Glioblastoma multiforme (GBM) is a highly lethal brain tumor. Due to resistance to current therapies, patient prognosis remains poor and development of novel and effective GBM therapy is crucial. Glioma stem cells (GSCs) have gained attention as a therapeutic target in GBM due to their relative resistance to current therapies and potent tumor-initiating ability. Previously, we identified that the mitotic kinase maternal embryonic leucine-zipper kinase (MELK) is highly expressed in GBM tissues, specifically in GSCs, and its expression is inversely correlated with the post-surgical survival period of GBM patients. In addition, patient-derived GSCs depend on MELK for their survival and growth both in vitro and in vivo. Here, we demonstrate evidence that the role of MELK in the GSC survival is specifically dependent on its kinase activity. With in silico structure-based analysis for protein-compound interaction, we identified the small molecule Compound 1 (C1) is predicted to bind to the kinase-active site of MELK protein. Elimination of MELK kinase activity was confirmed by in vitro kinase assay in nano-molar concentrations. When patient-derived GSCs were treated with C1, they underwent mitotic arrest and subsequent cellular apoptosis in vitro, a phenotype identical to that observed with shRNA-mediated MELK knockdown. In addition, C1 treatment strongly induced tumor cell apoptosis in slice cultures of GBM surgical specimens and attenuated growth of mouse intracranial tumors derived from GSCs in a dose-dependent manner. Lastly, C1 treatment sensitizes GSCs to radiation treatment. Collectively, these data indicate that targeting MELK kinase activity is a promising approach to attenuate GBM growth by eliminating GSCs in tumors. © 2014 Minata et.

We have performed angle-integrated and angle-resolved photoemission measurements at 20 K on well-characterized single crystals of high Tc cuprates (both 1:2:3-type and 2:2:1:2-type) cleaved in situ, and find a relatively large, resolution limited Fermi edge which shows large amplitude variations with photon energy, indicative of band structure final state effects. The lineshape of the spectra of the 1:2:3 materials as a function of photon energy are well reproduced by band structure predictions, indicating a correct mix of 2p and 3d orbitals in the calculations, while the energy positions of the peaks agree with calculated bands to within approx;;0.5 eV. This may yet prove to reflect the effects of Coulomb correlation. We nevertheless conclude that a Fermi liquid approach to conductivity is appropriate. Angle-resolved data, while still incomplete, suggest agreement with the Fermi surface predicted by the LDA calculations. A BCS-like energy gap is observed in the 2:2:1:2 materials, whose magnitude is twice the weak coupling BCS value (i.e., 2Δ approx;; 7kTc). © 1990 IOP Publishing Ltd.

We have performed angle-integrated photoemission measurements at 20 K on well-oxygenated (Tc=92 K) single crystals of YBa2Cu3O6.9 cleaved n situ, and find a relatively large, resolution-limited Fermi edge which shows large amplitude variations with photon energy, indicative of band-structure final-state effects. Some dispersion is seen even in our angle-integrated measurements. Our best estimate of N(EF) per Cu atom is that it is about 20% that of Cu metal with about a 20-80 mix of Cu 3d and O 2p orbitals. Dispersive and final-state effects are seen throughout the valence bands. The line shapes of the spectra as a function of photon energy are very well reproduced by band-structure predictions, indicating a correct mix of 2p and 3d orbitals in the calculations, while the energy positions of the peak agree with calculated bands to within 0.5 eV. We conclude that a Fermi-liquid approach to conductivity is appropriate. © 1989 The American Physical Society.

Creating oxide interfaces with precise chemical specificity at the atomic layer level is desired for the engineering of quantum phases and electronic applications, but highly challenging, owing partially to the lack of in situ tools to monitor the chemical composition and completeness of the surface layer during growth. Here we report the in situ observation of atomic layer-by-layer inner potential variations by analysing the Kikuchi lines during epitaxial growth of strontium titanate, providing a powerful real-time technique to monitor and control the chemical composition during growth. A model combining the effects of mean inner potential and step edge density (roughness) reveals the underlying mechanism of the complex and previously not well-understood reflection high-energy electron diffraction oscillations observed in the shuttered growth of oxide films. General rules are proposed to guide the synthesis of atomically and chemically sharp oxide interfaces, opening up vast opportunities for the exploration of intriguing quantum phenomena at oxide interfaces.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble models performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Genetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3 × 10(-6)) had not been highlighted in previous studies. While rs56137030was correlated at r(2)>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

The E12-14-012 experiment, performed in Jefferson Lab Hall A, has collected exclusive electron-scattering data (e,e′p) in parallel kinematics using natural argon and natural titanium targets. Here we report the first results of the analysis of the data set corresponding to beam energy 2222 GeV, electron scattering angle 21.5∘, and proton emission angle -50∘. The differential cross sections, measured with ≈4% uncertainty, have been studied as a function of missing energy and missing momentum, and compared to the results of Monte Carlo simulations, obtained from a model based on the distorted-wave impulse approximation.