Search

Slag viscosity effect the physical and chemical process of the converter.In the paper, thermodynamic calculations and interruption experiments are carried out to explore the slag viscosity and phase translated. With the increase of new components Al2O3 and TiO2, the viscosity is decreased. According to experiment result, the low-basicity slag is in molten state except for a small amount of SiO2,and the SiO2, Al2O3 and Fe2O3 are not melted in the high-basicity slag. Thus the reasonable basicity should be controlled at 2,4 ~ 3,2 at 1 500°C.

Stable L12 structured Cr3Cu precipitates were determined in a Cu-4.06Cr-1.25Nb alloy rather than b.c.c. structured Cr precipitates by transmission electron microscope (TEM) and three-dimension atom probe tomography (3DAP) at 450 oC. The precipitation sequence of the studied alloy aged at 400 oC was supersaturated solid solution → f.c.c. Cr phase → Cr3Cu phase (L12). Nb atoms would segregate in the interface between the Cu and Cr phase, reduce the Cu/Cr interfacial energy, affect the precipitation, growth, phase transformation, and coarsening of the precipitate. These Cr3Cu precipitates significantly improved the high-temperature strength of the Cu-Cr-Nb alloy (223 ± 5 MPa at 500 oC).

Abstract We report the first measurement of the absolute branching fraction of the inclusive decay $$\Lambda _c^+ \rightarrow K_S^0X$$ Λ c + → K S 0 X . The analysis is performed using an $$e^+e^-$$ e + e - collision data sample corresponding to an integrated luminosity of 567 $$\hbox {pb}^{-1}$$ pb - 1 taken at $$\sqrt{s}$$ s = 4.6 GeV with the BESIII detector. Using eleven Cabibbo-favored $${\bar{\Lambda }}_c^-$$ Λ ¯ c - decay modes and the double-tag technique, this absolute branching fraction is measured to be $${\mathcal {B}}(\Lambda _c^+ \rightarrow K_S^0X)=(9.9\pm 0.6\pm 0.4)\%$$ B ( Λ c + → K S 0 X ) = ( 9.9 ± 0.6 ± 0.4 ) % , where the first uncertainty is statistical and the second systematic. The relative deviation between the branching fractions for the inclusive decay and the observed exclusive decays is $$(18.7\pm 8.3)\%$$ ( 18.7 ± 8.3 ) % , which indicates that there may be some unobserved decay modes with a neutron or excited baryons in the final state.

Abstract Using a sample of $$1.31\times 10^{9} ~J/\psi $$ 1.31×109J/ψ events collected with the BESIII detector, we perform a study of $$J/\psi \rightarrow \gamma K{\bar{K}}\eta '$$ J/ψ→γKK¯η′ . X(2370) is observed in the $$K{\bar{K}}\eta '$$ KK¯η′ invariant-mass distribution with a statistical significance of $$8.3\sigma $$ 8.3σ . Its resonance parameters are measured to be $$M=2341.6\pm 6.5 \, \text {(stat.)} \pm 5.7 \, \text {(syst.)}~ \hbox {MeV}/c^{2}$$ M=2341.6±6.5(stat.)±5.7(syst.)MeV/c2 and $$\Gamma = 117\pm 10 \, \text {(stat.)}\pm 8 \, \text {(syst.)}~\hbox {MeV}$$ Γ=117±10(stat.)±8(syst.)MeV . The product branching fractions for $$J/\psi \rightarrow \gamma X(2370),X(2370)\rightarrow K^{+}K^{-}\eta '$$ J/ψ→γX(2370),X(2370)→K+K-η′ and $$J/\psi \rightarrow \gamma X(2370),X(2370)\rightarrow K_{S}^{0}K_{S}^{0}\eta '$$ J/ψ→γX(2370),X(2370)→KS0KS0η′ are determined to be $$(1.79\pm 0.23\, \text {(stat.)}\pm 0.65\,\text {(syst.)})\times 10^{-5}$$ (1.79±0.23(stat.)±0.65(syst.))×10-5 and $$(1.18\pm 0.32\, \text {(stat.)}\pm 0.39\, \text {(syst.)})\times 10^{-5}$$ (1.18±0.32(stat.)±0.39(syst.))×10-5 , respectively. No evident signal for X(2120) is observed in the $$K{\bar{K}}\eta '$$ KK¯η′ invariant-mass distribution. The upper limits for the product branching fractions of $${\mathcal {B}}(J/\psi \rightarrow \gamma X(2120)\rightarrow \gamma K^{+} K^{-} \eta ')$$ B(J/ψ→γX(2120)→γK+K-η′) and $${\mathcal {B}}(J/\psi \rightarrow \gamma X(2120)\rightarrow \gamma K_{S}^{0} K_{S}^{0} \eta ')$$ B(J/ψ→γX(2120)→γKS0KS0η′) are determined to be $$1.49\times 10^{-5}$$ 1.49×10-5 and $$6.38\times 10^{-6}$$ 6.38×10-6 at the 90% confidence level, respectively.

