Olfactory receptor (OR)-associated events are mediated by well-conserved components in the olfactory epithelium, including olfactory G-protein (G_olf), adenylate cyclase III (ACIII), and olfactory marker protein (OMP). The expression of ORs has recently been observed in non-olfactory tissues where they are involved in monitoring extracellular chemical cues. The large number of OR genes and their sequence similarities illustrate the need to find an effective and simple way to detect non-olfactory OR-associated events. In addition, expression profiles and physiological functions of ORs in non-olfactory tissues are largely unknown. To overcome limitations associated with using OR as a target protein, this study used OMP with G_olf and ACIII as targets to screen for potential OR-mediated sensing systems in non-olfactory tissues. Here, we show using western blotting, real-time PCR, and single as well as double immunoassays that ORs and OR-associated proteins are co-expressed in diverse tissues. The results of immunohistochemical analyses showed OMP (+) cells in mouse heart and in the following cells using the corresponding marker proteins c-kit, keratin 14, calcitonin, and GFAP in mouse tissues: interstitial cells of Cajal of the bladder, medullary thymic epithelial cells of the thymus, parafollicular cells of the thyroid, and Leydig cells of the testis. The expression of ORs in OMP (+) tissues was analyzed using a refined microarray analysis and validated with RT-PCR and real-time PCR. Three ORs (olfr544, olfr558, and olfr1386) were expressed in the OMP (+) cells of the bladder and thyroid as shown using a co-immunostaining method. Together, these results suggest that OMP is involved in the OR-mediated signal transduction cascade with olfactory canonical signaling components between the nervous and endocrine systems. The results further demonstrate that OMP immunohistochemical analysis is a useful tool for identifying expression of ORs, suggesting OMP expression is an indicator of potential OR-mediated chemoreception in non-olfactory systems.

Myeonghwa Lee, Seonho An, Min-Soo Kim. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2024.

Age-related macular degeneration (AMD) is the main cause of irreversible blindness among the elderly and require early diagnosis to prevent vision loss, and careful treatment is essential. Optical coherence tomography (OCT), the most commonly used imaging method in the retinal area for the diagnosis of AMD, is usually interpreted by a clinician, and OCT can help diagnose disease on the basis of the relevant diagnostic criteria, but these judgments can be somewhat subjective. We propose an algorithm for the detection of AMD based on a weakly supervised convolutional neural network (CNN) model to support computer-aided diagnosis (CAD) system. Our main contributions are the following three things. (1) We propose a concise CNN model for OCT images, which outperforms the existing large CNN models using VGG16 and GoogLeNet architectures. (2) We propose an algorithm called Expressive Gradients (EG) that extends the existing Integrated Gradients (IG) algorithm so as to exploit not only the input-level attribution map, but also the high-level attribution maps. Due to enriched gradients, EG can highlight suspicious regions for diagnosis of AMD better than the guided-backpropagation method and IG. (3) Our method provides two visualization options: overlay and top-k bounding boxes, which would be useful for CAD. Through experimental evaluation using 10,100 clinical OCT images from AMD patients, we demonstrate that our EG algorithm outperforms the IG algorithm in terms of localization accuracy and also outperforms the existing object detection methods in terms of class accuracy.