Treatment with the PPARα agonist fenofibrate improves the efficacy of CD8+ T cell therapy for melanoma.

Adoptive transfer of tumor antigen-specific CD8+ T cells can limit tumor progression but is hampered by the T cells' rapid functional impairment within the tumor microenvironment (TME). This is in part caused by metabolic stress due to lack of oxygen and glucose. Here, we report that fenofibrate treatment of human ex vivo expanded tumor-infiltrating lymphocytes (TILs) improves their ability to limit melanoma progression in a patient-derived xenograft (PDX) mouse model. TILs treated with fenofibrate, a peroxisome proliferator receptor alpha (PPARα) agonist, switch from glycolysis to fatty acid oxidation (FAO) and increase the ability to slow the progression of autologous melanomas in mice with freshly transplanted human tumor fragments or injected with tumor cell lines established from the patients' melanomas and ex vivo expanded TILs.

Heterologous chimpanzee adenovirus vector immunizations for SARS-CoV-2 spike and nucleocapsid protect hamsters against COVID-19.

Available COVID-19 vaccine only provide protection for a limited time due in part to the rapid emergence of viral variants with spike protein mutations, necessitating the generation of new vaccines to combat SARS-CoV-2. Two serologically distinct replication-defective chimpanzee-origin adenovirus (Ad) vectors (AdC) called AdC6 and AdC7 expressing early SARS-CoV-2 isolate spike (S) or nucleocapsid (N) proteins, the latter expressed as a fusion protein within herpes simplex virus glycoprotein D (gD), were tested individually or as a mixture in a hamster COVID-19 SARS-CoV-2 challenge model. The S protein expressing AdC (AdC-S) vectors induced antibodies including those with neutralizing activity that in part cross-reacted with viral variants. Hamsters vaccinated with the AdC-S vectors were protected against serious disease and showed accelerated recovery upon SARS-CoV-2 challenge. Protection was enhanced if AdC-S vectors were given together with the AdC vaccines that expressed the gD N fusion protein (AdC-gDN). In contrast hamsters that just received the AdC-gDN vaccines showed only marginal lessening of symptoms compared to control animals. These results indicate that immune response to the N protein that is less variable than the S protein may potentiate and prolong protection achieved by the currently used S protein based genetic COVID-19 vaccines.

The Effect of Rapamycin and Ibrutinib on Antibody Responses to Adeno-Associated Virus Vector-Mediated Gene Transfer.

Adeno-associated virus (AAV) vector-mediated gene transfer is lessening the impact of monogenetic disorders. Human AAV gene therapy recipients commonly mount immune responses to AAV or the encoded therapeutic protein, which requires transient immunosuppression. Most efforts to date have focused on blunting AAV capsid-specific T cell responses, which have been implicated in elimination of AAV-transduced cells. Here, we explore the use of immunosuppressants, rapamycin given alone or in combination with ibrutinib to inhibit AAV vector- or transgene product-specific antibody responses. Our results show that rapamycin or ibrutinib given alone reduces primary antibody responses against AAV capsid, but the combination of rapamycin and ibrutinib is more effective, blunts recall responses, and reduces numbers of circulating antibody-secreting plasma cells. The drugs fail to lower B cell memory formation or to reduce the inhibitory effects of pre-existing AAV capsid-specific antibodies on transduction efficiency.

T cell responses to adenoviral vectors expressing the SARS-CoV-2 nucleoprotein.

SARS-CoV-2 vaccines aim to protect against COVID-19 through neutralizing antibodies against the viral spike protein. Mutations within the spike's receptor-binding domain may eventually reduce vaccine efficacy, necessitating periodic updates. Vaccine-induced immunity could be broadened by adding T cell-inducing antigens such as SARS-CoV-2's nucleoprotein (N). Here we describe two replication-defective chimpanzee adenovirus (AdC) vectors from different serotypes expressing SARS-CoV-2 N either in its wild-type form or fused into herpes simplex virus glycoprotein D (gD), an inhibitor of an early T cell checkpoint. The vaccines induce potent and sustained CD8+ T cell responses that are broadened upon inclusion of gD. Depending on the vaccine regimen booster immunizations increase magnitude and breadth of T cell responses. Epitopes that are recognized by the vaccine-induced T cells are highly conserved among global SARS-CoV-2 isolates indicating that addition of N to COVID-19 vaccines may lessen the risk of loss of vaccine-induced protection due to variants.

