Resident microbiota activate regulatory cells that modulate intestinal inflammation and promote and maintain intestinal homeostasis. IL-10 is a key mediator of immune regulatory function. Our studies ...described the functional importance and mechanisms by which gut microbiota and specific microbial components influenced the development of intestinal IL-10-producing B cells. We used fecal transplant to germ-free (GF) Il10+/EGFP reporter and Il10-/- mice to demonstrate that microbiota from specific pathogen-free mice primarily stimulated IL-10-producing colon-specific B cells and T regulatory-1 cells in ex-GF mice. IL-10 in turn down-regulated microbiota-activated mucosal inflammatory cytokines. TLR2/9 ligands and enteric bacterial lysates preferentially induced IL-10 production and regulatory capacity of intestinal B cells. Analysis of Il10+/EGFP mice crossed with additional gene-deficient strains and B cell co-transfer studies demonstrated that microbiota-induced IL-10-producing intestinal B cells ameliorated chronic T cell-mediated colitis in a TLR2, MyD88 and PI3K-dependent fashion. In vitro studies implicated PI3Kp110δ and AKT downstream signaling. These studies demonstrated that resident enteric bacteria activated intestinal IL-10-producing B cells through TLR2, MyD88 and PI3K pathways. These B cells reduced colonic T cell activation and maintained mucosal homeostasis in response to intestinal microbiota.
We describe a huge planetary‐scale disturbance in the highest‐speed Jovian jet at latitude 23.5°N that was first observed in October 2016 during the Juno perijove‐2 approach. An extraordinary ...outburst of four plumes was involved in the disturbance development. They were located in the range of planetographic latitudes from 22.2° to 23.0°N and moved faster than the jet peak with eastward velocities in the range 155 to 175 m s−1. In the wake of the plumes, a turbulent pattern of bright and dark spots (wave number 20–25) formed and progressed during October and November on both sides of the jet, moving with speeds in the range 100–125 m s−1 and leading to a new reddish and homogeneous belt when activity ceased in late November. Nonlinear numerical models reproduce the disturbance cloud patterns as a result of the interaction between local sources (the plumes) and the zonal eastward jet.
Key Points
A planetary‐scale disturbance developed in the highest‐speed Jupiter jet at 23.5°N latitude during October and November 2016
Four “plumes” were involved in the outbreak moving with speeds between 155 and 175 m s−1, the fastest features at cloud level
Nonlinear numerical models reproduce the disturbance from the interaction between local sources (the plumes) and the zonal eastward jet
Abstract Despite significant advances in the fabrication of bioengineered scaffolds for tissue engineering, delivery of nutrients in complex engineered human tissues remains a challenge. By taking ...advantage of the similarities in the vascular structure of plant and animal tissues, we developed decellularized plant tissue as a prevascularized scaffold for tissue engineering applications. Perfusion-based decellularization was modified for different plant species, providing different geometries of scaffolding. After decellularization, plant scaffolds remained patent and able to transport microparticles. Plant scaffolds were recellularized with human endothelial cells that colonized the inner surfaces of plant vasculature. Human mesenchymal stem cells and human pluripotent stem cell derived cardiomyocytes adhered to the outer surfaces of plant scaffolds. Cardiomyocytes demonstrated contractile function and calcium handling capabilities over the course of 21 days. These data demonstrate the potential of decellularized plants as scaffolds for tissue engineering, which could ultimately provide a cost-efficient, “green” technology for regenerating large volume vascularized tissue mass.
Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and ...increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake‐specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake‐specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid‐century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.
Abstract
This review gives first a brief view of the potential availability of sustainable energy. It is clear that over 100 times more solar photovoltaic energy than necessary is readily accessible ...and that practically available wind alone may deliver sufficient energy supply to the world. Due to the intermittency of these sources, effective and inexpensive energy-conversion and storage technology is needed. Motivation for the possible electrolysis application of reversible solid-oxide cells (RSOCs), including a comparison of power-to-fuel/fuel-to-power to other energy-conversion and storage technologies is presented. RSOC electrochemistry and chemistry of H2O, CO2, H2, CO, CnHm (hydrocarbons) and NH3, including thermodynamics and cell performance, are described. The mechanical strength of popular cell supports is outlined, and newly found stronger materials are mentioned. Common cell-degradation mechanisms, including the effect of common impurities in gases and materials (such as S and Si), plus the deleterious effects of carbon deposition in the fuel electrode are described followed by explanations of how to avoid or ease the consequences. Visions of how RSOCs powered by sustainable energy may be applied on a large scale for the transportation sector via power-to-fuel technology and for integration with the electrical grid together with seasonal storage are presented. Finally, a brief comparison of RSOCs to other electrolysis cells and an outlook with examples of actions necessary to commercialize RSOC applications are sketched.
The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with ...state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling framework with a use‐case of predicting depth‐specific lake water temperatures. The PGDL model has three primary components: a deep learning model with temporal awareness (long short‐term memory recurrence), theory‐based feedback (model penalties for violating conversation of energy), and model pretraining to initialize the network with synthetic data (water temperature predictions from a process‐based model). In situ water temperatures were used to train the PGDL model, a deep learning (DL) model, and a process‐based (PB) model. Model performance was evaluated in various conditions, including when training data were sparse and when predictions were made outside of the range in the training data set. The PGDL model performance (as measured by root‐mean‐square error (RMSE)) was superior to DL and PB for two detailed study lakes, but only when pretraining data included greater variability than the training period. The PGDL model also performed well when extended to 68 lakes, with a median RMSE of 1.65 °C during the test period (DL: 1.78 °C, PB: 2.03 °C; in a small number of lakes PB or DL models were more accurate). This case‐study demonstrates that integrating scientific knowledge into deep learning tools shows promise for improving predictions of many important environmental variables.
Key Points
Process‐Guided Deep Learning (PGDL) models integrate advanced empirical techniques with process knowledge
We used PGDL to accurately predict lake water temperatures for various conditions
PGDL performance improved significantly when pretraining data included diverse conditions generated by an existing process‐based model
Harvesting energy from multiple sources available in our personal and daily environments is highly desirable, not only for powering personal electronics, but also for future implantable ...sensor-transmitter devices for biomedical and healthcare applications. Here we present a hybrid energy scavenging device for potential in vivo applications. The hybrid device consists of a piezoelectric poly(vinylidene fluoride) nanofiber nanogenerator for harvesting mechanical energy, such as from breathing or from the beat of a heart, and a flexible enzymatic biofuel cell for harvesting the biochemical (glucose/O2) energy in biofluid, which are two types of energy available in vivo. The two energy harvesting approaches can work simultaneously or individually, thereby boosting output and lifetime. Using the hybrid device, we demonstrate a “self-powered” nanosystem by powering a ZnO nanowire UV light sensor.
The wavelength-selective, reversible photocontrol over various molecular processes in parallel remains an unsolved challenge. Overlapping ultraviolet-visible spectra of frequently employed ...photoswitches have prevented the development of orthogonally responsive systems, analogous to those that rely on wavelength-selective cleavage of photo-removable protecting groups. Here we report the orthogonal and reversible control of two distinct types of photoswitches in one solution, that is, a donor-acceptor Stenhouse adduct (DASA) and an azobenzene. The control is achieved by using three different wavelengths of irradiation and a thermal relaxation process. The reported combination tolerates a broad variety of differently substituted photoswitches. The presented system is also extended to an intramolecular combination of photoresponsive units. A model application for an intramolecular combination of switches is presented, in which the DASA component acts as a phase-transfer tag, while the azobenzene moiety independently controls the binding to α-cyclodextrin.
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