Phase transitions for the cavity approach to the clique problem on random graphs

We give a rigorous proof of two phase transitions for a disordered system designed to find large cliques inside Erdos random graphs. Such a system is associated with a conservative probabilistic cellular automaton inspired by the cavity method originally introduced in spin glass theory.Comment: 36 pages, 4 figure

673. Study of Prescribing patterns and Effectiveness of Ceftolozane/Tazobactam Real-world Analysis (SPECTRA): Results from a multi-national, multicenter observational study

Abstract Background Ceftolozane/tazobactam (C/T) has demonstrated efficacy to treat complicated intra-abdominal infections (cIAI), complicated urinary tract infections (cUTI) and hospital acquired bacterial and ventilator-associated bacterial pneumonia. However, physicians, providers, and other stakeholders including payers want broader real-world evidence to inform clinical decisions and optimize healthcare resource use. Methods SPECTRA is a multi-national, multicenter, retrospective, inpatient, observational study of patients treated with C/T in Australia, Austria, Germany, Italy, Mexico, Spain and The United Kingdom. Adult inpatients treated with ≥48 hours of C/T were included. Demographics, clinical characteristics, treatment management patterns, and outcomes were analyzed. Results There were 687 patients from 38 participating hospitals in 7 countries. The average age was 57.6 years (±17.3 [SD]) and most were male 456 (66.4%). The majority had at least one comorbidity 563 (82.0%), with the most common being heart disease 208 (30.3%), immunocompromised state 207 (30.1%) and chronic pulmonary disease 195 (28.4%). The most common indications were pneumonia 204 (29.7%), sepsis 147 (21.4%), and cIAI 106 (15.4%); 162 (23.6%) had multiple sites of infection and 245 (35.7%) were polymicrobial infections. Median C/T treatment was 12.0 days (11.0 [IQR]). Half of the patients were admitted to the ICU 343 (49.9%), 43.4% of which was related to the infection. Clinical success was 66.1%. All-cause in-hospital mortality was 22.0% with 8.7% being infection related. 30-day all-cause readmission was 9.8% and 4.7% were infection related. Conclusion C/T was used to treat infections among critically ill patients and for multi-source, polymicrobial infections. Despite the complexity of the patients in this real-world analysis, most C/T patients had beneficial outcomes that are similar to results of controlled clinical trials. Disclosures Alex Soriano, MD, MSD, Pfizer, Shionogi, Angelini, Menarini, Gilead: Honoraria Laura A. Puzniak, MPH, PhD, Merck & Co., Inc.: former employee and stockholder David Paterson, MBBS, Accelerate: Honoraria|bioMerieux: Honoraria|Entasis: Advisor/Consultant|Janssen-Cilag: Grant/Research Support|MSD: Advisor/Consultant|MSD: Grant/Research Support|MSD: Honoraria|Pfizer: Grant/Research Support|Pfizer: Honoraria|PPD: Grant/Research Support|Shionogi: Grant/Research Support|VenatoRx: Advisor/Consultant Stefan Kluge, MD, Astrazeneca: Lecture fees|Biotest: Lecture fees|Cytosorbents: Grant/Research Support|Cytosorbents: Lecture fees|Daiichi Sankyo: Grant/Research Support|Daiichi Sankyo: Lecture fees|Fresenius Medical Care: Advisor/Consultant|Fresenius Medical Care: Lecture fees|Gilead: Advisor/Consultant|Gilead: Lecture fees|Mitsubishi Tanabe Pharma: Lecture fees|MSD: Advisor/Consultant|MSD: Lecture fees|Pfizer: Advisor/Consultant|Pfizer: Lecture fees|Phillips: Lecture fees|Zoll: Lecture fees Alexandre H. Watanabe, PharmD, Merck & Co., Inc.: Employee Engels N. Obi, PhD, Merck & Co., Inc.: Employee|Merck & Co., Inc.: Stocks/Bonds Sunny Kaul, BSc, MBChB, PHD, FRCP, FFICM, Chiesi: Speaker fees|Gilead: Speaker fees|GlaxoSmithKline: Speaker fees|MSD: Grant/Research Support|MSD: Speaker fees|Shionogi: Speaker fees|Vifor Pharma: Grant/Research Support

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High‐Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology

