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The Arabidopsis (Arabidopsis thaliana) TRANSPARENT TESTA GLABRA2 (TTG2) gene encodes a WRKY transcription factor that regulates a range of development events like trichome, seed coat, and atrichoblast formation. Loss-of-function of TTG2 was previously shown to reduce or eliminate trichome specification and branching. Here, we report the identification of an allele of TTG2, ttg2-6. In contrast to the ttg2 mutants described before, ttg2-6 displayed unique trichome phenotypes. Some ttg2-6 mutant trichomes were hyper-branched, whereas others were hypo-branched, distorted, or clustered. Further, we found that in addition to specifically activating R3 MYB transcription factor TRIPTYCHON (TRY) to modulate trichome specification, TTG2 also integrated cytoskeletal signaling to regulate trichome morphogenesis. The ttg2-6 trichomes displayed aberrant cortical microtubules (cMTs) and actin filaments (F-actin) configurations. Moreover, genetic and biochemical analyses showed that TTG2 could directly bind to the promoter and regulate the expression of BRICK1 (BRK1), which encodes a subunit of the actin nucleation promoting complex suppressor of cyclic AMP repressor (SCAR)/Wiskott–Aldrich syndrome protein family verprolin homologous protein (WAVE). Collectively, taking advantage of ttg2-6, we uncovered a function for TTG2 in facilitating cMTs and F-actin cytoskeleton-dependent trichome development, providing insight into cellular signaling events downstream of the core transcriptional regulation during trichome development in Arabidopsis.

 

Carbohydrate-derived molecular gelators have found many practical applications as soft materials. To better understand the structure and molecular gelation relationship and further explore the applications of sugar-based gelators, we designed and synthesized eight trimeric branched sugar triazole derivatives and studied their self-assembling properties. These included glucose, glucosamine, galactose, and maltose derivatives. Interestingly, the gelation properties of these compounds exhibited correlations with the peripheral sugar structures. The maltose derivative did not form gels in the tested solvents, but all other compounds exhibited gelation properties in at least one of the solvents. Glucose derivatives showed superior performance, followed by glucosamine derivatives. They typically formed gels in toluene and alcohols; some formed gels in ethanol-water mixtures or DMSO water mixtures. The glycoclusters 9 and 10 demonstrated rate acceleration for the copper-catalyzed azide-alkyne cycloaddition (CuAAC) reactions. These were further studied for their metallogels formation properties, and the copper metallogels from compound 9 were successfully utilized to catalyze click reactions. These metallogels were able to form a gel column, which was effective in converting the reactants into the triazole products in multiple cycles. Moreover, the same gel column was used to transform a second click reaction using different reactants. The synthesis and characterization of these compounds and their applications for catalytic reactions were discussed.

 

The kidney tubule consists of a single layer of epithelial cells supported by the tubular basement membrane (TBM), a thin layer of specialized extracellular matrix (ECM). The mechanical properties of the ECM are important for regulating a wide range of cell functions including proliferation, differentiation and cell survival. Increased ECM stiffness plays a role in promoting multiple pathological conditions including cancer, fibrosis and heart disease. How changes in TBM mechanics regulate tubular epithelial cell behavior is not fully understood. Here we introduce a cell culture system that utilizes in vivo-derived TBM to investigate cell–matrix interactions in kidney proximal tubule cells. Basement membrane mechanics was controlled using genipin, a biocompatibility crosslinker. Genipin modification resulted in a dose-dependent increase in matrix stiffness. Crosslinking had a marginal but statistically significant impact on the diffusive molecular transport properties of the TBM, likely due to a reduction in pore size. Both native and genipin-modified TBM substrates supported tubular epithelial cell growth. Cells were able to attach and proliferate to form confluent monolayers. Tubular epithelial cells polarized and assembled organized cell–cell junctions. Genipin modification had minimal impact on cell viability and proliferation. Genipin stiffened TBM increased gene expression of pro-fibrotic cytokines and altered gene expression for N-cadherin, a proximal tubular epithelial specific cell–cell junction marker. This work introduces a new cell culture model for cell-basement membrane mechanobiology studies that utilizes in vivo-derived basement membrane. We also demonstrate that TBM stiffening affects tubular epithelial cell function through altered gene expression of cell-specific differentiation markers and induced increased expression of pro-fibrotic growth factors.

 

Bioengineered in vitro models of the kidney offer unprecedented opportunities to better mimic the in vivo microenvironment. Kidney-on-a-chip technology reproduces 2D or 3D features which can replicate features of the tissue architecture, composition, and dynamic mechanical forces experienced by cells in vivo. Kidney cells are exposed to mechanical stimuli such as substrate stiffness, shear stress, compression, and stretch, which regulate multiple cellular functions. Incorporating mechanical stimuli in kidney-on-a-chip is critically important for recapitulating the physiological or pathological microenvironment. This review will explore approaches to applying mechanical stimuli to different cell types using kidney-on-a-chip models and how these systems are used to study kidney physiology, model disease, and screen for drug toxicity. We further discuss sensor integration into kidney-on-a-chip for monitoring cellular responses to mechanical or other pathological stimuli. We discuss the advantages, limitations, and challenges associated with incorporating mechanical stimuli in kidney-on-a-chip models for a variety of applications. Overall, this review aims to highlight the importance of mechanical stimuli and sensor integration in the design and implementation of kidney-on-a-chip devices. 

