@article {70359, title = {Adapting upright light sheet fluorescence microscopy for imaging at air-liquid interface}, journal = {bioRxiv}, year = {2026}, month = {2026 Apr 09}, abstract = {

Light sheet fluorescence microscopy (LSFM) is increasingly appreciated as the gold standard for gentle, volumetric imaging with fast acquisition speeds and/or long imaging durations. However, the often-constrained sample space of these microscopes has precluded a specific class of biological specimens from being studied with these tools: those requiring an air-liquid interface (ALI). Here, we present a device for robust imaging at ALI on an upright light sheet microscope with dipping objectives. We demonstrate the system using three relevant use-cases: ex vivo embryonic mouse salivary glands, human epidermal equivalent cultures, and in vivo adult Drosophila melanogaster brains. While the device presented is engineered for one specific light sheet microscope design, it provides a blueprint for easy adaptation to other systems. In doing so, it can potentially spur the use of LSFM for model systems that have so far been unable to take advantage of this powerful technology.

}, doi = {10.64898/2026.04.07.716945}, url = {https://www.biorxiv.org/content/early/2026/04/09/2026.04.07.716945}, author = {Hobson, Chad M. and Izumi, Kenji and Aaron, Jesse S. and Bharathan, Navaneetha Krishnan and Ceriani, M. Fernanda and Giang, William and Ispizua, Juan I. and Kowalczyk, Andrew P. and Lee, Rachel M. and Morales, E. Angelo and Puls, Owen F. and Quarles, Ellen and Rodriguez-Caron, Micaela and Stahley, Sara N. and Tassara, Francisco and Wang, Shaohe and Yao, Shunze and Tsuchiya, Takanori and Chew, Teng-Leong} } @article {70379, title = {Whole-body 3D kinematics of freely behaving Drosophila}, journal = {bioRxiv}, year = {2026}, month = {2026 May 04}, abstract = {

Understanding how nervous systems generate coordinated movement requires precise measurement of body kinematics during natural behavior. The fruit fly, Drosophila, is a model organism with sophisticated behavior and well-studied neural circuits, but tracking fly movements in 3D remains challenging because of their teeny bodies, rapid movements, and frequent self-occlusions. Here we present a pipeline for markerless, full-body 3D pose estimation of fly terrestrial behavior, combining seven synchronized high-speed cameras to capture whole-body kinematics at 800 frames per second. We trained a hybrid 2D/3D deep learning model to track 50 keypoints, then refined them to produce anatomically feasible kinematic trajectories through a retargeting process that solved an inverse kinematics problem constrained by a biomechanical body model. Analysis of 3D kinematics revealed that flies perform grounded running across their full speed range, without transitioning between discrete gaits. Using multi-animal tracking, we found that courting males coordinate both wings during song and modulate body pitch to track the female{\textquoteright}s vertical position. Our open-source pipeline and 3D kinematic dataset of fly behavior provide a foundation for neuromechanical modeling and mechanistic studies of motor control in a genetically tractable model organism.

}, doi = {10.64898/2026.05.03.722293}, url = {https://www.biorxiv.org/content/early/2026/05/04/2026.05.03.722293}, author = {Ispizua, Juan I. and Abe, Elliott T. T. and Yan, Jinyao and Othayoth, Ratan and Sawtelle, Steven and Atkins, Felisha and Shiozaki, Hiroshi and Meier, Niko R. and Wong, Jovanka and Tran, Tiffany T. and Mori, Catherine K. and Voigts, Jakob and Stern, David L. and Brunton, Bingni W. and Tuthill, John C. and Johnson, Robert Evan} }