Neutrino Masses and the LHC: Testing Type II Seesaw

We demonstrate how to systematically test a well-motivated mechanism for neutrino mass generation (Type-II seesaw) at the LHC, in which a Higgs triplet is introduced. In the optimistic scenarios with a small Higgs triplet vacuum expectation value vd < 10^{-4} GeV, one can look for clean signals of lepton number violation in the decays of doubly charged and singly charged Higgs bosons to distinguish the Normal Hierarchy (NH), the Inverted Hierarchy (IH) and the Quasi-Degenerate (QD) spectrum for the light neutrino masses. The observation of either H+ --> tau+ nubar or H+ --> e+ nubar will be particularly robust for the spectrum test since they are independent of the unknown Majorana phases. The H++ decays moderately depend on a Majorana phase Phi2 in the NH, but sensitively depend on Phi1 in the IH. In a less favorable scenario vd > 2 10^{-4} GeV, when the leptonic channels are suppressed, one needs to observe the decays H+ --> W+ H_1 and H+ --> t bbar to confirm the triplet-doublet mixing which in turn implies the existence of the same gauge-invariant interaction between the lepton doublet and the Higgs triplet responsible for the neutrino mass generation. In the most optimistic situation, vd approx 10^{-4} GeV, both channels of the lepton pairs and gauge boson pairs may be available simultaneously. The determination of their relative branching fractions would give a measurement for the value of vd.Comment: 50 pages, 51 figures, minor corrections, one reference added, to appear in Physical Review

Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

In this paper, we propose an efficient and effective framework to fuse hyperspectral and Light Detection And Ranging (LiDAR) data using two coupled convolutional neural networks (CNNs). One CNN is designed to learn spectral-spatial features from hyperspectral data, and the other one is used to capture the elevation information from LiDAR data. Both of them consist of three convolutional layers, and the last two convolutional layers are coupled together via a parameter sharing strategy. In the fusion phase, feature-level and decision-level fusion methods are simultaneously used to integrate these heterogeneous features sufficiently. For the feature-level fusion, three different fusion strategies are evaluated, including the concatenation strategy, the maximization strategy, and the summation strategy. For the decision-level fusion, a weighted summation strategy is adopted, where the weights are determined by the classification accuracy of each output. The proposed model is evaluated on an urban data set acquired over Houston, USA, and a rural one captured over Trento, Italy. On the Houston data, our model can achieve a new record overall accuracy of 96.03%. On the Trento data, it achieves an overall accuracy of 99.12%. These results sufficiently certify the effectiveness of our proposed model

V2C MXene-modified g-C3N4 for enhanced visible-light photocatalytic activity

Increasing the efficiency of charge transfer and separation efficiency of photogenerated carriers are still the main challenges in the field of semiconductor-based photocatalysts. Herein, we synthesized g-C3N4@V2C MXene photocatalyst by modifying g-C3N4 using V2C MXene. The prepared photocatalyst exhibited outstanding photocatalytic performance under visible light. The degradation efficiency of methyl orange by g-C3N4@V2C MXene photocatalyst was as high as 94.5%, which is 1.56 times higher than that by g-C3N4. This was attributed to the V2C MXene inhibiting the rapid recombination of photogenerated carriers and facilitating rapid transfer of photogenerated electrons (e) from g-C3N4 to MXene. Moreover, g-C3N4@V2C MXene photocatalyst showed good cycling stability. The photocatalytic performance was higher than 85% after three cycles. Experiments to capture free radicals revealed that superoxide radicals (02) are the main contributors to the photocatalytic activity. Thus, the proposed g-C3N4@V2C MXene photocatalyst is a promising visible-light catalyst.Comment: 20 pages, 9 figure

Deep Learning Applications Based on WISE Infrared Data: Classification of Stars, Galaxies and Quasars

The Wide-field Infrared Survey Explorer (WISE) has detected hundreds of millions of sources over the entire sky. However, classifying them reliably is a great challenge due to degeneracies in WISE multicolor space and low detection levels in its two longest-wavelength bandpasses. In this paper, the deep learning classification network, IICnet (Infrared Image Classification network), is designed to classify sources from WISE images to achieve a more accurate classification goal. IICnet shows good ability on the feature extraction of the WISE sources. Experiments demonstrates that the classification results of IICnet are superior to some other methods; it has obtained 96.2% accuracy for galaxies, 97.9% accuracy for quasars, and 96.4% accuracy for stars, and the Area Under Curve (AUC) of the IICnet classifier can reach more than 99%. In addition, the superiority of IICnet in processing infrared images has been demonstrated in the comparisons with VGG16, GoogleNet, ResNet34, MobileNet, EfficientNetV2, and RepVGG-fewer parameters and faster inference. The above proves that IICnet is an effective method to classify infrared sources

