Impact of Single-Top Measurement to Littlest Higgs Model with T-Parity

We show that a precise measurement of the single-top production cross section at the Tevatron and the LHC can strongly constrain the model parameters of the Littlest Higgs model with T-parity. A reduction in the single-top production rate from the Standard Model prediction implies new physics phenomena generated by the heavy T-parity partners of the top quark. We show that the degree of polarization of the top quark produced from the decay of its heavy T-odd partner ($T_{-}$) can be utilized to determine the new physics energy scale, and the mass of $T_{-}$ can be measured from the missing transverse momentum distribution in the $T_{-}\bar{T}_{-}$ event

Search for New Physics via Single Top Production at the LHC

We consider single-top production as a probe for new physics effects at the Large Hadron Collider (LHC). We argue that for natural theories a small deviation from the Standard Model tree-level couplings in this reaction can be parameterized by 3 higher dimension operators. Precision measurement of these effective couplings in the single-top events, via studying their interference effects with the SM contributions, can discriminate several new physics models. In particular, combining the production rate of three single-top production modes will provide a severe test of the Little Higgs model with T-parity. We find that at the LHC, a 5% accuracy in the measurement of the single-top cross sections would probe the new physics scale up to about $3 {\rm TeV}$.Comment: version to appear in Physics Letters

Monitoring for airborne respiratory viruses in a general pediatric ward in Singapore

There is an increasing body of evidence suggesting that transmission of respiratory viruses occurs through the inhalation of virus-laden particles. Our study describes the use of an aerosol sampling system to monitor the prevalence of airborne viruses in a hospital setting. Using SKC AirCheck Touch pumps, with National Institute for Occupational Safety and Health (NIOSH) bioaerosol samplers and SKC filter cassette blanks, 28 aerosol samples were collected in a hospital ward in Singapore. Following DNA/RNA extraction, real-time RT-PCR/PCR was used for the detection of influenza A, B and D viruses, coronaviruses, enteroviruses, and adenoviruses. Airborne virus was detected in nine (32%) of 28 samples. Among the nine positive samples, eight were PCR-positive for adenovirus and one for influenza A virus. Our data suggest that bioaerosol sampling could be valuable in monitoring for airborne respiratory viruses in clinical environments to better understand the risk of infection during a hospital visit

NUCKS Is a Positive Transcriptional Regulator of Insulin Signaling.

published_or_final_versio

Unitarity of Little Higgs Models Signals New Physics of UV Completion

The ``Little Higgs'' opens up a new avenue for natural electroweak symmetry breaking in which the standard model Higgs particle is realized as a pseudo-Goldstone boson and thus is generically light. The symmetry breaking structure of the Little Higgs models predicts a large multiplet of (pseudo-)Goldstone bosons and their low energy interactions below the ultraviolet (UV) completion scale $\Lambda \sim 4\pi f \sim O(10)$ TeV, where $f$ is the Goldstone decay constant. We study unitarity of the Little Higgs models by systematically analyzing the high energy scatterings of these (pseudo-)Goldstone bosons. We reveal that the collective effect of the Goldstone scatterings via coupled channel analysis tends to push the unitarity violation scale $\Lambda_U$ significantly below the conventional UV scale $\Lambda \sim 4\pi f$ as estimated by naive dimensional analysis (NDA). Specifically, $\Lambda_U \sim (3-4)f$, lying in the multi-TeV range for $f\sim 1$ TeV. We interpret this as an encouraging sign that the upcoming LHC may explore aspects of Little Higgs UV completions, and we discuss some potential signatures. The meanings of the two estimated UV scales $\Lambda_U$ (from unitarity violation) and $\Lambda$ (from NDA) together with their implications for an effective field theory analysis of the Little Higgs models are also discussed.Comment: To match Phys.Lett.B version (9pp, only minor rewording

Associated production of the scalars and new gauge bosons from a little Higgs model at the LHC

The littlest Higgs model with T-parity ($LHT$ model) predicts the existence of the T-odd scalars ($\phi^{\pm}$, $\phi^{0}$, and $\phi^{p}$). We consider production of these new particles associated with T-odd gauge bosons at the $LHC$. We find that the partonic process $q\bar{q'}\to\phi^{+}B_{H}$ can generate a number of the characteristic signal events with a charged lepton and large missing energy at the $LHC$.Comment: 11 pages, 3 figure

Linear B-cell epitopes in the spike and nucleocapsid proteins as markers of SARS-CoV-2 exposure and disease severity

BACKGROUND Given the unceasing worldwide surge in COVID-19 cases, there is an imperative need to develop highly specific and sensitive serology assays to define exposure to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). METHODS Pooled plasma samples from PCR positive COVID-19 patients were used to identify linear B-cell epitopes from a SARS-CoV-2 peptide library of spike (S), envelope (E), membrane (M), and nucleocapsid (N) structural proteins by peptide-based ELISA. Hit epitopes were further validated with 79 COVID-19 patients with different disease severity status, 13 seasonal human CoV, 20 recovered SARS patients and 22 healthy donors. FINDINGS Four immunodominant epitopes, S14P5, S20P2, S21P2 and N4P5, were identified on the S and N viral proteins. IgG responses to all identified epitopes displayed a strong detection profile, with N4P5 achieving the highest level of specificity (100%) and sensitivity (>96%) against SARS-CoV-2. Furthermore, the magnitude of IgG responses to S14P5, S21P2 and N4P5 were strongly associated with disease severity. INTERPRETATION IgG responses to the peptide epitopes can serve as useful indicators for the degree of immunopathology in COVID-19 patients, and function as higly specific and sensitive sero-immunosurveillance tools for recent or past SARS-CoV-2 infections. The flexibility of these epitopes to be used alone or in combination will allow for the development of improved point-of-care-tests (POCTs)

Genomewide association study of leprosy.

