The developmental process of embryos follows a monotonic order. An embryo can progressively cleave from one cell to multiple cells and finally transform to morula and blastocyst. For time-lapse videos of embryos, most existing developmental stage classification methods conduct per-frame predictions using an image frame at each time step. However, classification using only images suffers from overlapping between cells and imbalance between stages. Temporal information can be valuable in addressing this problem by capturing movements between neighboring frames. In this work, we propose a two-stream model for developmental stage classification. Unlike previous methods, our twostream model accepts both temporal and image information. We develop a linear-chain conditional random field (CRF) on top of neural network features extracted from the temporal and image streams to make use of both modalities. The linear-chain CRF formulation enables tractable training of global sequential models over multiple frames while also making it possible to inject monotonic development order constraints into the learning process explicitly. We demonstrate our algorithm on two timelapse embryo video datasets: i) mouse and ii) human embryo datasets. Our method achieves 98.1% and 80.6% for mouse and human embryo stage classification, respectively. Our approach will enable more profound clinical and biological studies and suggests a new direction for developmental stage classification by utilizing temporal information.
Cells are the basic units of all living matter which harness the flow of energy to drive the processes of life. While the biochemical networks involved in energy transduction are well-characterized, the energetic costs and constraints for specific cellular processes remain largely unknown. In particular, what are the energy budgets of cells? What are the constraints and limits energy flows impose on cellular processes? Do cells operate near these limits, and if so how do energetic constraints impact cellular functions? Physics has provided many tools to study nonequilibrium systems and to define physical limits, but applying these tools to cell biology remains a challenge. Physical bioenergetics, which resides at the interface of nonequilibrium physics, energy metabolism, and cell biology, seeks to understand how much energy cells are using, how they partition this energy between different cellular processes, and the associated energetic constraints. Here we review recent advances and discuss open questions and challenges in physical bioenergetics.
Calorimetry has long been used to probe the physical state of a system by measuring the heat exchanged with the environment as a result of chemical reactions or phase transitions. Application of calorimetry to microscale biological samples, however, is hampered by insufficient sensitivity and the difficulty of handling liquid samples at this scale. Here, a micromachined calorimeter sensor that is capable of resolving picowatt levels of power is described. The sensor consists of low-noise thermopiles on a thin silicon nitride membrane that allow direct differential temperature measurements between a sample and four coplanar references, which significantly reduces thermal drift. The partial pressure of water in the ambient around the sample is maintained at saturation level using a small hydrogel-lined enclosure. The materials used in the sensor and its geometry are optimized to minimize the noise equivalent power generated by the sensor in response to the temperature field that develops around a typical sample. The experimental response of the sensor is characterized as a function of thermopile dimensions and sample volume, and its capability is demonstrated by measuring the heat dissipated during an enzymatically catalyzed biochemical reaction in a microliter-sized liquid droplet. The sensor offers particular promise for quantitative measurements on biological systems
Living matter moves, deforms, and organizes itself. In cells this is made possible by networks of polymer filaments and crosslinking molecules that connect filaments to each other and that act as motors to do mechanical work on the network. For the case of highly cross-linked filament networks, we discuss how the material properties of assemblies emerge from the forces exerted by microscopic agents. First, we introduce a phenomenological model that characterizes the forces that crosslink populations exert between filaments. Second, we derive a theory that predicts the material properties of highly crosslinked filament networks, given the crosslinks present. Third, we discuss which properties of crosslinks set the material properties and behavior of highly crosslinked cytoskeletal networks. The work presented here, will enable the better understanding of cytoskeletal mechanics and its molecular underpinnings. This theory is also a first step toward a theory of how molecular perturbations impact cytoskeletal organization, and provides a framework for designing cytoskeletal networks with desirable properties in the lab.
