Evidence map›Paper›PMID 39568639›Full record

ArticlePatterns (New York, N.Y.)2024

A FAIR, open-source virtual reality platform for dendritic spine analysis.

Marike L Reimer, Sierra D Kauer, Curtis A Benson, Jared F King, Siraj Patwa, Sarah Feng, Maile A Estacion, Lakshmi Bangalore, Stephen G Waxman, Andrew M Tan

Abstract read
In one paragraph

Article in Patterns (New York, N.Y.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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

10 authors.

Marike L ReimerDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Sierra D KauerDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Curtis A BensonDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Jared F KingDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Siraj PatwaDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Sarah FengDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Maile A EstacionDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Lakshmi BangaloreDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Stephen G WaxmanDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.
Andrew M TanDepartment of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Neuroanatomy is fundamental to understanding the nervous system, particularly dendritic spines, which are vital for synaptic transmission and change in response to injury or disease. Advancements in imaging have allowed for detailed three-dimensional (3D) visualization of these structures. However, existing tools for analyzing dendritic spine morphology are limited. To address this, we developed an open-source virtual reality (VR) structural analysis software ecosystem (coined "VR-SASE") that offers a powerful, intuitive approach for analyzing dendritic spines. Our validation process confirmed the method's superior accuracy, outperforming recognized gold-standard neural reconstruction techniques. Importantly, the VR-SASE workflow automatically calculates key morphological metrics, such as dendritic spine length, volume, and surface area, and reliably replicates established datasets from published dendritic spine studies. By integrating the Neurodata Without Borders (NWB) data standard, VR-SASE datasets can be preserved/distributed through DANDI Archives, satisfying the NIH data sharing mandate.

Indexed as

DataJointdata standarddendritic spinesFAIRimage analysisneuroimagingNWBSCIvirtual reality

Identifiers

PMID39568639
PMCPMC11573899

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.