Specifying An Efficient Renewable Energy Feed-in Tariff

This paper derives efficient pricing formulae for renewable energy Feed-in Tariff (FiT) designs that incorporate exposure to uncertain market prices by using option pricing theory. Such FiT designs are presented as a means to delineate market price risk amongst investors and policymakers when designing renewable energy support schemes. Sequential game theory provides the theoretical framework through which we model the strategic interaction of policymakers and investors during policy formulation. This model is solved using option pricing theory when a FiT is comprised of market prices combined with a guaranteed element. This solution also allows for an analytical formulation of the policy cost of subsidisation. Partial derivatives characterise sensitivity of policy cost and investor remuneration to deviations in market conditions beyond those expected. Analytical derivations provide a set of tools which may guide more efficient FiT policy and investment decisions. Numerical simulations demonstrate application for a stylised Irish case study, with a scenario analysis providing further insight into the relative sensitivity of policy cost and investor remuneration under different market conditions

Specifying An Efficient Renewable Energy Feed-in Tariff

This paper derives efficient pricing formulae for renewable energy Feed-in Tariff (FiT) designs that incorporate exposure to uncertain market prices by using option pricing theory. Such FiT designs are presented as a means to delineate market price risk amongst investors and policymakers when designing renewable energy support schemes. Sequential game theory provides the theoretical framework through which we model the strategic interaction of policymakers and investors during policy formulation. This model is solved using option pricing theory when a FiT is comprised of market prices combined with a guaranteed element. This solution also allows for an analytical formulation of the policy cost of subsidisation. Partial derivatives characterise sensitivity of policy cost and investor remuneration to deviations in market conditions beyond those expected. Analytical derivations provide a set of tools which may guide more efficient FiT policy and investment decisions. Numerical simulations demonstrate application for a stylised Irish case study, with a scenario analysis providing further insight into the relative sensitivity of policy cost and investor remuneration under different market conditions

Inhibiting the oncogenic translation program is an effective therapeutic strategy in multiple myeloma

Published in final edited form as: Sci Transl Med. 2017 May 10; 9(389). https://doi.org/10.1126/scitranslmed.aal2668.Multiple myeloma (MM) is a frequently incurable hematological cancer in which overactivity of MYC plays a central role, notably through up-regulation of ribosome biogenesis and translation. To better understand the oncogenic program driven by MYC and investigate its potential as a therapeutic target, we screened a chemically diverse small-molecule library for anti-MM activity. The most potent hits identified were rocaglate scaffold inhibitors of translation initiation. Expression profiling of MM cells revealed reversion of the oncogenic MYC-driven transcriptional program by CMLD010509, the most promising rocaglate. Proteome-wide reversion correlated with selective depletion of short-lived proteins that are key to MM growth and survival, most notably MYC, MDM2, CCND1, MAF, and MCL-1. The efficacy of CMLD010509 in mouse models of MM confirmed the therapeutic relevance of these findings in vivo and supports the feasibility of targeting the oncogenic MYC-driven translation program in MM with rocaglates

Technology Development Roadmap: A Technology Development Roadmap for a Future Gravitational Wave Mission

