Evidence map›Paper›PMID 38585877›Full record

ArticlebioRxiv : the preprint server for biology2024

A high-throughput method for quantifying

Andreana Gomez, Sergio Gonzalez, Ashwini Oke, Jiayu Luo, Johnny B Duong, Raymond M Esquerra, Thomas Zimmerman, Sara Capponi, Jennifer C Fung, Todd G Nystul

Abstract readPreprint
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Andreana GomezUniversity of California, San Francisco, Department of Anatomy.
Sergio GonzalezSan Francisco State University, Department of Biology.
Ashwini OkeSan Francisco State University, Department of Chemistry and Biochemistry; University of California, San Francisco, OB/GYN Department.
Jiayu LuoSan Francisco State University, Department of Biology.
Johnny B DuongCenter for Cellular Construction, San Francisco, CA.
Raymond M EsquerraCenter for Cellular Construction, San Francisco, CA.
Thomas ZimmermanCenter for Cellular Construction, San Francisco, CA.
Sara CapponiCenter for Cellular Construction, San Francisco, CA.
Jennifer C FungSan Francisco State University, Department of Chemistry and Biochemistry; University of California, San Francisco, OB/GYN Department.
Todd G NystulUniversity of California, San Francisco, Department of Anatomy.ORCID 0000-0002-6250-2394

Funding

UCSF Environmental Research and Translation for Health Center (EaRTH Center)P30ES030284 · NIEHS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JENNIFER C FUNG, Tracey J. Woodruff · 2020 to 2026
$11.2M
U-RISE at San Francisco State UniversityT34GM145400 · NIGMS · SAN FRANCISCO STATE UNIVERSITY · PI Raymond M. Esquerra, MEGUMI M. FUSE · 2022 to 2026
$4.6M
Cell Fate Decisions in Epithelial Stem Cell LineagesR35GM136348 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Todd Nystul · 2020 to 2026
$3.9M
NIEHS NIH HHS P30 ES030284NIGMS NIH HHS R35 GM136348NIGMS NIH HHS T34 GM145400
6 · The paper itself

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

Identifiers

PMID38585877
PMCPMC10996622

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.