Showing papers by "University of Nevada, Reno published in 2021"

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Genomic evidence for reinfection with SARS-CoV-2: a case study.

Abstract: Summary Background The degree of protective immunity conferred by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently unknown. As such, the possibility of reinfection with SARS-CoV-2 is not well understood. We describe an investigation of two instances of SARS-CoV-2 infection in the same individual. Methods A 25-year-old man who was a resident of Washoe County in the US state of Nevada presented to health authorities on two occasions with symptoms of viral infection, once at a community testing event in April, 2020, and a second time to primary care then hospital at the end of May and beginning of June, 2020. Nasopharyngeal swabs were obtained from the patient at each presentation and twice during follow-up. Nucleic acid amplification testing was done to confirm SARS-CoV-2 infection. We did next-generation sequencing of SARS-CoV-2 extracted from nasopharyngeal swabs. Sequence data were assessed by two different bioinformatic methodologies. A short tandem repeat marker was used for fragment analysis to confirm that samples from both infections came from the same individual. Findings The patient had two positive tests for SARS-CoV-2, the first on April 18, 2020, and the second on June 5, 2020, separated by two negative tests done during follow-up in May, 2020. Genomic analysis of SARS-CoV-2 showed genetically significant differences between each variant associated with each instance of infection. The second infection was symptomatically more severe than the first. Interpretation Genetic discordance of the two SARS-CoV-2 specimens was greater than could be accounted for by short-term in vivo evolution. These findings suggest that the patient was infected by SARS-CoV-2 on two separate occasions by a genetically distinct virus. Thus, previous exposure to SARS-CoV-2 might not guarantee total immunity in all cases. All individuals, whether previously diagnosed with COVID-19 or not, should take identical precautions to avoid infection with SARS-CoV-2. The implications of reinfections could be relevant for vaccine development and application. Funding Nevada IDEA Network of Biomedical Research, and the National Institute of General Medical Sciences (National Institutes of Health).

Insect decline in the Anthropocene: Death by a thousand cuts

Abstract: Nature is under siege. In the last 10,000 y the human population has grown from 1 million to 7.8 billion. Much of Earth’s arable lands are already in agriculture (1), millions of acres of tropical forest are cleared each year (2, 3), atmospheric CO2 levels are at their highest concentrations in more than 3 million y (4), and climates are erratically and steadily changing from pole to pole, triggering unprecedented droughts, fires, and floods across continents. Indeed, most biologists agree that the world has entered its sixth mass extinction event, the first since the end of the Cretaceous Period 66 million y ago, when more than 80% of all species, including the nonavian dinosaurs, perished. Ongoing losses have been clearly demonstrated for better-studied groups of organisms. Terrestrial vertebrate population sizes and ranges have contracted by one-third, and many mammals have experienced range declines of at least 80% over the last century (5). A 2019 assessment suggests that half of all amphibians are imperiled (2.5% of which have recently gone extinct) (6). Bird numbers across North America have fallen by 2.9 billion since 1970 (7). Prospects for the world’s coral reefs, beyond the middle of this century, could scarcely be more dire (8). A 2020 United Nations report estimated that more than a million species are in danger of extinction over the next few decades (9), but also see the more bridled assessments in refs. 10 and 11. Although a flurry of reports has drawn attention to declines in insect abundance, biomass, species richness, and range sizes (e.g., refs. 12⇓⇓⇓⇓⇓–18; for reviews see refs. 19 and 20), whether the rates of declines for insects are on par with or exceed those for other groups remains unknown. There are still too … [↵][1]1To whom correspondence may be addressed. Email: david.wagner{at}uconn.edu. [1]: #xref-corresp-1-1