BACKGROUND: The narrow host range of Mycobacterium leprae and the fact that it is refractory to growth in culture has limited research on and the biologic understanding of leprosy. Host genetic factors are thought to influence susceptibility to infection as well as disease progression. METHODS: We performed a two-stage genomewide association study by genotyping 706 patients and 1225 controls using the Human610-Quad BeadChip (Illumina). We then tested three independent replication sets for an association between the presence of leprosy and 93 single-nucleotide polymorphisms (SNPs) that were most strongly associated with the disease in the genomewide association study. Together, these replication sets comprised 3254 patients and 5955 controls. We also carried out tests of heterogeneity of the associations (or lack thereof) between these 93 SNPs and disease, stratified according to clinical subtype (multibacillary vs. paucibacillary). RESULTS: We observed a significant association (P<1.00x10(-10)) between SNPs in the genes CCDC122, C13orf31, NOD2, TNFSF15, HLA-DR, and RIPK2 and a trend toward an association (P=5.10x10(-5)) with a SNP in LRRK2. The associations between the SNPs in C13orf31, LRRK2, NOD2, and RIPK2 and multibacillary leprosy were stronger than the associations between these SNPs and paucibacillary leprosy. CONCLUSIONS: Variants of genes in the NOD2-mediated signaling pathway (which regulates the innate immune response) are associated with susceptibility to infection with M. leprae

<i>Neisseria</i> species as pathobionts in bronchiectasis

Neisseria species are frequently identified in the bronchiectasis microbiome, but they are regarded as respiratory commensals. Using a combination of human cohorts, next-generation sequencing, systems biology, and animal models, we show that bronchiectasis bacteriomes defined by the presence of Neisseria spp. associate with poor clinical outcomes, including exacerbations. Neisseria subflava cultivated from bronchiectasis patients promotes the loss of epithelial integrity and inflammation in primary epithelial cells. In vivo animal models of Neisseria subflava infection and metabolipidome analysis highlight immunoinflammatory functional gene clusters and provide evidence for pulmonary inflammation. The murine metabolipidomic data were validated with human Neisseria-dominant bronchiectasis samples and compared with disease in which Pseudomonas-, an established bronchiectasis pathogen, is dominant. Metagenomic surveillance of Neisseria across various respiratory disorders reveals broader importance, and the assessment of the home environment in bronchiectasis implies potential environmental sources of exposure. Thus, we identify Neisseria species as pathobionts in bronchiectasis, allowing for improved risk stratification in this high-risk group.Published versio

An Improved PSO Algorithm for Generating Protective SNP Barcodes in Breast Cancer

BACKGROUND: Possible single nucleotide polymorphism (SNP) interactions in breast cancer are usually not investigated in genome-wide association studies. Previously, we proposed a particle swarm optimization (PSO) method to compute these kinds of SNP interactions. However, this PSO does not guarantee to find the best result in every implement, especially when high-dimensional data is investigated for SNP-SNP interactions. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we propose IPSO algorithm to improve the reliability of PSO for the identification of the best protective SNP barcodes (SNP combinations and genotypes with maximum difference between cases and controls) associated with breast cancer. SNP barcodes containing different numbers of SNPs were computed. The top five SNP barcode results are retained for computing the next SNP barcode with a one-SNP-increase for each processing step. Based on the simulated data for 23 SNPs of six steroid hormone metabolisms and signalling-related genes, the performance of our proposed IPSO algorithm is evaluated. Among 23 SNPs, 13 SNPs displayed significant odds ratio (OR) values (1.268 to 0.848; p<0.05) for breast cancer. Based on IPSO algorithm, the jointed effect in terms of SNP barcodes with two to seven SNPs show significantly decreasing OR values (0.84 to 0.57; p<0.05 to 0.001). Using PSO algorithm, two to four SNPs show significantly decreasing OR values (0.84 to 0.77; p<0.05 to 0.001). Based on the results of 20 simulations, medians of the maximum differences for each SNP barcode generated by IPSO are higher than by PSO. The interquartile ranges of the boxplot, as well as the upper and lower hinges for each n-SNP barcode (n = 3∼10) are more narrow in IPSO than in PSO, suggesting that IPSO is highly reliable for SNP barcode identification. CONCLUSIONS/SIGNIFICANCE: Overall, the proposed IPSO algorithm is robust to provide exact identification of the best protective SNP barcodes for breast cancer