Fate and persistence of Azadirachtin a following applications to mesocosms in a small forest lake.
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Biomedical subjects
Publications and source records attributed to S Capell.
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Assigning anatomic labels to coronary arteries in X-ray angiograms is an important task in medical imaging, motivated by the desire to standardize the assessment of coronary artery disease and to facilitate the three-dimensional (3-D) reconstruction and visualization of the coronary vasculature. However, automatic labeling poses a number of significant challenges, including the presence of noise, artifacts, competing structures, misleading visual cues, and other difficulties associated with a dynamic and inherently complex structure. We have developed a model-guided approach that addresses these challenges and automatically labels the vascular structure in coronary angiographic images. The approach consists of two models: 1) a symbolic model, represented through a directed acyclic graph, that captures vascular tree hierarchies and branch interrelationships and 2) a generalized 3-D model that captures spatial and geometric relationships. Importantly, the approach detects ambiguities (such as vessel overlaps) that may be found in a frame of a ciné sequence, and resolves these ambiguities by considering the information derived from other (unambiguous) frames in the temporal sequence, employing dynamic programming methods to match the image features found in the different (ambiguous and unambiguous) frames. This paper presents this model-guided labeling algorithm and discusses the experimental results obtained from implementing and applying the resulting labeling system to a variety of clinical images. The results indicate the feasibility of achieving robust and consistently accurate image labeling through this model-guided, temporal disambiguation method.
OBJECTIVE: To evaluate the influence of functional status on the outcome in older patients with bacteremia. DESIGN: Prospective study of all episodes of bacteremia that occurred in adults during a 27-month period (January 1991 to March 1993). SETTING: A 280-bed community hospital. PARTICIPANTS: During the study period, bacteremia was diagnosed in 242 consecutive patients (incidence of 11.2 bacteremic episodes per 1000 hospital admissions). One hundred twenty-seven of these patients were 65 years of age or older, and 115 were less than age 65. MEASUREMENTS: On identification of a positive blood culture, data on demographics, clinical findings, and a series of factors frequently cited as predisposing to infection were collected. The patient's functional status was assessed using the Barthel index (a score of < 60 identifies moderately and highly dependent patients). RESULTS: The overall mortality rate was 14.9% (36 of 242). In the univariate analysis, mortality was associated significantly with age greater than 65 years, nosocomial infection, absence of fever, shock, leukocytosis or leukopenia, inappropriate therapy, more than one underlying disease, immuno-compromised state, and limited functional status. Multiple logistic regression analysis revealed that shock (OR = 27.6, 95% CI 5.7-133), a Barthel score less than 60 (OR = 11.7, 95% CI 3.2-43), nosocomial infection (OR = 6.7, 95% CI 1.8-25.5), absence of fever (OR = 5.2, 95% CI 1.05-26), and immunocompromised state (OR = 15.6, 95% CI 2.4-101.5) were significantly associated with death attributable to bacteremia. CONCLUSION: The main prognostic factors in a patient with bacteremia were the presence of shock, impaired functional status, immunodeficiency state, acquisition of infection in the hospital, and absence of fever on admission. Age alone did not influence outcome.
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A 76-yr-old man developed necrotizing fasciitis due to Salmonella enteritidis 1 month after an episode of gastroenteritis due to the same microorganism. The fact that S. enteritidis was the only organism isolated despite adequate anaerobic cultures confirm the ability of salmonellae to produce severe monomicrobial soft tissue infections.
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