Total Nuclear Reaction Cross Section Induced by Halo Nuclei and Stable Nuclei

We develop the method for the calculation of the total reaction cross sections induced by the halo nuclei and stable nuclei. This approach is based on the Glauber theory, which is valid for nuclear reactions at high energy. It is extended for nuclear reactions at low energy and intermediate energy by including both the quantum correction and Coulomb correction under the assumption of the effective nuclear density distribution. The calculated results of the total reaction cross section induced by stable nuclei agree well with the 30 experimental data within 10 percent accuracy.The comparison between the numerical results and the 20 experimental data for the total nuclear reaction cross section induced by the neutron halo nuclei and the proton halo nuclei indicates a satisfactory agreement after considering the halo structure of these nuclei, which implies the quite different mean fields for the nuclear reactions induced by halo nuclei and stable nuclei. The halo nucleon distributions and the root mean square radii of these nuclei can be extracted from above comparison based on the improved Glauber model, which indicate clearly the halo structures of these nuclei. Especially, it is clear to see that the medium correction of the nucleon-nucleon collision has little effect on the total reaction cross sections induced by the halo nuclei due to the very weak binding and the very extended density distribution.Comment: 15 pages,2 figures. Communucations in Theoretical Physics, (2003) in pres

Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks

While genes are defined by sequence, in biological systems a protein's function is largely determined by its three-dimensional structure. Evolutionary information embedded within multiple sequence alignments provides a rich source of data for inferring structural constraints on macromolecules. Still, many proteins of interest lack sufficient numbers of related sequences, leading to noisy, error-prone residue-residue contact predictions. Here we introduce DeepContact, a convolutional neural network (CNN)-based approach that discovers co-evolutionary motifs and leverages these patterns to enable accurate inference of contact probabilities, particularly when few related sequences are available. DeepContact significantly improves performance over previous methods, including in the CASP12 blind contact prediction task where we achieved top performance with another CNN-based approach. Moreover, our tool converts hard-to-interpret coupling scores into probabilities, moving the field toward a consistent metric to assess contact prediction across diverse proteins. Through substantially improving the precision-recall behavior of contact prediction, DeepContact suggests we are near a paradigm shift in template-free modeling for protein structure prediction. Many protein structures of interest remain out of reach for both computational prediction and experimental determination. DeepContact learns patterns of co-evolution across thousands of experimentally determined structures, identifying conserved local motifs and leveraging this information to improve protein residue-residue contact predictions. DeepContact extracts additional information from the evolutionary couplings using its knowledge of co-evolution and structural space, while also converting coupling scores into probabilities that are comparable across protein sequences and alignments. Keywords: contact prediction; convolutional neural networks; deep learning; protein structure prediction; structure prediction; co-evolution; evolutionary couplingsNational Institutes of Health (U.S.) (Grant R01GM081871

Observing white dwarf tidal stripping with TianQin gravitational wave observatory

Recently discovered regular X-ray bursts known as quasi-periodic eruptions have a proposed model that suggests a tidal stripping white dwarf inspiralling into the galaxy's central black hole on an eccentric orbit. According to this model, the interaction of the stripping white dwarf with the central black hole would emit gravitational wave signals as well, their detection can help explore the formation mechanism of quasi-periodic eruptions and facilitate multi-messenger observations. In this paper, we aim to perform a preliminary study of the gravitation wave observation of TianQin on this stripping white dwarf model. We investigated the horizon distance of TianQin on this type of gravitation wave signal and found it can be set to 200Mpc. We also find that those stripping white dwarf model sources with central black hole mass within $10^4\sim10^{5.5}M_\odot$ are more likely to be detected by TianQin. We assessed the parameter estimation precision of TianQin on those stripping white dwarf model sources. Our result shows that, even in the worst case, TianQin can determine the central black hole mass, the white dwarf mass, the central black hole spin, and the orbital initial eccentricity with a precision of $10^{-2}$. In the optimistic case, TianQin can determine the central black hole mass and the white dwarf mass with a precision of $10^{-7}$, determine the central black hole spin with a precision of $10^{-5}$, and determine the orbital initial eccentricity with a precision of $10^{-8}$. Moreover, TianQin can determine the luminosity distance with a precision of $10^{-1}$ and determine the sky localization with a precision of $10^{-2}\sim10$ $\rm deg^2$.Comment: 9 pages, 4 figure

