939 resultados para VP-SEM-EDS


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Unstimulated adherent mouse peritoneal cells were cultured in vitro and infected with equal numbers of a single strain of Leishmania m. mexicana amastigotes (AM), virulent promastigotes (VP), avirulent promastigotes (AVP) and fixed promastigotes (FP). Duplicate May-Grünwald-Giemsa stained coverslips were examined at time intervals up to 13 days. By 3 hr post infection, the number of macrophages containing parasites varied between 60.5% (VP) and 84% (AM) for macrophages exposed to living parasites, compared to 6.5% for macrophages exposed for FP. However, variable numbers of parasites showed degenerative changes by 3 hr, and the number of macrophages containing morphologically intact parasites varied significantly between cells infected with AM (84%) and those infected with VP (42%) or AVP(40%). The mean number on intacte parasites/macrophage also differed significantly between AM-infected cells and living or fixed promastigotes-infected cells. Quantitation of intact and degenerated parasites indicated parasite multiplication, as well as destruction, in VP-infected cells and parasite survival and multiplication in AM-infecte monolayers; in contrast no evidence of parasite multiplication was seen in AVP-infected cells. Changes in the mono layer itself (cell loss and macrophage vacuolization) were also evaluated. These results suggest that crucial events determining the outcome of infection occur in the host-parasite relationship during the fist 24 hours of infection. These events are apparently influenced not only by parasite or host strain but by environmentally induced variation within a given strain.

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BACKGROUND: Many emergency department (ED) providers do not follow guideline recommendations for the use of the pneumonia severity index (PSI) to determine the initial site of treatment for patients with community-acquired pneumonia (CAP). We identified the reasons why ED providers hospitalize low-risk patients or manage higher-risk patients as outpatients. METHODS: As a part of a trial to implement a PSI-based guideline for the initial site of treatment of patients with CAP, we analyzed data for patients managed at 12 EDs allocated to a high-intensity guideline implementation strategy study arm. The guideline recommended outpatient care for low-risk patients (nonhypoxemic patients with a PSI risk classification of I, II, or III) and hospitalization for higher-risk patients (hypoxemic patients or patients with a PSI risk classification of IV or V). We asked providers who made guideline-discordant decisions on site of treatment to detail the reasons for nonadherence to guideline recommendations. RESULTS: There were 1,306 patients with CAP (689 low-risk patients and 617 higher-risk patients). Among these patients, physicians admitted 258 (37.4%) of 689 low-risk patients and treated 20 (3.2%) of 617 higher-risk patients as outpatients. The most commonly reported reasons for admitting low-risk patients were the presence of a comorbid illness (178 [71.5%] of 249 patients); a laboratory value, vital sign, or symptom that precluded ED discharge (73 patients [29.3%]); or a recommendation from a primary care or a consulting physician (48 patients [19.3%]). Higher-risk patients were most often treated as outpatients because of a recommendation by a primary care or consulting physician (6 [40.0%] of 15 patients). CONCLUSION: ED providers hospitalize many low-risk patients with CAP, most frequently for a comorbid illness. Although higher-risk patients are infrequently treated as outpatients, this decision is often based on the request of an involved physician.

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Nowadays, many of the health care systems are large and complex environments and quite dynamic, specifically Emergency Departments, EDs. It is opened and working 24 hours per day throughout the year with limited resources, whereas it is overcrowded. Thus, is mandatory to simulate EDs to improve qualitatively and quantitatively their performance. This improvement can be achieved modelling and simulating EDs using Agent-Based Model, ABM and optimising many different staff scenarios. This work optimises the staff configuration of an ED. In order to do optimisation, objective functions to minimise or maximise have to be set. One of those objective functions is to find the best or optimum staff configuration that minimise patient waiting time. The staff configuration comprises: doctors, triage nurses, and admissions, the amount and sort of them. Staff configuration is a combinatorial problem, that can take a lot of time to be solved. HPC is used to run the experiments, and encouraging results were obtained. However, even with the basic ED used in this work the search space is very large, thus, when the problem size increases, it is going to need more resources of processing in order to obtain results in an acceptable time.

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Background: The objective of this study was to determine if mental health and substance use diagnoses were equally detected in frequent users (FUs) compared to infrequent users (IUs) of emergency departments (EDs). Methods: In a sample of 399 adult patients (>= 18 years old) admitted to a teaching hospital ED, we compared the mental health and substance use disorders diagnoses established clinically and consigned in the medical files by the ED physicians to data obtained in face-to-face research interviews using the Primary Care Evaluation of Mental Disorders (PRIME-MD) and the Alcohol, Smoking and Involvement Screening Test (ASSIST). Between November 2009 and June 2010, 226 FUs (>4 visits within a year) who attended the ED were included, and 173 IUs (<= 4 visits within a year) were randomly selected from a pool of identified patients to comprise the comparison group. Results: For mental health disorders identified by the PRIME-MD, FUs were more likely than IUs to have an anxiety (34 vs. 16%, Chi2(1) = 16.74, p <0.001), depressive (47 vs. 25%, Chi2(1) = 19.11, p <0.001) or posttraumatic stress (PTSD) disorder (11 vs. 5%, Chi2(1) = 4.87, p = 0.027). Only 3/76 FUs (4%) with an anxiety disorder, 16/104 FUs (15%) with a depressive disorder and none of the 24 FUs with PTSD were detected by the ED medical staff. None of the 27 IUs with an anxiety disorder, 6/43 IUs (14%) with a depressive disorder and none of the 8 IUs with PTSD were detected. For substance use disorders identified by the ASSIST, FUs were more at risk than IUs for alcohol (24 vs. 7%, Chi2(1) = 21.12, p <0.001) and drug abuse/dependence (36 vs. 25%, Chi2(1) = 5.52, p = 0.019). Of the FUs, 14/54 (26%) using alcohol and 8/81 (10%) using drugs were detected by the ED physicians. Of the IUs, 5/12 (41%) using alcohol and none of the 43 using drugs were detected. Overall, there was no significant difference in the rate of detection of mental health and substance use disorders between FUs and IUs (Fisher's Exact Test: anxiety, p = 0.567; depression, p = 1.000; PTSD, p = 1.000; alcohol, p = 0.517; and drugs, p = 0.053). Conclusions: While the prevalence of mental health and substance use disorders was higher among FUs, the rates of detection were not significantly different for FUs vs. IUs. However, it may be that drug disorders among FUs were more likely to be detected.

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Review of Nigel Smith, Is Milton Better Than Shakespeare; Paradise Lost, introduced by Philip Pullman; Paradise Lost, ed Barbara Lewalski; Milton and Toleration, eds. Sharon Achinstein and Elizabeth Sauer; Concise Companion to Milton, ed Angelica Duran.