Wilson Lines and a Canonical Basis of SU(4) Heterotic Standard Models

The spontaneous breaking of SU(4) heterotic standard models by Z_3 x Z_3 Wilson lines to the MSSM with three right-handed neutrino supermultiplets and gauge group SU(3)_C x SU(2)_L x U(1) x U(1) is explored. The two-dimensional subspace of the Spin(10) Lie algebra that commutes with su(3)_C + su(2)_L is analyzed. It is shown that there is a unique basis for which the initial soft supersymmetry breaking parameters are uncorrelated and for which the U(1) x U(1) field strengths have no kinetic mixing at any scale. If the Wilson lines "turn on" at different scales, there is an intermediate regime with either a left-right or a Pati-Salam type model. We compute their spectra directly from string theory, and adjust the associated mass parameter so that all gauge parameters exactly unify. A detailed analysis of the running gauge couplings and soft gaugino masses is presented.Comment: 59 pages, 9 figure

The Minimal Theory for R-parity Violation at the LHC

We investigate the simplest gauge theory for spontaneous R-parity breaking and its testability at the LHC. This theory based on a local B-L gauge symmetry can be considered as the simplest framework for understanding the origin of the R-parity violating interactions, giving rise to potential lepton number violating signals and suppressed baryon number violating operators. The full spectrum of the theory and the constraints coming from neutrino masses are analyzed in great detail. We discuss the proton decay issue and the possible dark matter candidates. In order to assess the testability of the theory we study the properties of the new gauge boson, the neutralino decays and the main production channels for the charged sleptons at the LHC. We find that the channels with four charged leptons, three of them with the same sign, and four jets give us the most striking signals for the testability of lepton number violation at the LHC.Comment: minor corrections, to appear in JHE

R-parity Conservation via the Stueckelberg Mechanism: LHC and Dark Matter Signals

We investigate the connection between the conservation of R-parity in supersymmetry and the Stueckelberg mechanism for the mass generation of the B-L vector gauge boson. It is shown that with universal boundary conditions for soft terms of sfermions in each family at the high scale and with the Stueckelberg mechanism for generating mass for the B-L gauge boson present in the theory, electric charge conservation guarantees the conservation of R-parity in the minimal B-L extended supersymmetric standard model. We also discuss non-minimal extensions. This includes extensions where the gauge symmetries arise with an additional U(1)_{B-L} x U(1)_X, where U(1)_X is a hidden sector gauge group. In this case the presence of the additional U(1)_X allows for a Z' gauge boson mass with B-L interactions to lie in the sub-TeV region overcoming the multi-TeV LEP constraints. The possible tests of the models at colliders and in dark matter experiments are analyzed including signals of a low mass Z' resonance and the production of spin zero bosons and their decays into two photons. In this model two types of dark matter candidates emerge which are Majorana and Dirac particles. Predictions are made for a possible simultaneous observation of new physics events in dark matter experiments and at the LHC.Comment: 38 pages, 7 fig

Cascade Textures and SUSY SO(10) GUT

We give texture analyses of cascade hierarchical mass matrices in supersymmetric SO(10) grand unified theory. We embed cascade mass textures of the standard model fermion with right-handed neutrinos into the theory, which gives relations among the mass matrices of the fermions. The related phenomenologies, such as the lepton flavor violating processes and leptogenesis, are also investigated in addition to the PMNS mixing angles.Comment: 27 pages, 4 figures, comments and references added, final versio

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

Right-handed Sneutrino Dark Matter in Supersymmetric B-L Model

We show that the lightest right-handed sneutrino in TeV scale supersymmetric B-L model with inverse seesaw mechanism is a viable candidate for cold dark matter. We find that it accounts for the observed dark matter relic abundance in a wide range of parameter space. The spin-independent cross section of B-L right-handed sneutrino is consistent with the recent results CDMS II and XENON experiments and it is detectable in future direct detection experiments. Although the B-L right-handed sneutrinos annihilate into leptons, the PAMELA results can not be explained in this model unless a huge boost factor is considered. Also the muon flux generated by B-L right-handed sneutrino in the galactic center is smaller than Super-Kamiokande's upper bound.Comment: 16 pages, 7 figures; version accepted for publication in Journal of High Energy Physic

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

Evaluation and Treatment of Iron Deficiency Anemia: A Gastroenterological Perspective

A substantial volume of the consultations requested of gastroenterologists are directed towards the evaluation of anemia. Since iron deficiency anemia often arises from bleeding gastrointestinal lesions, many of which are malignant, establishment of a firm diagnosis usually obligates an endoscopic evaluation. Although the laboratory tests used to make the diagnosis have not changed in many decades, their interpretation has, and this is possibly due to the availability of extensive testing in key populations. We provide data supporting the use of the serum ferritin as the sole useful measure of iron stores, setting the lower limit at 100 μg/l for some populations in order to increase the sensitivity of the test. Trends of the commonly obtained red cell indices, mean corpuscular volume, and the red cell distribution width can provide valuable diagnostic information. Once the diagnosis is established, upper and lower gastrointestinal endoscopy is usually indicated. Nevertheless, in many cases a gastrointestinal source is not found after routine evaluation. Additional studies, including repeat upper and lower endoscopy and often investigation of the small intestine may thus be required. Although oral iron is inexpensive and usually effective, there are many gastrointestinal conditions that warrant treatment of iron deficiency with intravenous iron

Climate-smart agriculture practices for mitigating greenhouse gas emissions

Agricultural lands make up approximately 37% of the global land surface, and agriculture is a significant source of greenhouse gas (GHG) emissions, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). Those GHGs are responsible for the majority of the anthropogenic globalwarming effect.Agricultural GHG emissions are associated with agricultural soil management (e.g. tillage), use of both synthetic and organic fertilisers, livestock management, burning of fossil fuel for agricultural operations, and burning of agricultural residues and land use change. When natural ecosystems such as grasslands are converted to agricultural production, 20-40% of the soil organic carbon (SOC) is lost over time, following cultivation.We thus need to develop management practices that can maintain or even increase SOC storage in and reduce GHG emissions from agricultural ecosystems. We need to design systematic approaches and agricultural strategies that can ensure sustainable food production under predicted climate change scenarios, approaches that are being called climate-smart agriculture (CSA). Climate-smart agricultural management practices, including conservation tillage, use of cover crops and biochar application to agricultural fields, and strategic application of synthetic and organic fertilisers have been considered a way to reduce GHG emission from agriculture. Agricultural management practices can be improved to decreasing disturbance to the soil by decreasing the frequency and extent of cultivation as a way to minimise soil C loss and/or to increase soil C storage. Fertiliser nitrogen (N) use efficiency can be improved to reduce fertilizer N application and N loss. Management measures can also be taken to minimise agricultural biomass burning. This chapter reviews the current literature on CSA practices that are available to reduce GHG emissions and increase soil C sequestration and develops a guideline on best management practices to reduce GHG emissions, increase C sequestration, and enhance crop productivity in agricultural production systems