ASU Scholarship Showcase

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy.

Background: Worksites are important locations for interventions to promote health. However, occupational programs with documented efficacy often are not used, and those being implemented have not been studied. The research in this report was funded through the American Reinvestment and Recovery Act Challenge Topic 'Pathways for Translational Research,' to define and prioritize determinants that enable and hinder translation of evidenced-based health interventions in well-defined settings.

Methods: The IGNITE (investigation to guide new insights for translational effectiveness) trial is a prospective cohort study of a worksite wellness and injury reduction program from adoption to final outcomes among 12 fire departments. It will employ a mixed methods strategy to define a translational model. We will assess decision to adopt, installation, use, and outcomes (reach, individual outcomes, and economic effects) using onsite measurements, surveys, focus groups, and key informant interviews. Quantitative data will be used to define the model and conduct mediation analysis of each translational phase. Qualitative data will expand on, challenge, and confirm survey findings and allow a more thorough understanding and convergent validity by overcoming biases in qualitative and quantitative methods used alone.

Discussion: Findings will inform worksite wellness in fire departments. The resultant prioritized influences and model of effective translation can be validated and manipulated in these and other settings to more efficiently move science to service.

Two distinct monocyte (Mo)/macrophage (Mp) subsets (Ly6C^low and Ly6C^hi) orchestrate cardiac recovery process following myocardial infarction (MI). Prostaglandin (PG) E₂ is involved in the Mo/Mp-mediated inflammatory response, however, the role of its receptors in Mos/Mps in cardiac healing remains to be determined. Here we show that pharmacological inhibition or gene ablation of the Ep3 receptor in mice suppresses accumulation of Ly6C^low Mos/Mps in infarcted hearts. Ep3 deletion in Mos/Mps markedly attenuates healing after MI by reducing neovascularization in peri-infarct zones. Ep3 deficiency diminishes CX3C chemokine receptor 1 (CX3CR1) expression and vascular endothelial growth factor (VEGF) secretion in Mos/Mps by suppressing TGFβ1 signaling and subsequently inhibits Ly6C^low Mos/Mps migration and angiogenesis. Targeted overexpression of Ep3 receptors in Mos/Mps improves wound healing by enhancing angiogenesis. Thus, the PGE₂/Ep3 axis promotes cardiac healing after MI by activating reparative Ly6C^low Mos/Mps, indicating that Ep3 receptor activation may be a promising therapeutic target for acute MI.

Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.

The compositional dependence of the lowest direct and indirect band gaps in Ge_1-ySn_y alloys has been determined from room-temperature photoluminescence measurements. This technique is particularly attractive for a comparison of the two transitions because distinct features in the spectra can be associated with the direct and indirect gaps. However, detailed modeling of these room temperature spectra is required to extract the band gap values with the high accuracy required to determine the Sn concentration y_c at which the alloy becomes a direct gap semiconductor. For the direct gap, this is accomplished using a microscopic model that allows the determination of direct gap energies with meV accuracy. For the indirect gap, it is shown that current theoretical models are inadequate to describe the emission properties of systems with close indirect and direct transitions. Accordingly, an ad hoc procedure is used to extract the indirect gap energies from the data. For y < 0.1 the resulting direct gap compositional dependence is given by ΔE₀ = −(3.57 ± 0.06)y (in eV). For the indirect gap, the corresponding expression is ΔE_ind = −(1.64 ± 0.10)y (in eV). If a quadratic function of composition is used to express the two transition energies over the entire compositional range 0 ≤ y ≤ 1, the quadratic (bowing) coefficients are found to be b₀ = 2.46 ± 0.06 eV (for E0) and b_ind = 1.03 ± 0.11 eV (for E_ind). These results imply a crossover concentration y_c = $0.073 [+0.007 over -0.006], much lower than early theoretical predictions based on the virtual crystal approximation, but in better agreement with predictions based on large atomic supercells.

Earth-abundant sustainable inorganic thin-film solar cells, independent of precious elements, pivot on a marginal material phase space targeting specific compounds. Advanced materials characterization efforts are necessary to expose the roles of microstructure, chemistry, and interfaces. Herein, the earth-abundant solar cell device, Cu₂ZnSnS_(4-x)Se_x, is reported, which shows a high abundance of secondary phases compared to similarly grown Cu₂ZnSnSe₄.

