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    Histopathologic effects of obstetric gel on the vaginal tissue: in vaginal trauma formed rat model
    (Taylor & Francis Ltd, 2024) Kaplan, Selcuk; Turk, Bilge Aydin; Elibol, Ebru; Ozbey, Guerkan; Ekinci, Tekin
    The present study aimed to investigate the histopathological effects of obstetric gel (OG) on vaginal tissue. In this study, 21 female Wistar albino rats were divided into three groups, comprising seven animals in each group. The first group (group 1) was the control group, the second group (group 2) was the physiological saline (PS) group, and the third group (group 3) was the OG group. In group 1, dilatation was performed using Hegar dilators from Hegar 5 to Hegar 10 without any vaginal application. In group 2, the vagina was washed with a PS-filled applicator. In group 3, the vagina was washed with an OG-filled applicator and Hegar dilators were used to achieve vaginal dilatation. In the group of OG-applied rats, there was an increase in mast cell infiltration, tissue epithelial thickness, and fibrillin-1 levels of the mucosa in the vaginal tissue. The present study is the first to investigate the histopathological effects of OG used for vaginal tissue dilatation in rats. OGs have no early effectiveness in preventing the damage caused by compression of the vaginal wall; however, OGs may have a protective effect against pelvic floor pathologies.
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    PFP-LHCINCA: Pyramidal Fixed-Size Patch-Based Feature Extraction and Chi-Square Iterative Neighborhood Component Analysis for Automated Fetal Sex Classification on Ultrasound Images
    (Hindawi Limited, 2022) Kaplan, Ela; Ekinci, Tekin; Kaplan, Selcuk; Barua, Prabal Datta; Dogan, Sengul; Tuncer, Turker; Acharya, U. Rajendra
    Objectives. Fetal sex determination with ultrasound (US) examination is indicated in pregnancies at risk of X-linked genetic disorders or ambiguous genitalia. However, misdiagnoses often arise due to operator inexperience and technical difficulties while acquiring diagnostic images. We aimed to develop an efficient automated US-based fetal sex classification model that can facilitate efficient screening and reduce misclassification. Methods. We have developed a novel feature engineering model termed PFP-LHCINCA that employs pyramidal fixed-size patch generation with average pooling-based image decomposition, handcrafted feature extraction based on local phase quantization (LPQ), and histogram of oriented gradients (HOG) to extract directional and textural features and used Chi-square iterative neighborhood component analysis feature selection (CINCA), which iteratively selects the most informative feature vector for each image that minimizes calculated feature parameter-derived k-nearest neighbor-based misclassification rates. The model was trained and tested on a sizeable expert-labeled dataset comprising 339 males' and 332 females' fetal US images. One transverse fetal US image per subject zoomed to the genital area and standardized to 256 × 256 size was used for analysis. Fetal sex was annotated by experts on US images and confirmed postnatally. Results. Standard model performance metrics were compared using five shallow classifiers - k-nearest neighbor (kNN), decision tree, naïve Bayes, linear discriminant, and support vector machine (SVM) - with the hyperparameters tuned using a Bayesian optimizer. The PFP-LHCINCA model achieved a sex classification accuracy of ≥88% with all five classifiers and the best accuracy rates (>98%) with kNN and SVM classifiers. Conclusions. US-based fetal sex classification is feasible and accurate using the presented PFP-LHCINCA model. The salutary results support its clinical use for fetal US image screening for sex classification. The model architecture can be modified into deep learning models for training larger datasets. © 2022 Ela Kaplan et al.
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    The role of toll-like receptor 4 in the development of endometriosis and the benefits of trastuzumab in the treatment of endometriosis: a rat model
    (Taylor & Francis Ltd, 2025) Korun, Zeynep Ece Utkan; Kirici, Pinar; Elibol, Ebru; Kaplan, Selcuk; Karacor, Talip
    We aimed to investigate TLR-4 receptor activity in the development of endometriosis and the effect of trastuzumab in experimentally induced endometriotic tissue via TLR-4 in this study. Twenty-eight female Wistar-Albino rats were divided into four groups: Group 1 (Control Group), Group 2 (Endometriosis Group), Group 3 (Endometriosis + Trastuzumab Group), and Group 4 (Trastuzumab Group). All animal tissue samples were collected. Histopathological, immunohistochemical, and biochemical analyses were performed. In histopathological analysis, there was a significant difference between Group 2 and other groups in terms of connective tissue edema, inflammation, hemorrhage, epithelial damage, and mast cell density. In immunohistochemical analysis with TLR-4, Group 2 exhibited strong staining. In biochemical analysis, it was found that there was a highly significant difference between Group 2 and Group 1 considering the Malondialdehyde (MDA) levels in plasma samples. There was no significant difference in terms of the MDA levels among other groups. Considering the glutathione levels in the plasma samples, it was found that there was a highly significant difference between Group 2 and Groups 3 and 4. Trastuzumab may play a role in the treatment of histopathological damage and fibrosis in experimentally induced endometriotic implants by showing anti-inflammatory and antiproliferative activity.