2,089 research outputs found
Characterization and formation of on-disk spicules in the Ca II K and Mg II k spectral lines
We characterize, for the first time, type-II spicules in Ca II K 3934\AA\
using the CHROMIS instrument at the Swedish 1-m Solar Telescope. We find that
their line formation is dominated by opacity shifts with the K minimum
best representing the velocity of the spicules. The K features are either
suppressed by the Doppler-shifted K or enhanced via an increased
contribution from the lower layers, leading to strongly enhanced but un-shifted
K peaks, with widening towards the line-core as consistent with
upper-layer opacity removal via Doppler-shift. We identify spicule spectra in
concurrent IRIS Mg II k 2796\AA\ observations with very similar properties.
Using our interpretation of spicule chromospheric line-formation, we produce
synthetic profiles that match observations.Comment: 10 pages, 8 figures, accepted for publication in Astronomy and
Astrophysics Letter
Selective inhibition of miR-21 by phage display screened peptide
miRNAs are nodal regulators of gene expression and deregulation of miRNAs is causally associated with different diseases, including cancer. Modulation of miRNA expression is thus of therapeutic importance. Small molecules are currently being explored for their potential to downregulate miRNAs. Peptides have shown to have better potency and selectivity toward their targets but their potential in targeting and modulating miRNAs remain unexplored. Herein, using phage display we found a very selective peptide against pre-miR-21. Interestingly, the peptide has the potential to downregulate miR-21, by binding to pre-miR-21 and hindering Dicer processing. It is selective towards miR-21 inside the cell. By antagonising miR-21 function, the peptide is able to increase the expression of its target proteins and thereby increase apoptosis and suppress cell proliferation, invasion and migration. This peptide can further be explored for its anti-cancer activity in vivo and may be even extended to clinical studies
The chromosphere underneath a Coronal Bright Point
Coronal Bright Points (CBPs) are sets of small-scale coronal loops,
connecting opposite magnetic polarities, primarily characterized by their
enhanced extreme-ultraviolet (EUV) and X-ray emission. Being ubiquitous, they
are thought to play an important role in heating the solar corona. We aim at
characterizing the barely-explored chromosphere underneath CBPs, focusing on
the related spicular activity and on the effects of small-scale magnetic flux
emergence on CBPs. We used high-resolution observations of a CBP in H
and Fe I 617.3 nm from the Swedish 1-m Solar Telescope (SST) in coordination
with the Solar Dynamics Observatory (SDO). This work presents the first
high-resolution observation of spicules imaged in H. The spicules were
automatically detected using advanced image processing techniques, which were
applied to the Dopplergrams derived from H. Here we report their
abundant occurrence close to the CBP ``footpoints", and find that the
orientation of such spicules is aligned along the EUV loops, indicating that
they constitute a fundamental part of the whole CBP magnetic structure.
