Article in Journal of cell science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
0numbers the graph read from it
0cells of the map it votes in
4citing 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.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
23 authors.
Luke SorensenDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0009-0008-8931-5135
Adam HumenickFlinders Health and Medical Research Institute , College of Medicine and Public Health, Flinders University, Bedford Park, SA 5042, Australia.
Sabrina S B PoonDepartment of Anatomy and Physiology, The University of Melbourne, Parkville, VIC 3052, Australia.
Myat Noe HanDepartment of Anatomy and Physiology, The University of Melbourne, Parkville, VIC 3052, Australia.ORCID 0000-0003-3028-7359
Narges S MahdavianDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0000-0001-6708-1165
Matthew C RoweDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.
Ryan HamnettWu Tsai Neurosciences Institute , Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-9118-1585
Estibaliz Gómez-de-MariscalOptical Cell Biology Group, Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal.ORCID 0000-0003-2082-3277
Peter H NeckelInstitute of Clinical Anatomy and Cell Analysis , University of Tübingen, Tübingen 72076, Germany.ORCID 0000-0003-1976-0512
Ayame SaitoDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0000-0001-8477-9944
Keith MutunduweDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0000-0003-0672-183X
Christie GlennanDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0000-0003-0507-8897
Robert HaaseCenter for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig , Universität Leipzig, Humboldtstraße 25, Leipzig 04105, Germany.ORCID 0000-0001-5949-2327
Rachel M McQuadeGut Barrier and Disease Laboratory, Department of Anatomy and Physiology, The University of Melbourne, Melbourne, VIC 3010, Australia.ORCID 0000-0002-3510-1288
Jaime P P FoongDepartment of Anatomy and Physiology, The University of Melbourne, Parkville, VIC 3052, Australia.ORCID 0000-0003-2082-5520
Simon J H BrookesFlinders Health and Medical Research Institute , College of Medicine and Public Health, Flinders University, Bedford Park, SA 5042, Australia.ORCID 0000-0001-5635-0876
Julia A KaltschmidtWu Tsai Neurosciences Institute , Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-2893-1793
Arrate Muñoz-BarrutiaBioengineering Department, Universidad Carlos III de Madrid, ES 28911, Leganés, Spain.ORCID 0000-0002-1573-1661
Sebastian K KingDepartment of Paediatric Surgery, The Royal Children's Hospital, Parkville, VIC 3052, Australia.ORCID 0000-0001-5396-0265
Nicholas A VeldhuisDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0000-0002-8902-9365
Simona E CarboneDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0000-0002-4350-6357
Daniel P PooleDrug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia.ORCID 0000-0002-6168-8422
Pradeep RajasekharCentre for Dynamic Imaging, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia.ORCID 0000-0002-1983-7244
Funding
Comprehensive Structural and Functional Mapping of Mammalian Colonic Nervous SystemOT2OD024899 · OD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MULUGETA, MILLION, TACHE, YVETTE FRANCE · 2017 to 2021
$13.1M
Australian GovernmentAustralian Government Research Training Program (RTP)Australian Research Council FT220100617Calouste Gulbenkian FoundationEMBOEuropean Molecular Biology Organization EMBO ALTF 174-2022Fundação Calouste GulbenkianHorizon Europe 101057970-AI4LIFEHORIZON EUROPE European Research CouncilMelbourne Research Scholarship, University of MelbourneMonash UniversityNational Health and Medical Research Council GNT1183420National Insitutes of HealthNIH HHS 1OT2OD24899NIH HHS OT2 OD024899University of Melbourne
6 · The paper itself
Abstract
The enteric nervous system (ENS) consists of an extensive network of neurons and glial cells embedded within the wall of the gastrointestinal (GI) tract. Alterations in neuronal distribution and function are strongly associated with GI dysfunction. Current methods for assessing neuronal distribution suffer from undersampling, partly due to challenges associated with imaging and analyzing large tissue areas, and operator bias due to manual analysis. We present the Gut Analysis Toolbox (GAT), an image analysis tool designed for characterization of enteric neurons and their neurochemical coding using two-dimensional images of GI wholemount preparations. GAT is developed in Fiji, has a user-friendly interface, and offers rapid and accurate segmentation via custom deep learning (DL)-based cell segmentation models developed using StarDist, as well as a ganglia segmentation model in deepImageJ. We apply proximal neighbor-based spatial analysis to reveal differences in cellular distribution across gut regions using a public dataset. In summary, GAT provides an easy-to-use toolbox to streamline routine image analysis tasks in ENS research. GAT enhances throughput, allowing rapid unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples.
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 Socratic graph.
Gut Analysis Toolbox - automating quantitative analysis of enteric neurons. · full record | Socratic