Widespread deoxygenation of temperate lakes

Abstract: The concentration of dissolved oxygen in aquatic systems helps to regulate biodiversity1,2, nutrient biogeochemistry3, greenhouse gas emissions4, and the quality of drinking water5. The long-term declines in dissolved oxygen concentrations in coastal and ocean waters have been linked to climate warming and human activity6,7, but little is known about the changes in dissolved oxygen concentrations in lakes. Although the solubility of dissolved oxygen decreases with increasing water temperatures, long-term lake trajectories are difficult to predict. Oxygen losses in warming lakes may be amplified by enhanced decomposition and stronger thermal stratification8,9 or oxygen may increase as a result of enhanced primary production10. Here we analyse a combined total of 45,148 dissolved oxygen and temperature profiles and calculate trends for 393 temperate lakes that span 1941 to 2017. We find that a decline in dissolved oxygen is widespread in surface and deep-water habitats. The decline in surface waters is primarily associated with reduced solubility under warmer water temperatures, although dissolved oxygen in surface waters increased in a subset of highly productive warming lakes, probably owing to increasing production of phytoplankton. By contrast, the decline in deep waters is associated with stronger thermal stratification and loss of water clarity, but not with changes in gas solubility. Our results suggest that climate change and declining water clarity have altered the physical and chemical environment of lakes. Declines in dissolved oxygen in freshwater are 2.75 to 9.3 times greater than observed in the world’s oceans6,7 and could threaten essential lake ecosystem services2,3,5,11. Analysis of temperate lakes finds a widespread decline in dissolved oxygen concentrations in surface and deep waters, which is associated with reduced solubility at warmer surface water temperatures and increased stratification at depth.

Insects and recent climate change

Abstract: Insects have diversified through more than 450 million y of Earth's changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.

STREME: accurate and versatile sequence motif discovery

Abstract: Motivation Sequence motif discovery algorithms can identify novel sequence patterns that perform biological functions in DNA, RNA and protein sequences-for example, the binding site motifs of DNA-and RNA-binding proteins. Results The STREME algorithm presented here advances the state-of-the-art in ab initio motif discovery in terms of both accuracy and versatility. Using in vivo DNA (ChIP-seq) and RNA (CLIP-seq) data, and validating motifs with reference motifs derived from in vitro data, we show that STREME is more accurate, sensitive and thorough than several widely used algorithms (DREME, HOMER, MEME, Peak-motifs) and two other representative algorithms (ProSampler and Weeder). STREME's capabilities include the ability to find motifs in datasets with hundreds of thousands of sequences, to find both short and long motifs (from 3 to 30 positions), to perform differential motif discovery in pairs of sequence datasets, and to find motifs in sequences over virtually any alphabet (DNA, RNA, protein and user-defined alphabets). Unlike most motif discovery algorithms, STREME reports a useful estimate of the statistical significance of each motif it discovers. STREME is easy to use individually via its web server or via the command line, and is completely integrated with the widely-used MEME Suite of sequence analysis tools. The name STREME stands for "Simple, Thorough, Rapid, Enriched Motif Elicitation". Availability The STREME web server and source code are provided freely for non-commercial use at http://meme-suite.org.

Widespread introgression across a phylogeny of 155 Drosophila genomes

Abstract: Genome-scale sequence data has invigorated the study of hybridization and introgression, particularly in animals. However, outside of a few notable cases, we lack systematic tests for introgression at a larger phylogenetic scale across entire clades. Here we leverage 155 genome assemblies, from 149 species, to generate a fossil-calibrated phylogeny and conduct multilocus tests for introgression across 9 monophyletic radiations within the genus Drosophila. Using complementary phylogenomic approaches, we identify widespread introgression across the evolutionary history of Drosophila. Mapping gene-tree discordance onto the phylogeny revealed that both ancient and recent introgression has occurred, with introgression at the base of species radiations being particularly common. Our results provide the first evidence of introgression occurring across the evolutionary history of Drosophila and highlight the need to continue to study the evolutionary consequences of hybridization and introgression in this genus and across the Tree of Life.

A window to the world of global insect declines: Moth biodiversity trends are complex and heterogeneous

Abstract: Moths are the most taxonomically and ecologically diverse insect taxon for which there exist considerable time-series abundance data. There is an alarming record of decreases in moth abundance and diversity from across Europe, with rates varying markedly among and within regions. Recent reports from Costa Rica reveal steep cross-lineage declines of caterpillars, while other sites (Ecuador and Arizona, reported here) show no or only modest long-term decreases over the past two decades. Rates of decline for dietary and ecological specialists are steeper than those for ecologically generalized taxa. Additional traits commonly associated with elevated risks include large wingspans, small geographic ranges, low dispersal ability, and univoltinism; taxa associated with grasslands, aridlands, and nutrient-poor habitats also appear to be at higher risk. In temperate areas, many moth taxa limited historically by abiotic factors are increasing in abundance and range. We regard the most important continental-scale stressors to include reductions in habitat quality and quantity resulting from land-use change and climate change and, to a lesser extent, atmospheric nitrification and introduced species. Site-specific stressors include pesticide use and light pollution. Our assessment of global macrolepidopteran population trends includes numerous cases of both region-wide and local losses and studies that report no declines. Spatial variation of reported losses suggests that multiple stressors are in play. With the exception of recent reports from Costa Rica, the most severe examples of moth declines are from Northern Hemisphere regions of high human-population density and intensive agriculture.

Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l.

Abstract: Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations. [Amaranthaceae; gene tree discordance; hybridization; incomplete lineage sorting; phylogenomics; species network; species tree; transcriptomics.].

Screening for Dark Personalities: The Short Dark Tetrad (SD4)

Abstract: . Consensus is emerging that the constellation of dark personalities should include the sadistic personality. To build a four-factor measure, we modified and extended the Short Dark Triad (...

The olfactory nerve is not a likely route to brain infection in COVID-19: a critical review of data from humans and animal models.

Abstract: One of the most frequent symptoms of COVID-19 is the loss of smell and taste. Based on the lack of expression of the virus entry proteins in olfactory receptor neurons, it was originally assumed that the new coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) does not infect olfactory neurons. Recent studies have reported otherwise, opening the possibility that the virus can directly infect the brain by traveling along the olfactory nerve. Multiple animal models have been employed to assess mechanisms and routes of brain infection of SARS-CoV-2, often with conflicting results. We here review the current evidence for an olfactory route to brain infection and conclude that the case for infection of olfactory neurons is weak, based on animal and human studies. Consistent brain infection after SARS-CoV-2 inoculation in mouse models is only seen when the virus entry proteins are expressed abnormally, and the timeline and progression of rare neuro-invasion in these and in other animal models points to alternative routes to the brain, other than along the olfactory projections. COVID-19 patients can be assured that loss of smell does not necessarily mean that the SARS-CoV-2 virus has gained access to and has infected their brains.

Gut Microbial Dysbiosis in the Pathogenesis of Gastrointestinal Dysmotility and Metabolic Disorders.

Abstract: Of all microorganisms in the human body, the largest and most complex population resides in the gastrointestinal (GI) tract. The gut microbiota continuously adapts to the host environment and serves multiple critical functions for their hosts, including regulating host immunity, procuring energy from food, and preventing the colonization of pathogens. Mounting evidence has suggested gut microbial imbalance (dysbiosis) as a core pathophysiology in the development of GI motility and metabolic disorders, such as irritable bowel syndrome and diabetes. Current research has focused on discovering associations between these disorders and gut microbial dysbiosis; however, whether these associations are a consequence or cause is still mostly unexplored. State-of-the-art studies have investigated how gut microbes communicate with our body systems through microbiota-derived metabolites and how they are able to modulate host physiology. There is now mounting evidence that alterations in the composition of small intestinal microbes have an association with GI dysmotility and metabolic disorders. Although treatment options for gut microbial dysbiosis are currently limited, antibiotics, fecal microbiota transplantation, probiotics, and dietary interventions are currently the best options. However, treatment with broad-spectrum antibiotics has been viewed with skepticism due to the risk of developing antibiotic resistant bacteria. Studies are warranted to elucidate the cellular and molecular pathways underlying gut microbiota-host crosstalk and for the development of a powerful platform for future therapeutic approaches. Here, we review recent literature on gut microbial alterations and/or interactions involved in the pathophysiology of GI dysmotility and metabolic disorders.

Multiscale Structural Modulation of Anisotropic Graphene Framework for Polymer Composites Achieving Highly Efficient Thermal Energy Management.

