3,434 research outputs found

    Water Quality Control and Management of Animal Wastes Through Culture with Selected Fishes

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    Research Report 151, Final Report, Project A-083-ILL, Agreement No. 14-34-001-8015Report issued on: April 1980Submitted to unspecified recipien

    Periodicity and Growth in a Lattice Gas with Dynamical Geometry

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    We study a one-dimensional lattice gas "dynamical geometry model" in which local reversible interactions of counter-rotating groups of particles on a ring can create or destroy lattice sites. We exhibit many periodic orbits and and show that all other solutions have asymptotically growing lattice length in both directions of time. We explain why the length grows as t\sqrt{t} in all cases examined. We completely solve the dynamics for small numbers of particles with arbitrary initial conditions.Comment: 18 pages, LaTe

    Exposure to fumigants in containers: a questionnaire assessment on 125 French dockers

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    Background: Cases of intoxications to gas from container’s atmosphere have been described. For diagnosis, Fum Ex 2 questionnaire has been developed by the European Society for Environmental and Occupational Medicine. The aim of this study was to enhance knowledge on health effects of toxic substances in containers and to validate this questionnaire in medical follow-up and diagnosis. Materials and methods: In 2014, 125 French dockers answered the questionnaire in a face-to-face interview. Results: 83.5% declared no exposure to fumigants or pesticides. Most frequently declared symptoms were fatigue and neurological disorders for dockers and respiratory irritation for refrigeration technicians. Only 28 workers wore regularly individual protection equipment. Conclusions: A “healthy worker” effect could explain low level of symptoms. Fum Ex 2 questionnaire is relevant for diagnosis. Workers in all steps of the logistic transport chain and consumers are exposed to containers’ atmosphere

    Antibiotic Stewardship-Programme reduzieren die Inzidenz von Infektionen und Kolonisation durch Antibiotika- resistente Bakterien und Clostridium difficile: Eine systematische Review und Meta-Analyse

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    Zusammenfassung: Antibiotic Stewardship-Programme sind effektiv um antibiotischen Verbrauch und Krankenhauskosten zu reduzieren[1]. Die Zielsetzung dieser Studie ist es, den Effekt von Antibiotic Stewardship-Programmen auf die Inzidenzrate von Infektionen und Kolonisation mit antibiotisch resistenten Keimen zu untersuchen[1]. Für diese systematische Review und Meta-Analyse wurden PubMed, die Cochrane Database of Systematic Reviews, das Cochrane Central Register of Controlled Trials und das Web of Science vom ersten Januar 1960 bis 31ten Mai 2016 nach Artikeln durchsucht, welche sich mit dem Effekt von Antibiotic Stewardship-Programmen auf die Inzidenzrate von Infektionen und Kolonisation mit antibiotisch resistenten Keimen und C. difficile Infektionen in hospitalisierten Patienten beschäftigten[1]. Zwei Forscher haben unabhängig voneinander die Einschlussfähigkeit der Artikel geprüft und Daten extrahiert[1]. Studien die Langzeitpflegeeinrichtungen miteinbeziehen wurden ausgeschlossen[1]. Das Hauptergebnis der Datenanalyse stellte hierbei das Inzidenzverhältnis von Infektionen und Kolonisation pro 1000 Patiententage vor und nach der Implementation eines Antibiotic Stewardship-Programmes dar[1]. Die Meta- analyse wurde mit einem „random-effect“ Modell und die Heterogenität mit der I2 Methode berechnet[1]. Es wurden 32 Studien in die Meta-analyse eingeschlossen, welche 9056241 Patiententage und Schätzungen von 159 Inzidenzverhältnissen umfassten[1]. Antibiotic Stewardship Programme reduzierten die Inzidenzraten von Infektionen und Kolonisation mit multiresistenten gramnegativen Bakterien (51% Reduktion; IV 0,49, 95% CI 0,35–0,68; p<0,0001), „extended-spectrum ß- lactamse“-produzierenden gramnegativen Bakterien (48%; 0,52, 0,27–0,98; p=0,0428) und Meticillin-resistentem Staphylococcus aureus (37%; 0,63, 0,45– 0,88; p=0,0065), sowie die Inzidenzrate von C. difficile Infektionen (32%; 0,68, 0,53–0,88; p=0,0029)[1]. Antibiotic Stewardship-Programme waren effektiver, wenn Infektionskontroll- maßnahmen co-implementiert wurden (IV 0,69, 0,54–0,88; p=0,0030), insbesondere bei paralleler Einführung von Händehygiene-Interventionen (0,34, 64 0,21–0,54; p<0,0001), als bei alleiniger Einführung[1]. Antibiotic Stewardship- Programme hatten keinen Einfluss auf die Inzidenzverhältnisse von Vancomycin-resistenten Enterococci und Quinolon-resistenten und Aminoglykosid-resistenten gramnegativen Bakterien[1]. Zwischen den Studien wurde eine signifikante Heterogenität festgestellt, welche teilweise durch die unterschiedlichen Interventionsformen und die Co-Resistenz Muster der Zielpathogene erklärt werden kann[1]. Antibiotic Stewardship-Programme reduzieren die Inzidenz von Infektionen und Kolonisation mit Antibiotika-resistenten Bakterien und Clostridium difficile Infektionen in hospitalisierten Patienten signifikant[1]. Diese Ergebnisse liefern „Stakeholdern“ und Richtlinienverfassern den Nachweis, dass die Implementation eines Antibiotic Stewardship-Programmes die Belastung durch Antibiotika-resistente Bakterien verringern kann[1]

