconstruction. This new model is only trained once and viability of each cell can be predicted from its hologram. © 2019 CBMS-0001.
Citation - Scopus: 3
Development of Chrono-Spectral Gold Nanoparticle Growth Based Plasmonic Biosensor Platform
(Elsevier, 2024) Sözmen, Alper Baran; Elveren, Beste; Erdoğan, Duygu; Mezgil, Bahadır; Baştanlar, Yalın; Yıldız, Ümit Hakan; Arslan Yıldız, Ahu
Plasmonic sensor platforms are designed for rapid, label-free, and real-time detection and they excel as the next generation biosensors. However, current methods such as Surface Plasmon Resonance require expertise and well-equipped laboratory facilities. Simpler methods such as Localized Surface Plasmon Resonance (LSPR) overcome those limitations, though they lack sensitivity. Hence, sensitivity enhancement plays a crucial role in the future of plasmonic sensor platforms. Herein, a refractive index (RI) sensitivity enhancement methodology is reported utilizing growth of gold nanoparticles (GNPs) on solid support and it is backed up with artificial neural network (ANN) analysis. Sensor platform fabrication was initiated with GNP immobilization onto solid support; immobilized GNPs were then used as seeds for chrono-spectral growth, which was carried out using NH2OH at varied incubation times. The response to RI change of the platform was investigated with varied concentrations of sucrose and ethanol. The detection of bacteria E.coli BL21 was carried out for validation as a model microorganism and results showed that detection was possible at 102 CFU/ml. The data acquired by spectrophotometric measurements were analyzed by ANN and bacteria classification with percentage error rates near 0% was achieved. The proposed LSPR-based, label-free sensor application proved that the developed methodology promises utile sensitivity enhancement potential for similar sensor platforms. © 2024 The Author(s)
Citation - WoS: 4
Citation - Scopus: 7
Lensless Digital In-Line Holographic Microscopy for Space Biotechnology Applications
(Institute of Electrical and Electronics Engineers Inc., 2019) Delikoyun, Kerem; Çine, Ersin; Anıl İnevi, Müge; Özuysal, Mustafa; Özçivici, Engin; Tekin, Hüseyin Cumhur
Biomechanical changes at cellular level can dramatically affect living organisms in both aviation and space applications. Weightlessness induces morphological alteration of cells, which leads to tissue loss. Therefore, scientists have been studying the effect of weightlessness using cell culture based biological experiments using conventional microscopes. However, strict requirements regarding cost, weight and functionality limit the use of conventional microscopes in space environment. Lensless digital in-line holographic microscopy enables to use low-weight, low-cost and robust elements, such as a light emitting diode (LED), an aperture and an imaging sensor, instead of bulky, expensive and fragile optical elements, such as lenses, mirrors and filters. This technology offers a high field of view compared to conventional microscopes without affecting the resolution and it is also suitable for remote sensing applications with automated imaging capabilities. Here, we present a portable digital in-line holographic microscopy platform that allows to visualize cells and to analyze their viability in a microfluidic chip. The platform offers microscopic imaging with 1.55 mu m spatial resolution, 21.7 mm(2) field of view and image coloring capability. This platform could potentially play an important role in space biotechnology applications by enabling low-cost, high-resolution and portable monitoring of cells.
Citation - WoS: 16
Citation - Scopus: 19
Pixelated Colorimetric Nucleic Acid Assay
(Elsevier, 2020) Aydın, Hakan Berk; Cheema, Jamal Ahmed; Arnmanath, Gopal; Toklucu, Cihan; Yücel, Müge; Özenler, Sezer; Yıldız, Ümit Hakan
Conjugated polyelectrolytes (CPEs) have been widely used as reporters in colorimetric assays targeting nucleic acids. CPEs provide naked eye detection possibility by their superior optical properties however, as concentration of target analytes decrease, trace amounts of nucleic acid typically yield colorimetric responses that are not readily perceivable by naked eye. Herein, we report a pixelated analysis approach for correlating colorimetric responses of CPE with nucleic acid concentrations down to 1 nM, in plasma samples, utilizing a smart phone with an algorithm that can perform analytical testing and data processing. The detection strategy employed relies on conformational transitions between single stranded nucleic acid-cationic CPE duplexes and double stranded nucleic acid-CPE triplexes that yield distinct colorimetric responses for enabling naked eye detection of nucleic acids. Cationic poly[N,N,N-triethyl-3-((4-methylthiophen-3-yl)oxy)propan-1-aminium bromide] is utilized as the CPE reporter deposited on a polyvinylidene fluoride (PVDF) membrane for nucleic acid assay. A smart phone application is developed to capture and digitize the colorimetric response of the individual pixels of the digital images of CPE on the PVDF membrane, followed by an analysis using the algorithm. The proposed pixelated approach enables precise quantification of nucleic acid assay concentrations, thereby eliminating the margin of error involved in conventional methodologies adopted for interpretation of colorimetric responses, for instance, RGB analysis. The obtained results illustrate that a ubiquitous smart phone could be utilized for point of care colorimetric nucleic acids assays in complex matrices without requiring sophisticated software or instrumentation.

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Browsing Bioengineering / Biyomühendislik by Department "İzmir Institute of Technology. Computer Engineering"