Abstract We measure the branching fractions for seven D s + $$ {D}_s^{+} $$ two-body decays to pseudo-scalar mesons, by analyzing data collected at s $$ \sqrt{s} $$ = 4.178 ∼ 4.226 GeV with the BESIII detector at the BEPCII collider. The branching fractions are determined to be B D s + → K + η ' = 2.68 ± 0.17 ± 0.17 ± 0.08 × 10 − 3 , B D s + → η ' π + = 37.8 ± 0.4 ± 2.1 ± 1.2 × 10 − 3 , B D s + → K + η = 1.62 ± 0.10 ± 0.03 ± 0.05 × 10 − 3 , B D s + → η π + = 17.41 ± 0.18 ± 0.27 ± 0.54 × 10 − 3 , B D s + → K + K S 0 = 15.02 ± 0.10 ± 0.27 ± 0.47 × 10 − 3 , B D s + → K S 0 π + = 1.109 ± 0.034 ± 0.023 ± 0.035 × 10 − 3 , B D s + → K + π 0 = 0.748 ± 0.049 ± 0.018 ± 0.035 × 10 − 3 , $$ {\displaystyle \begin{array}{c}\mathcal{B}\left({D}_s^{+}\to {K}^{+}\eta \hbox{'}\right)=\left(2.68\pm 0.17\pm 0.17\pm 0.08\right)\times {10}^{-3},\\ {}\mathcal{B}\left({D}_s^{+}\to \eta \hbox{'}{\pi}^{+}\right)=\left(37.8\pm 0.4\pm 2.1\pm 1.2\right)\times {10}^{-3},\\ {}\mathcal{B}\left({D}_s^{+}\to {K}^{+}\eta \right)=\left(1.62\pm 0.10\pm 0.03\pm 0.05\right)\times {10}^{-3},\\ {}\mathcal{B}\left({D}_s^{+}\to \eta {\pi}^{+}\right)=\left(17.41\pm 0.18\pm 0.27\pm 0.54\right)\times {10}^{-3},\\ {}\mathcal{B}\left({D}_s^{+}\to {K}^{+}{K}_S^0\right)=\left(15.02\pm 0.10\pm 0.27\pm 0.47\right)\times {10}^{-3},\\ {}\mathcal{B}\left({D}_s^{+}\to {K}_S^0{\pi}^{+}\right)=\left(1.109\pm 0.034\pm 0.023\pm 0.035\right)\times {10}^{-3},\\ {}\mathcal{B}\left({D}_s^{+}\to {K}^{+}{\pi}^0\right)=\left(0.748\pm 0.049\pm 0.018\pm 0.035\right)\times {10}^{-3},\end{array}} $$ where the first uncertainties are statistical, the second are systematic, and the third are from external input branching fraction of the normalization mode D s + $$ {D}_s^{+} $$ → K + K − π +. Precision of our measurements is significantly improved compared with that of the current world average values.

Aluminum-doped zinc oxide (AZO) films were prepared by radio-frequency magnetron sputtering from powder target, and the photo-electric properties of the films were tuned by the electrical and chemical interactions. The microstructure and photo-electrical properties of the films were characterized by Raman spectroscopy, X-ray diffraction (XRD), UV-visible spectrophotometer and Hall Effect apparatus. The results show both resistivity and transmittance of the AZO film treated under the electrical and chemical action decrease as the pH of the electrolyte decreases. At pH = 5, the photo-electric property of the treated AZO film is the most excellent. The resistivity is reduced to 3,7×10-3 Ω・cm from 7,1×10-1 Ω・cm of the as-prepared AZO film, and the transmittance is reduced to 90,1 % from 91,3 % of the as-prepared AZO film.