Lensing reconstruction from the cosmic microwave background polarization with machine learning

The lensing effect of the cosmic microwave background (CMB) is a powerful tool for our study of the distribution of matter in the universe. Currently, the quadratic estimator (EQ) method, which is widely used to reconstruct lensing potential, has been known to be sub-optimal for the low-noise levels polarization data from next-generation CMB experiments. To improve the performance of the reconstruction, other methods, such as the maximum likelihood estimator and machine learning algorithms are developed. In this work, we present a deep convolutional neural network model named the Residual Dense Local Feature U-net (RDLFUnet) for reconstructing the CMB lensing convergence field. By simulating lensed CMB data with different noise levels to train and test network models, we find that for noise levels less than $5\mu$K-arcmin, RDLFUnet can recover the input gravitational potential with a higher signal-to-noise ratio than the previous deep learning and the traditional QE methods at almost the entire observation scales.Comment: 12 pages, 8 figures, accepted by Ap

Dexamethasone disrupts intercellular junction formation and cytoskeleton organization in human trabecular meshwork cells

Purpose: Patients reproduce symptoms of primary open-angle glaucoma (POAG) when treated with glucocorticoids (GCs) topically on the eyes. Here we investigated the effects of GCs on junctional protein expression and cytoskeleton organization in primary human trabecular meshwork (TM) cultures to understand the molecular pathologies of POAG. Methods: Human TM cells from POAG (GTM) and age-matched nondiseased (NTM) individuals were obtained by standard surgical trabeculectomy. Some of the cultures were treated with dexamethasone (DEX), a synthetic GC, at 1-5x10(-7) mol/l for 1-7 days. The expression levels of zonula occluden-1 (ZO-1) and connexin43 (Cx43) in TM cells with or without DEX treatment were measured using reverse transcription (RT)-PCR, immunocytochemistry, and western blot analysis. Results: mRNA and proteins of ZO-1 and Cx43 were found in both NTM and GTM cells. ZO-1 and Cx43 were located on the plasma membrane, especially along the border of adjacent cells. ZO-1 had no marked changes in localization in NTM and GTM cells after treatment with 10(-7) mol/l DEX for 48 h, whereas Cx43 appeared to increase in the cytoplasm. mRNA of two ZO-1 isoforms, alpha+ and alpha-, were present in TM cells, and the former was expressed less than the latter. Only ZO-1 alpha-isoform protein was expressed in NTM cells, whereas proteins of both isoforms were found in GTM cells. DEX increased the protein levels of ZO-1 and Cx43 in both NTM and GTM cells. DEX also altered the F-actin architecture and promoted cross-linked actin network formation, the effects of which were more pronounced in GTM cells. Conclusions: Our findings not only provide molecular insights to the pathogenesis of GC-induced glaucoma but also suggest that junctional proteins ZO-1 and Cx43 as well as F-actin are targets for developing new modalities in glaucoma therapy

Association between vitamin D level and pediatric inflammatory bowel disease: A systematic review and meta-analysis

BackgroundPrevious studies have reported that the incidence of pediatric inflammatory bowel disease (IBD) is related to vitamin D, but it is still unclear. This study intends to calculate the relationship between pediatric IBD and vitamin D.MethodsA comprehensive literature search from inception to January 2023 was performed in the PubMed, EMBASE, Medline, Web of Science, and Google Scholar databases. Relevant data were extracted as required and used for subsequent calculations.ResultsSixteen papers were included, and there was no significant difference between the average vitamin D level in IBD patients and healthy controls. In addition, the overall pooled results showed that C-reactive protein (CRP) was 2.65 higher before vitamin D supplementation than after supplementation [SMD = 2.65, 95% CI = (2.26, 3.04)]. Moreover, patients with IBD in remission were 0.72 higher before vitamin D supplementation than after supplementation [OR = 0.72, 95% CI = (0.52, 1.00)].ConclusionThis study suggested that there was no obvious relationship between pediatric IBD and vitamin D, while vitamin D supplementation can improve disease activity. Therefore, follow-up still needs many prospective studies to confirm the relationship between pediatric IBD and vitamin D