Verifying Quantum Advantage Experiments with Multiple Amplitude Tensor Network Contraction.

The quantum supremacy experiment, such as Google Sycamore [F. Arute et al., Nature (London) 574, 505 (2019).NATUAS0028-083610.1038/s41586-019-1666-5], poses a great challenge for classical verification due to the exponentially increasing compute cost. Using a new-generation Sunway supercomputer within 8.5 d, we provide a direct verification by computing 3×10^{6} exact amplitudes for the experimentally generated bitstrings, obtaining a cross-entropy benchmarking fidelity of 0.191% (the estimated value is 0.224%). The leap of simulation capability is built on a multiple-amplitude tensor network contraction algorithm which systematically exploits the "classical advantage" (the inherent "store-and-compute" operation mode of von Neumann machines) of current supercomputers, and a fused tensor network contraction algorithm which drastically increases the compute efficiency on heterogeneous architectures. Our method has a far-reaching impact in solving quantum many-body problems, statistical problems, as well as combinatorial optimization problems.

Construction and validation of a prognostic nomogram in metastatic breast cancer patients of childbearing age: A study based on the SEER database and a Chinese cohort.

Introduction: Cancer in patients of childbearing age continues to become increasingly common. The purpose of this study was to explore the impact of metastatic breast cancer (MBC) on overall survival (OS) and cancer-specifific survival (CSS) in patients of childbearing age and to construct prognostic nomograms to predict OS and CSS. Methods: Data from MBC patients of childbearing age were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, and the patients were randomly assigned into the training and validation cohorts. Univariate and multivariate Cox analyses were used to search for independent prognostic factors impacting OS and CSS, and these data were used to construct nomograms. The concordance index (C-index), area under the curve (AUC), and calibration curves were used to determine the predictive accuracy and discriminative ability of the nomograms. Additional data were obtained from patients at the Yunnan Cancer Hospital to further verify the accuracy of the nomograms. Results: A total of 1,700 MBC patients of childbearing age were identifified from the SEER database, and an additional 92 eligible patients were enrolled at the Yunnan Cancer Hospital. Multivariate Cox analyses identifified 10 prognostic factors for OS and CSS that were used to construct the nomograms. The calibration curve for the probabilities of OS and CSS showed good agreement between nomogram prediction and clinical observations. The C-index of the nomogram for OS was 0.735 (95% CI = 0.725-0.744); the AUC at 3 years was 0.806 and 0.794 at 5 years.The nomogram predicted that the C-index of the CSS was 0.740 (95% CI = 0.730- 0.750); the AUC at 3 years was 0.811 and 0.789 at 5 years. The same results were observed in the validation cohort. Kaplan- Meier curves comparing the low-,medium-, and high-risk groups showed strong prediction results for the prognostic nomogram. Conclusion: We identifified several independent prognostic factors and constructed nomograms to predict the OS and CSS for MBC patients of childbearing age.These prognostic models should be considered in clinical practice to individualize treatments for this group of patients.

Fluxes of H2S and SO2 above a subtropical forest under natural and disturbed conditions induced by temporal land-use change.

Hydrogen sulfide (H2S) is one of predominant biogenic sulfur gases, influencing aerosol formation and climate change. There is considerable uncertainty of the global budget of H2S due to limited field data, especially in subtropical forests. In addition, an interaction between soil-emitted H2S and ambient sulfur dioxide (SO2) might exist within forest ecosystems. In this study, the aerodynamic gradient method was applied to consecutively measure H2S and SO2 fluxes above a subtropical forest canopy in Southwest China under natural and disturbed conditions induced by temporal land-use changes. The average H2S concentration and flux under natural conditions were 0.79 ± 0.07 ppbv and 0.04 ± 0.01 g S m-2 yr-1, respectively. The emission was larger than that in most croplands and freshwater wetlands. Vegetation emissions might account for about 26% of the total forest H2S emissions at this site. The deposition of SO2 was likely balanced by H2S oxidization under the forest canopy, with the mean concentration and net flux as 1.23 ± 0.11 ppbv and -0.03 ± 0.10 g S m-2 yr-1, respectively. Under disturbed conditions with soils excavation and scattering on the forest floor, simultaneously high emissions of H2S and SO2 were observed above the canopy, reaching 5.78 ± 0.16 and 1.60 ± 0.87 g S m-2 yr-1, respectively. This suggested that land-use change in subtropical forests might lead to release of legacy S in subsoils to the atmosphere in the form of H2S and SO2. Regarding the widely documented large S accumulation and expanding deforestation across subtropical forests, potentially high emissions of H2S and SO2 from subtropical forests should be carefully considered in regional air quality control and forest management.