Humankind will detect the first gravitational wave (GW) signals from the Universe in the current decade using ground-based detectors. But the richest trove of astrophysical information lies at lower frequencies in the spectrum only accessible from space. Signals are expected from merging massive black holes throughout cosmic history, from compact stellar remnants orbiting central galactic engines from thousands of close contact binary systems in the Milky Way, and possibly from exotic sources, some not yet imagined. These signals carry essential information not available from electromagnetic observations, and which can be extracted with extraordinary accuracy. For 20 years, NASA, the European Space Agency (ESA), and an international research community have put considerable effort into developing concepts and technologies for a GW mission. Both the 2000 and 2010 decadal surveys endorsed the science and mission concept of the Laser Interferometer Space Antenna (LISA). A partnership of the two agencies defined and analyzed the concept for a decade. The agencies partnered on LISA Pathfinder (LPF), and ESA-led technology demonstration mission, now preparing for a 2015 launch. Extensive technology development has been carried out on the ground. Currently, the evolved Laser Interferometer Space Antenna (eLISA) concept, a LISA-like concept with only two measurement arms, is competing for ESA's L2 opportunity. NASA's Astrophysics Division seeks to be a junior partner if eLISA is selected. If eLISA is not selected, then a LISA-like mission will be a strong contender in the 2020 decadal survey. This Technology Development Roadmap (TDR) builds on the LISA concept development, the LPF technology development, and the U.S. and European ground-based technology development. The eLISA architecture and the architecture of the Mid-sized Space-based Gravitational-wave Observatory (SGO Mid)-a competitive design with three measurement arms from the recent design study for a NASA-led mission after 2020-both use the same technologies. Further, NASA participation in an ESA-led mission would likely augment the eLISA architecture with a third arm to become the SGO Mid architecture. For these reasons, this TDR for a future GW mission applies to both designs and both programmatic paths forward. It is adaptable to the different timelines and roles for an ESA-led or a NASA-led mission, and it is adaptable to available resources. Based on a mature understanding of the interaction between technology and risk, the authors of this TDR have chosen a set of objectives that are more expansive than is usual. The objectives for this roadmap are: (1) reduce technical and development risks and costs; (2) understand and, where possible, relieve system requirements and consequences; (3) increase technical insight into critical technologies; and (4) validate the design at the subsystem level. The emphasis on these objectives, particularly the latter two, is driven by outstanding programmatic decisions, namely whether a future GW mission is ESA-led or NASA-led, and availability of resources. The relative emphasis is best understood in the context of prioritization

An Early Biomarker Algorithm Predicts Lethal Graft-Vs-Host Disease and Survival after Allogeneic Hematopoietic Cell Transplantation

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Biomarkers Predict Graft-Vs-Host Disease Outcomes Better Than Clinical Response after One Week of Treatment

