Browsing by Author "Demirci, U."

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Open Access
Bio-inspired magnetic beads for isolation of sperm from heterogenous samples ın forensic applications
(Elsevier BV, 2021-05) İnci, Fatih; Karaaslan, M. G.; Gupta, R.; Avadhani, A.; Öğüt, M. G.; Atila, E. E.; Duncan, G.; Klevan, L.; Demirci, U.
Rapid and efficient processing of sexual assault evidence will accelerate forensic investigation and decrease casework backlogs. The standardized protocols currently used in forensic laboratories require the continued innovation to handle the increasing number and complexity of samples being submitted to forensic labs. Here, we present a new technique leveraging the integration of a bio-inspired oligosaccharide (i.e., Sialyl‐LewisX) with magnetic beads that provides a rapid, inexpensive, and easy-to-use strategy that can potentially be adapted with current differential extraction practice in forensics labs. This platform (i) selectively captures sperm; (ii) is sensitive within the forensic cut-off; (iii) provides a cost effective solution that can be automated with existing laboratory platforms; and (iv) handles small volumes of sample (∼200 μL). This strategy can rapidly isolate sperm within 25 minutes of total processing that will prepare the extracted sample for downstream forensic analysis and ultimately help accelerate forensic investigation and reduce casework backlogs.
Open Access
A confirmatory test for sperm in sexual assault samples using a microfluidic-integrated cell phone imaging system
(Elsevier, 2020) Deshmukh, S.; İnci, Fatih; Karaaslan, M. G.; Öğüt, M. G.; Duncan, D.; Klevan, L.; Duncan, G.; Demirci, U.
Rapid and efficient processing of sexual assault evidence to accelerate forensic investigation and decrease casework backlogs is urgently needed. Therefore, the standardized protocols currently used in forensic laboratories can benefit from continued innovation to handle the increasing number and complexity of samples being submitted to forensic labs. To our knowledge, there is currently no available rapid and portable forensic screening technology based on a confirmatory test for sperm identification in a sexual assault kit. Here, we present a novel forensic sample screening tool, i.e., a microchip integrated with a portable cell phone imaging platform that records and processes images for further investigation and storage. The platform (i) precisely and rapidly screens swab samples (<15 min after sample preparation on-chip); (ii) selectively captures sperm from mock sexual assault samples using a novel and previously published SLeX-based surface chemistry treatment (iii) separates non-sperm contents (epithelial cells and debris in this case) out of the channel by flow prior to imaging; (iv) captures cell phone images on a portable cellphone-integrated imaging platform, (v) quantitatively differentiates sperm cells from epithelial cells, using a morphology detection code that leverages Laplacian of Gaussian and Hough gradient transform methods; (vi) is sensitive within a forensic cut-off (>95% accuracy) compared to the manual counts; (vii) provides a cost-effective and timely solution to a problem which in the past has taken a great deal of time; and (viii) handles small volumes of sample (20 μL). This integration of the cellphone imaging platform and cell recognition algorithms with disposable microchips can be a new direction toward a direct visual test to screen and differentiate sperm from epithelial cell types in forensic samples for a crime laboratory scenario. With further development, this integrated platform could assist a sexual assault nurse examiner (SANE) in a hospital or sexual assault treatment center facility to flag sperm-containing samples prior to further downstream testing.
Open Access
Enhancing the nanoplasmonic signal by a nanoparticle sandwiching strategy to detect viruses
(Elsevier, 2020-05) Inci, Fatih; Karaaslan, M. G.; Mataji-Kojouri, A.; Saylan, Y.; Zeng, Y.; Avadhani, A.; Sinclair, R.; Lau, D. T.-Y.; Demirci, U.
Nanoparticles that can assemble and bind selectively on surfaces in intricate geometries can trigger multiple plasmonic modalities and enable wide applications in agriculture such as pesticide monitoring, in medical imaging such as targeted cancer detection, in bioengineering such as biotarget detection and biosensing, and in healthcare such as selection of drugs and their binding kinetics. However, these particles mainly rely on binding of the target to a surface to create a plasmonic resonance and subsequent shifts by binding of biotargets, which limit the flexibility to control overall sensitivity. Here, we present an unconventional way that sandwiches a virus (i.e., Hepatitis B virus: HBV) topographically between two or more nanoparticles on the top and the bottom to create a double-step shifting effect amplifying the total resonance wavelength shift on the surface by 1.53 - 1.77 times that significantly enhances the sensitivity. We successfully applied this approach to an intact HBV sensing application, which accurately quantified the viral load. This method establishes a new nanoparticle-based sandwiched nanoplasmonic approach to detect and quantify viral load using two-step sensing with broad applications in biosensing.
