Drosophila melanogaster has emerged as a useful model to study cardiovascular diseases, including both developmental abnormalities and adult functional impairments. Despite being much simpler, the Drosophila heart displays several developmental and functional similarities to the vertebrate heart. The fruit fly heart, located ~100 μm below the dorsal surface, has also the advantage of being easily accessed by optical imaging. Thorough analysis of Drosophila high-speed cardiac recordings requires high-throughput measurement techniques; however, current methods using canonical analysis software are time consuming. In a new study, researchers at the University of Alabama at Birmingham report the development of two machine-learning pipelines for rapid analysis of Drosophila cardiac recordings. The two pipelines, integrating the analysis of several cardiac parameters from high-speed cardiac optical recordings, were able to predict fly aging, with 83.3% and 79.1% accuracies, respectively. The deep-learning methodology was also used to assess cardiac dysfunction associated with the knock-down of oxoglutarate dehydrogenase (OGDH), revealing its potential to study dilated cardiomyopathy and other cardiovascular pathologies in the Drosophila model.

Original reference: Melkani, Y. et al. Commun. Biol. 7, 702 (2024)

黑腹果蝇已成为研究心血管疾病（包括发育异常和成人功能障碍）的有用模型。尽管要简单得多，但果蝇心脏在发育和功能上与脊椎动物心脏表现出一些相似之处。果蝇心位于背表面以下 ~100 μm 处，还具有易于通过光学成像进入的优势。对果蝇高速心脏记录的全面分析需要高通量测量技术;然而，目前使用 Canonical 分析软件的方法非常耗时。在一项新研究中，阿拉巴马大学伯明翰分校的研究人员报告了两种用于快速分析果蝇心脏记录的机器学习管道的开发。这两个管道整合了对高速心脏光学记录中多个心脏参数的分析，能够预测苍蝇衰老，准确率分别为 83.3% 和 79.1%。深度学习方法还用于评估与氧戊二酸脱氢酶 （OGDH） 敲低相关的心功能障碍，揭示了其在果蝇模型中研究扩张型心肌病和其他心血管病变的潜力。

原始参考资料：Melkani， Y. 等人。公社。生物。7， 702 （2024）