Aluminum (Al) toxicity in acidic soils is a major factor restricting crop production. Although the molecular mechanisms of Al responses have been extensively investigated, microRNA (miRNA) mediated differential Al tolerance in different soybean genotypes remains largely unknown. In this study, two soybean [Glycine max (L.) Merr.] genotypes, Al-tolerant BX10 and Al-sensitive BD2, were treated with 0 and 50 μM AlCl3 and then used to construct the miRNA libraries for deep sequencing. Results revealed 453 miRNAs, whose expression patterns were affected by Al stress. We also identified 32 differentially expressed miRNAs: 19 in BX10, 7 in BD2, and 6 in both genotypes. The gene ontology analysis of their putative target genes indicated that stress-responsive genes and amino-acid-metabolism-related processes preferentially existed in BX10. Comprehensive analysis demonstrated that conserved miRNAs, such as gma-miR166k/o, gma-miR390g, and gma-miR396c/k, mediated root elongation in BX10, whereas gma-miR169r triggered oxidative stress in BD2. These processes could be regarded as important mechanisms conferring differential Al tolerance in BX10 and BD2. This study provided new insights into different Al response mechanisms in various soybean genotypes.

We previously reported that LeMYB1 might be a crucial transcription factor in regulating shikonin formation in Lithospermum erythrorhizon. In this study, by overexpressing LeMYB1 under the control of CaMV35S promoter in L. erythrorhizon hairy roots, we further clarified the role of LeMYB1 in the shikonin formation and its regulation. The LeMYB1-overexpressing transgenic hairy roots were successfully induced by infecting seedling nodes with Agrobacterium rhizogenes strain ATCC15834 that carried the pBI121-LeMYB1 vector. The LeMYB1 transcripts were significantly up-regulated in the transgenic hairy root lines compared with the wild type lines, and the total content of shikonin and its derivatives was dramatically enhanced by the LeMYB1 overexpression. Real-time PCR results reveal that the enhanced shikonin biosynthesis in the overexpressing lines were mainly caused by a highly up-regulated expression of genes coding key enzymes (PAL, HMGR, and PGT) and key regulators (LeDI-2 and LePS-2) involved in the shikonin biosynthesis. Overall, our results suggest that LeMYB1 plays a positive role in regulating the shikonin biosynthesis in L. erythrorhizon.

Three types of post-weld heat treatment (PWHT), i.e. solution treatment + primary aging + secondary aging (I), secondary aging (II), and primary aging + secondary aging (III), were applied to a single crystal nickel-based superalloy joint made with linear friction welding (LFW). The results show that the grains in the thermomechanically affected zone (TMAZ) coarsen seriously and the primary γ' phase in the TMAZ precipitates unevenly after PWHT I. The primary γ' phase in the TMAZ and weld zone (WZ) precipitates insufficiently and fine granular secondary γ' phase is observed in the matrix after PWHT II. After PWHT III, the primary γ' phase precipitates more sufficiently and evenly compared to PWHTs I and II. Moreover, the grains in the TMAZ have not coarsened seriously and fine granular secondary γ' phase is not found after PWHT III. PWHT III seems more suitable to the LFWed single crystal nickel-based superalloy joints when performing PWHT.

Museum studies, is the study of museums, museum curation, and how and why museums developed into their institutional role in education and culture through scientific, social, political and other related forces. The purpose of this study is to shed light on the application trends of the international literature related to museum studies on the SCIE, SSCI, and AHCI databases between 1995 and 2014 using a bibliometric technique and citation analysis. The results of this study reveal that influences of the literature related to museum studies on other subject areas continue to expand. Considering the publication of major countries, subject areas, journal and institutions, the results also discussed that the future trend through analysing most cited articles. Moreover, 12 core journal lists are identified by Bradford’s law.