The causal relationship between COVID-19 and ten esophageal diseases: a study utilizing Mendelian randomization

BackgroundClinical signs of dysphagia, pancreatic achalasia, and esophagitis have been reported in patients with COVID-19. However, the causal relationship between COVID-19 and esophageal diseases is not clear. Therefore, we utilized Mendelian randomization to explore the potential association between COVID-19 and esophageal diseases.MethodsThe summary statistics for a Genome-wide association study (GWAS) were obtained from The COVID-19 Host Genetics Initiative, encompassing four types of COVID-19 as exposure: severe COVID-19, hospitalized COVID-19 versus ambulatory COVID-19, hospitalized COVID-19 versus uninfected, and confirmed COVID-19. Additionally, summary statistics for ten esophageal diseases as outcomes were sourced from the GWAS Catalog and FinnGen databases. Univariate Mendelian randomization (MR) analysis was utilized to thoroughly investigate and validate the potential causal association between COVID-19 and various esophageal conditions, including esophageal varices, Barrett’s esophagus, esophagitis, esophageal obstruction, esophageal ulcer, esophageal perforation, gastroesophageal reflux, congenital esophageal malformations, benign esophageal tumors, and esophageal adenocarcinoma.ResultsAn inverse variance-weighted (IVW) model was utilized for univariate Mendelian randomization (MR) analysis, which revealed that genetic liability in patients with confirmed COVID-19 was associated with esophageal obstruction (OR [95% CI]: 0.5275458 [0.2822400–0.9860563]; p-value = 0.0450699). Furthermore, a suggestive causal association was found between genetic liability and a reduced risk of benign esophageal tumors (OR [95% CI]: 0.2715453 [0.09368493–0.7870724]; p-value = 0.0163510), but with a suggestively increased risk of congenital esophageal malformations (OR [95% CI]: 6.959561 [1.1955828–40.51204]; p-value = 0.03086835). Additionally, genetic liability in hospitalized COVID-19 patients, compared to non-hospitalized COVID-19 patients, was suggestively associated with an increased risk of esophagitis (OR [95% CI]: 1.443859 [1.0890568–1.914252]; p-value = 0.01068201). The reliability of these causal findings is supported by Cochran’s Q statistic and the MR-Egger intercept test.ConclusionThe results of this study suggest the existence of a causal relationship between COVID-19 and esophageal diseases, highlighting differing risk effects of COVID-19 on distinct esophageal conditions

Toxic Markers of Matrine Determined Using 1

Matrine is one of the main bioactive alkaloids of Sophora flavescens Aiton, which has been widely used to treat various diseases in China. These diseases include viral hepatitis, liver fibrosis, cardiac arrhythmia, skin diseases, and tumors. However, matrine is also the main toxic compound of this herb, and the available biomarkers are not reliable in detecting or quantifying matrine risk. Metabolomics is a powerful tool used to identify early toxicity biomarkers that are specific indicators of damage to biosystems. This study aimed to find the potential biomarkers of the matrine-induced toxic effects in rats and HepG2 cells. The toxicological effects of rats induced by matrine could be derived from the elevated taurine and trimethylamine N-oxide levels and the depletion in hippurate and tricarboxylic acid cycle intermediates, such as 2-oxoglutarate, citrate, and succinate in the urine. Cell metabolomics revealed that the levels of alanine, choline, glutathione, lactate, phosphocholine, and cholesterol showed dose-dependent decreases, whereas the levels of taurine, fatty acid, and unsaturated fatty acid showed dose-dependent increases. Overall, a significant perturbation of metabolites in response to high dose of matrine was observed both in vivo and in vitro, and the selected metabolites particularly represent an attractive marker for matrine-induced toxicity

The Herbal Combination of Radix astragali, Radix angelicae sinensis, and Caulis lonicerae Regulates the Functions of Type 2 Innate Lymphocytes and Macrophages Contributing to the Resolution of Collagen-Induced Arthritis

