Minor impurities can cause catastrophic fracture of normally ductile metals. Here, a classic example is represented by the sulfur embrittlement of nickel, whose atomic-level mechanism has puzzled researchers for nearly a century. In this study, coupled aberration-corrected electron microscopy and semi-grand-canonical-ensemble atomistic simulation reveal, unexpectedly, the universal formation of amorphous-like and bilayer-like facets at the same general grain boundaries. Challenging the traditional view, the orientation of the lower-Miller-index grain surface, instead of the misorientation, dictates the interfacial structure. We also find partial bipolar structural orders in both amorphous-like and bilayer-like complexions (a.k.a. thermodynamically two-dimensional interfacial phases), which cause brittle intergranular fracture. Such bipolar, yet largely disordered, complexions can exist in and affect the properties of various other materials. Beyond the embrittlement mechanism, this study provides deeper insight to better understand abnormal grain growth in sulfur-doped Ni, and generally enriches our fundamental understanding of performance-limiting and more disordered interfaces.

Pedigree genome-wide association studies (GWAS) (Option 29) in the current version of the Mendel software is an optimized subroutine for performing large-scale genome-wide quantitative trait locus (QTL) analysis. This analysis (a) works for random sample data, pedigree data, or a mix of both; (b) is highly efficient in both run time and memory requirement; (c) accommodates both univariate and multivariate traits; (d) works for autosomal and x-linked loci; (e) correctly deals with missing data in traits, covariates, and genotypes; (f) allows for covariate adjustment and constraints among parameters; (g) uses either theoretical or single nucleotide polymorphism (SNP)-based empirical kinship matrix for additive polygenic effects; (h) allows extra variance components such as dominant polygenic effects and household effects; (i) detects and reports outlier individuals and pedigrees; and (j) allows for robust estimation via the t-distribution. This paper assesses these capabilities on the genetics analysis workshop 19 (GAW19) sequencing data. We analyzed simulated and real phenotypes for both family and random sample data sets. For instance, when jointly testing the 8 longitudinally measured systolic blood pressure and diastolic blood pressure traits, it takes Mendel 78 min on a standard laptop computer to read, quality check, and analyze a data set with 849 individuals and 8.3 million SNPs. Genome-wide expression QTL analysis of 20,643 expression traits on 641 individuals with 8.3 million SNPs takes 30 h using 20 parallel runs on a cluster. Mendel is freely available at http://www.genetics.ucla.edu/software.

Pedigree GWAS (Option 29) in the current version of the Mendel software is an optimized subroutine for performing large scale genome-wide QTL analysis. This analysis (a) works for random sample data, pedigree data, or a mix of both, (b) is highly efficient in both run time and memory requirement, (c) accommodates both univariate and multivariate traits, (d) works for autosomal and x-linked loci, (e) correctly deals with missing data in traits, covariates, and genotypes, (f) allows for covariate adjustment and constraints among parameters, (g) uses either theoretical or SNP-based empirical kinship matrix for additive polygenic effects, (h) allows extra variance components such as dominant polygenic effects and household effects, (i) detects and reports outlier individuals and pedigrees, and (j) allows for robust estimation via the $t$-distribution. The current paper assesses these capabilities on the genetics analysis workshop 19 (GAW19) sequencing data. We analyzed simulated and real phenotypes for both family and random sample data sets. For instance, when jointly testing the 8 longitudinally measured systolic blood pressure (SBP) and diastolic blood pressure (DBP) traits, it takes Mendel 78 minutes on a standard laptop computer to read, quality check, and analyze a data set with 849 individuals and 8.3 million SNPs. Genome-wide eQTL analysis of 20,643 expression traits on 641 individuals with 8.3 million SNPs takes 30 hours using 20 parallel runs on a cluster. Mendel is freely available at \url{http://www.genetics.ucla.edu/software}.

Single nucleotide polymorphism (SNP) set tests have been a powerful method in analyzing next-generation sequencing (NGS) data. The popular sequence kernel association test (SKAT) method tests a set of variants as random effects in the linear mixed model setting. Its P-value is calculated based on asymptotic theory that requires a large sample size. Therefore, it is known that SKAT is conservative and can lose power at small or moderate sample sizes. Given the current cost of sequencing technology, scales of NGS are still limited. In this report, we derive and implement computationally efficient, exact (nonasymptotic) score (eScore), likelihood ratio (eLRT), and restricted likelihood ratio (eRLRT) tests, ExactVCTest, that can achieve high power even when sample sizes are small. We perform simulation studies under various genetic scenarios. Our ExactVCTest (i.e., eScore, eLRT, eRLRT) exhibits well-controlled type I error. Under the alternative model, eScore P-values are universally smaller than those from SKAT. eLRT and eRLRT demonstrate significantly higher power than eScore, SKAT, and SKAT optimal (SKAT-o) across all scenarios and various samples sizes. We applied these tests to an exome sequencing study. Our findings replicate previous results and shed light on rare variant effects within genes. The software package is implemented in the open source, high-performance technical computing language Julia, and is freely available at https://github.com/Tao-Hu/VarianceComponentTest.jl Analysis of each trait in the exome sequencing data set with 399 individuals and 16,619 genes takes around 1 min on a desktop computer.

