Objective: The aim of this study is to estimate gender with parameters obtained from the upper dental arcade by using machine learning algorithms and artificial neural networks. Methods: The study was conducted on cone-beamed computed tomography images of 176 individuals between the ages of 18 and 55 who did not have any pathologies or surgical interventions in their upper dental arcade. The images obtained were transferred to RadiAnt DICOM Viewer program in Digital Imaging and Communications in Medicine format and all images were brought to orthogonal plane by applying 3D Curved Multiplanar Reconstruction. Length and curvature length measurements were performed on these images brought to orthogonal plane. The data obtained were used in machine learning algorithms (ML) and artificial neural networks input and rates of gender estimation were shown. Results: In the study, an accuracy ratio of 0.86 was found with ML models linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR) algorithm and an accuracy ratio of 0.86 was found with random forest (RF) algorithm. It was found with SHAP analyser of RF algorithm that the parameter of width at the level of 3rd molar teeth contributed the most to gender. An accuracy rate of 0.92 was found as a result of training for 500 times with multilayer perceptron classifier (MLCP), which is an artificial neural network (ANN) model. Conclusion: As a result of our study, it was found that the parameters obtained from the upper dental arcade showed a high accuracy in estimation of gender. In this context, we believe that the present study will make important contributions to forensic sciences.

Monosodium glutamate (MSG) is a widely used flavoring agent worldwide. Although MSG is found in many packaged and ready-to-eat foods, it also has many side effects. The aim of this study was to investigate the effects of MSG on body weight, brain and cognitive functions histopathologically and biochemically. Starting from the first day of the experiment, 4 mg/kg saline was given to the control group and 4 mg/kg MSG to the experimental group for 28 days. The rats were also subjected to Barnes maze test every day. At the end of the experiment, the animals were decapitated, and brain tissues were removed. Biochemical and histopathological analyses were performed on the removed brain tissues. At the end of the experiment, there was a statistically significant (p < 0.000) increase in the average weight of the experimental group. There was a statistically significant difference between the experimental group and the control group in terms of Barnes Maze test times (p < 0.000) and number of trials (p < 0.001). Total antioxidant status (TAS) was 1.75 ± 0.14 mmol Trolox equiv/L in the control group and 1.40 ± 0.21 mmol Trolox Equiv/L in the experimental group. Total oxidant status (TOS) was 4.22 ± 1.71 µmol H2O2 Equiv/L in the control group and 7.15 ± 1.35 µmol H2O2 Equiv/L in the experimental group. Oxidative stress index (OSI) was 2.46 ± 1.05 in the control group and 5.23 ± 1.40 in the experimental group. These differences in TAS, TOS and OSI were statistically significant (p < 0.000). Histological analysis showed shrinkage, degeneration, pyknosis, karyolysis, necrosis and mild satellitosis in the experimental group. The results of this study revealed that MSG had negative effects on body weight, brain function and cognitive capacity of rats, caused negative changes in the cellular structure of brain tissue and increased oxidative stress in the tissue.

The skull is highly durable and plays a significant role in sex determination as one of the most dimorphic bones. The facial canal (FC), a clinically significant canal within the temporal bone, houses the facial nerve. This study aims to estimate sex using morphometric measurements from the FC through machine learning (ML) and artificial neural networks (ANNs). The study utilized Computed Tomography (CT) images of 200 individuals (100 females, 100 males) aged 19–65 years. These images were retrospectively retrieved from the Picture Archiving and Communication Systems (PACS) at Düzce University Faculty of Medicine, Department of Radiology, covering 2021–2024. Bilateral measurements of nine temporal bone parameters were performed in axial, coronal, and sagittal planes. ML algorithms including Quadratic Discriminant Analysis (QDA), Linear Discriminant Analysis (LDA), Decision Tree (DT), Extra Tree Classifier (ETC), Random Forest (RF), Logistic Regression (LR), Gaussian Naive Bayes (GaussianNB), and k-Nearest Neighbors (k-NN) were used, alongside a multilayer perceptron classifier (MLPC) from ANN algorithms. Except for QDA (Acc 0.93), all algorithms achieved an accuracy rate of 0.97. SHapley Additive exPlanations (SHAP) analysis revealed the five most impactful parameters: right SGAs, left SGAs, right TSWs, left TSWs and, the inner mouth width of the left FN, respectively. FN-centered morphometric measurements show high accuracy in sex determination and may aid in understanding FN positioning across sexes and populations. These findings may support rapid and reliable sex estimation in forensic investigations—especially in cases with fragmented craniofacial remains—and provide auxiliary diagnostic data for preoperative planning in otologic and skull base surgeries. They are thus relevant for surgeons, anthropologists, and forensic experts. Not applicable.

Aim: In order to prevent any microbiological contamination in laboratories, it is vital to determine both routine microbiological screening and the appropriate protocol. This study was based on this hypothesis and discussed the microbiological contamination and prevention procedures in an anatomy laboratory. Methods: The study was carried out on 34 different spots in an anatomy laboratory. Swab samples taken from these points were examined for contamination and contamination was detected. The samples were taken from various locations, including the head, upper and lower extremities of both male and female cadavers, the door handle, the floor in front of the door, the faucet, the head, body, and foot parts of the dissection table, the dissection tool, the trailer, the inner and outer coating of the cadaver pool, the sink, the floor in front of the window, the stool, the living room wall, the formaldehyde liquid in the cadaver pool, the window handle, the instrument table, the morgue unit, the exterior surfaces of three different organ storage boxes, the inner surface of an organ storage box, the medical waste container, the handle of the organ storage cabinet, a training model, the lower surface of the dissection table, the medical waste storage box for dissection, and the blackboard. Results: Bacillus subtilis was found in 16 out of 34 different spots and mold fungus was found in 2 of them. No contamination was detected in the remaining 16 spots. 69% of the spots were directly related to the cadaver. Conclusion: As a result of our study, the importance of scanning anatomy laboratories in terms of microbiological contamination was highlighted and an appropriate protocol was determined.