We present two-dimensional Mg(OH)₂ sheets and their vertical heterojunctions with CVD-MoS₂ for the first time as flexible 2D insulators with anomalous lattice vibration and chemical and physical properties. New hydrothermal crystal growth technique enabled isolation of environmentally stable monolayer Mg(OH)₂ sheets. Raman spectroscopy and vibrational calculations reveal that the lattice vibrations of Mg(OH)₂ have fundamentally different signature peaks and dimensionality effects compared to other 2D material systems known to date. Sub-wavelength electron energy-loss spectroscopy measurements and theoretical calculations show that Mg(OH)₂ is a 6 eV direct-gap insulator in 2D, and its optical band gap displays strong band renormalization effects from monolayer to bulk, marking the first experimental confirmation of confinement effects in 2D insulators. Interestingly, 2D-Mg(OH)₂ sheets possess rather strong surface polarization (charge) effects which is in contrast to electrically neutral h-BN materials. Using 2D-Mg(OH)₂ sheets together with CVD-MoS₂ in the vertical stacking shows that a strong change transfer occurs from n-doped CVD-MoS₂ sheets to Mg(OH)₂, naturally depleting the semiconductor, pushing towards intrinsic doping limit and enhancing overall optical performance of 2D semiconductors. Results not only establish unusual confinement effects in 2D-Mg(OH)₂, but also offer novel 2D-insulating material with unique physical, vibrational, and chemical properties for potential applications in flexible optoelectronics.

Transition metal trichalcogenides form a class of layered materials with strong in-plane anisotropy. For example, titanium trisulfide (TiS₃) whiskers are made out of weakly interacting TiS₃ layers, where each layer is made of weakly interacting quasi-one-dimensional chains extending along the b axis. Here we establish the unusual vibrational properties of TiS₃ both experimentally and theoretically. Unlike other two-dimensional systems, the Raman active peaks of TiS₃ have only out-of-plane vibrational modes, and interestingly some of these vibrations involve unique rigid-chain vibrations and S–S molecular oscillations. High-pressure Raman studies further reveal that the A_g^S-S S-S molecular mode has an unconventional negative pressure dependence, whereas other peaks stiffen as anticipated. Various vibrational modes are doubly degenerate at ambient pressure, but the degeneracy is lifted at high pressures. These results establish the unusual vibrational properties of TiS₃ with strong in-plane anisotropy, and may have relevance to understanding of vibrational properties in other anisotropic two-dimensional material systems.

Vibrational spectroscopy in the electron microscope would be transformative in the study of biological samples, provided that radiation damage could be prevented. However, electron beams typically create high-energy excitations that severely accelerate sample degradation. Here this major difficulty is overcome using an ‘aloof’ electron beam, positioned tens of nanometres away from the sample: high-energy excitations are suppressed, while vibrational modes of energies <1 eV can be ‘safely’ investigated. To demonstrate the potential of aloof spectroscopy, we record electron energy loss spectra from biogenic guanine crystals in their native state, resolving their characteristic C–H, N–H and C=O vibrational signatures with no observable radiation damage. The technique opens up the possibility of non-damaging compositional analyses of organic functional groups, including non-crystalline biological materials, at a spatial resolution of ∼10 nm, simultaneously combined with imaging in the electron microscope.

Accumulating data from genome-wide association studies (GWAS) have provided a collection of novel candidate genes associated with complex diseases, such as atherosclerosis. We identified an atherosclerosis-associated single-nucleotide polymorphism (SNP) located in the intron of the long noncoding RNA (lncRNA) LINC00305 by searching the GWAS database. Although the function of LINC00305 is unknown, we found that LINC00305 expression is enriched in atherosclerotic plaques and monocytes. Overexpression of LINC00305 promoted the expression of inflammation-associated genes in THP-1 cells and reduced the expression of contractile markers in co-cultured human aortic smooth muscle cells (HASMCs). We showed that overexpression of LINC00305 activated nuclear factor-kappa beta (NF-κB) and that inhibition of NF-κB abolished LINC00305-mediated activation of cytokine expression. Mechanistically, LINC00305 interacted with lipocalin-1 interacting membrane receptor (LIMR), enhanced the interaction of LIMR and aryl-hydrocarbon receptor repressor (AHRR), and promoted protein expression as well as nuclear localization of AHRR. Moreover, LINC00305 activated NF-κB exclusively in the presence of LIMR and AHRR. In light of these findings, we propose that LINC00305 promotes monocyte inflammation by facilitating LIMR and AHRR cooperation and the AHRR activation, which eventually activates NF-κB, thereby inducing HASMC phenotype switching.