Seven equimolar, five-component, metal diborides were fabricated via high-energy ball milling and spark plasma sintering. Six of them, including (Hf_0.2Zr_0.2Ta_0.2Nb_0.2Ti_0.2)B₂, (Hf_0.2Zr_0.2Ta_0.2Mo_0.2Ti_0.2)B₂, (Hf_0.2Zr_0.2Mo_0.2Nb_0.2Ti_0.2)B₂, (Hf_0.2Mo_0.2Ta_0.2Nb_0.2Ti_0.2)B₂, (Mo_0.2Zr_0.2Ta_0.2Nb_0.2Ti_0.2)B₂, and (Hf_0.2Zr_0.2Ta_0.2Cr_0.2Ti_0.2)B₂, possess virtually one solid-solution boride phase of the hexagonal AlB₂ structure. Revised Hume-Rothery size-difference factors are used to rationalize the formation of high-entropy solid solutions in these metal diborides. Greater than 92% of the theoretical densities have been generally achieved with largely uniform compositions from nanoscale to microscale. Aberration-corrected scanning transmission electron microscopy (AC STEM), with high-angle annular dark-field and annular bright-field (HAADF and ABF) imaging and nanoscale compositional mapping, has been conducted to confirm the formation of 2-D high-entropy metal layers, separated by rigid 2-D boron nets, without any detectable layered segregation along the c-axis. These materials represent a new type of ultra-high temperature ceramics (UHTCs) as well as a new class of high-entropy materials, which not only exemplify the first high-entropy non-oxide ceramics (borides) fabricated but also possess a unique non-cubic (hexagonal) and layered (quasi-2D) high-entropy crystal structure that markedly differs from all those reported in prior studies. Initial property assessments show that both the hardness and the oxidation resistance of these high-entropy metal diborides are generally higher/better than the average performances of five individual metal diborides made by identical fabrication processing.

Background

Eicosanoid and related docosanoid polyunsaturated fatty acids (PUFAs) and their oxygenated derivatives have been proposed as noninvasive lipidomic biomarkers of nonalcoholic steatohepatitis (NASH). Therefore, we investigated associations between plasma eicosanoids and liver fibrosis to evaluate their utility in diagnosing and monitoring NASH-related fibrosis.

Methods

Our analysis used baseline eicosanoid data from 427 patients with biopsy-confirmed nonalcoholic fatty liver disease (NAFLD), and longitudinal measurements along with liver fibrosis staging from 63 patients with NASH and stage 2/3 fibrosis followed for 24 weeks in a phase II trial.

Results

At baseline, four eicosanoids were significantly associated with liver fibrosis stage: 11,12-DIHETE, tetranor 12-HETE, adrenic acid, and 14, 15-DIHETE. Over 24 weeks of follow up, a combination of changes in seven eicosanoids [5-HETE, 7,17-DHDPA, adrenic acid, arachidonic acid (AA), eicosapentaenoic acid (EPA), 16-HDOHE, and 9-HODE) had good diagnostic accuracy for the prediction of ⩾1 stage improvement in fibrosis (AUROC: 0.74; 95% CI: 0.62-0.87), and a combination of four eicosanoids (7,17-DHDPA, 14,15-DIHETRE, 9-HOTRE, and free adrenic acid) accurately predicted improvement in hepatic collagen content (AUROC: 0.72; 95% CI: 0.50-0.77).

Conclusion

This study provides preliminary evidence that plasma eicosanoids may serve as noninvasive biomarkers of liver fibrosis and may predict liver fibrosis improvement in NASH.

Stem cell therapy in heart disease is challenged by mis-injection, poor survival, and low cell retention. Here, we describe a biocompatible multifunctional silica-iron oxide nanoparticle to help solve these issues. The nanoparticles were made via an in situ growth of Fe₃O₄ nanoparticles on both the external surfaces and pore walls of mesocellular foam silica nanoparticles. In contrast to previous work, this approach builds a magnetic moiety inside the pores of a porous silica structure. These materials serve three roles: drug delivery, magnetic manipulation, and imaging. The addition of Fe₃O₄ to the silica nanoparticles increased their colloidal stability, T₂-based magnetic resonance imaging contrast, and superparamagnetism. We then used the hybrid materials as a sustained release vehicle of insulin-like growth factor-a pro-survival agent that can increase cell viability. In vivo rodent studies show that labeling stem cells with this nanoparticle increased the efficacy of stem cell therapy in a ligation/reperfusion model. The nanoparticle-labeled cells increase the mean left ventricular ejection fraction by 11 and 21% and the global longitudinal strain by 24 and 34% on days 30 and 60, respectively. In summary, this multifunctional nanomedicine improves stem cell survival via the sustained release of pro-survival agents.