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The latency to display eating or drinking during hypothalamic stimulation was compared with the preferred duration of the same stimulus intensity in a self-stimulation situation. All the animals preferred longer stimulus durations than those required to elicit eating or drinking
Many morphologically distinguishable filamentous spore-forming bacteria symbiotic in the paunch (hypertrophied hindguts) of wood-eating insects have been seen since Arthromitus was first described and named as a plant by Leidy in 1850. Previous descriptions were inadequate for acceptance of the group in modern bacteriological literature. Twenty-two distinguishable arthromitids in nine different arthropod hosts are recorded on the basis of microscopic studies. Five are named, including two whose ultrastructure are detailed: Arthromitus chasei sp. nov. that lives in the damp wood-eating termite Zootermopsis angusticollis (from the west coast of North America) and Arthromitus reticulitermitidis sp. nov. from the subterranean west coast termite Reticulitermes tibialis. A pterotermiditis from the desert termite Pterotermitidis occidentis; A. zootermopsidis, also from Z. angusticollis; and A. cristatus (Leidy, 1881) from Reticulitermes flavipes of eastern North America are also named here. Characterized by trichomes that show a morphogenetic sequence from no spores through immature spores to mature spores with spore filaments, Arthromitus symbionts can be identified as members of the genus by light microscopy and habitat. Electron microscopy reveals their remarkable complexity. They attach by spore filaments to various objects including the host gut wall; their maturation extends distally toward the termite lumen. By surface sterilization of the termite, maceration of the paunch, exposure to boiling temperatures and plating on soft acetate agar, the heat resistant nature of the spores and facultatively aerobic nature of Arthromitus sp. (from Zootermopsis) was demonstrated.
Astronauts cannot live on dehydrated ice cream alone. Like everyone else, they need their vegetables. Enter VEGGIE, the Deployable Vegetable System, currently under development by Orbital Technologies Corporation (ORBITEC). VEGGIE is the latest in a long line of vegetable production units ORBITEC is currently working on, with NASA assistance, to grow salad crops to supplement prepackaged foods during long stays in space. The primary goal of the VEGGIE project is to provide flight crews with palatable, nutritious, and safe sources of fresh food with minimal volume and operational resources. In addition, ORBITEC recognizes the age-old adage that gardening is good for the soul, and it acknowledges that gardens are beneficial for relaxation and recreation. As evidence, astronauts on the International Space Station (ISS), who often stay for periods of 6 months, have been enjoying plant experiments, which provide them with much missed greenery and can occupy valuable free time with an enjoyable task. VEGGIE is a project that grew out of technology developed by ORBITEC for the Biomass Production System (BPS). The BPS is equivalent in size to a Space Shuttle middeck locker, and provides four plant growth chambers. Each chamber has independent control of temperature, humidity, nutrient and water delivery, lighting, and atmospheric composition. The BPS flew to the ISS in 2002, and astronaut Dan Bursch had positive comments about his interaction with the plants while in orbit. Astronaut Peggy Whitson had similarly positive remarks during the following expedition while she was growing soybeans for another experiment. Whitson reflects on her time in space with the plantings on Expedition 5, "Although it doesn t sound like much, it was really exciting to see something green. I assumed that this was just because I really enjoy plants, but it surprised me that both of my crewmates were just as excited. They wanted photos of themselves with the plants and asked if they could eat some of them, too!" The astronauts did not eat the plants, but these initial experiments gave the researchers information they needed about the basics of growing crops in space.
Astronauts cannot have their cake and eat it too, but what about growing a salad and eating it? As NASA continues to push the envelope on Space exploration and inhabitance the need for a fresh food source becomes more vital. The Life Support team at NASA is using a system developed by ORBITEC the VEGGIE, in which astronauts aboard the ISS, and potentially the Moon and Mars, will be capable of growing food. The introduction of plants not only gives astronauts a means of independently supplying food, but also recreation, oxygen replenishment and psychological benefits. The plants were grown in "pillows", the system used for growing plants within the VEGGIE. This test included 4 types of media mixtures that are composed of a clay based media called Arcilite and Fafard #2, which is a peat moss-based media ( <1 mm Arcilite, 1-2 mm of Arcilite, 1:1 <1 mm & 1-2 mm mixture and 1:1 Arcilite & Fafard mixture). Currently, 3 lettuce cultivars are being grown in 4 mixtures of media. Tests were being conducted to see which form of media has the ratio of best growth and least amount of microbes that are harmful. That is essential because a person's body becomes more susceptible to illness when they leave Earth. As a result, test must be conducted on the "pillow" system to assess the levels of microbial activity. The cultivars were tested at different stages during their growing process for microbes. Datum show that the mix of Fafard and Arcilite had the best growth, but also the most microbes. This was due to the fact that Fafard is an organic substance so it contains material necessary for microbes to live. Data suggest that the <1 mm Arcilite has an acceptable amount of growth and a lower level of microbes, because it is non-organic.
