Purpose: Despite the proliferation of numerous morphometric and anthropometric methods for sex identification based on linear, angular, and regional measurements of various parts of the body, these methods are subject to error due to the observer’s knowledge and expertise. This study aimed to explore the possibility of automated sex determination using convolutional neural networks (CNNs) based on lateral cephalometric radiographs. Materials and Methods: Lateral cephalometric radiographs of 1,476 Iranian subjects (794 women and 682 men) from 18 to 49 years of age were included. Lateral cephalometric radiographs were considered as a network input and output layer including 2 classes (male and female). Eighty percent of the data was used as a training set and the rest as a test set. Hyperparameter tuning of each network was done after preprocessing and data augmentation steps. The predictive performance of different architectures (DenseNet, ResNet, and VGG) was evaluated based on their accuracy in test sets. Results: The CNN based on the DenseNet121 architecture, with an overall accuracy of 90%, had the best predictive power in sex determination. The prediction accuracy of this model was almost equal for men and women. Furthermore, with all architectures, the use of transfer learning improved predictive performance. Conclusion The results confirmed that a CNN could predict a person’s sex with high accuracy. This prediction was independent of human bias because feature extraction was done automatically. However, for more accurate sex determination on a wider scale, further studies with larger sample sizes are desirable.

Alzheimer disease (AD) is a common neurodegenerative disorder, characterized by memory impairment, dementia, and diminished cognitive function. This disease affects more than 20 million people worldwide. Amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs) are important pathological markers of AD. Multiple studies have indicated a potential association between elevated cholesterol levels and increased risk of AD, suggesting that lowering the cholesterol level could be a viable strategy for AD treatment or prevention. Statins, potent inhibitors of cholesterol synthesis, are widely used in clinical practice to decrease the plasma levels of LDL cholesterol in patients with hyperlipidemia. Statins are known to play a neuroprotective role in limiting Aβ pathology through cholesterol-lowering therapies. In addition to Aβ plaques and neurofibrillary tangles, the brains of AD patients exhibit signs of oxidative stress, neuroinflammatory responses, and synaptic disruption.Consequently, compounds with antioxidant, anti-inflammatory, and/or neuroprotective properties could be beneficial components of AD treatment strategies. In addition to lowering LDL cholesterol, statins have demonstrated therapeutic efficacy in various forms, including antioxidant, anti-inflammatory, and neuroprotective effects. These properties of statins are potential mechanisms underlying their beneficial effects in treating neurodegenerative diseases. Therefore, this review was conducted to provide an overview of the protective effects of statins against AD.

OBJECTIVE: Accumulation of estrogenic compounds and other carcinogens in normal breast tissues contributes to unpredictable breast cancer incidence during adolescence and throughout life. To assess the role of parabens in this phenomenon, the paraben content of adjacent normal-malignant breast tissues is measured in women with breast cancer living in Isfahan Province, Iran. METHODS: Adjacent normal-malignant breast tissue samples were obtained from 53 subjects. The parabens including methyl-paraben (MePB), ethyl-paraben (EtPB), propyl-paraben (PrPB), and butylparaben (BuPB) were extracted from the sample supernatant and then subjected to gas chromatography analysis. RESULTS: Some risk factors for breast cancer were stimulated by parabens in adjacent malignant-normal breast tissues among young and middle-aged women with breast cancer. We observed a significant association for dose-response pattern of MePB [OR = 98.34 (11.43-185.2), P = 0.027] for both ER+ and PR+ women and MePB [OR = 164.3 (CI: 112.3-216.3), P < 0.001] for HER2+ women than women with negative receptors. The risk of 95-fold increase in MePB dose and 164-fold increase in ΣPBs dose were significant for women with hereditary breast cancer in first-degree relatives. CONCLUSION These results may promote future epidemiology studies and strategies to improve women's lifestyle and consume paraben-free products.