Abstract Graft-versus-host disease (GVHD), the primary cause of non-relapse mortality (NRM) following allogeneic hematopoietic stem cell transplantation, does not always respond to treatment with high dose systemic corticosteroids. We have recently shown that a combination of three biomarkers (TNFR1, ST2, and REG3α) measured at onset of GVHD can predict day 28 response to treatment and 6-month NRM (Levine, Lancet Haem, 2015). Our goal in the current study was to determine if the same biomarker-based Ann Arbor GVHD algorithm can alsopredict treatment response andmortality whenapplied after one week of systemic corticosteroid treatment. The study population consisted of 378 patients (pts) with acute GVHD from 11 centers in the Mount Sinai Acute GVHD International Consortium. All pts were treated with systemic steroids and provided a plasma or serum sample obtained after one week of treatment (±3 days). The median starting dose of systemic steroids for Grade II-IV GVHD was 2.0 mg/kg/day and for Grade I was 1.0 mg/kg/day, after which treatment varied. Patients were divided into test (n=236) and validation (n=142) cohorts. We applied the Ann Arbor GVHD algorithm to concentrations of TNFR1, ST2, and REG3α measured after one week of treatment to generate a predicted probability of 6-month NRM, which we term the treatment score (TS). We employed unsupervised k-medoidclustering to partition TS values from the test cohort into two groups (high and low). This unbiased approach identified a high score group made up of 25% of pts (n=58) in the test cohort. We observed that the day 28 response rate (complete, CR + partial, PR) was significantly lower in pts with high scores compared to low scores in the test cohort (24% vs 65%, p<0.0001) (Fig 1A). Analysis of the validation cohort using the same TS definitions showed similar differences in response rates (22% vs 61%, p<0.0001) (Fig 1B). Further, nearly four times as many pts with high scores in both cohorts died within 6 months from non-relapse causes compared to pts with low scores (test: 57% vs 17%, p<0.0001; validation: 57% vs 14%, p<0.0001) (Fig 1C/D). As expected, the majority of non-relapse deaths in pts treated for GVHD were directly attributable to GVHD (test: 95%; validation: 89%). Relapse rates for high and low score pts were similar (data not shown), and thus pts with a high TS experienced significantly worse overall survival in both cohorts (test: 37% vs 72%, p<0.0001; validation: 38% vs 79%, p<0.0001) (Fig 1E/F). Approximately half of the pts in each cohort (test: 48%; validation: 44%) responded (CR+PR) to the first week of steroids and these ptshad significantly lower 6-month NRM than non-responders (NR) (test: 17% vs 36%, p=0.0002; validation: 13% vs 36%, p=0.0014). Yet the TS continued to stratify mortality risk independently of clinical response. In the test cohort, pts with a high score comprised 16% of all early responders and experienced more than twice the NRM of early responders with a low score (33% vs 13%, p=0.022) (Fig 2A). Conversely, test cohort pts who did not respond by day 7, but had a low score, fared much better than non-responders with a high score (NRM 21% vs 68%, p<0.0001) (Fig 2B). Two thirds of early non-responders comprised this more favorable group. These highly significant results reproduced in the independent validation cohort in similar proportions (CR+PR: 45% vs 6%, p=0.0003; NR: 61% vs 22%, p=0.0001) (Fig 2C/D). Finally, a subset analysis revealed that pts classified as NR after one week of steroids due to isolated, yet persistent, grade I skin GVHD (24/378, 6%) overwhelmingly had low treatment scores (22/24, 92%) and experienced rates of NRM (9%) comparable to responders with low scores, thus forming a distinct, albeit small, subset of pts with non-responsive GVHD that fares particularly well (Fig 3). In conclusion, a treatment score based on three GVHD biomarkers measured after one week of steroids stratifies pts into two groups with distinct risks for treatment failure and 6-month NRM. It is particularly noteworthy that the TS identifies two subsets of pts with steroid refractory (SR) GVHD who have highly different outcomes (Fig 2B/D). The much larger group, approximately two thirds of all SR pts, may not need the same degree of treatment escalation as is traditional for clinical non-response, and thus overtreatment might be avoided. Because the TSis measured at a common decision making time point, it may prove useful to guide risk-adapted therapy. Disclosures Mielke: Novartis: Consultancy; MSD: Consultancy, Other: Travel grants; Celgene: Other: Travel grants, Speakers Bureau; Gilead: Other: Travel grants; JAZZ Pharma: Speakers Bureau. Kroeger:Novartis: Honoraria, Research Funding. Chen:Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding. Jagasia:Therakos: Consultancy. Kitko:Therakos: Honoraria, Speakers Bureau. Ferrara:Viracor: Patents & Royalties: GVHD biomarker patent. Levine:Viracor: Patents & Royalties: GVHD biomarker patent

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Programmed death ligand-1 expression on donor T cells drives graft-versus-host disease lethality

Programmed death ligand-1 (PD-L1) interaction with PD-1 induces T cell exhaustion and is a therapeutic target to enhance immune responses against cancer and chronic infections. In murine bone marrow transplant models, PD-L1 expression on host target tissues reduces the incidence of graft-versus-host disease (GVHD). PD-L1 is also expressed on T cells; however, it is unclear whether PD-L1 on this population influences immune function. Here, we examined the effects of PD-L1 modulation of T cell function in GVHD. In patients with severe GVHD, PD-L1 expression was increased on donor T cells. Compared with mice that received WT T cells, GVHD was reduced in animals that received T cells from Pdl1–/– donors. PD-L1–deficient T cells had reduced expression of gut homing receptors, diminished production of inflammatory cytokines, and enhanced rates of apoptosis. Moreover, multiple bioenergetic pathways, including aerobic glycolysis, oxidative phosphorylation, and fatty acid metabolism, were also reduced in T cells lacking PD-L1. Finally, the reduction of acute GVHD lethality in mice that received Pdl1–/– donor cells did not affect graft-versus-leukemia responses. These data demonstrate that PD-L1 selectively enhances T cell–mediated immune responses, suggesting a context-dependent function of the PD-1/PD-L1 axis, and suggest selective inhibition of PD-L1 on donor T cells as a potential strategy to prevent or ameliorate GVHD