RESUMEN
Organisms track time of day through the function of cell-autonomous molecular clocks. In addition to a central clock located in the brain, molecular clocks are present in most peripheral tissues. Circadian clocks are coordinated within and across tissues, but the manner through which this coordination is achieved is not well understood. We reasoned that the ability to track in vivo molecular clock activity in specific tissues of the fruit fly, Drosophila melanogaster, would facilitate an investigation into the relationship between different clock-containing tissues. Previous efforts to monitor clock gene expression in single flies in vivo have used regulatory elements of several different clock genes to dictate expression of a luciferase reporter enzyme, the activity of which can be monitored using a luminometer. Although these reporter lines have been instrumental in our understanding of the circadian system, they generally lack cell specificity, making it difficult to compare molecular clock oscillations between different tissues. Here, we report the generation of several novel lines of flies that allow for inducible expression of a luciferase reporter construct for clock gene transcriptional activity. We find that these lines faithfully report circadian transcription, as they exhibit rhythmic luciferase activity that is dependent on a functional molecular clock. Furthermore, we take advantage of our reporter lines' tissue specificity to demonstrate that peripheral molecular clocks are able to retain rhythmicity for multiple days under constant environmental conditions.
Asunto(s)
Relojes Circadianos , Proteínas de Drosophila , Animales , Relojes Circadianos/genética , Drosophila , Drosophila melanogaster/genética , Ritmo Circadiano/genética , Proteínas de Drosophila/genética , Luciferasas/genéticaRESUMEN
Objective: This study aims to assess a machine learning (ML) algorithm using multimodal imaging to accurately identify risk factors for uveal melanoma (UM) and aid in the diagnosis of melanocytic choroidal tumors. Subjects and Methods: This study included 223 eyes from 221 patients with melanocytic choroidal lesions seen at the eye clinic of the University of Illinois at Chicago between 01/2010 and 07/2022. An ML algorithm was developed and trained on ultra-widefield fundus imaging and B-scan ultrasonography to detect risk factors of malignant transformation of choroidal lesions into UM. The risk factors were verified using all multimodal imaging available from the time of diagnosis. We also explore classification of lesions into UM and choroidal nevi using the ML algorithm. Results: The ML algorithm assessed features of ultra-widefield fundus imaging and B-scan ultrasonography to determine the presence of the following risk factors for malignant transformation: lesion thickness, subretinal fluid, orange pigment, proximity to optic nerve, ultrasound hollowness, and drusen. The algorithm also provided classification of lesions into UM and choroidal nevi. A total of 115 patients with choroidal nevi and 108 patients with UM were included. The mean lesion thickness for choroidal nevi was 1.6 mm and for UM was 5.9 mm. Eleven ML models were implemented and achieved high accuracy, with an area under the curve of 0.982 for thickness prediction and 0.964 for subretinal fluid prediction. Sensitivity/specificity values ranged from 0.900/0.818 to 1.000/0.727 for different features. The ML algorithm demonstrated high accuracy in identifying risk factors and differentiating lesions based on the analyzed imaging data. Conclusions: This study provides proof of concept that ML can accurately identify risk factors for malignant transformation in melanocytic choroidal tumors based on a single ultra-widefield fundus image or B-scan ultrasound at the time of initial presentation. By leveraging the efficiency and availability of ML, this study has the potential to provide a non-invasive tool that helps to prevent unnecessary treatment, improve our ability to predict malignant transformation, reduce the risk of metastasis, and potentially save patient lives.
RESUMEN
Many behaviors exhibit ~24-h oscillations under control of an endogenous circadian timing system that tracks time of day via a molecular circadian clock. In the fruit fly, Drosophila melanogaster, most circadian research has focused on the generation of locomotor activity rhythms, but a fundamental question is how the circadian clock orchestrates multiple distinct behavioral outputs. Here, we have investigated the cells and circuits mediating circadian control of feeding behavior. Using an array of genetic tools, we show that, as is the case for locomotor activity rhythms, the presence of feeding rhythms requires molecular clock function in the ventrolateral clock neurons of the central brain. We further demonstrate that the speed of molecular clock oscillations in these neurons dictates the free-running period length of feeding rhythms. In contrast to the effects observed with central clock cell manipulations, we show that genetic abrogation of the molecular clock in the fat body, a peripheral metabolic tissue, is without effect on feeding behavior. Interestingly, we find that molecular clocks in the brain and fat body of control flies gradually grow out of phase with one another under free-running conditions, likely due to a long endogenous period of the fat body clock. Under these conditions, the period of feeding rhythms tracks with molecular oscillations in central brain clock cells, consistent with a primary role of the brain clock in dictating the timing of feeding behavior. Finally, despite a lack of effect of fat body selective manipulations, we find that flies with simultaneous disruption of molecular clocks in multiple peripheral tissues (but with intact central clocks) exhibit decreased feeding rhythm strength and reduced overall food intake. We conclude that both central and peripheral clocks contribute to the regulation of feeding rhythms, with a particularly dominant, pacemaker role for specific populations of central brain clock cells.