Evidence map›Paper›PMID 42538975›Full record

ArticlebioRxiv : the preprint server for biology2026

Real-Time Axial Motion Compensation for Intravital Two-Photon Imaging of Mechanically Loaded Bone.

Samantha Bratcher, Macy Mora-Antoinette, Karl J Lewis

Abstract readPreprint
In one paragraph

Article 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 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

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

3 authors.

Samantha BratcherMeinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
Macy Mora-AntoinetteMeinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
Karl J LewisMeinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.ORCID 0000-0002-6184-7526

Funding

A Light Sheet Microscope for the Cornell BRC Imaging FacilityS10OD023466 · OD · CORNELL UNIVERSITY · PI WILLIAMS, REBECCA M · 2017 to 2017
$364k
NIH HHS S10 OD023466
6 · The paper itself

Abstract

Motion artifacts present a major challenge for intravital imaging of tissues undergoing physiological movement or mechanical loading. Blurring or artificial changes in image intensity due to shifting on the z-axis reduce data reproducibility and reliability. Existing post-acquisition approaches can partially compensate for motion, but they increase experimental complexity and are not well suited for use in mechanically loaded bone. Therefore, we developed a novel method for real-time correction of axial motion during mechanical loading of bone by synchronizing the movement of the objective to the actuator. Synchronization was achieved by linking the position of the actuator piezo motor to the objective piezo motor with a user refined reduction via potentiometer. Applying axial motion correction effectively removed artificial changes in fluorescent intensity in a static fluorescent marker up to 3000με in bone as measured by similarity and average intensity before and during loading. This improvement was reflected in the improved accuracy in capture of a dynamic fluorescent calcium indicator (GCaMP6f) in osteocytes. Our system provides a user-friendly, robust framework that can be easily adapted to other mechanically loaded tissues, improving data collection and expanding the utility of two-photon imaging across a variety of biological applications.

Indexed as

Calcium SignalingIntravital ImagingMotion CorrectionTwo-photon Microscopy

Identifiers

PMID42538975
PMCPMC13419491

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.