Consequences of Supergravity with Gauged U(1)R\rm U(1)_R Symmetry

The structure of gauged R supergravity Lagrangians is reviewed, and we consider models with a hidden sector plus light fields of the MSSM. A simple potential for the hidden sector is presented which has a global minimum with zero cosmological constant and spontaneously broken SUSY and R-symmetry. The $\rm U(1)_R$ vector multiplet acquires a Planck scale mass through the Higgs mechanism, and it decouples at low energy. Due to very interesting cancellations, the $\rm U(1)_R$ D-terms also drop out at low energy. Thus no direct effects of the gauging of R-symmetry remain in the low energy effective Lagrangian, and this result is model independent, requiring only that R-symmetry be broken at the Planck scale and $= 0$, where $D$ is the auxiliary field of the $\rm U(1)_R$ vector multiplet. The low energy theory is fairly conventional with soft SUSY breaking terms for the MSSM fields. As a remnant of the gauging of R-symmetry, it also contains light fields, some required to cancel R-anomalies and others from the hidden sector.Comment: 36 pages, plain LaTeX, all macros included, no figure

R-mediation of Dynamical Supersymmetry Breaking

We propose a simple scenario of the dynamical supersymmetry breaking in four dimensional supergravity theories. The supersymmetry breaking sector is assumed to be completely separated as a sequestered sector from the visible sector, except for the communication by the gravity and U(1)_R gauge interactions, and the supersymmetry breaking is mediated by the superconformal anomaly and U(1)_R gauge interaction. Supersymmetry is dynamically broken by the interplay between the non-perturbative effect of the gauge interaction and Fayet-Iliopoulos D-term of U(1)_R which necessarily exists in supergravity theories with gauged U(1)_R symmetry. We construct an explicit model which gives phenomenologically acceptable mass spectrum of superpartners with vanishing (or very small) cosmological constant.Comment: 12 pages, to be published in Phys. Rev.

Scale dependence of the quark masses and mixings: leading order

We consider the Renormalization Group Equations (RGE) for the couplings of the Standard Model and its extensions. Using the hierarchy of the quark masses and of the Cabibbo-Kobayashi-Maskawa (CKM) matrix our argument is that a consistent approximation for the RGE should be based on the parameter $\lambda= |\hat{V}_{ud}| \approx0.22$. We consider the RGE in the approximation where we neglect all the relative terms of the order $\sim\lambda^{4}$ and higher. Within this approximation we find the exact solution of the evolution equations of the quark Yukawa couplings and of the vacuum expectation value of the Higgs field. Then we derive the evolution of the observables: quark masses, CKM matrix, Jarlskog invariant, Wolfenstein parameters of the CKM matrix and the unitarity triangle. We show that the angles of the unitarity triangle remain constant. This property may restrict the possibility of new symmetries or textures at the grand unification scale.Comment: 15 pages, 4 figures, author of one reference adde

Electron and Neutron Electric Dipole Moments in the Constrained MSSM

We analyze the effects of CP-violating phases on the electric dipole moment (EDM) of electron and neutron in the constrained minimal supersymmetric model. We find that the phases phi_{\mu} and phi_{A_0} have to be strongly correlated, in particular for small values of the SUSY mass parameters. We calculate the neutron EDM in two different models, the Quark-Parton Model and the Chiral Quark Model. It turns out that the predictions are quite sensitive to the model used. We show parameter regions in the M_0-M_1/2 plane which are excluded by considering simultaneously the experimental bounds of both electron and neutron EDM, assuming specific values for the phases phi_{\mu} and phi_{A_0}.Comment: 23 pages LaTeX with 8 figures included, using the epsfig-stylefil

Signatures of Baryon non-conserving Yukawa couplings in a supersymmetric theory

Renormalization effects of large baryon-nonconserving Yukawa couplings $\lambda^{\prime\prime}_{ijk} \overline{U_i} \overline{D_j} \overline{D_k}$ lower the right handed squark masses keeping the left-handed squark masses virtually untouched at the lowest order. At low energy they enhance the mass-splitting between left and right handed squarks of the same generation as well as intergenerational mass splitting among squarks, potentially detectable in future colliders or in rare decays. The predicted mass of the lightest stop squark becomes lower than the experimental bound for larger ranges of parameter space than that of the Baryon-conserving case, hence, further constraining the parameter space of a supersymmetric theory when baryon violation is included.Comment: 16 pages, six figures, captions.sty include

Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries