果蠅(Drosophila melanogaster)的習得性無助表現之研究
習得性無助是個體經多次追求獎賞或逃離困境失敗後產生的一種消極行為表現。習得性無助的行為研究雖多,但對其神經機制的研究卻甚少。 本研究發現273,cha-Gal80>CsC-mCh是適合光遺傳學訓練的果蠅殖系。在白光點獎賞記憶訓練中,使273,cha-Gal80>CsC-mCh果蠅學會白光點視覺訊號代表著獎賞,並發現其白光獎賞記憶能持續7分鐘以上但未達10分鐘。藉已建立白光視覺訊號與獎賞連結的273,cha-Gal80>CsC-mCh,發現重複追求獎賞失敗的實驗組,相較於持續接受獎賞與完成獎賞記憶訓練而無任何操作的對照組,明顯表現習得性無助,本研究亦發現習得性無助個體也表現了活動力、覓食表現及攝食動機的下降。 本研究成功建立高成效的果蠅成蟲光遺傳學習得性無助訓練,並針對果蠅成蟲的習得性無助行為表現進行完整的研究,未來期望本於此訓練方式進行特定腦區、神經群和神經傳遞物之探究,建構果蠅習得性無助的神經網路機制。
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.
Sequentially bidirectional gastrovascular flows in highly branched digestive tracts of panocerid flatworm
Examination of the predation behavior of polyclad flatworms is extremely rare. This study collects Paraplanocera oligoglena, the most common species in Taiwan. Tank-based feeding experiments reveal that Paraplanocera oligoglena can prey on several species of gastropods, such as sea snails and sea hares. Predation behavior encompasses attack, invasion and ingestion periods. This research pioneers the use of stained clam and static image analysis to observe the highly branched digestive system of flatworms. The sequentially bidirectional flow of gastrovascular cavity is first found in polyclad flatworms by the post-stain active tracking technique. Measuring peristalsis movement in inward and outward directions and segmented movement, the contraction frequencies are roughly the same in subsequent order of given branches. Confirmation is provided that the circular membrane-like muscles within the digestive tract are the main driving force for transporting and mixing food. The food dyeing technology used in this experiment also provides the possibility of future research on food chains in the wild.