Biology subjects

La Riviere, P. J.

Publications and source records attributed to La Riviere, P. J..

5 recordsLinked to original sources

bioRxiv2025

Observing biological spatio-angular structures and dynamics with statistical image reconstruction and polarized fluorescence microscopy

Understanding molecular orientation and density distributions is essential for exploring biological structure and function. Polarized fluorescence microscopy (PFM) provides insights into molecular architecture but struggles to resolve three-dimensional (3D) molecular orientation distributions, particularly in densely labeled or structurally complex specimens. To address this, we introduce the efficient generalized Richardson-Lucy (eGRL) algorithm, a robust framework for reconstructing 3D molecular density and orientation (spatio-angular) distributions from PFM data. By modeling the imaging process in spatio-angular hyperspace, we propose a maximum-likelihood solution enhanced by dimensionality reduction and angular domain transformation to overcome computational challenges. eGRL improves accuracy and efficiency across different PFM implementations, enabling use on standard platforms. We utilize our methods to resolve biological spatio-angular structures and dynamics otherwise impossible to resolve, including the tangential alignment of actin filaments in U2OS cells, nanowire-guided cytoskeletal organization in NIH3T3 cells, rotational actin patterns in live HeLa protrusions, and membrane tension-induced anisotropy in live macrophages.

bioengineering↗

bioRxiv2025

Chromatix: a differentiable, GPU-accelerated wave-optics library

Modern microscopy methods incorporate computational modeling as an integral part of the imaging process, either to solve inverse problems or optimize the optical system design itself. These methods often depend on differentiable optics simulations, yet no standardized framework exists--forcing computational optics researchers to repeatedly and independently implement simulations with limited reusability and performance. These common problems limit the potential impact of computational optics as a field. Here we present Chromatix: an open-source, GPU-accelerated, differentiable wave optics simulation library. Chromatix builds on JAX to democratize fast, parallelized simulation of diverse optical systems and expand the design space in computational optics. Chromatix standardizes a growing collection of optical elements and propagation methods allowing a broad range of applications, which we demonstrate here for snapshot microscopy, holography, and phase retrieval. We demonstrate speed improvements of 2-6x on a single GPU and up to 22x on 8 GPUs.

bioinformatics↗

bioRxiv2023

Phase diversity-based wavefront sensing for fluorescence microscopy

Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs. Here we introduce a rapid, sensitive, and robust wavefront sensing scheme based on phase diversity, a method successfully deployed in astronomy but underused in microscopy. Our method enables accurate wavefront sensing to less than {lambda}/35 root mean square (RMS) error with few measurements, and AO with no additional hardware besides a corrective element. After validating the method with simulations, we demonstrate calibration of a deformable mirror > 100-fold faster than comparable methods (corresponding to wavefront sensing on the ~100 ms scale), and sensing and subsequent correction of severe aberrations (RMS wavefront distortion exceeding {lambda}/2), restoring diffraction-limited imaging on extended biological samples.

bioengineering↗

bioRxiv2023

Quantitative Geometric Modeling of Blood Cells from X-ray Histotomograms of Whole Zebrafish Larvae

Tissue phenotyping is foundational to understanding and assessing the cellular aspects of disease in organismal context and an important adjunct to molecular studies in the dissection of gene function, chemical effects, and disease. As a first step toward computational tissue phenotyping, we explore the potential of cellular phenotyping from 3-Dimensional (3D), 0.74 {micro}m isotropic voxel resolution, whole zebrafish larval images derived from X-ray histotomography, a form of micro-CT customized for histopathology. As proof of principle towards computational tissue phenotyping of cells, we created a semi-automated mechanism for the segmentation of blood cells in the vascular spaces of zebrafish larvae, followed by modeling and extraction of quantitative geometric parameters. Manually segmented cells were used to train a random forest classifier for blood cells, enabling the use of a generalized cellular segmentation algorithm for the accurate segmentation of blood cells. These models were used to create an automated data segmentation and analysis pipeline to guide the steps in a 3D workflow including blood cell region prediction, cell boundary extraction, and statistical characterization of 3D geometric and cytological features. We were able to distinguish blood cells at two stages in development (4- and 5-days-post-fertilization) and wild-type vs. polA2 huli hutu (hht) mutants. The application of geometric modeling across cell types to and across organisms and sample types may comprise a valuable foundation for computational phenotyping that is more open, informative, rapid, objective, and reproducible.

systems biology↗

bioRxiv2021

A Wide-Field Micro-Computed Tomography Detector: Micron Resolution at Half-centimeter Scale

Ideal 3-dimensional imaging of many complex samples, such as biological tissues made up of micro-scale structures extending over millimeter- to centimeter-scale tissue samples and organisms, requires both a wide field-of-view and high resolution. With existing optics and detectors used for micro-CT imaging, sub-micron pixel resolution can only be achieved for fields-of-view of <2 mm. This manuscript presents a unique detector system with a 6-mm field-of-view image circle and 0.5 m pixel size that can be used in both synchrotron facilities and tabletop micro-CT units. A resolution-test pattern with linear microstructures and whole adult Daphnia magna were imaged on Beamline 8.3.2 of the Advanced Light Source. Volumes of 10,000 x 10,000 x 7,096 isotropic 0.5 m voxels were reconstructed over a 5.0 x 3.5 mm field-of-view. Measurements in the projection domain confirmed a 1.182 m measured spatial resolution that is largely Nyquist-limited. This unprecedented combination of field-of-view and resolution dramatically reduces the need for sectional scans and computational stitching for large samples, ultimately offering the means to elucidate change in tissue and cellular morphology in the context of larger whole, intact model organisms and specimens. This development is also anticipated to benefit micro-CT imaging in materials science, microelectronics, agricultural science, and biomedical engineering. SynopsisA custom wide-field lens and a new-generation megapixel camera enabled microCT scanning over a 3.5 x 5 mm field-of-view at a 1 m resolution / 0.5 m pixel size at the Berkeley Lawrence Advanced Light Source using a phantom with micron scale features. This novel combination of resolution and field-of-view will be broadly applicable to any setting in which micron-scale structures need to be characterized comprehensively in 3 dimensions over mm to cm scale.

bioinformatics↗