Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two-center cohort study with prospective sample collection from 1400 adult patients in emergency departments suspected of sepsis, we sought to determine the diagnostic and prognostic capabilities of a machine-learning algorithm based on clinical data and a set of uncommonly measured biomarkers. Specifically, we demonstrate that a machine-learning model developed using this dataset outputs a score with not only diagnostic capability but also prognostic power with respect to hospital length of stay (LOS), 30-day mortality, and 3-day inpatient re-admission both in our entire testing cohort and various subpopulations. The area under the receiver operating curve (AUROC) for diagnosis of sepsis was 0.83. Predicted risk scores for patients with septic shock were higher compared with patients with sepsis but without shock (p < 0.0001). Scores for patients with infection and organ dysfunction were higher compared with those without either condition (p < 0.0001). Stratification based on predicted scores of the patients into low, medium, and high-risk groups showed significant differences in LOS (p < 0.0001), 30-day mortality (p < 0.0001), and 30-day inpatient readmission (p < 0.0001). In conclusion, a machine-learning algorithm based on electronic medical record (EMR) data and three nonroutinely measured biomarkers demonstrated good diagnostic and prognostic capability at the time of initial blood culture.

Fate of allelochemicals in the soil / Destino de aleloquímicos no solo

Allelochemicals are compounds released by one plant or plant residues that may have a negative or positive effect on other plant. The importance of allelopathy was extensively explored during the past three decades, with the work concentrating in the extraction and identification of the chemicals, and demonstration of activity in petry dish experiments. These compounds interact in the soil environment similarly as herbicides and are subject to processes of degradation such as microbial degradation, oxidation, and photolysis, and processes of removal or transfer, such as volatilization and adsorption. The objective of this review was to access the fate of allelochemicals in the soil environment to help to find strategies to increase its activity. The activity of allelochemical is limited in time (because of slow release from the donor material) and in space (because of the interaction with the environment). Demonstration of allelopathy should include the fate of the proposed chemical in the soil environment, presenting studies of degradation and removal processes.

Aleloquímicos são compostos liberados por plantas ou seus resíduos e que podem ter efeito negativo ou positivo em outra planta. A importância da alelopatia foi estudada intensamente nas últimas três décadas, sendo que a maioria dos trabalhos abordou a extração e identificação dos compostos e, demonstração de seus efeitos em experimentos realizados em placas de petri. Estes químicos interagem no ambiente assim como os herbicidas e estão sujeitos aos processos de degradação por decomposição microbiana, fotólise e oxidação e, processos de remoção ou transferência como volatilização e adsorção. O objetivo desta revisão de literatura foi estudar o destino de aleloquímicos no ambiente para auxiliar na definição de estratégias para aumentar sua atividade. A atividade dos aleloquímicos é limitada pelo tempo (devido a liberação lenta do material doador) e pelo espaço (devido à interação com o ambiente). Demonstrações de alelopatia devem incluir o destino no ambiente do composto envolvido, apresentando estudos de processos de degradação e remoção.