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$_{3}$ minimum best representing the velocity of the spicules. The K$_{2}$ features are either suppressed by the Doppler-shifted K$_{3}$ or enhanced via an increased contribution from the lower layers, leading to strongly enhanced but un-shifted K$_{2}$ 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$\beta$ 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$\beta$. The spicules were automatically detected using advanced image processing techniques, which were applied to the Dopplergrams derived from H$\beta$. 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