MYB transcription factors (TFs) are known to have important functions in regulating the biosynthesis of secondary metabolites in plants. In this study, LeMYB1, a member of the MYB gene family of Lithospermum erythrorhizon, was cloned via the rapid amplification of cDNA ends. The alignment of the predicted translations of LeMYB1 with other MYB proteins revealed that LeMYB1 contained an N-terminal R2R3 repeat and a high degree of amino acid identity to NtMYBJS1 which is involved in jasmonic acid signalling and phenylpropanoid biosynthetic pathway regulation. To determine the expression pattern of LeMYB1, its promoter was cloned and the sequence analysis was performed. The results revealed a number of potential regulatory motifs related to tissue-specific gene expression and abiotic and biotic stress responses. Real-time PCR results suggest that LeMYB1 was induced transiently during the early stage when L. erythrorhizon cells were transferred from a B5 growth medium to a M9 production medium for shikonin formation. Exogenous methyl jasmonate (MeJA), an effective inducer of shikonin biosynthesis, induced the rapid LeMYB1 expression. In contrast, a treatment with ibuprofen (IBU), an inhibitor of jasmonate biosynthesis, significantly inhibited the LeMYB1 expression. Another inhibitor of shikonin formation, 2,4-dichlorophenoxyacetic acid (2,4-D), also markedly repressed the expression of LeMYB1. Tissue-specific expression analysis showed that LeMYB1 mRNA was predominantly accumulated in roots where shikonin was synthesized. Thus, the LeMYB1 gene may be a valuable member of the R2R3-MYB family in L. erythrorhizon and is possibly involved in the regulation of shikonin biosynthesis.

There is growing evidence that, corresponding to global dimming and brightening, surface solar radiation and sunshine hours over China have undergone decadal fluctuations during the 1960s–2000s. The results of a number of these analyses are, however, very different. In this study, we synthesize reliable results and conclusively address recent advances and insufficiencies in studies on dimming and brightening in China. A temporally and spatially prevalent dimming trend is noted in surface solar radiation, direct solar radiation and sunshine hours since the 1960s. Meanwhile, the changing trend in diffuse solar radiation is less pronounced. Increasing anthropogenic aerosol loading is regarded as the most plausible explanation for China's dimming. The brightening trend since 1990, which mainly occurs in southeastern China and in the spring season, is weak and insignificant. The reverse in the solar radiation trend is associated with climate change by cloud suppression and slowdown in anthropogenic emissions. The future solar radiation trend in China could largely depend on the development of air quality control. Other potential driving factors such as wind speed, water vapor and surface albedo are also non-negligible in specific regions of China. Hydrological implications of dimming and brightening in China lack systematic investigation. However, the fact that solar radiation and pan evaporation trends in China track a similar curve in 1990 further suggests that the pan evaporation paradox could be partly resolved by changes in solar radiation.

This study analyzed the variability in the number of rainfall events related to debris-flow occurrence in the Chenyulan stream watershed located in central Taiwan. Rainfall data between 1970 and 2009 measured at three meteorological stations nearby/in the watershed were collected and used to determine the corresponding regional average rainfall for the watershed. Data on debris-flow events between 1985 and 2009 were collected and used to study their dependence on regional average rainfall. The maximum 24-h regional rainfall Rd was used to analyze the number of rainfall events Nr, the number of rainfall events that triggered debris flows Nd, and the probability of debris-flows occurrences P. The variation trends in Nr, Nd and P over recent decades under three rainfall conditions (Rd > 20, 230, and 580 mm) related to debris-flow occurrence were analyzed. In addition, the influences of the Chi-Chi earthquake on Nd and P were presented. The results showed that the rainfall events with Rd > 20 mm during the earthquake-affected period (2000–2004) strongly responded to the increases in the average number of rainfall events that triggered debris flows and the average probability of debris-flows occurrences. The number of rainfall events with Rd > 230 mm (the lower boundary for the rainfall ever triggering debris flow before the Chi-Chi earthquake), and Rd > 580 mm (the lower boundary for extreme rainfall ever triggering numerous debris flows) in the Chenyulan stream watershed increased after 2000. The increase in the number of extreme rainfall events with Rd > 580 mm augmented the number of rainfall events ever triggering numerous debris flows in the last decade. The increase in both the number of rainfall events that ever triggered debris flows and the probability of debris-flow occurrences was greater in the last decade (2000–2009) than in 1990–1999.

On 7 August 2010, catastrophic debris flows were triggered by a rainstorm in the catchments of the Sanyanyu and Luojiayu torrents, Zhouqu County, Gansu Province northwestern China. These two debris flows originated shortly after a rainstorm with an intensity of 77.3 mm h−1 and transported a total volume of about 2.2 million m3, which was deposited on an existing debris fan and into a river. This catastrophic event killed 1765 people living on this densely urbanised fan. The poorly sorted sediment contains boulders up to 3–4 m in diameter. In this study, the geomorphological features of both debris flow catchment areas are analyzed based on the interpretation of high-resolution remote sensing imagery combined with field investigation. The characteristics of the triggering rainfall and the initiation of the debris flow occurrence are discussed. Using empirical equations, the peak velocities and discharges of the debris flows were estimated to be around 9.7 m s−1 and 1358 m3 s−1 for the Sanyanyu torrent and 11 m s−1 and 572 m3 s−1 for the Luojiayu torrent. The results of this study contribute to a better understanding of the conditions leading to catastrophic debris flow events.

