ArticlebioRxiv : the preprint server for biology2024
A high-throughput method for quantifying
Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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10 authors.
Funding
Abstract
Measurements of Drosophila fecundity are used in a wide variety of studies, such as investigations of stem cell biology, nutrition, behavior, and toxicology. In addition, because fecundity assays are performed on live flies, they are suitable for longitudinal studies such as investigations of aging or prolonged chemical exposure. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another; the RoboCam, a low-cost, custom built robotic camera to capture images of the wells automatically; and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period; and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.