Reducing human pressure on farmland could rescue China's declining wintering geese.

BACKGROUND: While goose populations worldwide benefit from food provided by farmland, China's threatened wintering goose populations have failed to capitalize on farmland. It has been proposed that, due to an exceptionally intense human pressure on Chinese farmland, geese cannot exploit farmland in their wintering sites and hence are confined to their deteriorating natural habitat. If this were true, locally decreasing this human pressure on farmland 'refuges' would represent a promising conservation measure. METHODS: We investigate habitat use of two declining migratory goose species in their core wintering (Yangtze River Floodplain) and stopover (Northeast China Plain) regions, compare the human pressure level at both regions, and adopt a mixed-effect resource selection function model to test how human pressure, food resource type (farmland or wetland/grass), distance to roosts, and their interaction terms influence the utilization of food resources for each species and region. To this aim we use satellite tracking of 28 tundra bean geese Anser serrirostris and 55 greater white-fronted geese A. albifrons, a newly produced 30 m land cover map, and the terrestrial human footprint map. RESULTS: Geese use farmland intensively at their stopover site, but hardly at their wintering site, though both regions have farmland available at a similar proportion. The human pressure on both farmland and wetland/grass is significantly lower at the stopover region compared to the wintering region. At both sites, the two goose species actively select for farmland and/or wetland/grass with a relatively low human pressure, positioned relatively close to their roosting sites. CONCLUSIONS: Our findings suggest that if human pressure were to decrease in the farmlands close to the roost, China's wintering geese could benefit from farmland. We recommend setting aside farmland near roosting sites that already experiences a relatively low human pressure as goose refuges, and adopt measures to further reduce human pressure and increase food quality and quantity, to help counter the decline of China's wintering goose populations. Our study has important conservation implications and offers a practical measure for migratory waterfowl conservation in areas of high human-wildlife conflict.

Identifying the Characteristics of Promising Renewable Replacement Chemicals.

Although several "renewable" strategies have been recently proposed to produce high-volume as well as new (replacement) chemicals, the identification of good targets for such strategies remains challenging. Such chemicals that are expensive to obtain today from fossil fuel feedstocks would have an advantage if produced cheaply using alternative methods in the future. In this work we identify the characteristics of such potentially promising replacement chemicals. We also identify the characteristic of promising bio-based replacement chemicals that are relatively easy to obtain through bio-conversions. This work provides insights into the development of renewable chemicals to support a sustainable economy.

Synthesis and techno-economic assessment of microbial-based processes for terpenes production.

BACKGROUND: Recent advances in metabolic engineering enable the production of chemicals from sugars through microbial bio-conversion. Terpenes have attracted substantial attention due to their relatively high prices and wide applications in different industries. To this end, we synthesize and assess processes for microbial production of terpenes. RESULTS: To explain a counterintuitive experimental phenomenon where terpenes such as limonene (normal boiling point 176 °C) are often found to be 100% present in the vapor phase after bio-conversion (operating at only ~ 30 °C), we first analyze the vapor-liquid equilibrium for systems containing terpenes. Then, we propose alternative production configurations, which are further studied, using limonene as an example, in several case studies. Next, we perform economic assessment of the alternative processes and identify the major cost components. Finally, we extend the assessment to account for different process parameters, terpene products, ways to address terpene toxicity (microbial engineering vs. solvent use), and cellulosic biomass as a feedstock. We identify the key cost drivers to be (1) feed glucose concentration (wt%), (2) product yield (% of maximum theoretical yield) and (3) VVM (Volume of air per Volume of broth liquid per Minute, i.e., aeration rate in min-1). The production of limonene, based on current experimental data, is found to be economically infeasible (production cost ~ 465 $/kg vs. market selling price ~ 7 $/kg), but higher glucose concentration and yield can lower the cost. Among 12 terpenes studied, limonene appears to be the most reasonable short-term target because of its large market size (~ 160 million $/year in the US) and the relatively easier to achieve break-even yield (~ 30%, assuming a 14 wt% feed glucose concentration and 0.1 min-1 VVM). CONCLUSIONS: The methods proposed in this work are applicable to a range of terpenes as well as other extracellular insoluble chemicals with density lower than that of water, such as fatty acids. The results provide guidance for future research in metabolic engineering toward terpenes production in terms of setting targets for key design parameters.

