In one paragraphArticle in bioRxiv : the preprint server for biology, 2026. 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 itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
20 authors.
Drew EhrlichDepartment of Computational Media, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0001-6794-6800 Yohei RosenUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0002-3870-2169 Santhosh ArulDepartment of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0002-9617-1319 John MinnickUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0003-2593-6342 Seth NicholsonUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0009-0009-3999-9302 Kateryna VoitiukUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0002-6392-5188 Spencer SeilerUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0002-0087-1346 Anna ToledoDepartment of Performance, Play and Design, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0009-0004-2066-520X Samira Vera-ChoqqueccotaUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0001-9554-5617 Neil DohertyDepartment of Molecular, Cellular, and Developmental Biology, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0009-0007-6260-5346 Jess SevetsonUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0001-7434-1447 Max McGlynnUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0009-0007-9019-7378 Kivilcim DoganyigitUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0009-0003-4607-9594 Maryam MoarefianUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0002-1875-0614 Sri KurniawanDepartment of Computational Media, University of California, Santa Cruz, Santa Cruz, CA, USA.
Mohammed A Mostajo-RadjiUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0002-1634-7514 Sofie R SalamaUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0001-6999-7193 Ethan WinklerDepartment of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0002-7908-7107 David HausslerUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0003-1533-4575 Mircea TeodorescuUC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.ORCID 0000-0001-7085-5248 Funding
Nanoparticle Tracking Analyzer (NTA) for the Center for Live Cell GenomicsRM1HG011543 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI HAUSSLER, DAVID H, SALAMA, SOFIE REDA · 2021 to 2025
$12.0MData Resource and Administrative Coordination Center for the Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes ConsortiumU24MH132628 · NIMH · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI DAVID H HAUSSLER, Tomasz Nowakowski · 2023 to 2026
$7.9MIRACDA at UCSC and CSUMBK12GM139185 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI FORSBERG, CAMILLA, HINCK, LINDSAY E · 2020 to 2024
$4.1MHuman Brain Single-Cell Genomics ExplorerU24NS146314 · NINDS · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI HAUSSLER, DAVID H, ZHU, JINGCHUN · 2025 to 2025
$3.7MTraining Program in Molecular, Cell, and Developmental BiologyT32GM133391 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI Needhi Bhalla · 2019 to 2026
$3.0MNHGRI NIH HHS RM1 HG011543NIGMS NIH HHS K12 GM139185NIGMS NIH HHS T32 GM133391NIMH NIH HHS U24 MH132628NINDS NIH HHS U24 NS146314
6 · The paper itselfAbstract
Longitudinal live cell imaging is valuable for characterizing dynamic morphological and phenotypic changes in biological systems. However, conventional approaches rely on manual microscope operation, which is labor-intensive, limits imaging frequency, and disrupts the cellular environment. These constraints reduce scalability, increase experimental variability, and restrict both the duration and temporal resolution of continuous imaging. Although automated imaging platforms partially address these limitations, existing solutions are often constrained by the cost, footprint, and inflexibility of in-incubator microscopes or stage-top incubators. Here, we present an automated in-incubator epifluorescence microscope designed for long-term operation. The system features a modular architecture with optional multi-fluorescence imaging, automated plate scanning, configurable light sources, and compatibility with multiple plate formats, including integration with fluidic automation devices. By positioning the light sources and control electronics outside the incubator, the platform improves thermal stability and long-term operational reliability. This approach enables continuous, high-frequency imaging over extended durations, providing a source of rich data for quantifying time-dependent tissue phenotypes, morphological remodeling, and transient biological processes.
Indexed as
Cell BiologyMicroscopyOpen Hardware
Identifiers
PMID41648487
PMCPMC12871646
What OpenQuestion holds
Textmetadata
LicenceCC BY-NC
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