Abstract: Graphene is usually embedded into polymer matrices for the development of thermally conductive composites, preferably forming an interconnected and anisotropic framework. Currently, the directional self-assembly of exfoliated graphene sheets is demonstrated to be the most effective way to synthesize anisotropic graphene frameworks. However, achieving a thermal conductivity enhancement (TCE) over 1500% with per 1 vol% graphene content in polymer matrices remains challenging, due to the high junction thermal resistance between the adjacent graphene sheets within the self-assembled graphene framework. Here, a multiscale structural modulation strategy for obtaining highly ordered structure of graphene framework and simultaneously reducing the junction thermal resistance is demonstrated. The resultant anisotropic framework contributes to the polymer composites with a record-high thermal conductivity of 56.8-62.4 W m-1 K-1 at the graphene loading of ≈13.3 vol%, giving an ultrahigh TCE per 1 vol% graphene over 2400%. Furthermore, thermal energy management applications of the composites as phase change materials for solar-thermal energy conversion and as thermal interface materials for electronic device cooling are demonstrated. The finding provides valuable guidance for designing high-performance thermally conductive composites and raises their possibility for practical use in thermal energy storage and thermal management of electronics.

From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?

Abstract: Dissolved oxygen (DO) reflects river metabolic pulses and is an essential water quality measure. Our capabilities of forecasting DO however remain elusive. Water quality data, specifically DO data here, often have large gaps and sparse areal and temporal coverage. Earth surface and hydrometeorology data, on the other hand, have become largely available. Here we ask: can a Long Short-Term Memory (LSTM) model learn about river DO dynamics from sparse DO and intensive (daily) hydrometeorology data? We used CAMELS-chem, a new data set with DO concentrations from 236 minimally disturbed watersheds across the U.S. The model generally learns the theory of DO solubility and captures its decreasing trend with increasing water temperature. It exhibits the potential of predicting DO in "chemically ungauged basins", defined as basins without any measurements of DO and broadly water quality in general. The model however misses some DO peaks and troughs when in-stream biogeochemical processes become important. Surprisingly, the model does not perform better where more data are available. Instead, it performs better in basins with low variations of streamflow and DO, high runoff-ratio (>0.45), and winter precipitation peaks. Results here suggest that more data collections at DO peaks and troughs and in sparsely monitored areas are essential to overcome the issue of data scarcity, an outstanding challenge in the water quality community.

A comprehensive survey of regulatory network inference methods using single-cell RNA sequencing data.

Abstract: Gene regulatory network is a complicated set of interactions between genetic materials, which dictates how cells develop in living organisms and react to their surrounding environment. Robust comprehension of these interactions would help explain how cells function as well as predict their reactions to external factors. This knowledge can benefit both developmental biology and clinical research such as drug development or epidemiology research. Recently, the rapid advance of single-cell sequencing technologies, which pushed the limit of transcriptomic profiling to the individual cell level, opens up an entirely new area for regulatory network research. To exploit this new abundant source of data and take advantage of data in single-cell resolution, a number of computational methods have been proposed to uncover the interactions hidden by the averaging process in standard bulk sequencing. In this article, we review 15 such network inference methods developed for single-cell data. We discuss their underlying assumptions, inference techniques, usability, and pros and cons. In an extensive analysis using simulation, we also assess the methods' performance, sensitivity to dropout and time complexity. The main objective of this survey is to assist not only life scientists in selecting suitable methods for their data and analysis purposes but also computational scientists in developing new methods by highlighting outstanding challenges in the field that remain to be addressed in the future development.

Fewer butterflies seen by community scientists across the warming and drying landscapes of the American West

Abstract: Uncertainty remains regarding the role of anthropogenic climate change in declining insect populations, partly because our understanding of biotic response to climate is often complicated by habitat loss and degradation among other compounding stressors. We addressed this challenge by integrating expert and community scientist datasets that include decades of monitoring across more than 70 locations spanning the western United States. We found a 1.6% annual reduction in the number of individual butterflies observed over the past four decades, associated in particular with warming during fall months. The pervasive declines that we report advance our understanding of climate change impacts and suggest that a new approach is needed for butterfly conservation in the region, focused on suites of species with shared habitat or host associations.

A global agenda for advancing freshwater biodiversity research.

Abstract: Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation.

Plasma Electrolytic Oxidation (PEO) Process-Processing, Properties, and Applications.

