796 research outputs found
X-ray absorption and photoemission spectroscopy of electronic phase separation inKxFe2−ySe2
No full textThe electronic structure of phase separated KxFe2-y Se-2 has been studied by means of x-ray absorption spectroscopy (XAS) and photoemission spectroscopy. Both Fe L-2,L-3-edge XAS and Fe 2p photoemission spectra show a signature of the metallic phase that is embedded in the insulating texture. Valence-band spectra, measured with different excitation energies, reveal a finite density of states at the Fermi level driven by the Fe 3d orbitals. A combined analysis of the Se L-2,L-3-edge and the Se K-edge XAS provides further information on a significant density of states of Se 4p character near the Fermi level, consistent with a large hybridization of these states with the Fe 3d orbitals. The K L-2,L-3-edge XAS spectrum is also presented to show element specific partial density of states. The results are discussed in connection with the electronic phase separation in K-x Fe2-y Se-2 driven by the Fe 3d states
A study of the electronic structure of FeSe1-xTex chalcogenides by Fe and Se K-edge x-ray absorption near edge structure measurements
No full textFe K-edge and Se K-edge x-ray absorption near edge structure (XANES) measurements are used to study the FeSe1-xTex electronic structure of chalcogenides. An intense Fe K-edge pre-edge peak due to Fe 1s -> 3d (and admixed Se/Te p states) is observed, showing substantial change with Te substitution and x-ray polarization. The main white line peak in the Se K-edge XANES due to Se 1s -> 4p transition appears similar to the one expected for Se2- systems and changes with Te substitution. Polarization dependence reveals that unoccupied Se orbitals near the Fermi level have predominant p(x,y) character. The results provide key information on the hybridization of Fe 3d and chalcogen p states in the Fe-based chalcogenide superconductors
Detection of the flux dynamical regimes in Bi4O4S3 by multiharmonic AC susceptibility
No full textThe temperature dependent first and third harmonics of the AC magnetic susceptibility χ1,3(T) have been measured on Bi4O4S3. The χ1(T) magnetic response is due to the intergranular contribution with a transition temperature Tc ≈ 4.4 K. The dependencies of the χ3(T) on the AC field amplitude and frequency reveal a critical state with the presence of the flux creep and the flux flow regimes. In fact, the field dependencies of the effective activation energy and of the frequency dependent critical current density have been found to be described with power laws characteristic of the collective creep regime involving large flux bundles
High-pressure X-ray absorption and diffraction study of the self-doped superconductor EuFBiS2
No full textThe BiS2-based layered materials are characterized by a highly susceptible physical state, revealing a large response to external conditions. A particular case is the EuFBiS2 compound, showing a superconducting transition temperature Tc∼0.3 K at ambient pressure. Upon increasing external pressure, Tc goes through a large amplification, accompanied by a structural phase transition (SPT) from tetragonal to monoclinic symmetry. Here, we use a combination of Eu L3-edge X-ray absorption spectroscopy and synchrotron X-ray diffraction to unveil the evolution of the Eu valence and lattice symmetry under high pressure. We find that the average Eu valence increases gradually with pressure, exhibiting a pressure plateau near the SPT, at which the Tc increases sharply. Since in EuFBiS2 the charge carriers are introduced via self-doping induced by the mixed valence of the Eu ions, our findings clearly indicate that the role of the charge doping is marginal in the Tc enhancement. On the other hand, the structural distortions, taking place at the SPT, play a central role in enhancing the superconducting properties of the EuFBiS2 system
Systems biology approaches to a rational drug discovery paradigm
No full textThe published manuscript is available at EurekaSelect via http://www.eurekaselect.com/openurl/content.php?genre=article&doi=10.2174/1568026615666150826114524.Prathipati P., Mizuguchi K.. Systems biology approaches to a rational drug discovery paradigm. Current Topics in Medicinal Chemistry, 16, 9, 1009. https://doi.org/10.2174/1568026615666150826114524.Ligand- and structure-based drug design approaches complement phenotypic and target screens, respectively, and are the two major frameworks for guiding early-stage drug discovery efforts. Since the beginning of this century, the advent of the genomic era has presented researchers with a myriad of high throughput biological data (parts lists and their interaction networks) to