    Imaging of Metal Ion Dissolution and Electrodeposition by Anodic Stripping Voltammetry – Scanning Electrochemical Microscopy

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    We have developed a new imaging method for SECM employing fast scan anodic stripping voltammetry (ASV) to provide sensitive and selective imaging of multiple chemical species at interfaces immersed in solution. A rapid CV scan (100 V/s) is used along with a short preconcentration time (300-750 ms) to allow images to be acquired in a normal SECM time frame. A Hg-Pt film electrode is developed having an equivalent Hg thickness of 40 nm that has good sensitivity at short preconcentration times and also retains thin-film behavior with high-speed voltammetric stripping. Fast scan anodic stripping currents are shown to be linear for 1-100 mM of Pb2+ and Cd2+ solutions using a preconcentration time of 300 ms. SECM images showing the presence of Pb2+ and Cd2+ at concentrations as low as 1 mM are presented. In addition, a single ASV-SECM image is shown to produce unique concentration maps indicating Cd2+ and Pb2+, generated in situ from a corroding sample, while simultaneously detecting the depletion of O2 at this sample. The transient voltammetric response at the film electrode is simulated and shows good agreement with the experimental behavior. We discuss the behavior of images and concentration profiles obtained with different imaging conditions and show that mass- transport limitations in the tip-substrate gap can induce dissolution. ASV-SECM can thus be used to detect and study induced dissolution not only at bulk metal surfaces but also on UPD layers, in this case Cd and Pb on Pt. In addition, we discuss how surface diffusion phenomena may relate to the observed ASV-SECM behavior

    Rapamycin has a biphasic effect on insulin sensitivity in C2C12 myotubes due to sequential disruption of mTORC1 and mTORC2

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    Rapamycin, an inhibitor of mTOR complex 1 (mTORC1), improves insulin sensitivity in acute studies in vitro and in vivo by disrupting a negative feedback loop mediated by S6 kinase. We find that rapamycin has a clear biphasic effect on insulin sensitivity in C2C12 myotubes, with enhanced responsiveness during the first hour that declines to almost complete insulin resistance by 24-48 h. We and others have recently observed that chronic rapamycin treatment induces insulin resistance in rodents, at least in part due to disruption of mTORC2, an mTOR-containing complex that is not acutely sensitive to the drug. Chronic rapamycin treatment may also impair insulin action via the inhibition of mTORC1-dependent mitochondrial biogenesis and activity, which could result in a buildup of lipid intermediates that are known to trigger insulin resistance. We confirmed that rapamycin inhibits expression of PGC-1α, a key mitochondrial transcription factor, and acutely reduces respiration rate in myotubes. However, rapamycin did not stimulate phosphorylation of PKCΘ, a central mediator of lipid-induced insulin resistance. Instead, we found dramatic disruption of mTORC2, which coincided with the onset of insulin resistance. Selective inhibition of mTORC1 or mTORC2 by shRNA-mediated knockdown of specific components (Raptor and Rictor, respectively) confirmed that mitochondrial effects of rapamycin are mTORC1-dependent, whereas insulin resistance was recapitulated only by knockdown of mTORC2.Thus, mTORC2 disruption, rather than inhibition of mitochondria, causes insulin resistance in rapamycin-treated myotubes, and this system may serve as a useful model to understand the effects of rapamycin on mTOR signaling in vivo

    Decision support by machine learning systems for acute management of severely injured patients: A systematic review

