835 resultados para Parallel version
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Cervical cancer results from cervical infection by human papillomaviruses (HPVs), especially HPV16. An effective vaccine against these HPVs is expected to have a dramatic impact on the incidence of this cancer and its precursor lesions. The leading candidate, a subunit prophylactic HPV virus-like particle (VLP) vaccine, can protect women from HPV infection. An alternative improved vaccine that avoids parenteral injection, that is efficient with a single dose, and that induces mucosal immunity might greatly facilitate vaccine implementation in different settings. In this study, we have constructed a new generation of recombinant Salmonella organisms that assemble HPV16 VLPs and induce high titers of neutralizing antibodies in mice after a single nasal or oral immunization with live bacteria. This was achieved through the expression of a HPV16 L1 capsid gene whose codon usage was optimized to fit with the most frequently used codons in Salmonella. Interestingly, the high immunogenicity of the new recombinant bacteria did not correlate with an increased expression of L1 VLPs but with a greater stability of the L1-expressing plasmid in vitro and in vivo in absence of antibiotic selection. Anti-HPV16 humoral and neutralizing responses were also observed with different Salmonella enterica serovar Typhimurium strains whose attenuating deletions have already been shown to be safe after oral vaccination of humans. Thus, our findings are a promising improvement toward a vaccine strain that could be tested in human volunteers.
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The statistical analysis of compositional data should be treated using logratios of parts,which are difficult to use correctly in standard statistical packages. For this reason afreeware package, named CoDaPack was created. This software implements most of thebasic statistical methods suitable for compositional data.In this paper we describe the new version of the package that now is calledCoDaPack3D. It is developed in Visual Basic for applications (associated with Excel©),Visual Basic and Open GL, and it is oriented towards users with a minimum knowledgeof computers with the aim at being simple and easy to use.This new version includes new graphical output in 2D and 3D. These outputs could bezoomed and, in 3D, rotated. Also a customization menu is included and outputs couldbe saved in jpeg format. Also this new version includes an interactive help and alldialog windows have been improved in order to facilitate its use.To use CoDaPack one has to access Excel© and introduce the data in a standardspreadsheet. These should be organized as a matrix where Excel© rows correspond tothe observations and columns to the parts. The user executes macros that returnnumerical or graphical results. There are two kinds of numerical results: new variablesand descriptive statistics, and both appear on the same sheet. Graphical output appearsin independent windows. In the present version there are 8 menus, with a total of 38submenus which, after some dialogue, directly call the corresponding macro. Thedialogues ask the user to input variables and further parameters needed, as well aswhere to put these results. The web site http://ima.udg.es/CoDaPack contains thisfreeware package and only Microsoft Excel© under Microsoft Windows© is required torun the software.Kew words: Compositional data Analysis, Software
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We have examined the internal validity of the French translation of the NEO PI-R personality test which measures the « big five » (Rolland, 1993). The impact of age, gender and professional categories on the NEO PI-R scales was assessed. A large sample (n=731) of subjects of different age, gender and profession and a sample of Swiss students (n=261) responding anonymously were used. Factor analyses confirmed the structure of the instrument (5 domains) and the structures of the domains in terms of facets (six facets within each domain). On the other hand, the age has a significant impact on all the domains of the NEO PI-R; the gender has an impact on the scores on N (neuroticism), O (openness) and A (agreeableness), and the profession has an impact on the domains E (extraversion), O (openness) and A (agreeableness). The scores on several facets are also affected by those three variables. Our study gives the researchers and the practitioner a reference score table according to the studied variables.
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We have examined the internal validity of the Levenson's locus of control scales (IPC, Internal, Powerful others and Chances), translated by Loas et al. (1994). The impact of different demographic variables on the Levenson's locus of control scales was assessed. After, we studied the relation between the IPC scales and the NEO PI R, personality inventory that measures the big five. A large sample (n=200) of subjects of different age, gender and profession and a sample of Swiss students (n=161) responding anonymously were used. The reliability of the IPC scale is acceptable. The analyses of the impact of the demographic variables show that gender and level of education have an influence on the I (intern) scale. Age, gender, level of education and profession have an impact on the P (powerful others) scale. The analyses of the relationship between locus of control and personality showed that there was a negative correlation between I (intern) and Neuroticism and a positive correlation between I and Extraversion and Consciousness. The P (powerful others) scale correlate positively with Neuroticism and negatively with Openness and Agreability. The C scale (chance) correlate positively with Neuroticism. Our study also gives the researchers and the practitioner a reference score table according to the gender, the age, the level of education and the profession.
