Dirac Leptogenesis with a Non-anomalous U(1)′U(1)^{\prime} Family Symmetry

We propose a model for Dirac leptogenesis based on a non-anomalous $U(1)^{\prime}$ gauged family symmetry. The anomaly cancellation conditions are satisfied with no new chiral fermions other than the three right-handed neutrinos, giving rise to stringent constraints among the charges. Realistic masses and mixing angles are obtained for all fermions. The model predicts neutrinos of the Dirac type with naturally suppressed masses. Dirac leptogenesis is achieved through the decay of the flavon fields. The cascade decays of the vector-like heavy fermions in the Froggatt-Nielsen mechanism play a crucial role in the separation of the primodial lepton numbers. We find that a large region of parameter space of the model gives rise to a sufficient cosmological baryon number asymmetry through Dirac leptogenesis.Comment: 8 pages, 8 figures, version to appear in JHE

Regulation of a rat VL30 element in human breast cancer cells in hypoxia and anoxia: role of HIF-1

Novel approaches to cancer gene therapy currently exploit tumour hypoxia to achieve transcriptional targeting using oxygen-regulated enhancer elements called hypoxia response elements. The activity of such elements in hypoxic cells is directly dependent on upregulation of the hypoxia-inducible transcription factor-1 However tumours also contain areas of anoxia, which may be considered a more tumour-selective transcriptional stimulus than hypoxia for targeting gene therapy to tumours. Another element, from the rat virus-like retrotransposon, VL30 (termed the ‘secondary anoxia response element’) has been reported to be more highly inducible in rat fibroblasts under anoxia than hypoxia. To investigate anoxia as a potential transcriptional target in human tumours, we have examined secondary anoxia response element inducibility in two human breast cancer cell lines, MCF-7 and T47D, under anoxia, hypoxia and normoxia. In both cell types, the trimerised secondary anoxia response element showed greater inducibility in anoxia than hypoxia (1% and 0.5% O2). The anoxic response of the secondary anoxia response element was shown to be dependent on hypoxia-inducible transcription factor-1 and the presence of a hypoxia-inducible transcription binding site consensus (5′-ACGTG-3′). Mutational analysis demonstrated that the base immediately 5′ to this modulates the anoxic/hypoxic induction of the secondary anoxia response element, such that TACGTG>GACGTG>>CACGTG. A similar correlation was found for erythropoietin, phosphoglycerate kinase 1, and aldolase hypoxia response elements, which contain these respective 5′ flanking bases

The clinical significance of serum and bronchoalveolar lavage inflammatory cytokines in patients at risk for Acute Respiratory Distress Syndrome

BACKGROUND: The predictive role of many cytokines has not been well defined in Acute Respiratory Distress Syndrome (ARDS). METHODS: We measured prospectively IL-4, IL-6, IL-6 receptor, IL-8, and IL-10, in the serum and bronchoalveolar lavage fluid (BALF) in 59 patients who were admitted to ICU in order to identify predictive factors for the course and outcome of ARDS. The patients were divided into three groups: those fulfilling the criteria for ARDS (n = 20, group A), those at risk for ARDS and developed ARDS within 48 hours (n = 12, group B), and those at risk for ARDS but never developed ARDS (n = 27, group C). RESULTS: An excellent negative predictive value for ARDS development was found for IL-6 in BALF and serum (100% and 95%, respectively). IL-8 in BALF and IL-8 and IL-10 serum levels were higher in non-survivors in all studied groups, and were associated with a high negative predictive value. A significant correlation was found between IL-8 and APACHE score (r = 0.60, p < 0.0001). Similarly, IL-6 and IL-6r were highly correlated with PaO2/FiO2 (r = -0.27, p < 0.05 and r = -0.55, p < 0.0001, respectively). CONCLUSIONS: BALF and serum levels of the studied cytokines on admission may provide valuable information for ARDS development in patients at risk, and outcome in patients either in ARDS or in at risk for ARDS

Measuring Invisible Particle Masses Using a Single Short Decay Chain

We consider the mass measurement at hadron colliders for a decay chain of two steps, which ends with a missing particle. Such a topology appears as a subprocess of signal events of many new physics models which contain a dark matter candidate. From the two visible particles coming from the decay chain, only one invariant mass combination can be formed and hence it is na\"ively expected that the masses of the three invisible particles in the decay chain cannot be determined from a single end point of the invariant mass distribution. We show that the event distribution in the $\log(E_{1T}/E_{2T})$ vs. invariant mass-squared plane, where $E_{1T}$, $E_{2T}$ are the transverse energies of the two visible particles, contains the information of all three invisible particle masses and allows them to be extracted individually. The experimental smearing and combinatorial issues pose challenges to the mass measurements. However, in many cases the three invisible particle masses in the decay chain can be determined with reasonable accuracies.Comment: 45 pages, 32 figure

Differentiating Embryonic Stem Cells Pass through ‘Temporal Windows’ That Mark Responsiveness to Exogenous and Paracrine Mesendoderm Inducing Signals

