969 resultados para Training load
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Magdeburg, Univ., Fak. für Humanwiss., Diss., 2013
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Fabienne-Agnes Baumann, Klaus Jenewein, Axel Müller
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Magdeburg, Univ., Fak. für Humanwiss., Diss., 2015
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Otto-von-Guericke-Universität Magdeburg, Fakultät für Maschinenbau, Univ., Dissertation, 2015
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RESUME Nous n'avons pas de connaissance précise des facteurs à l'origine de l'hétérogénéité phénotypique des cellules T CD4 mémoires. Une troisième population phénotypique des cellules T CD4 mémoires, caractérisée par les marqueurs CD45RA+CCR7- a été identifiée dans cette étude. Cette population présente un état de différentiation avancée, comme en témoigne son histoire de réplication, ainsi que sa capacité de prolifération homéostatique. Les réponses des cellules T CD4 mémoires à différentes conditions de persistance et charge antigénique ont trois patterns phénotypiques différents, caractérisés par les marqueurs CD45RA et CCR7. La réponse CD4 mono -phénotypique CD45RA-CCR7+ ou CD45RA- CCR7- est associée à des conditions d'élimination de l'antigène (telle la réponse CD4 tétanos spécifique) ou à des conditions de persistance antigénique et de virémie élevée (telle la réponse HIV chronique ou la primo-infection CMV) respectivement. D'autre part, les réponses T CD4 multi -phénotypiques CD45RA-CCR7+ sont associées à des conditions d'exposition antigénique prolongée et de faible virémie (telles les infections CMV, EBV et HSV ou les infections HIV chez les long term non progressons). La réponse mono -phénotypique CD45RA- CCR7+ est propre aux cellules T CD4 secrétant de IL2, définies également comme centrales mémoires, la réponse CD45RA- CCR7- aux cellules T CD4 secrétant de l'IFNγ et finalement la réponse mufti-phénotypique aux cellules T CD4 secrétant à la fois de l'IL2 et de l' IFNγ. En conclusion, ces résultats témoignent d'une régulation de l'hétérogénéité phénotypique par l'exposition et la charge antigénique. ABSTRACT The factors responsible for the phenotypic heterogeneity of memory CD4 T cells are unclear. In the present study, we have identified a third population of memory CD4 T cells characterized as CD45RA+CCRT that, based on its replication history and the homeostatic proliferative capacity, was at an advanced stage of differentiation. Three different phenotypic patterns of memory CD4 T cell responses were delineated under different conditions of antigen (Ag) persistence and load using CD45RA and CCR7 as markers of memory T cells. Mono-phenotypic CD45RA'CCR7+ or CD45RA'CCR7' CD4 T cell responses were associated with conditions of Ag clearance (tetanus toxoid-specific CD4 T cell response) or Ag persistence and high load (chronic HIV-1 and primary CMV infections), respectively. Multi-phenotypic CD45RA CCR7+, CD45RA'CCRT and CD45RA+CCRT CD4 T cell responses were associated with protracted Ag exposure and low load (chronic CMV, EBV and HSV infections and HIV-1 infection in long-term nonprogressors). The mono-phenotypic CD45RA'CCR7+ response was typical of central memory (TCM) IL-2-secreting CD4 T cells, the mono-phenotypic CD45RA CCRT response of effector memory (TEM) IFN-γ -secreting CD4 T cells and the multi-phenotypic response of both IL-2- and IFN-γ -secreting cells. The present results indicate that the heterogeneity of different Ag-specific CD4 T cell responses is regulated by Ag exposure and Ag load.
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OBJECTIVE: To examine the effectiveness of motivational interviewing (MI) training among medical students. METHODS: All students (n=131) (year 5) at Lausanne Medical School, Switzerland were randomized into an experimental or a control group. After a training in basic communication skills (control condition), an 8-h MI training was completed by 84.8% students in the exprimental group. One week later, students in both groups were invited to meet with two standardized patients. MI skills were coded by blinded research assistants using the Motivational Interviewing Treatment Integrity 3.0. RESULTS: Superior MI performance was shown for trained versus control students, as demonstrated by higher scores for "Empathy" [p<0.001] and "MI Spirit" [p<0.001]. Scores were similar between groups for "Direction", indicating that students in both groups invited the patient to talk about behavior change. Behavior counts assessment demonstrated better performance in MI in trained versus untrained students regarding occurences of MI-adherent behavior [p<0.001], MI non-adherent behavior [p<0.001], Closed questions [p<0.001], Open questions [p=0.001], simple reflections [p=0.03], and Complex reflections [p<0.001]. Occurrences were similar between groups regarding "Giving information". CONCLUSION: An 8-h training workshop was associated with improved MI performance. PRACTICE IMPLICATIONS: These findings lend support for the implementation of MI training in medical schools.
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Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.
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Background and Aims: IL28B polymorphisms, interferon (IFN)-gamma inducible protein-10 (IP-10) levels and the homeostasis model assessment of insulin resistance (HOMA-IR) score have been reported to predict rapid (RVR) and sustained (SVR) virological response in chronic hepatitis C (CHC), but it is not known whether these factors represent independent, clinically useful predictors. The aim of the study was to assess factors (including IL28B polymorphisms, IP-10 levels and HOMA-IR score) independently predicting response to therapy in CHC under real life conditions.Methods: Multivariate analysis of factors predicting RVR and SVR in 280 consecutive, treatment-naive CHC patients treated with pegylated IFN alpha and ribavirin in a prospective multicenter study.Results: Independent predictors of RVR were HCV RNA < 400,000 IU/ml (OR11.37; 95% CI 3.03-42.6), rs12980275 AA (vs. AG/GG) (OR 7.09; 1.97-25.56) and IP-10 (OR 0.04; 0.003-0.56) in HCV genotype 1 patients and lower baseline γ-glutamyl-transferase levels (OR = 0.02; 0.0009-0.31) in HCV genotype 3 patients. Independent predictors of SVR were rs12980275 AA (OR 9.68; 3.44-27.18), age < 40 yrs (OR = 4.79; 1.50-15.34) and HCV RNA < 400,000 IU/ml (OR 2.74; 1.03-7.27) in HCV genotype 1 patients and rs12980275 AA (OR = 6.26; 1.98-19.74) and age < 40 yrs (OR 5.37; 1.54-18.75) in the 88 HCV genotype 1 patients without a RVR. RVR was by itself predictive of SVR in HCV genotype 1 patients (32 of 33, 97%; OR 33.0; 4.06-268.32) and the only independent predictor of SVR in HCV genotype 2 (OR 9.0, 1.72-46.99; p=0.009) or 3 patients (OR 7.8, 1.43-42.67; p=0.01).Conclusions: In HCV genotype 1 patients, IL28B polymorphisms, HCV RNA load and IP-10 independently predict RVR. The combination of IL28B polymorphisms, HCV RNA level and age may yield more accurate pretreatment prediction of SVR. HOMA-IR score is not associated with viral response.
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Challenging environmental conditions, including heat and humidity, cold, and altitude, pose particular risks to the health of Olympic and other high-level athletes. As a further commitment to athlete safety, the International Olympic Committee (IOC) Medical Commission convened a panel of experts to review the scientific evidence base, reach consensus, and underscore practical safety guidelines and new research priorities regarding the unique environmental challenges Olympic and other international-level athletes face. For non-aquatic events, external thermal load is dependent on ambient temperature, humidity, wind speed and solar radiation, while clothing and protective gear can measurably increase thermal strain and prompt premature fatigue. In swimmers, body heat loss is the direct result of convection at a rate that is proportional to the effective water velocity around the swimmer and the temperature difference between the skin and the water. Other cold exposure and conditions, such as during Alpine skiing, biathlon and other sliding sports, facilitate body heat transfer to the environment, potentially leading to hypothermia and/or frostbite; although metabolic heat production during these activities usually increases well above the rate of body heat loss, and protective clothing and limited exposure time in certain events reduces these clinical risks as well. Most athletic events are held at altitudes that pose little to no health risks; and training exposures are typically brief and well-tolerated. While these and other environment-related threats to performance and safety can be lessened or averted by implementing a variety of individual and event preventative measures, more research and evidence-based guidelines and recommendations are needed. In the mean time, the IOC Medical Commission and International Sport Federations have implemented new guidelines and taken additional steps to mitigate risk even further.
