The design and fabrication of a very large-scale liver-lobule (VLSLL)-on-a-chip device, providing a microphysiological niche for hepatocytes, is described. The device consists of an integrated network of liver-lobule-like hexagonal tissue-culture chambers constructed in a hybrid layout with a separate seed-feed network. As a key feature, each chamber contains a central outlet mimicking the central vein of a liver lobule. Separating chamber walls located between the culture area and feed network protects cells from the shear force of the convective flow. Arrays of designated passages convey nutrients to the cells by diffusion-dominated mass transport. We simulated the flow velocity, shear stress and diffusion of glucose molecules inside and outside the culture chambers under a continuous flow rate of 1 μ l min ⁻¹ . As proof of concept, human hepatocellular carcinoma cells (HepG2) were cultured for periods of 5 and 14 days and human-induced pluripotent stem cell (hiPSC)-derived hepatocytes for 21 days. Stabilized albumin secretion and urea synthesis were observed in the microfluidic devices and cells maintained morphology and functionality during the culture period. Furthermore, we observed 3D tissue-like structure and bile-canaliculi network formation in the chips. Future applications of the described platform include drug development and toxicity studies, as well as the modeling of patient-specific liver diseases, and integration in multi-organ human-on-a-chip systems.

Background: The physiological regulation of ciliary beat frequency (CBF) within the fallopian tube is important for controlling the transport of gametes and the fertilized ovum. Progesterone influences gamete transport in the fallopian tube of several mammalian species. In fallopian tubes isolated from cows, treatment with 20 micromolar progesterone caused a rapid reduction of the tubal CBF. The aims of this study were to establish methodology for studying fallopian tube CBF in the mouse, as it is an important model species, and to investigate if progesterone rapidly affects the CBF of mice at nM concentrations. Methods: A method to assess tubal CBF of mice was developed. Fallopian tubes were dissected and the tissue was cut in small pieces. Tissue samples with moving cilia were located under an inverted bright field microscope and held still against the bottom of a petri dish by a motorized needle system. Images were acquired over 90 minutes at 35 degrees C with a high-speed camera and used for assessing changes in the CBF in response to the addition of hormone. Results: The baseline CBF of the mouse fallopian tube was 23.3 +/- 3.8 Hz. The CBF was stable over at least 90 minutes allowing establishment of a baseline frequency, addition of hormone and subsequent recordings. Progesterone at concentrations of 20 micromolar and 100 nM significantly reduced the CBF by 10% and 15% respectively after 30 minutes compared with controls. Conclusions: The present study demonstrates that the mouse, despite its small size, is a useful model for studying the fallopian tube CBF ex vivo. The rapid reduction in CBF by 100 nM progesterone suggests that gamete transport in the fallopian tube could be mediated by progesterone via a non-genomic receptor mechanism.

Upon hyperosmotic stress, the cytoplasm seems to play a protective role in the volume recovery of the nucleus.

Background: The transport of gametes as well as the zygote is facilitated by motile cilia lining the inside of the fallopian tube. Progesterone reduces the ciliary beat frequency within 30 minutes in both cows and mice. This rapid reduction suggest the involvement of a non-genomic signaling mechanism, although it is not known which receptors that are involved. Here we investigated the possible involvement of the classical progesterone receptor in this process. Method: The ciliary beat frequency of mice fallopian tube was measured ex vivo using an inverted bright field microscope and a high speed camera. The effects of the agonists progesterone and promegestone and an antagonist, mifeprestone, were investigated in wildtype mice. The effect of progesterone was also investigated in mice lacking the classical progesterone receptor. Results: Progesterone, as well as the more specific PR agonist promegestone, significantly reduced the CBF at concentrations of 10–100 nanomolar within 10–30 minutes. In the absence of progesterone, the PR antagonist mifeprestone had no effect on the ciliary beat frequency at a concentration of 1 micromolar. When ciliated cells were pre-incubated with 1 micromolar mifeprestone, addition of progesterone did not reduce the ciliary beat frequency. Accordingly, in ciliated cells from mice not expressing the classical progesterone receptor, exposure to 100 nanomolar progesterone did not reduce the ciliary beat frequency. Conclusions: This is the first study to provide comprehensive evidence that the classical progesterone receptor mediates the rapid reduction of the tubal ciliary beat frequency by progesterone.

Cell signaling, gene expression and metabolism are affected by cell-cell heterogeneity and random changes in the environment. The effects of such fluctuations on cell signaling and gene expression have recently been studied intensively using single-cell experiments. In metabolism heterogeneity may be particularly important because it may affect synchronisation of metabolic oscillations, an important example of cell-cell communication. This synchronisation is notoriously difficult to describe theoretically as the example of glycolytic oscillations shows: neither is the mechanism of glycolytic synchronisation understood nor the role of cell-cell heterogeneity. To pin down the mechanism and to assess its robustness and universality we have experimentally investigated the entrainment of glycolytic oscillations in individual yeast cells by periodic external perturbations. We find that oscillatory cells synchronise through phase shifts and that the mechanism is insensitive to cell heterogeneity (robustness) and similar for different types of external perturbations (universality).

Optical tweezers exploit light–matter interactions to trap particles ranging from single atoms to micrometer‐sized eukaryotic cells. For this reason, optical tweezers are a ubiquitous tool in physics, biology, and nanotechnology. Recently, the use of deep learning has started to enhance optical tweezers by improving their design, calibration, and real‐time control as well as the tracking and analysis of the trapped objects, often outperforming classical methods thanks to the higher computational speed and versatility of deep learning. In this perspective, we show how cutting‐edge deep learning approaches can remarkably improve optical tweezers, and explore the exciting, new future possibilities enabled by this dynamic synergy. Furthermore, we offer guidelines on integrating deep learning with optical trapping and optical manipulation in a reliable and trustworthy way.