Network verification often requires analyzing properties across different spaces (header space, failure space, or their product) under different failure models (deterministic and/or probabilistic). Existing verifiers efficiently cover the header or failure space, but not both, and efficiently reason about deterministic or probabilistic failures, but not both. Consequently, no single verifier can support all analyses that require different space coverage and failure models. This paper introduces Symbolic Router Execution (SRE), a general and scalable verification engine that supports various analyses. SRE symbolically executes the network model to discover what we call packet failure equivalence classes (PFECs), each of which characterises a unique forwarding behavior across the product space of headers and failures. SRE enables various optimizations during the symbolic execution, while remaining agnostic of the failure model, so it scales to the product space in a general way. By using BDDs to encode symbolic headers and failures, various analyses reduce to graph algorithms (e.g., shortest-path) on the BDDs. Our evaluation using real and synthetic topologies show SRE achieves better or comparable performance when checking reachability, mining specifications, etc. compared to state-of-the-art methods. 

Carbohydrate-based low-molecular-weight gelators (LMWGs) are useful classes of compounds due to their numerous applications. Among sugar-based LMWGs, certain peracetylated sugar beta-triazole derivatives were found to be effective organogelators and showed interesting self-assembling properties. To further understand the structural influence towards molecular assemblies and obtain new functional materials with interesting properties, we designed and synthesized a library of tetraacetyl beta-1-triazolyl alkyl-D-glucosides and D-galactosides, in which a two or three carbon spacer is inserted between the anomeric position and the triazole moiety. A series of 16 glucose derivatives and 14 galactose derivatives were synthesized and analyzed. The self-assembling properties of these new triazole containing glycoconjugates in different solvents were analyzed. Several glucose derivatives were found to be effective LMWGs, with compound 7a forming gels in a variety of organic solvents as well as in the presence of metal ions in aqueous solutions. The organogels formed by several compounds were characterized using optical microscopy, atomic force microscopy (AFM) and UV-vis spectroscopy, etc. The co-gels formed by compound 7a with the Fmoc derivative 7i showed interesting fluorescence enhancement upon gelation. Several gelators were also characterized using powder X-ray diffraction and FT-IR spectroscopy. The potential applications of these sugar-based gelators for drug delivery and dye removal were also studied. 

Abstract Despite the advantages and emerging applications, broader adoption of powder bed fusion (PBF) additive manufacturing is challenged by insufficient reliability and in-process variations. Finite element modeling and control-oriented modeling have been shown to be effective for predicting and engineering part qualities in PBF. This paper first builds a finite element model (FEM) of the thermal fields to look into the convoluted thermal interactions during the PBF process. Using the FEM data, we identify a novel surrogate system model from the laser power to the melt pool width. Linking a linear model with a memoryless nonlinear submodel, we develop a physics-based Hammerstein model that captures the complex spatiotemporal thermomechanical dynamics. We verify the accuracy of the Hammerstein model using the FEM and prove that the linearized model is only a representation of the Hammerstein model around the equilibrium point. Along the way, we conduct the stability and robustness analyses and formalize the Hammerstein model to facilitate the subsequent control designs. 

Abstract A high-precision additive manufacturing (AM) process, powder bed fusion (PBF) has enabled unmatched agile manufacturing of a wide range of products from engine components to medical implants. While finite element modeling and closed-loop control have been identified key for predicting and engineering part qualities in PBF, existing results in each realm are developed in opposite computational architectures wildly different in time scale. This paper builds a first-instance closed-loop simulation framework by integrating high-fidelity finite element modeling with feedback controls originally developed for general mechatronics systems. By utilizing the output signals (e.g., melt pool width) retrieved from the finite element model (FEM) to update directly the control signals (e.g., laser power) sent to the model, the proposed closed-loop framework enables testing the limits of advanced controls in PBF and surveying the parameter space fully to generate more predictable part qualities. Along the course of formulating the framework, we verify the FEM by comparing its results with experimental and analytical solutions and then use the FEM to understand the melt-pool evolution induced by the in- and cross-layer thermomechanical interactions. From there, we build a repetitive control (RC) algorithm to attenuate variations of the melt pool width. 

Emerging building analytics rely on data-driven machine learning algorithms. However, writing these analytics is still challenging— developers need to know not only what data are required by the analytics but also how to reach the data in each individual building, despite the existing solutions to standardizing data and resource management in buildings. To bridge the gap between analytics development and the specific details of reaching actual data in each building, we present Energon, an open-source system that enables portable building analytics. The core of Energon is a new data organization for building as well as tools that can effectively manage building data and support building analytics development. More specifically, we propose a new "logic partition" of data resources in buildings, and this abstraction universally applies to all buildings. We develop a declarative query language accordingly to f ind data resources in this new logic view with high-level queries, thus substantially reducing development efforts. We also develop a query engine with automatic data extraction by traversing building ontology that widely exists in buildings. In this way, Energon enables mapping of analytics requirements to building resources in a building-agnostic manner. Using four types of real-world building analytics, we demonstrate the use of Energon and its effectiveness in reducing development efforts.