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The direct conversion of syngas into hydrocarbons, catalyzed by a combination of metal oxide and acidic zeolite, has garnered increasing attention in the scientific community. The remarkable hydrocarbon selectivity achieved in the OX‐ZEO process is a key factor in this growing interest. This process involves two distinct steps: CO activation over the oxide and subsequent C−C coupling within the zeolite pores, connected by an unidentified oxygenate intermediate. In this study, we explored three proposed oxygenates as potential intermediates and compared their conversion within the OX‐ZEO process. Using a bifunctional ZnCr2O4/H‐MOR catalyst in a syngas‐fed batch reactor, we found that methanol (MeOH) and dimethyl ether (DME) produced a hydrocarbon distribution similar to syngas conversion. However, the conversion of acetic acid (AcOH) resulted in a notably distinct range of hydrocarbons, including short olefins not detected with other reagents. Our findings suggest that methanol/DME might serve as active intermediates in the OX‐ZEO process over the ZnCr2O4/H‐MOR catalyst. This study provides a deeper insight into the transformation of proposed intermediates, contributing to the identification of the bridging intermediate that links the two catalytic functions. [ABSTRACT FROM AUTHOR]

The increasing share of distributed renewable energy resources (DER) in the grid entails a paradigm shift in energy system operation demanding more flexibility on the prosumer side. In this work we show an implementation of linear economic model predictive control (MPC) for flexible microgrid dispatch based on time-variable electricity prices. We focus on small and medium enterprises (SME) where information and communications technology (ICT) is available on an industrial level. Our implementation uses field devices and is evaluated in a hardware-in-the-loop (HiL) test bench to achieve high technological maturity. We use available forecasting techniques for power demand and renewable energy generation and evaluate their influence on energy system operation compared to optimal operation under perfect knowledge of the future and compared to a status-quo operation strategy without control. The evaluation scenarios are based on an extensive electricity price analysis to increase representativeness of the simulation results and are based on the use of historic real-world measurements in an existing production facility. Due to real-world restrictions (imperfect forecast knowledge, implementation on field hardware, power fluctuations), between 72.2% and 85.5% of the economic optimum (rather than 100%) is reached. Together with reduced operation cost, the economic MPC implementation on field-typical industrial ICT leads to an increased share of renewable energy demand. [ABSTRACT FROM AUTHOR]

Segmentation is required to quantify cellular structures in microscopic images. This typically requires their fluorescent labeling. Convolutional neural networks (CNNs) can detect these structures also in only transmitted light images. This eliminates the need for transgenic or dye fluorescent labeling, frees up imaging channels, reduces phototoxicity and speeds up imaging. However, this approach currently requires optimized experimental conditions and computational specialists. Here, we introduce "aiSEGcell" a user-friendly CNN-based software to segment nuclei and cells in bright field images. We extensively evaluated it for nucleus segmentation in different primary cell types in 2D cultures from different imaging modalities in hand-curated published and novel imaging data sets. We provide this curated ground-truth data with 1.1 million nuclei in 20,000 images. aiSEGcell accurately segments nuclei from even challenging bright field images, very similar to manual segmentation. It retains biologically relevant information, e.g. for demanding quantification of noisy biosensors reporting signaling pathway activity dynamics. aiSEGcell is readily adaptable to new use cases with only 32 images required for retraining. aiSEGcell is accessible through both a command line, and a napari graphical user interface. It is agnostic to computational environments and does not require user expert coding experience. Author summary: Fluorescence microscopy is the most widely used method to monitor cellular structures in space and time. Fluorescently labeling cellular structures is typically required to localize ("segment") them in electronic images for subsequent quantification. Deep learning approaches can detect these structures also in only bright field images. This eliminates the need for a fluorescent label, frees up imaging channels, speeds up imaging, and reduces the harmful effects of exposing cells to high intensity light. However, label free segmentation currently requires optimized experimental conditions and computational specialists. Therefore, we developed "aiSEGcell" a user-friendly deep learning-based software to segment nuclei and cells in only bright field images. We extensively evaluated aiSEGcell on different common experimental conditions and showed that biologically even sensitive relevant information is retained. Furthermore, we demonstrated that aiSEGcell is adaptable by retraining to new applications with very little required data. We make it accessible for users with no required expert coding experience in a wide range of computational environments. Finally, we openly share our very large imaging data sets to further the development of other segmentation approaches. [ABSTRACT FROM AUTHOR]