Microbiological Areas of Concern: Astronaut Health; Vehicle integrity; Life support and other systems failure -Biofilm formation/biofouling -Bio-corrosion and biodegradation -Trash and human waste containment -Risk of condensation -Astronaut hygiene areas; Spaceflight foods -Impact of “pick and eat” foods on the environment -Impact of the environment on “pick and eat” foods -Rinsing food with potable water is impractical; Planetary protection -How do we track what we are leaving versus what we are finding in our search for life on other planets?
Abstract Affordable synthetic ammonia (NH 3 ) enables the production of nearly half of the food we eat and is emerging as a renewable energy carrier. Sodium‐promoted chemical looping NH 3 synthesis at atmospheric pressure using manganese (Mn) is here demonstrated. The looping process may be advantageous when inexpensive renewable hydrogen from electrolysis is available. Avoiding the high pressure of the Haber‐Bosch process by chemical looping using earth‐abundant materials may reduce capital cost, facilitate intermittent operation, and allow operation in geographic areas where infrastructure is less sophisticated. At this early stage, the data suggest that 0.28 m 3 of a 50 % porosity solid Mn bed may suffice to produce 100 kg NH 3 per day by chemical looping, with abundant opportunities for improvement.
Abstract Objective Because predation is thought to be the primary source of natural mortality for juvenile salmon first entering the ocean, we sought to identify regions where, on average, stock-specific spatial overlap between the distribution of threatened and endangered juvenile Chinook Salmon Oncorhynchus tshawytscha and abundant fish-eating seabirds (common murres Uria aalge and sooty shearwaters Ardenna grisea) suggests the greatest potential for ocean predation risk to juvenile Chinook Salmon. Methods The relative abundance and spatial distribution of seabird predators and juvenile Chinook Salmon were quantified as part of long-term ecosystem surveys during May 2003–2012 and June 2003–2022. Genetic stock identification methods were used to assign individual fish to their respective stock groups. Stock-specific species distribution models then generated maps and indices of average annual spatial overlap between predators and prey within the survey area. Result There is unequivocal evidence for spatial overlap between common murres, sooty shearwaters, and five genetic groups of interior and lower Columbia River juvenile Chinook Salmon. We found strongly positive (≥0.70) spatial correlations between predator and prey densities in both May and June, although spatial overlap was, in general, greater during May. The region of highest spatial overlap occurred on the inner continental shelf between the Columbia River mouth (46.2°N) and Grays Harbor (47.0°N), a region at the beginning of the juvenile salmon migratory pathway that is strongly affected by freshwater outflow from the river. Conclusion Our findings support the idea that ocean avian predation during early marine residence has the potential to affect marine survival of juvenile Chinook Salmon and should be further investigated to better inform and implement ecological models and possible recovery actions for Chinook Salmon populations of the Columbia River basin.
Timely removal of ice and snow from roads is critical to safe, fast, and uninterrupted transportation networks in cold regions. Constructing electrically conductive asphalt pavements to melt the ice and snow on the roads through resistive eating is an emerging alternative technology to traditional snow/ice removal approaches such as utilizing snowplow machines and deicing chemicals. Carbon-based fibers and fillers including carbon fiber and graphite have been widely reported to make electrically conductive hot mix asphalt mixtures for pavement snow/ice-melting applications. This study aimed to develop and demonstrate a novel type of electrically conductive asphalt pavements for snow/ice-melting, which utilizes electrically conductive cold mix asphalt (CMA) mixtures incorporating coal-derived carbon-based coke aggregate as resistive heating elements. Both laboratory experiments and field tests were conducted to investigate the electrical, mechanical, and thermal properties of such electrically conductive asphalt mixtures and pavements. The laboratory experiment results indicated that the electrically conductive CMA mixtures incorporating coke aggregate had sufficiently high electrical conductivity and satisfactory mechanical performance and the pavement prototype slab utilizing a thin layer of such CMA mixtures could successfully raise the pavement surface temperatures to 8.3–11.7 °C rom a low temperature of –5 °C with an input power density of 473 W/m 2 . The field test results showed that the full-scale coal-derived electrically conductive asphalt pavements were able to increase the pavement surface temperatures when electricity was applied, but the magnitude of temperature increase was highly dependent on the power density. Furthermore, it is promising to use coke aggregate to construct coal-derived electrically conductive asphalt pavements for snow/ice melting.
