Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 Valencia, Spain.
Sensors (Basel). 2020 Oct 22;20(21):5981. doi: 10.3390/s20215981.
Nowadays, various artificial vision-based machines automate the lifespan assays of . These automated machines present wider variability in results than manual assays because in the latter worms can be poked one by one to determine whether they are alive or not. Lifespan machines normally use a "dead or alive criterion" based on nematode position or pose changes, without poking worms. However, worms barely move on their last days of life, even though they are still alive. Therefore, a long monitoring period is necessary to observe motility in order to guarantee worms are actually dead, or a stimulus to prompt worm movement is required to reduce the lifespan variability measure. Here, a new automated vibrotaxis-based method for lifespan machines is proposed as a solution to prompt a motion response in all worms cultured on standard Petri plates in order to better distinguish between live and dead individuals. This simple automated method allows the stimulation of all animals through the whole plate at the same time and intensity, increasing the experiment throughput. The experimental results exhibited improved live-worm detection using this method, and most live nematodes (>93%) reacted to the vibration stimulus. This method increased machine sensitivity by decreasing results variance by approximately one half (from ±1 individual error per plate to ±0.6) and error in lifespan curve was reduced as well (from 2.6% to 1.2%).
如今,各种基于人工视觉的机器可以自动进行寿命测定实验。这些自动化机器的结果比手动测定实验更具变异性,因为在后者中,可以逐个戳虫子来确定它们是否还活着。寿命测定机器通常使用基于线虫位置或姿势变化的“死活标准”,而无需戳虫子。然而,在生命的最后几天,虫子几乎不动,即使它们还活着。因此,为了保证虫子确实已经死亡,需要进行长时间的监测以观察其运动情况,或者需要刺激促使虫子运动,以减少寿命测量的变异性。在这里,提出了一种新的基于振动趋性的自动化寿命测定机器方法,作为刺激培养在标准培养皿中的所有虫子产生运动反应的解决方案,以便更好地区分死活个体。这种简单的自动化方法允许同时以相同的强度刺激整个培养板上的所有动物,从而提高了实验通量。实验结果表明,使用这种方法可以提高活虫检测的灵敏度,并且大多数活线虫(>93%)对振动刺激有反应。该方法通过将每个板的误差减少约一半(从±1 个个体误差减少到±0.6)来降低机器的变异性,同时也降低了寿命曲线的误差(从 2.6%降低到 1.2%)。