19 resultados para Integrated teaching of portuguese

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Vital tissue provided by fresh frozen tissue banking is often required for genetic tumor profiling and tailored therapies. However, the potential patient benefits of fresh frozen tissue banking are currently limited to university hospitals. The objective of the present pilot study--the first one in the literature--was to evaluate whether fresh frozen tissue banking is feasible in a regional hospital without an integrated institute of pathology.

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This field study examined the vitellogenin (VTG) biomarker response under conditions of low and fluctuating activities of environmental estrogenicity. The present study was performed on immature brown trout (Salmo trutta) exposed to the small river Luetzelmurg, which is located in the prealpine Swiss midland region and receives effluents from a single sewage treatment plant (STP). To understand better factors influencing the relationship between estrogenic exposure and VTG induction, we compared VTG levels in caged (stationary) and feral (free-ranging) fish, VTG levels in fish from up- and downstream of the STP, and two different methods for quantifying VTG (enzyme-linked immunosorbent assay vs real-time reverse transcription-polymerase chain reaction), and we used passive samplers (polar organic chemical integrative sampler [POCIS]) to integrate the variable, bioaccumulative estrogenic load in the river water over time. The POCIS from the downstream site contained approximately 20-fold higher levels of bioassay-derived estrogen equivalents than the POCIS from the upstream site. In feral fish, this site difference in estrogenic exposure was reflected in VTG protein levels but not in VTG mRNA. In contrast, in caged fish, the site difference was evident only for VTG mRNA but not for VTG protein. Thus, the outcome of VTG biomarker measurements varied with the analytical detection method (protein vs mRNA) and with the exposure modus (caged vs feral). Our findings suggest that for environmental situations with low and variable estrogenic contamination, a multiple-assessment approach may be necessary for the assessment of estrogenic exposure in fish.

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Drug-induced respiratory depression is a common side effect of the agents used in anesthesia practice to provide analgesia and sedation. Depression of the ventilatory drive in the spontaneously breathing patient can lead to severe cardiorespiratory events and it is considered a primary cause of morbidity. Reliable predictions of respiratory inhibition in the clinical setting would therefore provide a valuable means to improve the safety of drug delivery. Although multiple studies investigated the regulation of breathing in man both in the presence and absence of ventilatory depressant drugs, a unified description of respiratory pharmacodynamics is not available. This study proposes a mathematical model of human metabolism and cardiorespiratory regulation integrating several isolated physiological and pharmacological aspects of acute drug-induced ventilatory depression into a single theoretical framework. The description of respiratory regulation has a parsimonious yet comprehensive structure with substantial predictive capability. Simulations relative to the synergistic interaction of the hypercarbic and hypoxic respiratory drive and the global effect of drugs on the control of breathing are in good agreement with published experimental data. Besides providing clinically relevant predictions of respiratory depression, the model can also serve as a test bed to investigate issues of drug tolerability and dose finding/control under non-steady-state conditions.

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Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

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Surface temperature is a key aspect of weather and climate, but the term may refer to different quantities that play interconnected roles and are observed by different means. In a community-based activity in June 2012, the EarthTemp Network brought together 55 researchers from five continents to improve the interaction between scientific communities who focus on surface temperature in particular domains, to exploit the strengths of different observing systems and to better meet the needs of different communities. The workshop identified key needs for progress towards meeting scientific and societal requirements for surface temperature understanding and information, which are presented in this community paper. A "whole-Earth" perspective is required with more integrated, collaborative approaches to observing and understanding Earth's various surface temperatures. It is necessary to build understanding of the relationships between different surface temperatures, where presently inadequate, and undertake large-scale systematic intercomparisons. Datasets need to be easier to obtain and exploit for a wide constituency of users, with the differences and complementarities communicated in readily understood terms, and realistic and consistent uncertainty information provided. Steps were also recommended to curate and make available data that are presently inaccessible, develop new observing systems and build capacities to accelerate progress in the accuracy and usability of surface temperature datasets.

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This study presents new paleoenvironmental data obtained from sedimentary cores from Lago Fagnano, an elon- gated lake located at 54°S in southernmost South America. Data from palynomorphs (pollen, spores and algae) and associated palynofacies as well as from diatom taxa retrieved from these cores compared with other regional proxies contribute to evaluate the similarities and differences in the climate patterns based on different proxies from southernmost Patagonia. The pollen analysis reveals that a grass steppe environment existed during the early Holocene (11,300–~8000 cal a BP) followed by a major vegetation change characterized by development of forest-steppe ecotone communities between ~8000 and ~6500 cal a BP, under more humid conditions. Between ~ 6500 and ~ 4000 cal a BP, expansion and colonization by Nothofagus forests reflect an increase in effec- tive moisture levels, while openness in the forest communities characterizes the region after ~ 1100 cal a BP. The palynological organic matter combined with the algal content reflects hydrological changes occurring in the lake and its nutrient status, probably in close relation with past climate oscillations. All these past ecological changes are closely related to oscillations in precipitation and temperature as a response to the variations in the latitudinal position and/or strength of the Southern Westerlies wind belt during the Holocene.

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BACKGROUND Clinical prognostic groupings for localised prostate cancers are imprecise, with 30-50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors. METHODS We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort [MSKCC] cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment. FINDINGS Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio [HR] 4·5 [95% CI 2·1-9·8]; p=0·00013; area under the receiver operator curve [AUC] 0·70 [95% CI 0·65-0·76]) and radical prostatectomy (4·0 [1·6-9·7]; p=0·0024; AUC 0·57 [0·52-0·61]) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3·8 [1·2-12]; p=0·019; AUC 0·67 [0·61-0·73]). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6·1 [95% CI 2·0-19]; p=0·0015; AUC 0·74 [95% CI 0·65-0·83]). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2·9 [95% CI 1·4-6·0]; p=0·0039; AUC 0·68 [95% CI 0·63-0·73]), and was better at predicting biochemical relapse than 23 previously published RNA signatures. INTERPRETATION This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials. FUNDING Movember Foundation, Prostate Cancer Canada, Ontario Institute for Cancer Research, Canadian Institute for Health Research, NIHR Cambridge Biomedical Research Centre, The University of Cambridge, Cancer Research UK, Cambridge Cancer Charity, Prostate Cancer UK, Hutchison Whampoa Limited, Terry Fox Research Institute, Princess Margaret Cancer Centre Foundation, PMH-Radiation Medicine Program Academic Enrichment Fund, Motorcycle Ride for Dad (Durham), Canadian Cancer Society.