ArticlePloS one2021
An open-source, lockable mouse wheel for the accessible implementation of time- and distance-limited elective exercise.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- REVS: A new open-source platform for high-resolution analysis of rodent wheel running behavior.Journal of neuroscience methods · 2025Article
- PAW, a cost-effective and open-source alternative to commercial rodent running wheels.HardwareX · 2024Article
- Development and implementation of a Dependable, Simple, and Cost-effective (DSC), open-source running wheel in High Drinking in the Dark and Heterogeneous Stock/Northport mice.Frontiers in behavioral neuroscience · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Current methods of small animal exercise involve either voluntary (wheel running) or forced (treadmill running) protocols. Although commonly used, each have several drawbacks which cause hesitancy to adopt these methods. While mice will instinctively run on a wheel, the distance and time spent running can vary widely. Forced exercise, while controllable, puts animals in stressful environments in which they are confined and often shocked for "encouragement." Additionally, both methods require expensive equipment and software, which limit these experiments to well-funded laboratories. To counter these issues, we developed a non-invasive mouse running device aimed to reduce handler-induced stress, provide time- and distance-based stopping conditions, and enable investigators with limited resources to easily produce and use the device. The Lockable Open-Source Training-Wheel (LOST-Wheel) was designed to be 3D printed on any standard entry-level printer and assembled using a few common tools for around 20 USD. It features an on-board screen and is capable of tracking distances, running time, and velocities of mice. The LOST-Wheel overcomes the largest drawback to voluntary exercise, which is the inability to control when and how long mice run, using a servo driven mechanism that locks and unlocks the running surface according to the protocol of the investigator. While the LOST-Wheel can be used without a computer connection, we designed an accompanying application to provide scientists with additional analyses. The LOST-Wheel Logger, an R-based application, displays milestones and plots on a user-friendly dashboard. Using the LOST-Wheel, we implemented a timed running experiment that showed distance-dependent decreases in serum myostatin as well as IL-6 gene upregulation in muscle. To make this device accessible, we are releasing the designs, application, and manual in an open-source format. The implementation of the LOST-Wheel and future iterations will improve upon existing murine exercise equipment and research.
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Identifiers
What OpenQuestion holds
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.