Passive safety systems have been widely applied to advanced water-cooled reactors, to enhance the safety of nuclear power plants. The ambitious program of the nuclear power development in China requires reactor concepts with high safety level. For the near-term and medium-term, the Chinese government decided for advanced pressurized water reactors with an extensive usage of passive safety systems. This paper describes some important criteria and the development program of the Chinese large-scale pressurized water reactors. An overview on representative research activities and results achieved so far on passive safety systems in various institutions is presented.

Abstract The recent emergence of multi-sample multi-condition single-cell multi-cohort studies allows researchers to investigate different cell states. The effective integration of multiple large-cohort studies promises biological insights into cells under different conditions that individual studies cannot provide. Here, we present scMerge2, a scalable algorithm that allows data integration of atlas-scale multi-sample multi-condition single-cell studies. We have generalized scMerge2 to enable the merging of millions of cells from single-cell studies generated by various single-cell technologies. Using a large COVID-19 data collection with over five million cells from 1000+ individuals, we demonstrate that scMerge2 enables multi-sample multi-condition scRNA-seq data integration from multiple cohorts and reveals signatures derived from cell-type expression that are more accurate in discriminating disease progression. Further, we demonstrate that scMerge2 can remove dataset variability in CyTOF, imaging mass cytometry and CITE-seq experiments, demonstrating its applicability to a broad spectrum of single-cell profiling technologies.

Abstract Background Unrevealing the interplay between diet, the microbiome, and the health state could enable the design of personalized intervention strategies and improve the health and well-being of individuals. A common approach to this is to divide the study population into smaller cohorts based on dietary preferences in the hope of identifying specific microbial signatures. However, classification of patients based solely on diet is unlikely to reflect the microbiome-host health relationship or the taxonomic microbiome makeup. Results We present a novel approach, the Nutrition-Ecotype Mixture of Experts (NEMoE) model, for establishing associations between gut microbiota and health state that accounts for diet-specific cohort variability using a regularized mixture of experts model framework with an integrated parameter sharing strategy to ensure data-driven diet-cohort identification consistency across taxonomic levels. The success of our approach was demonstrated through a series of simulation studies, in which NEMoE showed robustness with regard to parameter selection and varying degrees of data heterogeneity. Further application to real-world microbiome data from a Parkinson’s disease cohort revealed that NEMoE is capable of not only improving predictive performance for Parkinson’s Disease but also for identifying diet-specific microbial signatures of disease. Conclusion In summary, NEMoE can be used to uncover diet-specific relationships between nutritional-ecotype and patient health and to contextualize precision nutrition for different diseases. Video Abstract

IntroductionGanshu Nuodan is a liver-protecting dietary supplement composed of Ganoderma lucidum (G. lucidum) spore powder, Pueraria montana (Lour.) Merr. (P. montana), Salvia miltiorrhiza Bunge (S. miltiorrhiza) and Astragalus membranaceus (Fisch.) Bunge. (A. membranaceus). However, its pharmacodynamic material basis and mechanism of action remain unknown.MethodsA mouse model of acute alcohol liver disease (ALD) induced by intragastric administration of 50% alcohol was used to evaluate the hepatoprotective effect of Ganshu Nuodan. The chemical constituents of Ganshu Nuodan were comprehensively identified by UPLC-QTOF/MS, and then its pharmacodynamic material basis and potential mechanism of action were explored by proteomics and network pharmacology.ResultsGanshu Nuodan could ameliorate acute ALD, which is mainly manifested in the significant reduction of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in serum and malondialdehyde (MDA) content in liver and the remarkably increase of glutathione (GSH) content and superoxide dismutase (SOD) activity in liver. Totally 76 chemical constituents were identified from Ganshu Nuodan by UPLC-QTOF/MS, including 21 quinones, 18 flavonoids, 11 organic acids, 7 terpenoids, 5 ketones, 4 sterols, 3 coumarins and 7 others. Three key signaling pathways were identified via proteomics studies, namely Arachidonic acid metabolism, Retinol metabolism, and HIF-1 signaling pathway respectively. Combined with network pharmacology and molecular docking, six key targets were subsequently obtained, including Ephx2, Lta4h, Map2k1, Stat3, Mtor and Dgat1. Finally, these six key targets and their related components were verified by molecular docking, which could explain the material basis of the hepatoprotective effect of Ganshu Nuodan.ConclusionGanshu Nuodan can protect acute alcohol-induced liver injury in mice by inhibiting oxidative stress, lipid accumulation and apoptosis. Our study provides a scientific basis for the hepatoprotective effect of Ganshu Nuodan in acute ALD mice and supports its traditional application.