Open Access
Label-free identification of exosomes using raman spectroscopy and machine learning
(Wiley-VCH Verlag GmbH & Co. KGaA, 2023-01-15) Parlatan, U.; Ozen, M.O.; Kecoglu, I.; Koyuncu, B.; Torun, H.; Khalafkhany, D.; Loc, I.; Ogut, M.G.; Inci, Fatih; Akin, D.; Solaroglu, I.; Ozoren, N.; Unlu, M. B.; Demirci, U.
Exosomes, nano-sized extracellular vesicles (EVs) secreted from cells, carry various cargo molecules reflecting their cells of origin. As EV content, structure, and size are highly heterogeneous, their classification via cargo molecules by determining their origin is challenging. Here, a method is presented combining surface-enhanced Raman spectroscopy (SERS) with machine learning algorithms to employ the classification of EVs derived from five different cell lines to reveal their cellular origins. Using an artificial neural network algorithm, it is shown that the label-free Raman spectroscopy method's prediction ratio correlates with the ratio of HT-1080 exosomes in the mixture. This machine learning-assisted SERS method enables a new direction through label-free investigation of EV preparations by differentiating cancer cell-derived exosomes from those of healthy. This approach will potentially open up new avenues of research for early detection and monitoring of various diseases, including cancer.
Unknown
Portable microfluidic integrated plasmonic platform for pathogen detection
(Nature Publishing Group, 2015) Tokel, O.; Yildiz, U. H.; Inci, F.; Durmus, N. G.; Ekiz, O. O.; Turker, B.; Cetin, C.; Rao, S.; Sridhar, K.; Natarajan, N.; Shafiee, H.; Dana, A.; Demirci, U.
Timely detection of infectious agents is critical in early diagnosis and treatment of infectious diseases. Conventional pathogen detection methods, such as enzyme linked immunosorbent assay (ELISA), culturing or polymerase chain reaction (PCR) require long assay times, and complex and expensive instruments, which are not adaptable to point-of-care (POC) needs at resource-constrained as well as primary care settings. Therefore, there is an unmet need to develop simple, rapid, and accurate methods for detection of pathogens at the POC. Here, we present a portable, multiplex, inexpensive microfluidic-integrated surface plasmon resonance (SPR) platform that detects and quantifies bacteria, i.e., Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) rapidly. The platform presented reliable capture and detection of E. coli at concentrations ranging from ∼105 to 3.2 × 107 CFUs/mL in phosphate buffered saline (PBS) and peritoneal dialysis (PD) fluid. The multiplexing and specificity capability of the platform was also tested with S. aureus samples. The presented platform technology could potentially be applicable to capture and detect other pathogens at the POC and primary care settings. © 2015, Nature Publishing Group. All rights reserved.
Unknown
Tunable fano‐resonant metasurfaces on a disposable plastic‐template for multimodal and multiplex biosensing
(Wiley-VCH Verlag, 2020) Ahmed, R.; Özen, M. Ö.; Karaaslan, M. G.; Prator, C. A.; Thanh, C.; Kumar, S.; Torres, L.; Iyer, N.; Munter, S.; Southern, S.; Henrich, T. J.; İnci, Fatih; Demirci, U.
Metasurfaces are engineered nanostructured interfaces that extend the photonic behavior of natural materials, and they spur many breakthroughs in multiple fields, including quantum optics, optoelectronics, and biosensing. Recent advances in metasurface nanofabrication enable precise manipulation of light–matter interactions at subwavelength scales. However, current fabrication methods are costly and time‐consuming and have a small active area with low reproducibility due to limitations in lithography, where sensing nanosized rare biotargets requires a wide active surface area for efficient binding and detection. Here, a plastic‐templated tunable metasurface with a large active area and periodic metal–dielectric layers to excite plasmonic Fano resonance transitions providing multimodal and multiplex sensing of small biotargets, such as proteins and viruses, is introduced. The tunable Fano resonance feature of the metasurface is enabled via chemical etching steps to manage nanoperiodicity of the plastic template decorated with plasmonic layers and surrounding dielectric medium. This metasurface integrated with microfluidics further enhances the light–matter interactions over a wide sensing area, extending data collection from 3D to 4D by tracking real‐time biomolecular binding events. Overall, this work resolves cost‐ and complexity‐related large‐scale fabrication challenges and improves multilayer sensitivity of detection in biosensing applications.