A framework for the identification of promising bio-based chemicals.

Recent progress in metabolic engineering and synthetic biology enables the use of microorganisms for the production of chemicals-"bio-based chemicals." However, it is still unclear which chemicals have the highest economic prospect. To this end, we develop a framework for the identification of such promising ones. Specifically, we first develop a genome-scale constraint-based metabolic modeling approach, which is used to identify a candidate pool of 209 chemicals (together with the estimated yield, productivity, and residence time for each) from the intersection of the high-production-volume chemicals and the KEGG and MetaCyc databases. Second, we design three screening criteria based on a chemical's profit margin, market volume, and market size. The total process cost, including the downstream separation cost, is systematically incorporated into the evaluation. Third, given the three aforementioned criteria, we identify 32 products as economically promising if the maximum yields can be achieved, and 22 products if the maximum productivities can be achieved. The breakeven titer that renders zero profit margin for each product is also presented. Comparisons between extracellular and intracellular production, as well as Escherichia coli and Saccharomyces cerevisiae systems are also discussed. The proposed framework provides important guidance for future studies in the production of bio-based chemicals. It is also flexible in that the databases, yield estimations, and criteria can be modified to customize the screening.

Sequencing-based network analysis provides a core set of gene resource for understanding kidney immune response against Edwardsiella tarda infection in Japanese flounder.

Marine organisms are under a frequent threat from various pathogens. Edwardsiella tarda is one of the major fish pathogens infecting both cultured and wild fish species. It can also infect a variety of other vertebrates, including amphibians, reptiles, and mammals, and bacteremia caused by E. tarda can be fatal in humans. The kidney is the largest lymphoid organ in fish, and generating kidney transcriptomic information under different stresses is crucial for understanding molecular mechanisms underlying the immune responses in the kidneys. In this study, we performed transcriptome-wide gene expression profiling of the Japanese flounder (Paralichthys olivaceus) challenged by 8 and 48 h of E. tarda infection. An average of 40 million clean reads per library was obtained, and approximately 81.6% of these reads were successfully mapped to the reference genome. In addition, 1319 and 4439 differentially expressed genes (DEGs) were found at 8 and 48 h post-injection, respectively. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to search immune-related DEGs. A protein-protein interaction network was constructed to ascertain the relationship between interacting immune genes during pathogen-induced stress. Based on the KEGG and protein association networks analysis, 24 hub genes were discovered and validated by qRT-PCR. To our knowledge, this study is the first to represent the kidney transcriptome analysis based on protein-protein interaction networks in fish. Our results provide valuable gene resources for further research on kidney immune response in fish, which can significantly improve our understanding of the molecular mechanisms underlying the immune response to E. tarda in humans and other vertebrates.

Synthesis and analysis of separation networks for the recovery of intracellular chemicals generated from microbial-based conversions.

BACKGROUND: Bioseparations can contribute to more than 70% in the total production cost of a bio-based chemical, and if the desired chemical is localized intracellularly, there can be additional challenges associated with its recovery. Based on the properties of the desired chemical and other components in the stream, there can be multiple feasible options for product recovery. These options are composed of several alternative technologies, performing similar tasks. The suitability of a technology for a particular chemical depends on (1) its performance parameters, such as separation efficiency; (2) cost or amount of added separating agent; (3) properties of the bioreactor effluent (e.g., biomass titer, product content); and (4) final product specifications. Our goal is to first synthesize alternative separation options and then analyze how technology selection affects the overall process economics. To achieve this, we propose an optimization-based framework that helps in identifying the critical technologies and parameters. RESULTS: We study the separation networks for two representative classes of chemicals based on their properties. The separation network is divided into three stages: cell and product isolation (stage I), product concentration (II), and product purification and refining (III). Each stage exploits differences in specific product properties for achieving the desired product quality. The cost contribution analysis for the two cases (intracellular insoluble and intracellular soluble) reveals that stage I is the key cost contributor (>70% of the overall cost). Further analysis suggests that changes in input conditions and technology performance parameters lead to new designs primarily in stage I. CONCLUSIONS: The proposed framework provides significant insights for technology selection and assists in making informed decisions regarding technologies that should be used in combination for a given set of stream/product properties and final output specifications. Additionally, the parametric sensitivity provides an opportunity to make crucial design and selection decisions in a comprehensive and rational manner. This will prove valuable in the selection of chemicals to be produced using bioconversions (bioproducts) as well as in creating better bioseparation flow sheets for detailed economic assessment and process implementation on the commercial scale.