Reducing pollutant emissions from heavy-duty (HD) diesel engines is critical due to their significant environmental impact, particularly concerning NOx emissions. Understanding and optimizing modern diesel oxidation catalyst (DOC) and selective catalytic reduction (SCR) performance is essential for improving exhaust aftertreatment (EAT) system efficiency to meet stringent emissions regulations. The oxidation of nitric oxide (NO) to nitrogen dioxide (NO 2 ) in DOC plays a key role in improving SCR efficiency in reducing NO x . This study investigates the DOC performance in oxidizing NO to NO2 and its impact on the SCR efficiency of a 2021 MY Navistar E39 HD diesel engine. The influence of engine speed, load, exhaust gas temperature, and composition on DOC efficiency is experimentally investigated. The relationships between DOC inlet temperature, oxygen availability and NO 2 /NO x ratio at the DOC inlet are examined to better understand their effects on the overall DOC efficiency. The results indicate that DOC NO oxidation efficiency is highly dependent on exhaust temperature, with optimal oxidation occurring within a specific temperature range (275-350°C). Below this threshold, the chemical reactions are kinetically limited, while at higher temperatures, thermodynamic constraints reduce the efficiency of DOC in oxidizing NO to NO 2 . The experimental data further reveal that the NO 2 /NO x ratio peaks at medium loads before declining at higher loads due to reduced residence time and mass transfer effects. Additionally, the SCR NO x conversion efficiency is significantly influenced by the NO 2 /NO x ratio, achieving peak performance when the NO 2 /NO x ratio approaches 0.5. A DOC chemistry model was developed and validated against the experimental data to predict DOC oxidation behavior under various operating conditions. The findings of this study provide insights into the interdependencies between DOC and SCR performance, contributing to the optimization of SCR systems for optimized NOx reduction.
Here, we have developed an improved system to measure Cs-137 in wildlife at the Savannah River Site. This field-portable system consists of a shielded 5 cm by 10 cm by 40 cm NaI detector controlled by an Ametek Ortec Digibase. Measurement of an animal’s radioactivity is made by placing the animal at a predefined location on the detector system for a one minute count-time. The counts, animal type, and animal weight are then used as inputs to an algorithm which calculates the amount of Cs-137 within the whole animal and within the edible meat portion of the animal. The results from these calculations are used to estimate the received dose from eating this animal and is included in the Savannah River Site’s Hunter Dose Tracking System. This system has a detection limit of 0.60 pCi/g (22.20 Bq/kg) with a typical measurement uncertainty of less than 0.32 pCi/g (11.84 Bq/kg).
Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.
Cancer therapy-induced oral mucositis is a frequent major oncological problem, secondary to cytotoxicity of chemo-radiation treatment. Oral mucositis commonly occurs 7–10 days after initiation of therapy; it is a dose-limiting side effect causing significant pain, eating difficulty, need for parenteral nutrition and a rise of infections. The pathobiology derives from complex interactions between the epithelial component, inflammation, and the oral microbiome. Our longitudinal study analysed the dynamics of the oral microbiome (bacteria and fungi) in nineteen patients undergoing chemo-radiation therapy for oral and oropharyngeal squamous cell carcinoma as compared to healthy volunteers. The microbiome was characterized in multiple oral sample types using rRNA and ITS sequence amplicons and followed the treatment regimens. Microbial taxonomic diversity and relative abundance may be correlated with disease state, type of treatment and responses. Identification of microbial-host interactions could lead to further therapeutic interventions of mucositis to re-establish normal flora and promote patients’ health. Data presented here could enhance, complement and diversify other studies that link microbiomes to oral disease, prophylactics, treatments, and outcome.
