Recent insights into the role of hormones during development and their functional regulation.

Introduction: Hormones play a vital role in development from conception to birth and throughout the human lifespan. These periods are logically divided into fetal development, pre-pubertal growth, puberty, and adulthood. Deviations from standard physiological levels and release patterns of constituent hormones can lead to pathology affecting the normal developmental trajectory. Research is ongoing to better understand the mechanisms of these hormones and how their modulation affects development. Methods: This article focuses on recent developments in understanding the role hormones play in development. We also cover recent discoveries in signaling pathways and hormonal regulation. Results: New and continuing research into functional hormone regulation focuses on sex hormones, gonadotropic hormones, growth hormones, insulin-like growth factor, thyroid hormone, and the interconnectedness of each of these functional axes. Currently, the abundance of work focuses on fertility and correction of sex hormone levels based on an individual's condition and stage in life. Discussion: Continuing research is needed to fully understand the long-term effects of hormone modulation in growth and sexual development. The role of each hormone in parallel endocrine axes should also be more thoroughly investigated to help improve the safety and efficacy in endocrine pharmacotherapeutics.

Sex classification of 3D skull images using deep neural networks.

Determining the fundamental characteristics that define a face as "feminine" or "masculine" has long fascinated anatomists and plastic surgeons, particularly those involved in aesthetic and gender-affirming surgery. Previous studies in this area have relied on manual measurements, comparative anatomy, and heuristic landmark-based feature extraction. In this study, we collected retrospectively at Cedars Sinai Medical Center (CSMC) a dataset of 98 skull samples, which is the first dataset of this kind of 3D medical imaging. We then evaluated the accuracy of multiple deep learning neural network architectures on sex classification with this dataset. Specifically, we evaluated methods representing three different 3D data modeling approaches: Resnet3D, PointNet++, and MeshNet. Despite the limited number of imaging samples, our testing results show that all three approaches achieve AUC scores above 0.9 after convergence. PointNet++ exhibits the highest accuracy, while MeshNet has the lowest. Our findings suggest that accuracy is not solely dependent on the sparsity of data representation but also on the architecture design, with MeshNet's lower accuracy likely due to the lack of a hierarchical structure for progressive data abstraction. Furthermore, we studied a problem related to sex determination, which is the analysis of the various morphological features that affect sex classification. We proposed and developed a new method based on morphological gradients to visualize features that influence model decision making. The method based on morphological gradients is an alternative to the standard saliency map, and the new method provides better visualization of feature importance. Our study is the first to develop and evaluate deep learning models for analyzing 3D facial skull images to identify imaging feature differences between individuals assigned male or female at birth. These findings may be useful for planning and evaluating craniofacial surgery, particularly gender-affirming procedures, such as facial feminization surgery.

Incidence of Cancer and Role of Sentinel Lymph Node Biopsy in BRCA Mutation Carriers Undergoing Prophylactic Mastectomies.

INTRODUCTION: Breast surveillance in patients with BRCA mutations include mammography (MMG) and MRI. Patients may elect to undergo risk-reducing bilateral prophylactic mastectomies (BPM). Sentinel lymph node biopsies (SLNB) are frequently performed and associated with increased morbidity. This study sought to determine the correlation between preoperative imaging and the final pathology and evaluate the role of SLNB in these high-risk patients. METHODS: A prospective database identified BRCA patients who underwent BPM between 2006 and 2022. Imaging, pathology, and operative reports were reviewed. RESULTS: 170 patients with BRCA 1/2 mutations were identified. 162 (95.3%) had imaging within one year of BPM. Of these, 28 (17.3%) patients had a MMG/ultrasound, 53 (32.7%) had an MRI, and 81 (50%) had both; 21/162 (13.0%) patients had abnormal imaging. Bilateral SLNB were performed in 31 (18.2%) patients, of which 7 had abnormal imaging; unilateral SLNB were performed in 4 (2.4%) patients, of which 3 had abnormal imaging. 11/170 (6.4%) patients had a malignancy and only one (9%) of these patients had imaging abnormalities. 1/170 (0.6%) patient had an invasive carcinoma requiring an axillary lymph node dissection (ALND), and 10/170 (5.9%) patients had ductal carcinoma in situ (DCIS). 25/170 (14.7%) had ADH/ALH. Only 7/170 (4.1%) patients had imaging abnormalities and abnormal pathology. All SLNB and ALND performed demonstrated no metastatic disease. DISCUSSION: There is a high rate of discordance between preoperative imaging prior to surgery in BRCA patients undergoing prophylactic mastectomies and final pathology. This study does not support routine SLNB at the time of BPM.