We develop a continuum mechanics model of blastocyst hatching. The blastocyst and the zona pellucida are modeled as concentric thick-walled initially spherical shells embedded in a viscous medium. Each shell is characterized by a nonlinear elastic–viscous–constitutive relation. The stiffer outer shell (the zona pellucida) contains an opening. The softer inner shell (the blastocyst) is subject to a continually increasing pressure, which can eventually drive the escape of the inner shell from the outer shell (‘‘hatching’’). The focus is on the continuum mechanics modeling framework and illustrating the sort of quantitative predictions that can be made. Numerical examples are presented for the predicted dependence of the evolution of the escape process on values of parameters characterizing the constitutive response of the shells, on the viscosity of the external medium and on the size of the opening in the zona pellucida.
The spindle shows remarkable diversity, and changes in an integrated fashion, as cells vary over evolution. Here, we provide a mechanistic explanation for variations in the first mitotic spindle in nematodes. We used a combination of quantitative genetics and biophysics to rule out broad classes of models of the regulation of spindle length and dynamics, and to establish the importance of a balance of cortical pulling forces acting in different directions. These experiments led us to construct a model of cortical pulling forces in which the stoichiometric interactions of microtubules and force generators (each force generator can bind only one microtubule), is key to explaining the dynamics of spindle positioning and elongation, and spindle final length and scaling with cell size. This model accounts for variations in all the spindle traits we studied here, both within species and across nematode species spanning over 100 million years of evolution.
This study used noninvasive, fluorescence lifetime imaging microscopy (FLIM)-based imaging of NADH and FAD to characterize the metabolic response of mouse embryos to short-term oxygen deprivation. We investigated the response to hypoxia at various preimplantation stages.
Mouse oocytes and embryos were exposed to transient hypoxia by dropping the oxygen concentration in media from 5–0% over the course of ~1.5 h, then 5% O2 was restored. During this time, FLIM-based metabolic imaging measurements of oocyte/embryo cohorts were taken every 3 minutes. Experiments were performed in triplicate for oocytes and embryos at the 1- to 8-cell, morula, and blastocyst stages. Maximum hypoxia response for each of eight measured quantitative FLIM parameters was taken from the time points immediately before oxygen restoration.
Metabolic profiles showed significant changes in response to hypoxia for all stages of embryo development. The response of the eight measured FLIM parameters to hypoxia was highly stage-dependent. Of the eight FLIM parameters measured, NADH and FAD intensity showed the most dramatic metabolic responses in early developmental stages. At later stages, however, other parameters, such as NADH fraction engaged and FAD lifetimes, showed greater changes. Metabolic parameter values generally returned to baseline with the restoration of 5% oxygen.
Quantitative FLIM-based metabolic imaging was highly sensitive to metabolic changes induced by hypoxia. Metabolic response profiles to oxygen deprivation were distinct at different stages, reflecting differences in metabolic plasticity as preimplantation embryos develop.
A major challenge in clinical In-Vitro Fertilization (IVF) is selecting the highest quality embryo to transfer to the patient in the hopes of achieving a pregnancy. Time-lapse microscopy provides clinicians with a wealth of information for selecting embryos. However, the resulting movies of embryos are currently analyzed manually, which is time consuming and subjective. Here, we automate feature extraction of timelapse microscopy of human embryos with a machine-learning pipeline of five convolutional neural networks (CNNs). Our pipeline consists of (1) semantic segmentation of the regions of the embryo, (2) regression predictions of fragment severity, (3) classification of the developmental stage, and object instance segmentation of (4) cells and (5) pronuclei. Our approach greatly speeds up the measurement of quantitative, biologically relevant features that may aid in embryo selection. Please see here for more information: https://wdjang.github.io/miccai2020-ivf.github.io/
A van der Waals heterostructure built from atomically thin semiconducting transition metal dichalcogenides (TMDs) enables the formation of excitons from electrons and holes in distinct layers, producing interlayer excitons with large binding energy and a long lifetime. By employing heterostructures of monolayer TMDs, we realize optical and electrical generation of long-lived neutral and charged interlayer excitons. We demonstrate that neutral interlayer excitons can propagate across the entire sample and that their propagation can be controlled by excitation power and gate electrodes. We also use devices with ohmic contacts to facilitate the drift motion of charged interlayer excitons. The electrical generation and control of excitons provide a route for achieving quantum manipulation of bosonic composite particles with complete electrical tunability.