BACKGROUND: Mesendoderm induction during embryonic stem cell (ESC) differentiation in vitro is stimulated by the Transforming Growth Factor and Wingless (Wnt) families of growth factors. PRINCIPAL FINDINGS: We identified the periods during which Bone Morphogenetic Protein (BMP) 4, Wnt3a or Activin A were able to induce expression of the mesendoderm marker, Mixl1, in differentiating mouse ESCs. BMP4 and Wnt3a were required between differentiation day (d) 1.5 and 3 to most effectively induce Mixl1, whilst Activin A induced Mixl1 expression in ESC when added between d2 and d4, indicating a subtle difference in the requirement for Activin receptor signalling in this process. Stimulation of ESCs with these factors at earlier or later times resulted in little Mixl1 induction, suggesting that the differentiating ESCs passed through 'temporal windows' in which they sequentially gained and lost competence to respond to each growth factor. Inhibition of either Activin or Wnt signalling blocked Mixl1 induction by any of the three mesendoderm-inducing factors. Mixing experiments in which chimeric EBs were formed between growth factor-treated and untreated ESCs revealed that BMP, Activin and Wnt signalling all contributed to the propagation of paracrine mesendoderm inducing signals between adjacent cells. Finally, we demonstrated that the differentiating cells passed through 'exit gates' after which point they were no longer dependent on signalling from inducing molecules for Mixl1 expression. CONCLUSIONS: These studies suggest that differentiating ESCs are directed by an interconnected network of growth factors similar to those present in early embryos and that the timing of growth factor activity is critical for mesendoderm induction

Exploring novel correlations in trilepton channels at the LHC for the minimal supersymmetric inverse seesaw model

We investigate signatures of the minimal supersymmetric inverse seesaw model at the large hadron collider (LHC) with three isolated leptons and large missing energy (3\ell + \mET or 2\ell + 1\tau + \mET, with \ell=e,\mu) in the final state. This signal has its origin in the decay of chargino-neutralino (\chpm1\ntrl2) pair, produced in pp collisions. The two body decays of the lighter chargino into a charged lepton and a singlet sneutrino has a characteristic decay pattern which is correlated with the observed large atmospheric neutrino mixing angle. This correlation is potentially observable at the LHC by looking at the ratios of cross sections of the trilepton + \mET channels in certain flavour specific modes. We show that even after considering possible leading standard model backgrounds these final states can lead to reasonable discovery significance at the LHC with both 7 TeV and 14 TeV center-of-mass energy.Comment: 28 pages, 9 .eps figures. 3 new figures and discussions on LHC observables added, minor modifications in text and in the abstract, 23 new references added, matches with the published version in JHE

Closing in on Asymmetric Dark Matter I: Model independent limits for interactions with quarks

It is argued that experimental constraints on theories of asymmetric dark matter (ADM) almost certainly require that the DM be part of a richer hidden sector of interacting states of comparable mass or lighter. A general requisite of models of ADM is that the vast majority of the symmetric component of the DM number density must be removed in order to explain the observed relationship $\Omega_B\sim\Omega_{DM}$ via the DM asymmetry. Demanding the efficient annihilation of the symmetric component leads to a tension with experimental limits if the annihilation is directly to Standard Model (SM) degrees of freedom. A comprehensive effective operator analysis of the model independent constraints on ADM from direct detection experiments and LHC monojet searches is presented. Notably, the limits obtained essentially exclude models of ADM with mass 1GeV$\lesssim m_{DM} \lesssim$ 100GeV annihilating to SM quarks via heavy mediator states. This motivates the study of portal interactions between the dark and SM sectors mediated by light states. Resonances and threshold effects involving the new light states are shown to be important for determining the exclusion limits.Comment: 18+6 pages, 18 figures. v2: version accepted for publicatio

Decreased respiratory system compliance on the sixth day of mechanical ventilation is a predictor of death in patients with established acute lung injury

<p>Abstract</p> <p>Background</p> <p>Multiple studies have identified single variables or composite scores that help risk stratify patients at the time of acute lung injury (ALI) diagnosis. However, few studies have addressed the important question of how changes in pulmonary physiologic variables might predict mortality in patients during the subacute or chronic phases of ALI. We studied pulmonary physiologic variables, including respiratory system compliance, P/F ratio and oxygenation index, in a cohort of patients with ALI who survived more than 6 days of mechanical ventilation to see if changes in these variables were predictive of death and whether they are informative about the pathophysiology of subacute ALI.</p> <p>Methods</p> <p>Ninety-three patients with ALI who were mechanically ventilated for more than 6 days were enrolled in this prospective cohort study. Patients were enrolled at two medical centers in the US, a county hospital and a large academic center. Bivariate analyses were used to identify pulmonary physiologic predictors of death during the first 6 days of mechanical ventilation. Predictors on day 1, day 6 and the changes between day 1 and day 6 were compared in a multivariate logistic regression model.</p> <p>Results</p> <p>The overall mortality was 35%. In multivariate analysis, the PaO₂/FiO₂(OR 2.09, p < 0.04) and respiratory system compliance (OR 3.61, p < 0.01) were predictive of death on the 6^thday of acute lung injury. In addition, a decrease in respiratory system compliance between days 1 and days 6 (OR 2.14, p < 0.01) was independently associated with mortality.</p> <p>Conclusions</p> <p>A low respiratory system compliance on day 6 or a decrease in the respiratory system compliance between the 1^stand 6^thday of mechanical ventilation were associated with increased mortality in multivariate analysis of this cohort of patients with ALI. We suggest that decreased respiratory system compliance may identify a subset of patients who have persistent pulmonary edema, atelectasis or the fibroproliferative sequelae of ALI and thus are less likely to survive their hospitalization.</p

Sparse, interpretable and transparent predictive model identification for healthcare data analysis

Data-driven modelling approaches play an indispensable role in analyzing and understanding complex processes. This study proposes a type of sparse, interpretable and transparent (SIT) machine learning model, which can be used to understand the dependent relationship of a response variable on a set of potential explanatory variables. An ideal candidate for such a SIT representation is the well-known NARMAX (nonlinear autoregressive moving average with exogenous inputs) model, which can be established from measured input and output data of the system of interest, and the final refined model is usually simple, parsimonious and easy to interpret. The performance of the proposed SIT models is evaluated through two real healthcare datasets