https://hdl.handle.net/20.500.12573/397 PubMed Indexed Publications Collection 2026-05-08T06:32:50Z https://hdl.handle.net/20.500.12573/2542 An effective colorectal polyp classification for histopathological images based on supervised contrastive learning Yengec-Tasdemir,Sena Busra; Aydin,Zafer; Akay,Ebru; Doğan,Serkan; Yilmaz,Bulent Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic variants is crucial. This study introduces a cutting-edge computer-aided diagnosis system optimized for this task. Our system employs advanced Supervised Contrastive learning to ensure precise classification of colon histopathology images. Significantly, we have integrated the Big Transfer model, which has gained prominence for its exemplary adaptability to visual tasks in medical imaging. Our novel approach discerns between in-class and out-of-class images, thereby elevating its discriminatory power for polyp subtypes. We validated our system using two datasets: a specially curated one and the publicly accessible UniToPatho dataset. The results reveal that our model markedly surpasses traditional deep convolutional neural networks, registering classification accuracies of 87.1% and 70.3% for the custom and UniToPatho datasets, respectively. Such results emphasize the transformative potential of our model in polyp classification endeavors 2024-01-01T00:00:00Z https://hdl.handle.net/20.500.12573/2541 Matching variants for functional characterization of genetic variants Cevik,Sabiha; Zhao,Pei; Zorluer,Atiyye; Pir, Mustafa S.; Bian, Wenyin; Kaplan, Oktay I. Rapid and low-cost sequencing, as well as computer analysis, have facilitated the diagnosis of many genetic diseases, resulting in a substantial rise in the number of disease-associated genes. However, genetic diagnosis of many disorders remains problematic due to the lack of interpretation for many genetic variants, especially missenses, the infeasibility of high-throughput experiments on mammals, and the shortcomings of computational prediction technologies. Additionally, the available mutant databases are not well-utilized. Toward this end, we used Caenorhabditis elegans mutant resources to delineate the functions of eight missense variants (V444I, V517D, E610K, L732F, E817K, H873P, R1105K, and G1205E) and two stop codons (W937stop and Q1434stop), including several matching variants (MatchVar) with human in ciliopathy associated IFT-140 (also called CHE-11)//IFT140 (intraflagellar transport protein 140). Moreover, MatchVars carrying C. elegans mutants, including IFT-140(G680S) and IFT-140(P702A) for the human (G704S) (dbSNP: rs150745099) and P726A (dbSNP: rs1057518064 and a conflicting variation) were created using CRISPR/Cas9. IFT140 is a key component of IFT complex A (IFT-A), which is involved in the retrograde transport of IFT along cilia and the entrance of G protein-coupled receptors into cilia. Functional analysis of all 10 variants revealed that P702A and W937stop, but not others phenocopied the ciliary phenotypes (short cilia, IFT accumulations, mislocalization of membrane proteins, and cilia entry of nonciliary proteins) of the IFT-140 null mutant, indicating that both P702A and W937stop are phenotypic in C. elegans. Our functional data offered experimental support for interpreting human variants, by using ready-to-use mutants carrying MatchVars and generating MatchVars with CRISPR/Cas9. 2023-01-01T00:00:00Z https://hdl.handle.net/20.500.12573/2537 Electrochemical and Optical Multi-Detection of Escherichia coli Through Magneto-Optic Nanoparticles: A Pencil-on-Paper Biosensor Soysaldi, Furkan; Ekici, Derya Dincyurek; Soylu, Mehmet cagri; Mutlugun, Evren Escherichia coli (E. coli) detection suffers from slow analysis time and high costs, along with the need for specificity. While state-of-the-art electrochemical biosensors are cost-efficient and easy to implement, their sensitivity and analysis time still require improvement. In this work, we present a paper-based electrochemical biosensor utilizing magnetic core-shell Fe2O3@CdSe/ZnS quantum dots (MQDs) to achieve fast detection, low cost, and high sensitivity. Using electrochemical impedance spectroscopy (EIS) as the detection technique, the biosensor achieved a limit of detection of 2.7 x 10(2) CFU/mL for E. coli bacteria across a concentration range of 10(2)-10(8) CFU/mL, with a relative standard deviation (RSD) of 3.5781%. From an optical perspective, as E. coli concentration increased steadily from 10(4) to 10(7) CFU/mL, quantum dot fluorescence showed over 60% lifetime quenching. This hybrid biosensor thus provides rapid, highly sensitive E. coli detection with a fast analysis time of 30 min. This study, which combines the detection advantages of electrochemical and optical biosensor systems in a graphite-based paper sensor for the first time, has the potential to meet the needs of point-of-care applications. It is thought that future studies that will aim to examine the performance of the production-optimized, portable, graphite-based sensor system on real food samples, environmental samples, and especially medical clinical samples will be promising. 2024-01-01T00:00:00Z https://hdl.handle.net/20.500.12573/2536 Discovery of a C-S lyase inhibitor for the prevention of human body malodor formation: tannic acid inhibits the thioalcohol production in Staphylococcus hominis Fidan, Ozkan; Karipcin, Ayse Doga; Kose, Ayse Hamide; Anaz, Ayse; Demirsoy, Beyza Nur; Arslansoy, Nuriye; Sun, Lei; Mujwar, Somdutt Human body odor is a result of the bacterial biotransformation of odorless precursor molecules secreted by the underarm sweat glands. In the human axilla, Staphylococcus hominis is the predominant bacterial species responsible for the biotransformation process of the odorless precursor molecule into the malodorous 3M3SH by two enzymes, a dipeptidase and a specific C-S lyase. The current solutions for malodor, such as deodorants and antiperspirants are known to block the apocrine glands or disrupt the skin microbiota. Additionally, these chemicals endanger both the environment and human health, and their long-term use can influence the function of sweat glands. Therefore, there is a need for the development of alternative, environmentally friendly, and natural solutions for the prevention of human body malodor. In this study, a library of secondary metabolites from various plants was screened to inhibit the C-S lyase, which metabolizes the odorless precursor sweat molecules, through molecular docking and molecular dynamics (MD) simulation. In silico studies revealed that tannic acid had the strongest affinity towards C-S lyase and was stably maintained in the binding pocket of the enzyme during 100-ns MD simulation. We found in the in vitro biotransformation assays that 1 mM tannic acid not only exhibited a significant reduction in malodor formation but also had quite low growth inhibition in S. hominis, indicating the minimum inhibitory effect of tannic acid on the skin microflora. This study paved the way for the development of a promising natural C-S lyase inhibitor to eliminate human body odor and can be used as a natural deodorizing molecule after further in vivo analysis. 2025-01-01T00:00:00Z