Cytoskeletal networks are foundational examples of active matter and central to self-organized structures in the cell. In vivo, these networks are active and densely crosslinked. Relating their large-scale dynamics to the properties of their constituents remains an unsolved problem. Here, we study an in vitro active gel made from aligned microtubules and XCTK2 kinesin motors. Using photobleaching, we demonstrate that the gel’s aligned microtubules, driven by motors, continually slide past each other at a speed independent of the local microtubule polarity and motor concentration. This phenomenon is also observed, and remains unexplained, in spindles. We derive a general framework for coarse graining microtubule gels crosslinked by molecular motors from microscopic considerations. Using microtubule–microtubule coupling through a force–velocity relationship for kinesin, this theory naturally explains the experimental results: motors generate an active strain rate in regions of changing polarity, which allows microtubules of opposite polarities to slide past each other without stressing the material.
Cell biology has its beginnings in the first observations of cells through primitive microscopes and in the formulation of cell theory, which postulates that cells are the fundamental building blocks of life. Light microscopes showed that the insides of cells contained complex structures, such as nuclei, spindles, and chromosomes. The advent of electron microscopy in the mid 20th century brought the first truly detailed views of cell innards. Images revealed complexity at all observable scales, including cell-spanning networks of polymers, intricate organelles made of membranes, and a variety of micron- to nanometer-sized sacs and granules such as vesicles, lipid droplets, and ribosomes. (For a glossary of cellular components, see the Quick Study by Ned Wingreen, PHYSICS TODAY, September 2006, page 80.) Those structures are immersed in or part of the aqueous cytoplasm—the cell’s fluidic medium.
Spindle microtubules, whose dynamics vary over time and at different locations, cooperatively drive chromosome segregation. Measurements of microtubule dynamics and spindle ultrastructure can provide insight into the behaviors of microtubules, helping elucidate the mechanism of chromosome segregation. Much work has focused on the dynamics and organization of kinetochore microtubules, that is, on the region between chromosomes and poles. In comparison, microtubules in the central-spindle region, between segregating chromosomes, have been less thoroughly characterized. Here, we report measurements of the movement of central-spindle microtubules during chromosome segregation in human mitotic spindles and Caenorhabditis elegans mitotic and female meiotic spindles. We found that these central-spindle microtubules slide apart at the same speed as chromosomes, even as chromosomes move toward spindle poles. In these systems, damaging central-spindle microtubules by laser ablation caused an immediate and complete cessation of chromosome motion, suggesting a strong coupling between central-spindle microtubules and chromosomes. Electron tomographic reconstruction revealed that the analyzed anaphase spindles all contain microtubules with both ends between segregating chromosomes. Our results provide new dynamical, functional, and ultrastructural characterizations of central-spindle microtubules during chromosome segregation in diverse spindles and suggest that central-spindle microtubules and chromosomes are strongly coupled in anaphase.
Current strategies for embryo assessment in the assisted reproductive technology laboratories rely primarily on morphologic parameters that have limited accuracy for determining embryo viability. Even with the addition of invasive diagnostic interventions such as preimplantation genetic testing for aneuploidy alone or in combination with mitochondrial DNA copy number assessment, at least one third of embryos fail to implant. Therefore, at a time when the clinical benefits of single ET are widely accepted, improving viability assessment of embryos is ever more important. Building on the previous work demonstrating the importance of metabolic state in oocytes and embryos, metabolic imaging via fluorescence lifetime imaging microscopy offers new and potentially useful diagnostic method by detecting natural fluorescence of FAD and NADH, the two electron transporters that play a central role in oxidative phosphorylation. Recent studies demonstrate that fluorescence lifetime imaging microscopy can detect oocyte and embryo metabolic function and dysfunction in a multitude of experimental models and provide encouraging evidence for use in scientific investigation and possibly for clinical application.