address efficacy and toxicity, augmenting the traditional ligand- and structure-based approaches. This data rich era has also presented us with challenges related to integrating and analyzing these multi-platform and multi-dimensional datasets and translating them into viable hypotheses. Hence in the present paper, we review these existing approaches to drug discovery research and argue the case for a new systems biology based approach. We present the basic principles and the foundational arguments/underlying assumptions of the systems biology based approaches to drug design. Also discussed are systems biology data types (key entities, their attributes and their relationships with each other, and data models/representations), software and tools used for both retrospective and prospective analysis, and the hypotheses that can be inferred. In addition, we summarize some of the existing resources for a systems biology based drug discovery paradigm (open TG-GATEs, DrugMatrix, CMap and LINCs) in terms of their strengths and limitations
Effect of high-pressure annealing on the normal-state transport ofLaO0.5F0.5BiS2
No full textWe study normal state electrical, thermoelectrical, and thermal transport in polycrystalline BiS2-based compounds, which become superconducting by F doping on the O site. In particular, we explore undoped LaOBiS2 and doped LaO0.5F0.5BiS2 samples, prepared either with or without high-pressure annealing, in order to evidence the roles of doping and preparation conditions. The high-pressure annealed sample exhibits room temperature values of resistivity rho around 5 m Omega cm, Seebeck coefficient S around -20 mu V/K, and thermal conductivity kappa around 1.5 W/Km, while the Hall resistance R-H is negative at all temperatures and its value is -10(-8) m(3)/C at low temperature. The sample prepared at ambient pressure exhibits R-H positive in sign and five times larger in magnitude, and S negative in sign and slightly smaller in magnitude. These results reveal a complex multiband evolution brought about by high-pressure annealing. In particular, the sign inversion and magnitude suppression of R-H, indicating increased electron-type carrier density in the high-pressure sample, may be closely related to previous findings about change in lattice parameters and enhancement of superconducting T-c by high-pressure annealing. As for the undoped sample, it exhibits 10 times larger resistivity, 10 times larger vertical bar S vertical bar, and 10 times larger vertical bar R-H vertical bar than its doped counterpart, consistent with its insulating nature. Our results point out the dramatic effect of preparation conditions in affecting charge carrier density as well as structural, band, and electronic parameters in these systems
Identification of the differences in molecular networks between idiopathic pulmonary fibrosis and lung squamous cell carcinoma using machine learning
No full textNojima Y., Mizuguchi K.. Identification of the differences in molecular networks between idiopathic pulmonary fibrosis and lung squamous cell carcinoma using machine learning. Computational Biology and Chemistry 119, 108560 (2025); https://doi.org/10.1016/j.compbiolchem.2025.108560.Idiopathic pulmonary fibrosis (IPF) is an independent risk factor for lung cancer, especially squamous cell carcinoma (SCC). The prognosis of patients with both IPF and SCC is poorer than that of patients with only IPF, and preventive measures against SCC in patients with IPF remain elusive. Understanding the distinct mechanisms that induce both diseases is crucial for mitigating SCC onset in patients with IPF. We developed highly accurate machine learning (ML) models to classify patients with IPF or SCC using public RNA sequencing data. To construct the ML models, a random restart technique was applied to the five algorithms. To identify the differentially expressed genes (DEGs) between IPF and SCC, feature importance was calculated in the classification models. Furthermore, we detected somatic mutations affecting gene expression using SCC data. The ML models identified VCX2, TMPRSS11B, PRUNE2, PRG4, PZP, SCARA5, DES, HPSE2, HOXD11, S100A7A, and PLA2G2A as DEGs. Somatic mutations were detected in four transcription factors, BHLHE40, MYC, STAT1, and E2F4, which regulate the expression of these 11 genes. Furthermore, a molecular network comprising four transcription factors and 11 downstream genes was discovered. This newly identified molecular network enhances our understanding of the distinct mechanisms underlying IPF and SCC onset, and provides new insights into preventing SCC complications in patients with IPF
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