The application of convolution neural network based cell segmentation during cryopreservation

Real-time computer assisted measurement of oocyte and embryo volume for assessment of transport parameters

Cryopreservation of gametes has revolutionized both animal agriculture and human reproductive medicine. Although many new technologies have tremendously improved the cryopreservation of oocytes and embryos, osmotic stress encountered during the equilibration process can cause their loss of function. Rational cryoprotective agent (CPA) equilibration strategies can be used to minimize this stress but require trained personnel to monitor the process in individual oocytes or embryos or require the use of suboptimal average transport parameter values in mathematically guided protocols. To enable individually optimized equilibration of CPAs in individual cells, here we establish experimental and computational techniques to track the osmotic behavior of individual bovine oocytes and embryos during CPA equilibration in real time. We designed a microfluidic device to provide a controlled flow of CPA and modified standard image analysis techniques to estimate real-time cell volume changes. In particular, we used a level-set method to define a boundary within a contour plot which could automate the image analysis process. A colour based level set algorithm coupled with contour smoothing not only provided the best fit but also reduced the segmentation time to well under a second per image. The accuracy of the automated method was comparable to human segmented images for both oocytes and embryos. This technology should enable both rapid evaluation of key biophysical parameters in oocytes and embryos undergoing CPA equilibration and the development of real-time feedback-control of CPA equilibration, enabling individual oocyte- and embryo-specific optimal protocols.

Volumetric Semantic Instance Segmentation of the Plasma Membrane of HeLa Cells

In this work, an unsupervised volumetric semantic instance segmentation of the plasma membrane of HeLa cells as observed with serial block face scanning electron microscopy is described. The resin background of the images was segmented at different slices of a 3D stack of 518 slices with 8192 × 8192 pixels each. The background was used to create a distance map, which helped identify and rank the cells by their size at each slice. The centroids of the cells detected at different slices were linked to identify them as a single cell that spanned a number of slices. A subset of these cells, i.e., the largest ones and those not close to the edges were selected for further processing. The selected cells were then automatically cropped to smaller regions of interest of 2000 × 2000 × 300 voxels that were treated as cell instances. Then, for each of these volumes, the nucleus was segmented, and the cell was separated from any neighbouring cells through a series of traditional image processing steps that followed the plasma membrane. The segmentation process was repeated for all the regions of interest previously selected. For one cell for which the ground truth was available, the algorithm provided excellent results in Accuracy (AC) and the Jaccard similarity Index (JI): nucleus: JI =0.9665, AC =0.9975, cell including nucleus JI =0.8711, AC =0.9655, cell excluding nucleus JI =0.8094, AC =0.9629. A limitation of the algorithm for the plasma membrane segmentation was the presence of background. In samples with tightly packed cells, this may not be available. When tested for these conditions, the segmentation of the nuclear envelope was still possible. All the code and data were released openly through GitHub, Zenodo and EMPIAR.

Mathematical Modeling and Optimization of Cryopreservation in Single Cells

Cryobiology is a multiscale and interdisciplinary field. The scope and scale of interactions limit the gains that can be made by one theory or experiment alone. Because of this, modeling has played a critical role in both explaining cryobiological phenomena and predicting improved protocols. Modeling facilitates understanding of the biophysical and some of the biochemical mechanisms of damage during all phases of cryopreservation including CPA equilibration and cooling and warming. Moreover, as a tool for optimization of cryopreservation protocols, modeling has yielded many successes. Modern cryobiological modeling includes very detailed descriptions of the physical phenomena that occur during freezing, including ice growth kinetics and spatial gradients that define heat and mass transport models. Here we reduce the complexity and approach only a small but classic subset of these problems. Namely, here we describe the process of building and using a mathematical model of a cell in suspension where spatial homogeneity is assumed for all quantities. We define the models that describe the critical cell quantities used to describe optimal and suboptimal protocols and then give an overview of classical methods of how to determine optimal protocols using these models. We include practical considerations of modeling in cryobiology, including fitting transport models to cell volume data, performing optimization with cell volume constraints, and a look at expanding cost functions to cooling regimes.

A microfluidic approach for synchronous and nondestructive study of the permeability of multiple oocytes

Investigation of oocyte membrane permeability plays a crucial role in fertility preservation, reproductive medicine, and reproductive pharmacology. However, the commonly used methods have disadvantages such as high time consumption, low efficiency, and cumbersome data processing. In addition, the developmental potential of oocytes after measurement has not been fully validated in previous studies. Moreover, oocytes can only maintain their best status in vitro within a very limited time. To address these limitations, we developed a novel multichannel microfluidic chip with newly designed micropillars that provide feasible and repeatable oocyte capture. The osmotic responses of three oocytes at different or the same cryoprotectant (CPA) concentrations were measured simultaneously, which greatly improved the measurement efficiency. Importantly, the CPA concentration dependence of mouse oocyte membrane permeability was found. Moreover, a neural network algorithm was employed to improve the efficiency and accuracy of data processing. Furthermore, analysis of fertilization and embryo transfer after perfusion indicated that the microfluidic approach does not damage the developmental potential of oocytes. In brief, we report a new method based on a multichannel microfluidic chip that enables synchronous and nondestructive measurement of the permeability of multiple oocytes.

A microfluidic platform with cell-scale precise temperature control for simultaneous investigation of the osmotic responses of multiple oocytes

The temperature-dependent oocyte membrane permeability plays a significant role in oocyte cryopreservation, such as optimizing the addition/removal of cryoprotective agents and the rate of cooling/rewarming. However, the systems for studying the temperature dependence of oocyte membrane permeability are either too complicated or unable to achieve wide-range precise temperature control. In addition, these systems cannot achieve the simultaneous observation of multiple oocytes. Here, we report a novel microfluidic platform that combines a precise local temperature heater/detector and a simple global water bath to achieve wide-range accurate temperature control without increasing the difficulty of fabrication, and it also realizes non-interfering, position-controllable and non-missing capture of multiple oocytes for parallel experiments to increase throughput. The permeability coefficients (L_p, P_s) of the mouse oocyte membrane exposed to cryoprotective agents (1.5 M EG and 1.5 M PG) at four temperatures (4, 15, 25 and 37 °C) are consistent with those reported in previous works, which proves the feasibility and practicality of the microfluidic platform in this study.