Cells sense external stimuli with receptors and further process these stimuli via a variety of signaling pathways consisting of complex biochemical reaction cascades. For decades, cellular signaling was measured at population average level with snapshot data, without taking into account changing signaling activity over time (e.g. signaling dynamics) and cell-to-cell heterogeneity. Recent studies however show the importance of signaling dynamics for controlling future cell fates. As a master regulator of immune responses, the transcription factor nuclear factor kappa-light-chain-enhancer of activated B cells (Nf-κB) coordinates the expression of hundreds of target genes including its own inhibitors NFKBIA and TNFAIP3 in many cell types. While a link between Nf-κB dynamics and future cell state was shown in cell lines, its role in relevant primary cell types remains elusive. Here, we use continuous single-cell quantitative time-lapse imaging of 10 different hematopoietic cell types, including stem and early progenitor cells, from a GFPp65/H2BmCherry reporter mouse line, in custom microfluidic devices, to observe the dynamics of the Nf-κB signaling pathway activity, and investigate how those dynamics influence their fates. We demonstrate that upon an inflammatory challenge by tumor necrosis factor alpha (TNFα), different HSPCs exhibit different and cell type specific Nf-κB dynamics including sustained, transient and oscillatory behaviors. RNA expression kinetics analyses identify molecular regulators responsible for these different dynamics. Additionally, Nf-κB signaling dynamics can identify novel progenitor cell subpopulations with distinct lineage potential. These data demonstrate that signaling dynamics can identify subpopulations of traditionally described cell populations, and suggest a role of Nf-κB signaling dynamics for lineage choice and cell fate control. [ABSTRACT FROM AUTHOR]

Electrocatalytic hydrogenations (ECH) enable the reduction of organic substrates upon usage of electric current and present a sustainable alternative to conventional processes if green electricity is used. Opposed to most current protocols for electrode preparation, this work presents a one‐step binder‐ and additive‐free production of silver‐ and copper‐electroplated electrodes. Controlled adjustment of the preparation parameters allows for the tuning of catalyst morphology and its electrochemical properties. Upon optimization of the deposition protocol and carbon support, high faradaic efficiencies of 93 % for the ECH of the Vitamin A‐ and E‐synthon 2‐methyl‐3‐butyn‐2‐ol (MBY) are achieved that can be maintained at current densities of 240 mA cm−2 and minimal catalyst loadings of 0.2 mg cm−2, corresponding to an unmatched production rate of 1.47 kgMBE gcat−1 h−1. For a continuous hydrogenation process, the protocol can be directly transferred into a single‐pass operation mode giving a production rate of 1.38 kgMBE gcat−1 h−1. Subsequently, the substrate spectrum was extended to a total of 17 different C−C−, C−O− and N−O−unsaturated compounds revealing the general applicability of the reported process. Our results lay an important groundwork for the development of electrochemical reactors and electrodes able to directly compete with the palladium‐based thermocatalytic state of the art. [ABSTRACT FROM AUTHOR]

Cell fates are controlled by environmental stimuli that rapidly change the activity of intracellular signaling. Studying these processes requires rapid manipulations of micro-environmental conditions while continuously observing single cells over long periods of time. Current microfluidic devices are unable to simultaneously i) efficiently capture and concentrate rare cells, ii) conduct automated rapid media exchanges via diffusion without displacing non-adherent cells, and iii) allow sensitive high-throughput long-term time-lapse microscopy. Hematopoietic stem and progenitor cells pose a particular challenge for these types of experiments as they are impossible to obtain in very large numbers and are displaced by the fluid flow usually used to change culture media, thus preventing cell tracking. Here, we developed a programmable automated system composed of a novel microfluidic device for efficient capture of rare cells in independently addressable culture chambers, a custom incubation system, and user-friendly control software. The chip's culture chambers are optimized for efficient and sensitive fluorescence microscopy and their media can be individually and quickly changed by diffusion without non-adherent cell displacement. The chip allows efficient capture, stimulation, and sensitive high-frequency time-lapse observation of rare and sensitive murine and human primary hematopoietic stem cells. Our 3D-printed humidification and incubation system minimizes gas consumption, facilitates chip setup, and maintains stable humidity and gas composition during long-term cell culture. This approach now enables the required continuous long-term single-cell quantification of rare non-adherent cells with rapid environmental manipulations, e.g. of rapid signaling dynamics and the later stem cell fate choices they control. [ABSTRACT FROM AUTHOR]