Material remodeling and unconventional gaits facilitate locomotion of a robophysical rover over granular terrain.

Autonomous robots and vehicles must occasionally recover from locomotion failure in loosely consolidated granular terrain. Recent mobility challenges led NASA Johnson Space Center to develop a prototype robotic lunar rover Resource Prospector 15 (RP15) capable of wheeled, legged, and crawling behavior. To systematically understand the terradynamic performance of such a device, we developed a scaled-down rover robot and studied its locomotion on slopes of dry and wet granular media. Addition of a cyclic-legged gait to the robot's wheel spinning action changes the robot dynamics from that of a wheeled vehicle to a locomotor paddling through frictional fluid. Granular drag force measurements and modified resistive force theory facilitate modeling of such dynamics. A peculiar gait strategy that agitates and cyclically reflows grains under the robot allows it to "swim" up loosely consolidated hills. Whereas substrate disturbance typically hinders locomotion in granular media, the multimode design of RP15 and a diversity of possible gaits facilitate formation of self-organized localized frictional fluids that enable effective robust transport.

WASP 8: The Next Generation in the 50-year Evolution of USEPA's Water Quality Model.

The Water Quality Analysis Simulation Program (WASP) helps users interpret and predict water quality responses to natural phenomena and manmade pollution for various pollution management decisions. WASP is a dynamic compartment-modeling program for aquatic systems, including both the water column and the underlying benthos. WASP allows the user to investigate 1, 2 and 3 dimensional systems and a variety of pollutant types-including both conventional pollutants (e.g., dissolved oxygen, nutrients, phytoplankton, etc.) and toxic materials. WASP has capabilities of linking with hydrodynamic and watershed models which allows for multi-year analyses under varying meteorological and environmental conditions. WASP was originally developed by HydroScience, Inc. in 1970 and was later adapted by the US Environmental Protection Agency's Large Lakes Research Station (LLRS) for applications to the Great Lakes. The LLRS first publicly released the model in 1981. WASP has undergone continuous development since that time and this year will mark its 50th anniversary. This paper follows the development of WASP from its origin to the latest release of the model in 2020, documenting its evolution and present structure and capabilities.

Modeling framework for simulating concentrations of solute chemicals, nanoparticles, and solids in surface waters and sediments: WASP8 Advanced Toxicant Module.

Toxicant concentrations in surface waters are of environmental concern due to their potential impacts to humans and wildlife. Numerical models provide system insight, support management decisions, and provide scenario testing on the impacts of toxicants. The Water Quality Analysis Simulation Program (WASP) is a widely used framework for developing site-specific models for simulating toxicant concentrations in surface waters and sediments over a range of complexities and temporal and spatial scales. WASP8, with the Advanced Toxicant module, has been recently released, incorporating a complete architecture redesign for an increased number of state variables and different state variable types. WASP8 incorporates a new structure for simulating light intensity and photoreactions in the water column, including the distinction of 10 different wavelength bands, and nanoparticle heteroaggregation to solids. We present a hypothetical case study, using the Cape Fear River, North Carolina as a representative example for simulating solute chemicals, nanoparticles, and solids to demonstrate the new and updated capabilities of WASP8.

Application of ecosystem-scale fate and bioaccumulation models to predict fish mercury response times to changes in atmospheric deposition.

Management strategies for controlling anthropogenic mercury emissions require understanding how ecosystems will respond to changes in atmospheric mercury deposition. Process-based mathematical models are valuable tools for informing such decisions, because measurement data often are sparse and cannot be extrapolated to investigate the environmental impacts of different policy options. Here, we bring together previously developed and evaluated modeling frameworks for watersheds, water bodies, and food web bioaccumulation of mercury. We use these models to investigate the timescales required for mercury levels in predatory fish to change in response to altered mercury inputs. We model declines in water, sediment, and fish mercury concentrations across five ecosystems spanning a range of physical and biological conditions, including a farm pond, a seepage lake, a stratified lake, a drainage lake, and a coastal plain river. Results illustrate that temporal lags are longest for watershed-dominated systems (like the coastal plain river) and shortest for shallow water bodies (like the seepage lake) that receive most of their mercury from deposition directly to the water surface. All ecosystems showed responses in two phases: A relatively rapid initial decline in mercury concentrations (20-60% of steady-state values) over one to three decades, followed by a slower descent lasting for decades to centuries. Response times are variable across ecosystem types and are highly affected by sediment burial rates and active layer depths in systems not dominated by watershed inputs. Additional research concerning watershed processes driving mercury dynamics and empirical data regarding sediment dynamics in freshwater bodies are critical for improving the predictive capability of process-based mercury models used to inform regulatory decisions.

