果蠅緯度相關晝夜節律特徵:穩定性、活動量分佈與演化意義
Latitude-Dependent Circadian Traits in Drosophila: Stability, Activity Peaks, and Evolutionary Implications
生物時鐘可對生物體的行為與生理造成影響,在探討晝夜節律特徵的差異時,過去研究常侷限於北美大陸的品系,缺少赤道及南半球品系的晝夜節律特徵探討。有鑒於黑腹果蠅在全球各大洲的廣泛分佈,因此我們以黑腹果蠅(近赤道與中高緯度品系)為材料,研究果蠅是否因緯度而有相異的晝夜節律特徵?結果顯示不同緯度的果蠅品系展現出相異的晝夜節律特徵。赤報品系在全暗狀態下仍維持原本光暗12小時的穩定節律,而南北半球的中高緯度品系則具有相似節律特徵,即在全暗狀態下的節律不對齊原本正常光源的穩定節律,其他如活動量、週期、及節律強度等皆有著品系間的差異。更進一步比對實驗中各個品系基因序列,研究發現per和tim在調控區段有許多SNP變異,顯示其與晝夜節律特徵的關係,有助於後續尋找更多造成晝夜節律特徵差異的可能遺傳變異並探討。
BeeMind AI: Development of an AI-Based System to Assess Honeybee Health, Behavior, and Nutrient Effects on Learning and Memory
Due to their pollination services, honeybees are one of the most ecologically vital animals, being singlehandedly responsible for nearly 80% of global agricultural pollination [1]. However, in recent years, they have experienced large declines in populations, and as a survey reported roughly 50% of beekeepers in the US lost their honeybee colonies [2]. These losses are experienced globally due to a combination of many factors, including but not limited to habitat loss, pesticides, climate change, and other invasive species [3, 4]. One of the biggest factors attributed to the decline of honeybee colonies is the usage of pesticides, specifically neonicotinoids [3-6]. Neonicotinoid compounds have been used globally since their introduction in the early 1990s [4]. Studies have shown that neonicotinoids can have both sublethal and lethal effects on honeybees, depending on the dosages that they are exposed to, as neonicotinoids bind to nervous system receptors of honeybees [7]. These effects can range from behavior changes to altered motor functions [7-9]. Among the reported effects, one of the more significant ones is the effect of neonicotinoids on honeybee learning and memory [10, 11]. Additionally, there is a lack of availability for methods of monitoring of honeybee hives, essentially meaning that the only methods to track honeybee health are through obtrusive physical methods of inspection. This paper aims to develop a novel AI-based honeybee health assessment system, able to monitor beehives using the following functions: continuous temperature and humidity monitoring both inside and outside the hive, as well as video and audio recording to assess honeybee health as well as population. In addition, this system can be used for honeybee-related studies such as nutrition effects and evaluation on health, learning, and memory. To do this, four types of nutrition have been studied and their effects have been analyzed by a deep learning approach.