Ohio State University

About: Ohio State University is a education organization based out in Columbus, Ohio, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 102421 authors who have published 222715 publications receiving 8373403 citations. The organization is also known as: Ohio State & The Ohio State University.

Intonational structure in Japanese and English

Abstract: Comparisons between Japanese and English prosodics have usually either focused on the strikingly apparent phonetic differences between the stress patterns of English and the tonal accent patterns of Japanese or concentrated upon formal similarities between the abstract arrangements of the stresses and tones. A recent investigation of tone structure in Japanese (Pierrehumbert & Beckman forthcoming), however, has convinced us that if the proper prosodic phenomena are compared, far more pervasive similarities can be discovered and of a much more concrete sort than hitherto suspected. In particular, there is now extensive evidence that Japanese tonal patterns are very sparsely specified, which suggests that they are much more similar to English intonational structures than earlier descriptions would have allowed.

Systolic Blood Pressure at Admission, Clinical Characteristics, and Outcomes in Patients Hospitalized With Acute Heart Failure

Abstract: ContextThe association between systolic blood pressure (SBP) at admission, clinical characteristics, and outcomes in patients hospitalized for heart failure who have reduced or relatively preserved systolic function has not been well studied.ObjectiveTo evaluate the relationship between SBP at admission, clinical profile, and outcomes in patients hospitalized for acute heart failure.Design, Setting, and PatientsCohort study using data from the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) registry and performance-improvement program for patients hospitalized with heart failure at 259 US hospitals between March 2003 and December 2004. Patients were divided into quartiles by SBP at hospital admission ( 161 mm Hg). In-hospital outcomes were based on 48 612 patients aged 18 years or older with heart failure. Of the 41 267 patients with left ventricular function assessed, 21 149 (51%) had preserved left ventricular function. Postdischarge outcomes were based on a prespecified subgroup (n = 5791, 10% of patients) with follow-up data assessed between 60 and 90 days.Main Outcome MeasuresIn-hospital and postdischarge mortality.ResultsPatients with higher SBP were more likely to be female and black and to have preserved systolic function. Fifty percent of the patients had SBP higher than 140 mm Hg at admission. Patients with lower SBP at admission had higher in-hospital and postdischarge mortality rates. Higher SBP at admission was associated with lower in-hospital mortality rates: 7.2% ( 161 mm Hg) (P<.001 for overall difference). Postdischarge mortality rates in the follow-up cohort by SBP at admission were 14.0%, 8.4%, 6.0%, and 5.4%, respectively (P<.001 for overall difference).ConclusionsSystolic hypertension is common in patients hospitalized for heart failure. Systolic blood pressure is an independent predictor of morbidity and mortality in patients with heart failure with either reduced or relatively preserved systolic function. Low SBP (<120 mm Hg) at hospital admission identifies patients who have a poor prognosis despite medical therapy. These findings may have important therapeutic implications because characteristics and outcomes differ greatly among patients with heart failure with varying SBP.

GLIM Criteria for the Diagnosis of Malnutrition: A Consensus Report From the Global Clinical Nutrition Community

Abstract: Summary Rationale This initiative is focused on building a global consensus around core diagnostic criteria for malnutrition in adults in clinical settings Methods In January 2016, the Global Leadership Initiative on Malnutrition (GLIM) was convened by several of the major global clinical nutrition societies GLIM appointed a core leadership committee and a supporting working group with representatives bringing additional global diversity and expertise Empirical consensus was reached through a series of face-to-face meetings, telephone conferences, and e-mail communications Results A two-step approach for the malnutrition diagnosis was selected, ie, first screening to identify “at risk” status by the use of any validated screening tool, and second, assessment for diagnosis and grading the severity of malnutrition The malnutrition criteria for consideration were retrieved from existing approaches for screening and assessment Potential criteria were subjected to a ballot among the GLIM core and supporting working group members The top five ranked criteria included three phenotypic criteria (non-volitional weight loss, low body mass index, and reduced muscle mass) and two etiologic criteria (reduced food intake or assimilation, and inflammation or disease burden) To diagnose malnutrition at least one phenotypic criterion and one etiologic criterion should be present Phenotypic metrics for grading severity as Stage 1 (moderate) and Stage 2 (severe) malnutrition are proposed It is recommended that the etiologic criteria be used to guide intervention and anticipated outcomes The recommended approach supports classification of malnutrition into four etiology-related diagnosis categories Conclusion A consensus scheme for diagnosing malnutrition in adults in clinical settings on a global scale is proposed Next steps are to secure further collaboration and endorsements from leading nutrition professional societies, to identify overlaps with syndromes like cachexia and sarcopenia, and to promote dissemination, validation studies, and feedback The diagnostic construct should be re-considered every 3–5 years

Deep Reinforcement Learning for Dialogue Generation

Abstract: Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on future outcomes. Modeling the future direction of a dialogue is crucial to generating coherent, interesting dialogues, a need which led traditional NLP models of dialogue to draw on reinforcement learning. In this paper, we show how to integrate these goals, applying deep reinforcement learning to model future reward in chatbot dialogue. The model simulates dialogues between two virtual agents, using policy gradient methods to reward sequences that display three useful conversational properties: informativity, coherence, and ease of answering (related to forward-looking function). We evaluate our model on diversity, length as well as with human judges, showing that the proposed algorithm generates more interactive responses and manages to foster a more sustained conversation in dialogue simulation. This work marks a first step towards learning a neural conversational model based on the long-term success of dialogues.

Exposure to a Social Stressor Alters the Structure of the Intestinal Microbiota: Implications for Stressor-Induced Immunomodulation

Abstract: The bodies of most animals are populated by highly complex and genetically diverse communities of microorganisms. The majority of these microbes reside within the intestines in largely stable but dynamically interactive climax communities that positively interact with their host. Studies from this laboratory have shown that stressor exposure impacts the stability of the microbiota and leads to bacterial translocation. The biological importance of these alterations, however, is not well understood. To determine whether the microbiome contributes to stressor-induced immunoenhancement, mice were exposed to a social stressor called social disruption (SDR), that increases circulating cytokines and primes the innate immune system for enhanced reactivity. Bacterial populations in the cecum were characterized using bacterial tag-encoded FLX amplicon pyrosequencing. Stressor exposure significantly changed the community structure of the microbiota, particularly when the microbiota were assessed immediately after stressor exposure. Most notably, stressor exposure decreased the relative abundance of bacteria in the genus Bacteroides, while increasing the relative abundance of bacteria in the genus Clostridium. The stressor also increased circulating levels of IL-6 and MCP-1, which were significantly correlated with stressor-induced changes to three bacterial genera (i.e., Coprococcus, Pseudobutyrivibrio, and Dorea). In follow up experiments, mice were treated with an antibiotic cocktail to determine whether reducing the microbiota would abrogate the stressor-induced increases in circulating cytokines. Exposure to SDR failed to increase IL-6 and MCP-1 in the antibiotic treated mice. These data show that exposure to SDR significantly affects bacterial populations in the intestines, and remarkably also suggest that the microbiota are necessary for stressor-induced increases in circulating cytokines.