Did the nHZ Gravitational Waves Signatures Observed By NANOGrav Indicate Multiple Sector SUSY Breaking?

Discrete R symmetries always play an important role in low energy SUSY. The spontaneously broken of such discrete R symmetries, for example, by gaugino condensation, can lead to domain walls, which need to be either inflated away or collapse to avoid cosmic difficulties. We propose that explicitly R symmetry violation needed for collapse of domain walls can be the consequence of multiple sector SUSY breaking. The consistency constraints for the generation of non-problematic domain walls from gaugino condensation are discussed. We also study the emitted gravitational waves related to the collapse of domain walls. We find that, for SUSY breaking scale of order ${\cal O}(1)$ ${\rm GeV}$ in one of the sequestered sector (and also a low reheating temperature of order ${\rm MeV}$ if the reheating is not completed when the domain walls collapse), the peak frequency of gravitational waves emitted can lie at nHz. Such a low SUSY breaking scale can be consistency and natural in multiple sector SUSY breaking scenario. The GWs signal by NANOGrav could be a signal of such multiple sector SUSY breaking scenario and it may also indicate the existences of light goldstini at ${\rm eV}$ mass scale.Comment: 13 page

Kinematics of the Broad-line Region of 3C 273 from a Ten-year Reverberation Mapping Campaign

Despite many decades of study, the kinematics of the broad-line region of 3C~273 are still poorly understood. We report a new, high signal-to-noise, reverberation mapping campaign carried out from November 2008 to March 2018 that allows the determination of time lags between emission lines and the variable continuum with high precision. The time lag of variations in H$\beta$ relative to those of the 5100 Angstrom continuum is $146.8_{-12.1}^{+8.3}$ days in the rest frame, which agrees very well with the Paschen-$\alpha$ region measured by the GRAVITY at The Very Large Telescope Interferometer. The time lag of the H$\gamma$ emission line is found to be nearly the same as for H$\beta$. The lag of the Fe II emission is $322.0_{-57.9}^{+55.5}$ days, longer by a factor of $\sim$2 than that of the Balmer lines. The velocity-resolved lag measurements of the H$\beta$ line show a complex structure which can be possibly explained by a rotation-dominated disk with some inflowing radial velocity in the H$\beta$-emitting region. Taking the virial factor of $f_{\rm BLR} = 1.3$, we derive a BH mass of $M_{\bullet} = 4.1_{-0.4}^{+0.3} \times 10^8 M_{\odot}$ and an accretion rate of $9.3\,L_{\rm Edd}\,c^{-2}$ from the H$\beta$ line. The decomposition of its $HST$ images yields a host stellar mass of $M_* = 10^{11.3 \pm 0.7} M_\odot$, and a ratio of $M_{\bullet}/M_*\approx 2.0\times 10^{-3}$ in agreement with the Magorrian relation. In the near future, it is expected to compare the geometrically-thick BLR discovered by the GRAVITY in 3C 273 with its spatially-resolved torus in order to understand the potential connection between the BLR and the torus.Comment: 17 pages, 12 figures, 6 tables, accepted for publication in The Astrophysical Journa

Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer

HPLC method for the simultaneous determination of four compounds in rat plasma after intravenous administration of Portulaca oleracea L. extract

O objetivo do estudo foi desenvolver um método simples e específico de HPLC para a determinação simultânea de hesperidina (HP), ácido caféico (CA), ácido ferúlico (FA) e ácido p-cumárico (p-CA) em plasma de rato após a administração intravenosa de extrato Portulaca oleracea L. (POE) empregando hyperosídeo como padrão interno de referência. Metanol foi empregado para os analitos em plasma (0,2 mL). A fase móvel isocrática foi composta por metanol-acetonitrila-tetraidrofurano-0,5% ácido acético glacial (5:3:18:74, v/v/v/v). Curvas de calibração foram lineares na faixa de concentração de 0,1-25 µg mL-1, 0,1-25 µg mL-1, 0,1-25 µg mL-1 e 0,015-3 µg mL-1 para HP, CA, FA e p-CA, respectivamente. O método desenvolvido foi adequado para estudo farmacocinético de HP, CA, FA e p-CA em ratos após a administração intravenosa de POE.The objective of the present study was to develop a simple and selective HPLC method for the simultaneous determination of hesperidin (HP), caffeic acid (CA), ferulic acid (FA) and p-coumaric acid (p-CA) in rat plasma after intravenous administration of Portulaca oleracea L. extract (POE). With the hyperoside as the internal standard, the sample pretreatment procedure involved simple single-step extraction with methanol of 0.2 mL plasma. The mobile phase consisted of methanol-acetonitrile-tetrahydrofuran-0.5% glacial acetic acid (5:3:18:74, v/v/v/v). The calibration curves were linear over the range of 0.1-25 µg mL-1, 0.1-25 µg mL-1, 0.1-25 µg mL-1and 0.015-3 µg mL-1 for HP, CA, FA and p-CA, respectively. The method developed was suitable for the pharmacokinetic study of HP, CA, FA and p-CA in rats after intravenous administration of POE

Genetic Polymorphisms In Estrogen-related Genes And The Risk Of Breast Cancer Among Han Chinese Women

Exposure to high levels of estrogen is considered an important risk factor for susceptibility to breast cancer. Common polymorphisms in genes that affect estrogen levels may be associated with breast cancer risk, but no comprehensive study has been performed among Han Chinese women. In the present study, 32 single-nucleotide polymorphisms (SNPs) in estrogen-related genes were genotyped using the MassARRAY IPLEX platform in 1076 Han Chinese women. Genotypic and allelic frequencies were compared between case and control groups. Unconditional logistic regression was used to assess the effects of SNPs on breast cancer risk. Associations were also evaluated for breast cancer subtypes stratified by estrogen receptor (ER) and progesterone receptor (PR) status. Case-control analysis showed a significant relation between heterozygous genotypes of rs700519 and rs2069522 and breast cancer risk (OR = 0.723, 95% CI = 0.541-0.965, p = 0.028 and OR = 1.500, 95% CI = 1.078-2.087, p = 0.016, respectively). Subgroup comparisons revealed that rs2446405 and rs17268974 were related to ER status, and rs130021 was associated with PR status. Our findings suggest that rs700519 and rs2069522 are associated with susceptibility to breast cancer among the Han Chinese population and have a cumulative effect with three other identified SNPs. Further genetic and functional studies are needed to identify additional SNPs, and to elucidate the underlying molecular mechanisms