IntroductionXuanhuang Pill (XHP) is a traditional Chinese medicine oral formula composed of 10 herbs. This study aims to verify the hepatoprotective activity of XHP and explain its possible mechanism.MethodsThe hepatoprotective activity of XHP was evaluated by constructing a mouse model of alcoholic liver disease, and the mechanism of XHP was preliminarily explained by utilizing ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-QTOF/MS), proteomics and network pharmacology.ResultsThe current study demonstrated that treatment with XHP ameliorated acute alcohol-induced liver injury in mice by significantly reducing alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels and triglycerides (TGs) and malondialdehyde (MDA) content. Remarkably, treatment also increased superoxide dismutase (SOD) activity and glutathione (GSH) content. UPLC-QTOF/MS, 199 compounds were identified as within the make-up of the XHP. Network pharmacology analysis showed that 103 targets regulated by 163 chemical components may play an important role in the protective liver effect mediated by XHP. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis suggest that the HIF-1, FoxO, PI3K-Akt, insulin, and thyroid hormone signaling pathways are key modulators of XHP’s effects. Finally, eight key targets including Mapk1, Mapk3, Akt1, Map2k1, Pik3ca, Pik3cg, Raf1, and Prkca were verified by molecular docking and proteomics analysis, which provide insight into the hepatoprotective effect observed with XHP treatment.ConclusionIn summary, these results improved upon knowledge of the chemical composition and the potential mechanisms of hepatoprotective action of oral XHP treatment, providing foundational support for this formulation as a viable therapeutic option for alcoholic liver disease.

GRB 230307A is an extremely bright long-duration GRB with an observed gamma-ray fluence of ≳3 × 10 ^−3 erg cm ^−2 (10–1000 keV), second only to GRB 221009A. Despite its long duration, it is possibly associated with a kilonova, thus resembling the case of GRB 211211A. In analogy with GRB 211211A, we distinguish three phases in the prompt gamma-ray emission of GRB 230307A: an initial short duration, spectrally soft emission; a main long duration, spectrally hard burst; and a temporally extended and spectrally soft tail. We interpret the initial soft pulse as a bright precursor to the main burst and compare its properties with models of precursors from compact binary mergers. We find that to explain the brightness of GRB 230307A, a magnetar-like (≳10 ^15 G) magnetic field should be retained by the progenitor neutron star. Alternatively, in the postmerger scenario, the luminous precursor could point to the formation of a rapidly rotating massive neutron star.

COVID-19 patients display a wide range of disease severity, ranging from asymptomatic to critical symptoms with high mortality risk. Our ability to understand the interaction of SARS-CoV-2 infected cells within the lung, and of protective or dysfunctional immune responses to the virus, is critical to effectively treat these patients. Currently, our understanding of cell-cell interactions across different disease states, and how such interactions may drive pathogenic outcomes, is incomplete. Here, we developed a generalizable and scalable workflow for identifying cells that are differentially interacting across COVID-19 patients with distinct disease outcomes and use this to examine eight public single-cell RNA-seq datasets (six from peripheral blood mononuclear cells, one from bronchoalveolar lavage and one from nasopharyngeal), with a total of 211 individual samples. By characterizing the cell-cell interaction patterns across epithelial and immune cells in lung tissues for patients with varying disease severity, we illustrate diverse communication patterns across individuals, and discover heterogeneous communication patterns among moderate and severe patients. We further illustrate patterns derived from cell-cell interactions are potential signatures for discriminating between moderate and severe patients. Overall, this workflow can be generalized and scaled to combine multiple scRNA-seq datasets to uncover cell-cell interactions. Author summary Despite the availability of several studies of single-cell transcriptomics profiles from different geographic locations, our knowledge of cell-cell interactions across distinct disease states and how such interactions may drive pathogenic outcomes remains limited. Motivated by the need to gain insights into health and disease and to address challenges associated with the compilation and exploration of multiple large-scale data, we developed a generalizable and scalable workflow for identifying cells that are differentially interacting across COVID-19 patients with distinct disease outcomes. Our workflow shows how to characterize cellular communication patterns for patients with varying disease severity and thus aids in the understanding of disease progression. We show the scalability and interpretability of our approach by combining around half million of cells from eight COVID-19 scRNA-seq experiments to demonstrate that individuals have heterogeneous communication patterns. Such patterns are potential signatures to discriminate between moderate and severe patients. Overall, this workflow can be generalized and scaled to combine multiple scRNA-seq datasets to uncover cell-cell interactions in complex diseases.