Type 2 innate lymphocytes (ILC2s), promoting inflammation resolution, was a potential target for rheumatoid arthritis (RA) treatment. Our previous studies confirmed that R. astragali and R. angelicae sinensis could intervene in immunologic balance of T lymphocytes. C. lonicerae also have anti-inflammatory therapeutic effects. In this study, the possible molecular mechanisms of the combination of these three herbs for the functions of ILC2s and macrophages contributing to the resolution of collagen-induced arthritis (CIA) were studied. Therefore, we used R. astragali, R. angelicae sinensis, and C. lonicerae as treatment. The synovial inflammation and articular cartilage destruction were alleviated after herbal treatment. The percentages of ILC2s and Tregs increased significantly. The differentiation of Th17 cells and the secretion of IL-17 and IFN-γ significantly decreased. In addition, treatment by the combination of these three herbs could increase the level of anti-inflammatory cytokine IL-4 secreted, active the STAT6 signaling pathway, and then contribute to the transformation of M1 macrophages to M2 phenotype. The combination of the three herbs could promote inflammation resolution of synovial tissue by regulating ILC2s immune response network. The synergistic effects of three drugs were superior to the combination of R. astragali and R. angelicae sinensis or C. lonicerae alone

Immune Protection Induced on Day 10 Following Administration of the 2009 A/H1N1 Pandemic Influenza Vaccine

BACKGROUND: The 2009 swine-origin influenza virus (S-OIV) H1N1 pandemic has caused more than 18,000 deaths worldwide. Vaccines against the 2009 A/H1N1 influenza virus are useful for preventing infection and controlling the pandemic. The kinetics of the immune response following vaccination with the 2009 A/H1N1 influenza vaccine need further investigation. METHODOLOGY/PRINCIPAL FINDINGS: 58 volunteers were vaccinated with a 2009 A/H1N1 pandemic influenza monovalent split-virus vaccine (15 µg, single-dose). The sera were collected before Day 0 (pre-vaccination) and on Days 3, 5, 10, 14, 21, 30, 45 and 60 post vaccination. Specific antibody responses induced by the vaccination were analyzed using hemagglutination inhibition (HI) assay and enzyme-linked immunosorbent assay (ELISA). After administration of the 2009 A/H1N1 influenza vaccine, specific and protective antibody response with a major subtype of IgG was sufficiently developed as early as Day 10 (seroprotection rate: 93%). This specific antibody response could maintain for at least 60 days without significant reduction. Antibody response induced by the 2009 A/H1N1 influenza vaccine could not render protection against seasonal H1N1 influenza (seroconversion rate: 3% on Day 21). However, volunteers with higher pre-existing seasonal influenza antibody levels (pre-vaccination HI titer ≥1∶40, Group 1) more easily developed a strong antibody protection effect against the 2009 A/H1N1 influenza vaccine as compared with those showing lower pre-existing seasonal influenza antibody levels (pre-vaccination HI titer <1∶40, Group 2). The titer of the specific antibody against the 2009 A/H1N1 influenza was much higher in Group 1 (geometric mean titer: 146 on Day 21) than that in Group 2 (geometric mean titer: 70 on Day 21). CONCLUSIONS/SIGNIFICANCE: Recipients could gain sufficient protection as early as 10 days after vaccine administration. The protection could last at least 60 days. Individuals with a stronger pre-existing seasonal influenza antibody response may have a relatively higher potential for developing a stronger humoral immune response after vaccination with the 2009 A/H1N1 pandemic influenza vaccine

MiR-137 Targets Estrogen-Related Receptor Alpha and Impairs the Proliferative and Migratory Capacity of Breast Cancer Cells

ERRα is an orphan nuclear receptor emerging as a novel biomarker of breast cancer. Over-expression of ERRα in breast tumor is considered as a prognostic factor of poor clinical outcome. The mechanisms underlying the dysexpression of this nuclear receptor, however, are poorly understood. MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level and play important roles in tumor initiation and progression. In the present study, we have identified that the expression of ERRα is regulated by miR-137, a potential tumor suppressor microRNA. The bioinformatics search revealed two putative and highly conserved target-sites for miR-137 located within the ERRα 3′UTR at nt 480–486 and nt 596–602 respectively. Luciferase-reporter assay demonstrated that the two predicted target sites were authentically functional. They mediated the repression of reporter gene expression induced by miR-137 in an additive manner. Moreover, ectopic expression of miR-137 down-regulated ERRα expression at both protein level and mRNA level, and the miR-137 induced ERRα-knockdown contributed to the impaired proliferative and migratory capacity of breast cancer cells. Furthermore, transfection with miR-137mimics suppressed at least two downstream target genes of ERRα–CCNE1 and WNT11, which are important effectors of ERRα implicated in tumor proliferation and migration. Taken together, our results establish a role of miR-137 in negatively regulating ERRα expression and breast cancer cell proliferation and migration. They suggest that manipulating the expression level of ERRα by microRNAs has the potential to influence breast cancer progression