Abstract: Plasma electrolytic oxidation (PEO) is a novel surface treatment process to produce thick, dense metal oxide coatings, especially on light metals, primarily to improve their wear and corrosion resistance. The coating manufactured from the PEO process is relatively superior to normal anodic oxidation. It is widely employed in the fields of mechanical, petrochemical, and biomedical industries, to name a few. Several investigations have been carried out to study the coating performance developed through the PEO process in the past. This review attempts to summarize and explain some of the fundamental aspects of the PEO process, mechanism of coating formation, the processing conditions that impact the process, the main characteristics of the process, the microstructures evolved in the coating, the mechanical and tribological properties of the coating, and the influence of environmental conditions on the coating process. Recently, the PEO process has also been employed to produce nanocomposite coatings by incorporating nanoparticles in the electrolyte. This review also narrates some of the recent developments in the field of nanocomposite coatings with examples and their applications. Additionally, some of the applications of the PEO coatings have been demonstrated. Moreover, the significance of the PEO process, its current trends, and its scope of future work are highlighted.

Blockchain for Future Smart Grid: A Comprehensive Survey

Abstract: The concept of smart grid has been introduced as a new vision of the conventional power grid to figure out an efficient way of integrating green and renewable energy technologies. In this way, Internet-connected smart grid, also called energy Internet, is also emerging as an innovative approach to ensure the energy from anywhere at any time. The ultimate goal of these developments is to build a sustainable society. However, integrating and coordinating a large number of growing connections can be a challenging issue for the traditional centralized grid system. Consequently, the smart grid is undergoing a transformation to the decentralized topology from its centralized form. On the other hand, blockchain has some excellent features which make it a promising application for the smart grid paradigm. In this article, we aim to provide a comprehensive survey on the application of blockchain in smart grid. As such, we identify the significant security challenges of smart grid scenarios that can be addressed by blockchain. Then, we present a number of blockchain-based recent research works presented in different literature addressing security issues in the area of smart grid. We also summarize several related practical projects, trials, and products that have emerged recently. Finally, we discuss essential research challenges and future directions of applying blockchain to smart grid security issues.

The early impacts of the COVID-19 pandemic on business sales

Abstract: COVID-19 led to a massive shutdown of businesses in the second quarter of 2020. Estimates from the Current Population Survey, for example, indicate that the number of active business owners dropped by 22% from February to April 2020. We provide the first analysis of losses in sales among the universe of businesses in California using administrative data from the California Department of Tax and Fee Administration. Losses in taxable sales average 17% in the second quarter of 2020 relative to the second quarter of 2019 even though year-over-year sales typically grow by 3-4%. We find that sales losses were largest in businesses affected by mandatory lockdowns such as accommodations, which lost 91%, whereas online sales grew by 180%. Placing business types into different categories based on whether they were considered essential or nonessential (and thus subject to early lockdowns) and whether they have a moderate or high level of person-to-person contact, we find interesting correlations between sales losses and COVID-19 cases per capita across counties in California. The results suggest that local implementation and enforcement of lockdown restrictions as safety measures for public health and voluntary behavioral responses as reactions to the perceived local COVID-19 spread both played a role. Business sales dropped by 17% on average due to the pandemic during the second quarter of 2020 in California. Accommodations lost 91% of sales, whereas online sales grew by 180%. Sales fell more steeply in counties with more COVID-19 cases. We examine how much businesses lost in sales using administrative sales tax data. The average losses of 17% in the second quarter of 2020 relative to the second quarter of 2019 occurred even though year-over-year sales typically grow by 3-4%. We find that sales losses were largest in businesses affected by mandatory lockdowns such as accommodations, drinking places, and arts, entertainment, and recreation. Distinguishing between essential and nonessential businesses, which were subject to early lockdowns, and by the level of person-to-person contact, we find that local implementation and enforcement of lockdown restrictions for public health safety and voluntary responses to the perceived local COVID-19 spread both played a role. The results suggest that small businesses may need more support from governments and consumers to mitigate the strong shift to online vendors, and that the pandemic must be brought under control as a prerequisite to a full recovery.

Global transpiration data from sap flow measurements: the SAPFLUXNET database

Abstract: . Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land–atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/ , last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository ( https://doi.org/10.5281/zenodo.3971689 ; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.

Perfusion Assessment in Left-Sided/Low Anterior Resection (PILLAR III): A Randomized, Controlled, Parallel, Multicenter Study Assessing Perfusion Outcomes With PINPOINT Near-Infrared Fluorescence Imaging in Low Anterior Resection.