ERK and AKT signaling control pluripotent cell self-renewal versus differentiation. ERK pathway activity over time (i.e., dynamics) is heterogeneous between individual pluripotent cells, even in response to the same stimuli. To analyze potential functions of ERK and AKT dynamics in controlling mouse embryonic stem cell (ESC) fates, we developed ESC lines and experimental pipelines for the simultaneous long-term manipulation and quantification of ERK or AKT dynamics and cell fates. We show that ERK activity duration or amplitude or the type of ERK dynamics (e.g., transient, sustained, or oscillatory) alone does not influence exit from pluripotency, but the sum of activity over time does. Interestingly, cells retain memory of previous ERK pulses, with duration of memory retention dependent on duration of previous pulse length. FGF receptor/AKT dynamics counteract ERK-induced pluripotency exit. These findings improve our understanding of how cells integrate dynamics from multiple signaling pathways and translate them into cell fate cues. [Display omitted] • Optogenetic control of ERK and AKT activity in mouse embryonic stem cells • Pluripotency exit is due to cumulative ERK activity, not duration, amplitude, or shape • ESCs retain memory of ERK pulses with memory duration dependent on pulse duration • Lower AKT activity increases pluripotency exit Arekatla et al. use optogenetics to control ERK and AKT dynamics in mouse embryonic stem cells. Cumulative ERK activity over time—not duration, amplitude, or types of dynamics—induces pluripotency exit, and lower AKT activation, at constant ERK activity, contributes to higher pluripotency exit. [ABSTRACT FROM AUTHOR]

Transcription factor (TF) networks regulate the lineage choice of hematopoietic stem and progenitor cells (HSPCs). Previous studies suggested a functional antagonism between the core hematopoietic TFs PU.1 and GATA1, and their autoregulation as the basis for a cell-intrinsic stochastic switch regulating PU.1 expression in lineage choice of HSPCs. Using long-term quantitative time-lapse imaging of HSCs from the PU.1eYFP/GATA1mCherry reporter mouse line, we previously showed that a random PU.1 and GATA1 switch does not initiate myeloid lineage choice. To further analyze the regulation of PU.1, we generated a novel mouse line with an inducible PU.1-ERT2 allele co-expressed with the PU.1eYFP/GATA1mCherry reporter alleles. Using single-cell reprogramming assays, microfluidics facilitated reversible PU.1 induction by TNF and single-cell quantification in response to transgenic PU.1-ERT2 activation, we quantified PU.1 expression in thousands of single HSPCs to measure the short- and long- term autoregulation dynamics. Surprisingly, we do not observe direct autoregulation of PU.1 at many different stages of hematopoietic differentiation. We find PU.1 autoregulation not to be involved in initiating differentiation, but to be an indirect consequence of it. Finally, to dissect the molecular triad of PU.1, GATA1 and GATA2 in regulating HSC lineage choice, we have generated a novel reporter mouse line for GATA2 protein and continuously quantify its expression dynamics, simultaneous with that of GATA1 in living HSPCs along the megakaryocyte-erythrocyte and granulocyte-monocyte differentiation trajectories. These data disprove several previous assumptions about the regulation of HSPC fate control, identify novel regulators, and demonstrate vacancy for other cell-extrinsic and -intrinsic players in regulating hematopoietic TFs specifically and lineage choice of HSCs in general. [ABSTRACT FROM AUTHOR]