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    Introduction Treating severely injured patients requires numerous critical decisions within short intervals in a highly complex situation. The coordination of a trauma team in this setting has been shown to be associated with multiple procedural errors, even of experienced care teams. Machine learning (ML) is an approach that estimates outcomes based on past experiences and data patterns using a computer-generated algorithm. This systematic review aimed to summarize the existing literature on the value of ML for the initial management of severely injured patients. Methods We conducted a systematic review of the literature with the goal of finding all articles describing the use of ML systems in the context of acute management of severely injured patients. MESH search of Pubmed/Medline and Web of Science was conducted. Studies including fewer than 10 patients were excluded. Studies were divided into the following main prediction groups: (1) injury pattern, (2) hemorrhage/need for transfusion, (3) emergency intervention, (4) ICU/length of hospital stay, and (5) mortality. Results Thirty-six articles met the inclusion criteria; among these were two prospective and thirty-four retrospective case series. Publication dates ranged from 2000 to 2020 and included 32 different first authors. A total of 18,586,929 patients were included in the prediction models. Mortality was the most represented main prediction group (n = 19). ML models used were artificial neural network ( n = 15), singular vector machine (n = 3), Bayesian network (n = 7), random forest (n = 6), natural language processing (n = 2), stacked ensemble classifier [SuperLearner (SL), n = 3], k-nearest neighbor (n = 1), belief system (n = 1), and sequential minimal optimization (n = 2) models. Thirty articles assessed results as positive, five showed moderate results, and one article described negative results to their implementation of the respective prediction model. Conclusions While the majority of articles show a generally positive result with high accuracy and precision, there are several requirements that need to be met to make the implementation of such models in daily clinical work possible. Furthermore, experience in dealing with on-site implementation and more clinical trials are necessary before the implementation of ML techniques in clinical care can become a reality

    Young and old genetically heterogeneous HET3 mice on a rapamycin diet are glucose intolerant but insulin sensitive

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    Rapamycin, an inhibitor of the mechanistic target of rapamycin (mTOR) signaling pathway, extends the life span of yeast, worms, flies, and mice. Interventions that promote longevity are often correlated with increased insulin sensitivity, and it therefore is surprising that chronic rapamycin treatment of mice, rats, and humans is associated with insulin resistance (J Am Soc Nephrol., 19, 2008, 1411; Diabetes, 00, 2010, 00; Science, 335, 2012, 1638). We examined the effect of dietary rapamycin treatment on glucose homeostasis and insulin resistance in the genetically heterogeneous HET3 mouse strain, a strain in which dietary rapamycin robustly extends mean and maximum life span. We find that rapamycin treatment leads to glucose intolerance in both young and old HET3 mice, but in contrast to the previously reported effect of injected rapamycin in C57BL/6 mice, HET3 mice treated with dietary rapamycin responded normally in an insulin tolerance test. To gauge the overall consequences of rapamycin treatment on average blood glucose levels, we measured HBA1c. Dietary rapamycin increased HBA1c over the first 3 weeks of treatment in young animals, but the effect was lost by 3 months, and no effect was detected in older animals. Our results demonstrate that the extended life span of HET3 mice on a rapamycin diet occurs in the absence of major changes in insulin sensitivity and highlight the importance of strain background and delivery method in testing effects of longevity interventions.National Institutes of Health (U.S.)National Institute on Aging (Grant AG 035860)National Institute on Aging (Grant AG 022308)National Cancer Institute (U.S.) (Grant CA 129105)American Federation for Aging Research (Julie Martin Mid-Career Award in Aging Research)National Institutes of Health (U.S.) (National Institute on Aging K00/R00 Award 1K99AG041765-01A1

    RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback

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    To use reinforcement learning from human feedback (RLHF) in practical applications, it is crucial to learn reward models from diverse sources of human feedback and to consider human factors involved in providing feedback of different types. However, the systematic study of learning from diverse types of feedback is held back by limited standardized tooling available to researchers. To bridge this gap, we propose RLHF-Blender, a configurable, interactive interface for learning from human feedback. RLHF-Blender provides a modular experimentation framework and implementation that enables researchers to systematically investigate the properties and qualities of human feedback for reward learning. The system facilitates the exploration of various feedback types, including demonstrations, rankings, comparisons, and natural language instructions, as well as studies considering the impact of human factors on their effectiveness. We discuss a set of concrete research opportunities enabled by RLHF-Blender. More information is available at https://rlhfblender.info/.Comment: 14 pages, 3 figure
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