Atmospheric rivers (ARs) are now widely known for their association with high‐impact weather events and long‐term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR‐related metrics based on 20+ different AR identification and tracking methods applied to Modern‐Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria‐based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all‐method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR‐related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR‐related research to consider.Fil: Rutz, Jonathan J.. National Ocean And Atmospheric Administration; Estados UnidosFil: Shields, Christine A.. National Center for Atmospheric Research; Estados UnidosFil: Lora, Juan M.. University of Yale; Estados UnidosFil: Payne, Ashley E.. University of Michigan; Estados UnidosFil: Guan, Bin. California Institute of Technology; Estados UnidosFil: Ullrich, Paul. University of California at Davis; Estados UnidosFil: O'Brien, Travis. Lawrence Berkeley National Laboratory; Estados UnidosFil: Leung, Ruby. Pacific Northwest National Laboratory; Estados UnidosFil: Ralph, F. Martin. Center For Western Weather And Water Extremes; Estados UnidosFil: Wehner, Michael. Lawrence Berkeley National Laboratory; Estados UnidosFil: Brands, Swen. Meteogalicia; EspañaFil: Collow, Allison. Universities Space Research Association; Estados UnidosFil: Goldenson, Naomi. University of California at Los Angeles; Estados UnidosFil: Gorodetskaya, Irina. Universidade de Aveiro; PortugalFil: Griffith, Helen. University of Reading; Reino UnidoFil: Kashinath, Karthik. Lawrence Bekeley National Laboratory; Estados UnidosFil: Kawzenuk, Brian. Center For Western Weather And Water Extremes; Reino UnidoFil: Krishnan, Harinarayan. Lawrence Berkeley National Laboratory; Estados UnidosFil: Kurlin, Vitaliy. University of Liverpool; Reino UnidoFil: Lavers, David. European Centre For Medium-range Weather Forecasts; Estados UnidosFil: Magnusdottir, Gudrun. University of California at Irvine; Estados UnidosFil: Mahoney, Kelly. Universidad de Lisboa; PortugalFil: Mc Clenny, Elizabeth. University of California at Davis; Estados UnidosFil: Muszynski, Grzegorz. University of Liverpool; Reino Unido. Lawrence Bekeley National Laboratory; Estados UnidosFil: Nguyen, Phu Dinh. University of California at Irvine; Estados UnidosFil: Prabhat, Mr.. Lawrence Bekeley National Laboratory; Estados UnidosFil: Qian, Yun. Pacific Northwest National Laboratory; Estados UnidosFil: Ramos, Alexandre M.. Universidade Nova de Lisboa; PortugalFil: Sarangi, Chandan. Pacific Northwest National Laboratory; Estados UnidosFil: Viale, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentin

Genomic and transcriptomic analyses of breast cancer primaries and matched metastases in AURORA, the Breast International Group (BIG) molecular screening initiative

AURORA aims to study the processes of relapse in metastatic breast cancer (MBC) by performing multi-omics profiling on paired primary tumors and early-course metastases. Among 381 patients (primary tumor and metastasis pairs: 252 targeted gene sequencing, 152 RNA sequencing, 67 single nucleotide polymorphism arrays), we found a driver role for GATA1 and MEN1 somatic mutations. Metastases were enriched in ESR1, PTEN, CDH1, PIK3CA, and RB1 mutations; MDM4 and MYC amplifications; and ARID1A deletions. An increase in clonality was observed in driver genes such as ERBB2 and RB1. Intrinsic subtype switching occurred in 36% of cases. Luminal A/B to HER2-enriched switching was associated with TP53 and/or PIK3CA mutations. Metastases had lower immune score and increased immune-permissive cells. High tumor mutational burden correlated to shorter time to relapse in HR+/HER2- cancers. ESCAT tier I/II alterations were detected in 51% of patients and matched therapy was used in 7%. Integration of multi-omics analyses in clinical practice could affect treatment strategies in MBC. SIGNIFICANCE: The AURORA program, through the genomic and transcriptomic analyses of matched primary and metastatic samples from 381 patients with breast cancer, coupled with prospectively collected clinical data, identified genomic alterations enriched in metastases and prognostic biomarkers. ESCAT tier I/II alterations were detected in more than half of the patients.This article is highlighted in the In This Issue feature, p. 2659