Evaluating regional predictive capacity of a process-based mercury exposure model, regional-mercury cycling model, applied to 91 Vermont and New Hampshire lakes and ponds, USA.

Regulatory agencies must develop fish consumption advisories for many lakes and rivers with limited resources. Process-based mathematical models are potentially valuable tools for developing regional fish advisories. The regional mercury cycling model (R-MCM) specifically was designed to model a series of lakes for a given region with site-specific data and parameterization for each application. In this paper, we explore the feasibility of R-MCM application to develop regional fish advisories from existing data by testing model performance across 91 Vermont ([VT], USA) and New Hampshire ([NH], USA) lakes. We use a progressive method of parameter refinement ranging from simple defaults specified by the model to site-specific parameterization to evaluate potential improvements in model prediction. Model applications and parameter refinement tiers are based on Regional Environmental Monitoring Assessment Program (REMAP) data. Results show that R-MCM generally underpredicts water column methylmercury and total mercury concentrations and overpredicts sediment methylmercury concentrations. Default level input parameterization produced the largest amount of random scatter in model forecasted values. Using site-specific values for the default level characteristics reduced this variability but did not improve overall model performance. By separating the observed and predicted data by lake characteristics, we identify some overall trends in bias and fit, but are unable to identify systematic biases in model performance by lake type. This analysis suggests that process-based models like R-MCM cannot be used for a priori predictive applications at the regional scale at this time. Further, this work reinforces the need for additional research on the transport and transformation of mercury to elucidate parameterization useable in a modeling framework to help refine predictive capabilities of process-based models.

Modeling mercury fluxes and concentrations in a Georgia watershed receiving atmospheric deposition load from direct and indirect sources.

This paper presents a modeling analysis of airborne mercury (Hg) deposited on the Ochlockonee River watershed located in Georgia. Atmospheric deposition monitoring and source attribution data were used along with simulation models to calculate Hg buildup in the subwatershed soils, its subsequent runoff loading and delivery through the tributaries, and its ultimate fate in the mainstem river. The terrestrial model calculated annual watershed yields for total Hg ranging from 0.7 to 1.1 microg/m2. Results suggest that approximately two-thirds of the atmospherically deposited Hg to the watershed is returned to the atmosphere, 10% is delivered to the river, and the rest is retained in the watershed. A check of the aquatic model results against survey data showed a reasonable agreement. Comparing observed and simulated total and methylmercury concentrations gave root mean square error values of 0.26 and 0.10 ng/L, respectively, in the water column, and 5.9 and 1 ng/g, respectively, in the upper sediment layer. Sensitivity analysis results imply that mercury in the Ochlockonee River is dominated by watershed runoff inputs and not by direct atmospheric deposition, and that methylmercury concentrations in the river are determined mainly by net methylation rates in the watershed, presumably in wetted soils and in the wetlands feeding the river.

The cost of cardiac arrest in the workplace.

As documented in this study, 19 percent were found to have a significant risk of having a cardiac arrest. The impressive ROI calls out to other organizations that cardiac arrest testing is a good use of funds. But more important, yet more difficult to define, is the human impact. Cost savings aside, this form of testing may be able to offer a greater solution than the reactive measures employed to date. If we can reduce cardiac arrest proactively and save considerable amounts of money in the meantime, is there any reason not to try?

Robonaut: a robot designed to work with humans in space.

The Robotics Technology Branch at the NASA Johnson Space Center is developing robotic systems to assist astronauts in space. One such system, Robonaut, is a humanoid robot with the dexterity approaching that of a suited astronaut. Robonaut currently has two dexterous arms and hands, a three degree-of-freedom articulating waist, and a two degree-of-freedom neck used as a camera and sensor platform. In contrast to other space manipulator systems, Robonaut is designed to work within existing corridors and use the same tools as space walking astronauts. Robonaut is envisioned as working with astronauts, both autonomously and by teleoperation, performing a variety of tasks including, routine maintenance, setting up and breaking down worksites, assisting crew members while outside of spacecraft, and serving in a rapid response capacity.