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A review article of the The New England Journal of Medicine refers that almost a century ago, Abraham Flexner, a research scholar at the Carnegie Foundation for the Advancement of Teaching, undertook an assessment of medical education in 155 medical schools in operation in the United States and Canada. Flexner’s report emphasized the nonscientific approach of American medical schools to preparation for the profession, which contrasted with the university-based system of medical education in Germany. At the core of Flexner’s view was the notion that formal analytic reasoning, the kind of thinking integral to the natural sciences, should hold pride of place in the intellectual training of physicians. This idea was pioneered at Harvard University, the University of Michigan, and the University of Pennsylvania in the 1880s, but was most fully expressed in the educational program at Johns Hopkins University, which Flexner regarded as the ideal for medical education. (...)
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Intermittent hypoxic exposure with exercise training is based on the assumption that brief exposure to hypoxia is sufficient to induce beneficial muscular adaptations mediated via hypoxia-inducible transcription factors (HIF). We previously demonstrated (Mounier et al. Med Sci Sports Exerc 38:1410-1417, 2006) that leukocytes respond to hypoxia with a marked inter-individual variability in HIF-1alpha mRNA. This study compared the effects of 3 weeks of intermittent hypoxic training on hif gene expression in both skeletal muscle and leukocytes. Male endurance athletes (n = 19) were divided into an Intermittent Hypoxic Exposure group (IHE) and a Normoxic Training group (NT) with each group following a similar 3-week exercise training program. After training, the amount of HIF-1alpha mRNA in muscle decreased only in IHE group (-24.7%, P < 0.05) whereas it remained unchanged in leukocytes in both groups. The levels of vEGF(121) and vEGF(165) mRNA in skeletal muscle increased significantly after training only in the NT group (+82.5%, P < 0.05 for vEGF(121); +41.2%, P < 0.05 for vEGF(165)). In leukocytes, only the IHE group showed a significant change in vEGF(165) (-28.2%, P < 0.05). The significant decrease in HIF-1alpha mRNA in skeletal muscle after hypoxic training suggests that transcriptional and post-transcriptional regulations of the hif-1alpha gene are different in muscle and leukocytes.
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BACKGROUND: The value of adenovirus plasma DNA detection as an indicator for adenovirus disease is unknown in the context of T cell-replete hematopoietic cell transplantation, of which adenovirus disease is an uncommon but serious complication. METHODS: Three groups of 62 T cell-replete hematopoietic cell transplant recipients were selected and tested for adenovirus in plasma by polymerase chain reaction. RESULTS: Adenovirus was detected in 21 (87.5%) of 24 patients with proven adenovirus disease (group 1), in 4 (21%) of 19 patients who shed adenovirus (group 2), and in 1 (10.5%) of 19 uninfected control patients. The maximum viral load was significantly higher in group 1 (median maximum viral load, 6.3x10(6) copies/mL; range, 0 to 1.0x10(9) copies/mL) than in group 2 (median maximum viral load, 0 copies/mL; range, 0 to 1.7x10(8) copies/mL; P<.001) and in group 3 (median maximum viral load, 0 copies/mL; range 0-40 copies/mL; P<.001). All patients in group 2 who developed adenoviremia had symptoms compatible with adenovirus disease (i.e., possible disease). A minimal plasma viral load of 10(3) copies/mL was detected in all patients with proven or possible disease. Adenoviremia was detectable at a median of 19.5 days (range, 8-48 days) and 24 days (range, 9-41 days) before death for patients with proven and possible adenovirus disease, respectively. CONCLUSION: Sustained or high-level adenoviremia appears to be a specific and sensitive indicator of adenovirus disease after T cell-replete hematopoietic cell transplantation. In the context of low prevalence of adenovirus disease, the use of polymerase chain reaction of plasma specimens to detect virus might be a valuable tool to identify and treat patients at risk for viral invasive disease.