Spatio-temporal analysis across multiple channels indicates that there are
coronal propagating disturbances associated with the studied spicules,
producing transient EUV intensity variations of the individual CBP loops. Two
small-scale flux emergence episodes appearing below the CBP were analyzed; one
of them leading to quiet-sun Ellerman bombs and enhancing the nearby spicular
activity. This paper presents unique evidence of the tight coupling between the
lower and upper atmosphere of a CBP, thus helping to unravel the dynamic
phenomena underneath CBPs and their impact on the latter.Comment: Accepted for publication in the Astrophysical Journal. 16 pages, 11
figures. Animations embedde
Spicules in IRIS Mg II Observations: Automated Identification
We have developed an algorithm to identify solar spicules in the first-ever
systematic survey of on-disk spicules using exclusively Mg II spectral
observations. Using this algorithm we identify 2219 events in three IRIS
datasets with unique solar feature targets spanning a total of 300 minutes: 1)
an active region, 2) decayed active region/active network, and 3) a coronal
hole. We present event statistics and relate occurrence rates to underlying
photospheric magnetic field strength. This method identifies spicule event
densities and occurrence rates similar to previous studies performed using
H{\alpha} and Ca II observations of active regions. Additionally, this study
identifies spicule-like events at very low rates at magnetic field intensities
below 20 Gauss and increasing significantly between 100-200 Gauss in active
regions and above 20 Gauss in coronal holes, which can be used to inform future
observation campaigns. This information can be be used to help characterize
spicules over their full lifetime, and compliments existing H-{\alpha} spectral
capabilities and upcoming Ly-{\alpha} spectral observations on the SNIFS
Sounding Rocket. In total, this study presents a method for detecting solar
spicules using exclusively Mg II spectra, and provides statistics for spicule
occurrence in Mg II wavelengths with respect to magnetic field strength for the
purpose of predicting spicule occurrences.Comment: 17 pages, 9 figures, presented at the AGU Fall 2022 conference,
Submitted to AAS Journa
Salivary Metabolomics for Oral Precancerous Lesions: A Comprehensive Narrative Review
Oral submucous fibrosis (OSMF) is a chronic, potentially malignant disorder of the oral cavity, primarily associated with the consumption of areca nut products and other risk factors. Early and accurate diagnosis of OSMF is crucial to prevent its progression to oral cancer. In recent years, the field of metabolomics has gained momentum as a promising approach for disease detection and monitoring. Salivary metabolomics, a non-invasive and easily accessible diagnostic tool, has shown potential in identifying biomarkers associated with various oral diseases, including OSMF.
This review synthesizes current literature on the application of salivary metabolomics in the context of OSMF detection. The review encompasses a comprehensive analysis of studies conducted over the past decade, highlighting advancements in analytical techniques, metabolomic profiling, and identified biomarkers linked to OSMF progression. The primary objective of this review is to provide a critical assessment of the feasibility and reliability of salivary metabolomics as a diagnostic tool for OSMF, along with its potential to differentiate OSMF from other oral disorders.
In conclusion, salivary metabolomics holds great promise in revolutionizing OSMF detection through the identification of reliable biomarkers and the development of robust diagnostic models. However, challenges such as sample variability, validation of biomarkers, and standardization need to be addressed before its widespread clinical implementation. This review contributes to a comprehensive understanding of the current status, challenges, and future directions of salivary metabolomics in the realm of OSMF detection, emphasizing its potential impact on early intervention and improved patient outcomes
Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning
Solar activity plays a quintessential role in influencing the interplanetary
medium and space-weather around the Earth. Remote sensing instruments onboard
heliophysics space missions provide a pool of information about the Sun's
activity via the measurement of its magnetic field and the emission of light
from the multi-layered, multi-thermal, and dynamic solar atmosphere. Extreme UV
(EUV) wavelength observations from space help in understanding the subtleties
of the outer layers of the Sun, namely the chromosphere and the corona.
Unfortunately, such instruments, like the Atmospheric Imaging Assembly (AIA)
onboard NASA's Solar Dynamics Observatory (SDO), suffer from time-dependent
degradation, reducing their sensitivity. Current state-of-the-art calibration
techniques rely on periodic sounding rockets, which can be infrequent and
rather unfeasible for deep-space missions. We present an alternative
calibration approach based on convolutional neural networks (CNNs). We use
SDO-AIA data for our analysis. Our results show that CNN-based models could
comprehensively reproduce the sounding rocket experiments' outcomes within a
reasonable degree of accuracy, indicating that it performs equally well
compared with the current techniques. Furthermore, a comparison with a standard
"astronomer's technique" baseline model reveals that the CNN approach
significantly outperforms this baseline. Our approach establishes the framework
for a novel technique to calibrate EUV instruments and advance our
understanding of the cross-channel relation between different EUV channels.Comment: 12 pages, 7 figures, 8 tables. This is a pre-print of an article
submitted and accepted by A&A Journa
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