The current coronary artery disease (CAD) risk scores for predicting future cardiovascular events rely on well-recognized traditional cardiovascular risk factors derived from a population level but often fail individuals, with up to 25% of first-time heart attack patients having no risk factors. Non-invasive imaging technology can directly measure coronary artery plaque burden. With an advanced lipidomic measurement methodology, for the first time, we aim to identify lipidomic biomarkers to enable intervention before cardiovascular events. With 994 participants from BioHEART-CT Discovery Cohort, we collected clinical data and performed high-performance liquid chromatography with mass spectrometry to determine concentrations of 683 plasma lipid species. Statin-naive participants were selected based on subclinical CAD (sCAD) categories as the analytical cohort (n = 580), with sCAD+ (n = 243) compared to sCAD− (n = 337). Through a machine learning approach, we built a lipid risk score (LRS) and compared the performance of the existing Framingham Risk Score (FRS) in predicting sCAD+. We obtained individual classifiability scores and determined Body Mass Index (BMI) as the modifying variable. FRS and LRS models achieved similar areas under the receiver operating characteristic curve (AUC) in predicting the validation cohort. LRS enhanced the prediction of sCAD+ in the healthy-weight group (BMI < 25 kg/m2), where FRS performed poorly and identified individuals at risk that FRS missed. Lipid features have strong potential as biomarkers to predict CAD plaque burden and can identify residual risk not captured by traditional risk factors/scores. LRS compliments FRS in prediction and has the most significant benefit in healthy-weight individuals.

Abstract Genetic heterogeneity of tumor is closely related to its clonal evolution, phenotypic diversity and treatment resistance, and such heterogeneity has only been characterized at single-cell sub-chromosomal scale in liver cancer. Here we reconstructed the single-variant resolution clonal evolution in human liver cancer based on single-cell mutational profiles. The results indicated that key genetic events occurred early during tumorigenesis, and an early metastasis followed by independent evolution was observed in primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. By parallel single-cell RNA-Seq, the transcriptomic phenotype of HCC was found to be related with genetic heterogeneity. For the first time we reconstructed the single-cell and single-variant clonal evolution in human liver cancer, and dissection of both genetic and phenotypic heterogeneity will facilitate better understanding of their relationship.

Abstract Background Single-cell RNA-sequencing (scRNA-seq) is a transformative technology, allowing global transcriptomes of individual cells to be profiled with high accuracy. An essential task in scRNA-seq data analysis is the identification of cell types from complex samples or tissues profiled in an experiment. To this end, clustering has become a key computational technique for grouping cells based on their transcriptome profiles, enabling subsequent cell type identification from each cluster of cells. Due to the high feature-dimensionality of the transcriptome (i.e. the large number of measured genes in each cell) and because only a small fraction of genes are cell type-specific and therefore informative for generating cell type-specific clusters, clustering directly on the original feature/gene dimension may lead to uninformative clusters and hinder correct cell type identification. Results Here, we propose an autoencoder-based cluster ensemble framework in which we first take random subspace projections from the data, then compress each random projection to a low-dimensional space using an autoencoder artificial neural network, and finally apply ensemble clustering across all encoded datasets to generate clusters of cells. We employ four evaluation metrics to benchmark clustering performance and our experiments demonstrate that the proposed autoencoder-based cluster ensemble can lead to substantially improved cell type-specific clusters when applied with both the standard k-means clustering algorithm and a state-of-the-art kernel-based clustering algorithm (SIMLR) designed specifically for scRNA-seq data. Compared to directly using these clustering algorithms on the original datasets, the performance improvement in some cases is up to 100%, depending on the evaluation metric used. Conclusions Our results suggest that the proposed framework can facilitate more accurate cell type identification as well as other downstream analyses. The code for creating the proposed autoencoder-based cluster ensemble framework is freely available from https://github.com/gedcom/scCCESS