A5008103604- Biosensors and Analytical Detection
- Cell Image Analysis Techniques
- Advanced Biosensing Techniques and Applications
- Bacterial Identification and Susceptibility Testing
- Spectroscopy Techniques in Biomedical and Chemical Research
- Image Processing Techniques and Applications
- Gold and Silver Nanoparticles Synthesis and Applications
- Advanced biosensing and bioanalysis techniques
- SARS-CoV-2 detection and testing
- Microfluidic and Capillary Electrophoresis Applications
- Integrated Circuits and Semiconductor Failure Analysis
- Streptococcal Infections and Treatments
- Digital Holography and Microscopy
- Melamine detection and toxicity
- Drug Solubulity and Delivery Systems
- Plasmonic and Surface Plasmon Research
- SARS-CoV-2 and COVID-19 Research
- Identification and Quantification in Food
- Online Learning and Analytics
- Advanced Nanomaterials in Catalysis
- Electrochemical sensors and biosensors
- AI in Service Interactions
- Erythropoietin and Anemia Treatment
- Energetic Materials and Combustion
- Spectroscopy and Chemometric Analyses
Gazi University
2013-2025
University of California, Los Angeles
2023-2025
California NanoSystems Institute
2023-2025
Ankara (Czechia)
2018
We present a rapid and stain-free quantitative viral plaque assay using lensfree holographic imaging deep learning. This cost-effective, compact, automated device significantly reduces the incubation time needed for traditional assays while preserving their advantages over other virus quantification methods. captures ~0.32 Giga-pixel/hour phase information of objects per test well, covering an area ~30x30 mm^2, in label-free manner, eliminating staining entirely. demonstrated success this...
Large language models (LLMs) are artificial intelligence (AI) platforms capable of analyzing and mimicking natural processing. Leveraging deep learning, LLM capabilities have been advanced significantly, giving rise to generative chatbots such as Generative Pre‐trained Transformer (GPT). GPT‐1 was initially released by OpenAI in 2018. ChatGPT's release 2022 marked a global record speed technology uptake, attracting more than 100 million users two months. Consequently, the utility LLMs fields...
Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, data processing, coupled with deep learning, can help improve POCT. To demonstrate the performance our approach, present a rapid cost-effective paper-based high-sensitivity vertical flow (hs-VFA) for quantitative measurement cardiac troponin I (cTnI), biomarker widely used...
Gram staining has been a frequently used protocol in microbiology. It is vulnerable to artifacts due to, e.g., operator errors and chemical variations. Here, we introduce virtual of label-free bacteria using trained neural network that digitally transforms dark-field images unstained into their Gram-stained equivalents matching bright-field image contrast. After one-time training, the model processes an axial stack microscopy (never seen before) rapidly generate staining, bypassing several...
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, high-sensitivity detection of cardiac troponin I (cTnI) is demonstrated through chemiluminescence-based sensing, imaging, deep learning-driven analysis. This chemiluminescence vertical flow assay (CL-VFA) enables rapid, low-cost, precise quantification cTnI, a key protein for assessing heart muscle damage myocardial infarction. The...
Beta-hemolytic, Group A Streptococcus pyogenes (GAS) is a life-threating pathogen and the reason for prominent disease, pharyngitis. The conventional analysis of GAS, gold standard, takes 48 hours related rapid tests lack in accuracy sensitivity. In this study, firstly, efficiency swab sampling, which must GAS detection, was discussed with proposed surface-enhanced Raman spectroscopy (SERS)-based batch assay each step controlled by plate-counting method. Secondly, SERS-based lateral flow...
The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent virus control disease. Given sustained high infectivity evolution SARS-CoV-2, there is an ongoing interest in developing serology tests monitor population-level immunity. To address this critical need, we designed a paper-based multiplexed vertical flow assay (xVFA) using five structural proteins detecting IgG IgM antibodies changes immunity levels. Our platform not only tracked...
In this experimental study, we developed lateral flow immunoassay strips for the detection of <italic>Escherichia coli</italic>.
A nanosensing method based on surface-enhanced Raman spectroscopy was proposed for simultaneous quantification of nitramine compounds, HMX and RDX.
In this study, we proposed a rapid and sensitive method for quantification spatial distribution of salicylic acid in film tablets using FT-Raman spectroscopy with multivariate curve resolution (MCR). For purpose, the constituents were identified by spectroscopy, then eight different concentrations visualized Raman mapping. MCR was applied to mapping data expose active pharmaceutical ingredients presence other excipients monitoring maps combination enabled determination lower concentrations....
In this study, surface‐enhanced Raman spectroscopy (SERS) based quantification method for the total protein using o ‐phthalaldehyde is reported first time. For purpose, was chosen to form a complex with protein, and SERS signal observed in presence of gold nanoparticles. A calibration curve obtained by plotting intensity at 727 cm −1 versus concentration standard (bovine serum albumin, BSA). Thus, correlation found be linear within range 0.054–0.72 mg/ml BSA, limit detection determined 0.08...
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, we demonstrate high-sensitivity detection of cardiac troponin I (cTnI) through chemiluminescence-based sensing, imaging, deep learning-driven analysis. This chemiluminescence vertical flow assay (CL-VFA) enables rapid, low-cost, precise quantification cTnI, a key protein for assessing heart muscle damage myocardial infarction. The...
Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, data processing, coupled with deep learning, can help improve POCT. To demonstrate the performance our approach, present a rapid cost-effective paper-based high-sensitivity vertical flow (hs-VFA) for quantitative measurement cardiac troponin I (cTnI), biomarker widely used...
Gram staining has been one of the most frequently used protocols in microbiology for over a century, utilized across various fields, including diagnostics, food safety, and environmental monitoring. Its manual procedures make it vulnerable to errors artifacts due to, e.g., operator inexperience chemical variations. Here, we introduce virtual label-free bacteria using trained deep neural network that digitally transforms darkfield images unstained into their Gram-stained equivalents matching...
We report a rapid and automated viral plaque assay using time-lapse holographic imaging deep learning, significantly reducing the detection time needed for traditional assays entirely eliminating staining manual counting procedures.