1,487 research outputs found
The Dichotomy between Nodal and Antinodal Quasiparticles in Underdoped (LaSr)CuO Superconductors
High resolution angle-resolved photoemission measurements on underdoped
(LaSr)CuO system show that, at energies below 70 meV, the
quasiparticle peak is well defined around the (/2,/2) nodal region
and disappears rather abruptly when the momentum is changed from the nodal
point to the (,0) antinodal point along the underlying ``Fermi surface''.
It indicates that there is an extra low energy scattering mechanism acting upon
the antinodal quasiparticles. We propose that this mechanism is the scattering
of quasiparticles across the nearly parallel segments of the Fermi surface near
the antinodes.Comment: to appear in Phys. Rev. Let
Multiple Bosonic Mode Coupling in Electron Self-Energy of (La_2-xSr_x)CuO_4
High resolution angle-resolved photoemission spectroscopy data along the
(0,0)-(,) nodal direction with significantly improved statistics
reveal fine structure in the electron self-energy of the underdoped
(LaSr)CuO samples in the normal state. Fine structure at
energies of (4046) meV and (5863)meV, and possible fine structure
at energies of (2329)meV and (7585)meV, have been identified. These
observations indicate that, in LSCO, more than one bosonic modes are involved
in the coupling with electrons.Comment: 4 pages, 3 figures, Fig. 2 update
The hierarchy of multiple many-body interaction scales in high-temperature superconductors
To date, angle-resolved photoemission spectroscopy has been successful in
identifying energy scales of the many-body interactions in correlated
materials, focused on binding energies of up to a few hundred meV below the
Fermi energy. Here, at higher energy scale, we present improved experimental
data from four families of high-Tc superconductors over a wide doping range
that reveal a hierarchy of many-body interaction scales focused on: the low
energy anomaly ("kink") of 0.03-0.09eV, a high energy anomaly of 0.3-0.5eV, and
an anomalous enhancement of the width of the LDA-based CuO2 band extending to
energies of ~ 2 eV. Besides their universal behavior over the families, we find
that all of these three dispersion anomalies also show clear doping dependence
over the doping range presented.Comment: 7 pages, 6 figure
The composite picture of the charge carriers in La2-xSrxCuO4 (0.063 < x < 0.11) superconductors
Through far-infrared studies of La2-xSrxCuO4 single crystals for x = 0.063,
0.07, 0.09, and 0.11, we found that only ~ 0.2 % of the total holes
participated in the nearly dissipationless normal state charge transport and
superconductivity. We have also observed characteristic collective modes at w ~
18 cm-1 and 22 cm-1 due to the bound carriers in an electronic lattice (EL)
state and the free carriers are massively screened by the EL. Our findings lead
us to propose a composite picture of the charge system where the free carriers
are coupled to and riding on the EL. This unique composite system of charge
carriers may provide further insights into the understanding of the cuprate
physics.Comment: 10 pages, 4 figure
CAR T cells targeting BAFF-R can overcome CD19 antigen loss in B cell malignancies
CAR T cells targeting CD19 provide promising options for treatment of B cell malignancies. However, tumor relapse from antigen loss can limit efficacy. We developed humanized, second-generation CAR T cells against another B cell–specific marker, B cell activating factor receptor (BAFF-R), which demonstrated cytotoxicity against human lymphoma and acute lymphoblastic leukemia (ALL) lines. Adoptively transferred BAFF-R-CAR T cells eradicated 10-day preestablished tumor xenografts after a single treatment and retained efficacy against xenografts deficient in CD19 expression, including CD19-negative variants within a background of CD19-positive lymphoma cells. Four relapsed, primary ALLs with CD19 antigen loss obtained after CD19-directed therapy retained BAFF-R expression and activated BAFF-R-CAR, but not CD19-CAR, T cells. BAFF-R-CAR, but not CD19-CAR, T cells also demonstrated antitumor effects against an additional CD19 antigen loss primary patient–derived xenograft (PDX) in vivo. BAFF-R is amenable to CAR T cell therapy, and its targeting may prevent emergence of CD19 antigen loss variants
The identification of informative genes from multiple datasets with increasing complexity
Background
In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes.
Results
In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes.
Conclusions
We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events
Timescale Analysis of Spectral Lags
A technique for timescale analysis of spectral lags performed directly in the
time domain is developed. Simulation studies are made to compare the time
domain technique with the Fourier frequency analysis for spectral time lags.
The time domain technique is applied to studying rapid variabilities of X-ray
binaries and -ray bursts. The results indicate that in comparison with
the Fourier analysis the timescale analysis technique is more powerful for the
study of spectral lags in rapid variabilities on short time scales and short
duration flaring phenomena.Comment: 14 pages, 11 figures, to appear in Chin. J. Astron. Astrophy
Biodegradable, flexible silicon nanomembrane-based NO x gas sensor system with record-high performance for transient environmental monitors and medical implants
Abstract: A novel transient electronics technology that is capable of completely dissolving or decomposing in certain conditions after a period of operation offers unprecedented opportunities for medical implants, environmental sensors, and other applications. Here, we describe a biodegradable, flexible silicon-based electronic system that detects NO species with a record-breaking sensitivity of 136 Rs (5 ppm, NO2) and 100-fold selectivity for NO species over other substances with a fast response (~30 s) and recovery (~60 s). The exceptional features primarily depend on not only materials, dimensions, and design layouts but also temperatures and electrical operations. Large-scale sensor arrays in a mechanically pliable configuration exhibit negligible deterioration in performance under various modes of applied loads, consistent with mechanics modeling. In vitro evaluations demonstrate the capability and stability of integrated NOx devices in severe wet environments for biomedical applications
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