A roadmap for the synthesis of separation networks for the recovery of bio-based chemicals: Matching biological and process feasibility.

Microbial conversion of renewable feedstocks to high-value chemicals is an attractive alternative to current petrochemical processes because it offers the potential to reduce net CO2 emissions and integrate with bioremediation objectives. Microbes have been genetically engineered to produce a growing number of high-value chemicals in sufficient titer, rate, and yield from renewable feedstocks. However, high-yield bioconversion is only one aspect of an economically viable process. Separation of biologically synthesized chemicals from process streams is a major challenge that can contribute to >70% of the total production costs. Thus, process feasibility is dependent upon the efficient selection of separation technologies. This selection is dependent on upstream processing or biological parameters, such as microbial species, product titer and yield, and localization. Our goal is to present a roadmap for selection of appropriate technologies and generation of separation schemes for efficient recovery of bio-based chemicals by utilizing information from upstream processing, separation science and commercial requirements. To achieve this, we use a separation system comprising of three stages: (I) cell and product isolation, (II) product concentration, and (III) product purification and refinement. In each stage, we review the technology alternatives available for different tasks in terms of separation principles, important operating conditions, performance parameters, advantages and disadvantages. We generate separation schemes based on product localization and its solubility in water, the two most distinguishing properties. Subsequently, we present ideas for simplification of these schemes based on additional properties, such as physical state, density, volatility, and intended use. This simplification selectively narrows down the technology options and can be used for systematic process synthesis and optimal recovery of bio-based chemicals.

Endotoxins: The Critical Risk Factor in Reclaimed Water via Inhalation Exposure.

The use of reclaimed water for nonpotable uses requires consideration of potential adverse health effects. Considering that inhalation can be a significant route of transmission of microorganisms and inflammatory agents, this study used a mouse model to test the possible adverse effects of reclaimed water use during car washing where aerosols are generated. Intensive innate immune responses were found in the lungs after acute exposure, and the lavage polymorphonuclear cell proportion was the most sensitive end point. Four types of evidence are presented to demonstrate that the main risk factor that initiates innate inflammation is the free endotoxin. (1) Small molecules (<10 kDa) cannot induce inflammation. (2) The endotoxin levels of 11 water samples from five different plants showed positive correlations with inflammatory responses. (3) Actual water samples showed similar activities with free endotoxins other than bacterially bound endotoxins. (4) Specific removal of endotoxins with polymyxin B affinity chromatography further confirmed the role of free endotoxins. It is noteworthy that 62.9% of the investigated tertiary-treated water had endotoxin levels higher than the allowable acute threshold (120 endotoxin units/mL) under the hypothesized car wash condition, which strongly suggests the need to carefully consider the water treatment steps required to produce safe water for various reclaimed water end uses.

Exploring the structure determinants of pyrazinone derivatives as PDE5 3HC8 inhibitors: an in silico analysis.

Phosphodiesterase type 5 (PDE5) inhibitors are clinically indicated for the treatment of erectile dysfunction, pulmonary hypertension and various other diseases. In this work, both ligand- and receptor-based three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques on 122 pyrazinone derivatives as PDE inhibitors. The resultant optimum 3D-QSAR model exhibits a proper predictive ability as indicated by the statistical results of Q² of 0.584, R(ncv)² of 0.884 and R(pre)² of 0.817, respectively. In addition, docking analysis and molecular dynamics (MD) simulation were also applied to elucidate the probable binding modes of these inhibitors. Our main findings are: (1) Introduction of bulky, electropositive and hydrophobic substituents at 12- and 19-positions can increase the biological activities. (2) N atom at 8-position is detrimental to the inhibitor activity, and the effect of N atoms at 5- and 6-positions on compound activity is co-determined by both the hydrophobic force and the π-π stacking interaction. (3) Bulky and hydrophilic substitutions are favored at the 27-position of ring D. (4) Electronegative and hydrophilic substitutions around 5- and 6-positions increase the inhibitory activity. (5) Hydrophobic forces and π-π stacking interaction with Phe786 and Phe820 are crucial in determining the binding of pyrazinone derivatives to PDE5. (6) Bulky substitutions around ring C favors selectivity against PDE11, while bulky groups near the 21-position disfavor the selectivity. The information obtained from this work can be utilized to accurately predict the binding affinity of related analogues and also facilitate future rational designs of novel PDE5 inhibitors with improved activity and selectivity.