The autophagy-initiating human ULK complex consists of the kinase ULK1/2, FIP200, ATG13, and ATG101. Hydrogen-deuterium exchange mass spectrometry was used to map their mutual interactions. The N-terminal 640 residues (NTD) of FIP200 interact with the C-terminal IDR of ATG13. Mutations in these regions abolish their interaction. Negative stain EM and multiangle light scattering showed that FIP200 is a dimer, while a single molecule each of the other subunits is present. The FIP200NTD is flexible in the absence of ATG13, but in its presence adopts the shape of the letter C ~20 nm across. The ULK1 EAT domain interacts loosely with the NTD dimer, while the ATG13:ATG101 HORMA dimer does not contact the NTD. Cryo-EM of the NTD dimer revealed a structural similarity to the scaffold domain of TBK1, suggesting an evolutionary similarity between the autophagy-initiating TBK1 kinase and the ULK1 kinase complex.
Abstract Ectropis obliqua Prout (Lepidoptera: Geometridae) is a serious leaf‐eating pest in tea gardens throughout China, with rich bacterial communities in the larval gut. Few studies have investigated whether these bacteria play an important role in growth, development, and adaptability of E. obliqua . Axenic larval models are a useful tool for the study of interactions between gut bacteria and host insects. At present, artificial diet and antibiotics are typically used to remove larval gut bacteria for study; however, this method may change the natural food of insects and the habitat provided by their host plants, and cannot completely eliminate insect gut bacteria. Therefore, in order to establish an axenic insect feeding model, we first investigated the effects of egg age, different disinfectant concentration, and treatment time on the eggs of E. obliqua through orthogonal experiments. Next, we fed E. obliqua larvae tissue‐cultured tea seedlings under aseptic conditions. Thus, we successfully generated a feeding model of gut axenic larvae in the laboratory. Based on it, we then compared the mortality of axenic and non‐axenic E. obliqua larvae infected with the entomopathogenic fungus Beauveria bassiana (Balsamo) Vuill. These results demonstrated the feasibility of this axenic larval model and that B. bassiana is a broad‐spectrum entomogenous fungus with a toxic effect on E. obliqua .
ABSTRACT Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg , an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, “who is eating what?” and “who is active?” within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism’s taxonomic identity and genome composition while providing quantitative estimates of the microorganism’s isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.
Individual human location trajectory and check-in data have been the driving force for human mobility research in recent years. However, existing human mobility datasets are very limited in size and representativeness. For example, one of the largest and most commonly used datasets of individual human location trajectories, GeoLife, captures fewer than two hundred individuals. To help fill this gap, this Data and Resources paper leverages an existing data generator based on fine-grained simulation of individual human patterns of life to produce large-scale trajectory, check-in, and social network data. In this simulation, individual human agents commute between their home and work locations, visit restaurants to eat, and visit recreational sites to meet friends. We provide large datasets of months of simulated trajectories for two example regions in the United States: San Francisco and New Orleans. In addition to making the datasets available, we also provide instructions on how the simulation can be used to re-generate data, thus allowing researchers to generate the data locally without downloading prohibitively large files.
Naegleria fowleri is a pathogenic, thermophilic, free-living amoeba which causes primary amebic meningoencephalitis (PAM). Penetrating the olfactory mucosa, the brain-eating amoeba travels along the olfactory nerves, burrowing through the cribriform plate to its destination: the brain’s frontal lobes. The amoeba thrives in warm, freshwater environments, with peak infection rates in the summer months and has a mortality rate of approximately 97%. A major contributor to the pathogen’s high mortality is the lack of sensitivity of N . fowleri to current drug therapies, even in the face of combination-drug therapy. To enable rational drug discovery and design efforts we have pursued protein production and crystallography-based structure determination efforts for likely drug targets from N . fowleri . The genes were selected if they had homology to drug targets listed in Drug Bank or were nominated by primary investigators engaged in N . fowleri research. In 2017, 178 N . fowleri protein targets were queued to the Seattle Structural Genomics Center of Infectious Disease (SSGCID) pipeline, and to date 89 soluble recombinant proteins and 19 unique target structures have been produced. Many of the new protein structures are potential drug targets and contain structural differences compared to their human homologs, which could allow for the development of pathogen-specific inhibitors. Five of the structures were analyzed in more detail, and four of five show promise that selective inhibitors of the active site could be found. The 19 solved crystal structures build a foundation for future work in combating this devastating disease by encouraging further investigation to stimulate drug discovery for this neglected pathogen.
Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.