14,962 research outputs found
Some Thoughts on the Dynamics of Federal Trademark Legislation and the Trademark Dilution Act of 1995
Basic transcription factor 3 (BTF3) is a general RNA polymerase II transcription factor and is also involved in apoptosis regulation. Increasing evidence shows that BTF3 is aberrantly expressed in several kinds of malignancies, but there is no study to analyze BTF3 expression in colorectal cancer (CRC) patients. Applying immunohistochemistry, we detected BTF3 in CRCs (n = 156), the corresponding distant (n = 42), adjacent normal mucosa (n = 96), lymph node metastases (n = 35), and analyzed its relationships with clinicopathological and biological variables. Our results showed that BTF3 staining significantly increased from distant or adjacent normal mucosa to primary CRCs (p < 0.0001) or metastases (p = 0.002 and p < 0.0001). BTF3 was higher in distal cancers than in proximal cancers (57 % vs. 39 %, p = 0.041). It also showed stronger staining in primary CRCs stage I and II than that in stage III and IV (64 % vs. 35 %, p = 0.0004), or metastases (64 % vs. 29 %, p = 0.004). Cancers with better differentiation had a higher expression than those with worse differentiation (56 % vs. 37 %, p = 0.031). There were positive correlations of BTF3 expression with nuclear factor kappa B (NF-κB), RAD50, MRE11, NBS1, and AEG-1 (p < 0.05). In conclusion, BTF3 overexpression may be an early event in CRC development and could be useful biomarker for the early stage of CRCs. BTF3 has positive correlations with NF-κB, RAD50, MRE11, NBS1 and AEG-1, and might influence complex signal pathways in CRC
A Comprehensive Analysis of Fermi Gamma-Ray Burst Data. IV. Spectral Lag and its Relation to E p Evolution
The spectral evolution and spectral lag behavior of 92 bright pulses from 84 gamma-ray bursts observed by the Fermi Gamma-ray Burst Monitor (GBM) telescope are studied. These pulses can be classified into hard-to-soft pulses (H2S; 64/92), H2S-dominated-tracking pulses (21/92), and other tracking pulses (7/92). We focus on the relationship between spectral evolution and spectral lags of H2S and H2S-dominated-tracking pulses. The main trend of spectral evolution (lag behavior) is estimated with ( ), where E p is the peak photon energy in the radiation spectrum, t + t 0 is the observer time relative to the beginning of pulse −t 0, and is the spectral lag of photons with energy E with respect to the energy band 8–25 keV. For H2S and H2S-dominated-tracking pulses, a weak correlation between and k E is found, where W is the pulse width. We also study the spectral lag behavior with peak time of pulses for 30 well-shaped pulses and estimate the main trend of the spectral lag behavior with . It is found that is correlated with k E . We perform simulations under a phenomenological model of spectral evolution, and find that these correlations are reproduced. We then conclude that spectral lags are closely related to spectral evolution within the pulse. The most natural explanation of these observations is that the emission is from the electrons in the same fluid unit at an emission site moving away from the central engine, as expected in the models invoking magnetic dissipation in a moderately high-σ outflow
A comprehensive analysis of Fermi Gamma-Ray Burst Data: IV. Spectral lag and Its Relation to Ep Evolution
The spectral evolution and spectral lag behavior of 92 bright pulses from 84
gamma-ray bursts (GRBs) observed by the Fermi GBM telescope are studied. These
pulses can be classified into hard-to-soft pulses (H2S, 64/92),
H2S-dominated-tracking pulses (21/92), and other tracking pulses (7/92). We
focus on the relationship between spectral evolution and spectral lags of H2S
and H2S-dominated-tracking pulses. %in hard-to-soft pulses (H2S, 64/92) and
H2S-dominating-tracking (21/92) pulses. The main trend of spectral evolution
(lag behavior) is estimated with
(), where is the peak photon
energy in the radiation spectrum, is the observer time relative to the
beginning of pulse , and is the spectral lag of photons
with energy with respect to the energy band - keV. For H2S and
H2S-dominated-tracking pulses, a weak correlation between
and is found, where is the pulse width. We also study the spectral
lag behavior with peak time of pulses for 30 well-shaped pulses
and estimate the main trend of the spectral lag behavior with . It is found that is correlated with
. We perform simulations under a phenomenological model of spectral
evolution, and find that these correlations are reproduced. We then conclude
that spectral lags are closely related to spectral evolution within the pulse.
The most natural explanation of these observations is that the emission is from
the electrons in the same fluid unit at an emission site moving away from the
central engine, as expected in the models invoking magnetic dissipation in a
moderately-high- outflow.Comment: 58 pages, 11 figures, 3 tables. ApJ in pres
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Differentiation of Glial Cells From hiPSCs: Potential Applications in Neurological Diseases and Cell Replacement Therapy.
Glial cells are the most abundant cell type in the central nervous system (CNS) and play essential roles in maintaining brain homeostasis, forming myelin, and providing support and protection for neurons, etc. Over the past decade, significant progress has been made in the reprogramming field. Given the limited accessibility of human glial cells, in vitro differentiation of human induced pluripotent stem cells (hiPSCs) into glia may provide not only a valuable research tool for a better understanding of the functions of glia in the CNS but also a potential cellular source for clinical therapeutic purposes. In this review, we will summarize up-to-date novel strategies for the committed differentiation into the three major glial cell types, i.e., astrocyte, oligodendrocyte, and microglia, from hiPSCs, focusing on the non-neuronal cell effects on the pathology of some representative neurological diseases. Furthermore, the application of hiPSC-derived glial cells in neurological disease modeling will be discussed, so as to gain further insights into the development of new therapeutic targets for treatment of neurological disorders
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