Abstract: Background Indocyanine green fluoroscopy has been shown to improve anastomotic leak rates in early phase trials. Objective We hypothesized that the use of fluoroscopy to ensure anastomotic perfusion may decrease anastomotic leak following low anterior resection. Design We performed a 1:1 randomized, controlled, parallel study. Recruitment of 450-1000 patients was planned over 2-years. Setting Multicenter. Patients Patients undergoing resection defined as anastomosis within 10cm of anal verge. Intervention Patients underwent standard evaluation of tissue perfusion versus standard in conjunction with perfusion evaluation using indocyanine green fluoroscopy. Main outcome measure Primary outcome was anastomotic leak, with secondary outcomes of perfusion assessment and the rate of postoperative abscess requiring intervention. Results This study was concluded early due to decreasing accrual rates. A total of 25 centers recruited 347 patients, of which 178 were randomized to perfusion and 169 to standard. The groups had comparable tumor-specific and patient-specific demographics. Neoadjuvant chemoradiation was performed in 63.5% of perfusion and 65.7% of standard (p>0.05). Mean level of anastomosis was 5.2+3.1cm in perfusion compared to 5.2+3.3cm in standard (p>0.05). Sufficient visualization of perfusion was reported in 95.4% of patients in the perfusion group. Postoperative abscess requiring surgical management was reported in 5.7% of PFN and 4.2% of standard (p=0.75). Anastomotic leak was reported in 9.0% of perfusion compared to 9.6% of standard (p=0.37). On multivariate regression analysis, there was no difference in anastomotic leak rates between perfusion and standard (OR 0.845; 95% CI (0.375, 1.905); p=0.34). Limitations The pre-determined sample size to adequately reduce the risk of type II error was not achieved. Conclusion Successful visualization of perfusion can be achieved with ICG-F. However, no difference in anastomotic leak rates was observed between patients who underwent perfusion assessment versus standard surgical technique. In experienced hands, the addition of routine ICG-F to standard practice adds no evident clinical benefit. See Video Abstract at http://links.lww.com/DCR/B560 .

Polymer inhibitors enable >900 cm 2 dynamic windows based on reversible metal electrodeposition with high solar modulation

Abstract: Dynamic windows with adjustable tint give users control over the flow of light and heat to decrease the carbon footprint of buildings and improve the occupants’ comfort. Despite the benefits of dynamic windows, they are rarely deployed in buildings because the existing technology cannot achieve fast and colour-neutral tinting at an agreeable cost. Reversible metal electrodeposition is a promising approach to solve these problems. Here, we demonstrate the use of polymer inhibitors to reversibly deposit metal films with controlled morphology in dynamic windows. The windows that employ the polymer inhibitor can readily tint to below 0.001% visible transmittance in less than 3 min and exhibit high infrared reflectance (>70%), colour-neutral transmittance (C* 900 cm2 dynamic windows with fast response and excellent uniformity. Dynamic windows can reduce a building’s energy demand, yet the control of light and heat transmission remains challenging. Strand et al. show that polymer inhibitors improve the morphology of metal films allowing a wide modulation of light and heat flow in windows based on reversible metal electrodeposition.

Geological controls on geothermal resources for power generation

Abstract: Threats posed by the climate crisis have created an urgent need for sustainable green energy. Geothermal resources have the potential to provide up to 150 GWe of sustainable energy by 2050. However, the key challenge in successfully locating and drilling geothermal wells is to understand how the heterogeneous structure of the subsurface controls the existence of exploitable fluid reservoirs. In this Review, we discuss how key geological factors contribute to the profitable utilization of intermediate-temperature to high-temperature geothermal resources for power generation. The main driver of geothermal activity is elevated crustal heat flow, which is focused in regions of active magmatism and/or crustal thinning. Permeable structures such as faults exercise a primary control on local fluid flow patterns, with most upflow zones residing in complex fault interaction zones. Major risks in geothermal resource assessment and operation include locating sufficient permeability for fluid extraction, in addition to declining reservoir pressure and the potential of induced seismicity. Advanced computational methods permit effective integration of multiple datasets and, thus, can reduce potential risks. Future innovations involve engineered geothermal systems as well as supercritical and offshore geothermal resources, which could greatly expand the global application of geothermal energy but require detailed knowledge of the respective geological conditions. Successful discovery and operation of geothermal resources requires a thorough understanding of the heterogeneous geological subsurface. This Review discusses the key geological factors that contribute to the effective exploration of intermediate-temperature to high-temperature geothermal resources used for power generation and direct use applications.