Validation d'une version abrégée du TCI (TCI-56) sur un échantillon de jeunes fumeurs et non-fumeurs
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Introduction: The psychobiological seven-factor model proposed by Cloninger et al. (1993) takes into account temperament and character dimensions to describe personality. Four of the dimensions are linked with biological, genetic and neuroanatomic structures, whereas the three other dimensions are related to the degree of individual, social and spiritual development. A study conducted by Wills et al. (1994) with adolescents showed that substance abuse was associated with high scores on Novelty Seeking and low scores on Harm Avoidance and Reward Dependence. The aim of the present study was, firstly, to create a short form of Cloninger's (1993) Temperament and Character Inventory (TCI) and, secondly, to study the impact of nicotine dependence as well as demographic variables on a sample of young adults. Method: We created a short form of the TCI containing 56 items (TCI-56), 8 for each scale. Responses are made on a five-point Likert type scale. A Swiss sample (n=211), of 116 women and 95 men, aged from 15 to 30 years, participated in this study. Our population was divided into a group of 81 smokers and another of 130 non-smokers, according to their scores on the Fagerstörm test for nicotine dependence (1999). Results: The structural validation consisted of two separate factor analysis with varimax rotations, one for the temperamental items, and the other, for the character ones. The first factor analysis conducted on the items of the temperament scales allowed to extract 4 factors explaining 40.7% of the variance. The correlations between factors and scales are the following: r=.71 for Novelty Seeking, r=.69 for Persistence, r=.95 for Harm Avoidance, r=.94 for Reward Dependence. The second factor analysis conducted on the items of the character scales allowed to extract 3 factors explaining 41.5% of the variance. The correlations between factors and scales are the following: r=.94 for Self-Directedness, r=.91 for Cooperativeness and r=.99 for Self-Transcendence. The internal consistencies range from α=.65 to α=.75 for the temperament scales, and from α=.71 to α=.83 for the three character scales. Concerning, the impact of the nicotine dependence, we observed that smokers have significantly higher scores for Novelty seeking, than non-smokers (p=.01). We found no difference for Harm Avoidance and Reward Dependence. Nevertheless, smokers seem to have the tendency to score higher on Transcendence (p=.06). Moreover, people having smoked more than 100 cigarettes in their life have significantly higher scores on this scale (p.04) and the correlation between Transcendence and the Fagerstörm test is significant (r=.19). We also found gender differences: the women (N=116) obtain significantly higher scores for Harm Avoidance (p<.001), for Reward Dependence (p<.001) and for Cooperation (p=.01). We further found a significant correlation between age and Self-Directedness, r=.34. We observed no interaction between gender and smoking or age and smoking on the dimensions of the TCI-56. Discussion: The TCI short form (TCI-56) seems to be a valid and useful inventory to assess personality differences. Confirming the results of others about the relation between addiction and personality, we found that smokers have significantly higher scores for Novelty seeking, than non-smokers. But we were not able to find any significant differences for Harm Avoidance and Reward Dependence. This might be due to our sample that was made of young adults. This study also shows that Transcendence could be an interesting dimension for studies on Tobacco smoking to consider. Concerning the impact of demographic variables, we observed that age and gender have specific and coherent influence on personality.
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Three different short versions of the NEO-PI-R were compared: The NEO-FFI, the NEO-FFI-R, and a new short version developed in the current study (NEO-60). This new version is intended to improve the psychometric characteristics of the original NEO-FFI, specially in regard to the factor structure at the item-level. A French version of the NEO-PI-R was given to 1090 Swiss subjects, whereas the Spanish (Castilian) version of the NEO-PI-R was administered to 1006 Spanish subjects. Results replicate the limitations of the NEO-FFI already found in other countries. Compared to the NEO-FFI, reliability coefficients and factor structure was enhanced by the NEO-FFI-R and the NEO-60 in both samples, although substantial differences were not found. The factor structure of the NEO-60 shows the best fit since only three items do not load mainly on their own factor in both samples. Besides, correlations between items and NEO-PI-R domain scores are also higher for the items included in the NEO-60 version. On the other hand, convergent correlations with the NEO-PI-R dimensions were satisfactory irrespective of the version, and confirmatory factor analyses show slight differences among the different models generated after the three short versions.
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Référence bibliographique : Singer, 46
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Référence bibliographique : Singer, 46
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Référence bibliographique : Singer, 46
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BACKGROUND Breast cancer survivors suffer physical impairment after oncology treatment. This impairment reduces quality of life (QoL) and increase the prevalence of handicaps associated to unhealthy lifestyle (for example, decreased aerobic capacity and strength, weight gain, and fatigue). Recent work has shown that exercise adapted to individual characteristics of patients is related to improved overall and disease-free survival. Nowadays, technological support using telerehabilitation systems is a promising strategy with great advantage of a quick and efficient contact with the health professional. It is not known the role of telerehabilitation through therapeutic exercise as a support tool to implement an active lifestyle which has been shown as an effective resource to improve fitness and reduce musculoskeletal disorders of these women. METHODS / DESIGN This study will use a two-arm, assessor blinded, parallel randomized controlled trial design. People will be eligible if: their diagnosis is of stages I, II, or IIIA breast cancer; they are without chronic disease or orthopedic issues that would interfere with ability to participate in a physical activity program; they had access to the Internet and basic knowledge of computer use or living with a relative who has this knowledge; they had completed adjuvant therapy except for hormone therapy and not have a history of cancer recurrence; and they have an interest in improving lifestyle. Participants will be randomized into e-CUIDATE or usual care groups. E-CUIDATE give participants access to a range of contents: planning exercise arranged in series with breathing exercises, mobility, strength, and stretching. All of these exercises will be assigned to women in the telerehabilitation group according to perceived needs. The control group will be asked to maintain their usual routine. Study endpoints will be assessed after 8 weeks (immediate effects) and after 6 months. The primary outcome will be QoL measured by The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 version 3.0 and breast module called The European Organization for Research and Treatment of Cancer Breast Cancer-Specific Quality of Life questionnaire. The secondary outcomes: pain (algometry, Visual Analogue Scale, Brief Pain Inventory short form); body composition; physical measurement (abdominal test, handgrip strength, back muscle strength, and multiple sit-to-stand test); cardiorespiratory fitness (International Fitness Scale, 6-minute walk test, International Physical Activity Questionnaire-Short Form); fatigue (Piper Fatigue Scale and Borg Fatigue Scale); anxiety and depression (Hospital Anxiety and Depression Scale); cognitive function (Trail Making Test and Auditory Consonant Trigram); accelerometry; lymphedema; and anthropometric perimeters. DISCUSSION This study investigates the feasibility and effectiveness of a telerehabilitation system during adjuvant treatment of patients with breast cancer. If this treatment option is effective, telehealth systems could offer a choice of supportive care to cancer patients during the survivorship phase. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01801527.
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In the eighties, John Aitchison (1986) developed a new methodological approach for the statistical analysis of compositional data. This new methodology was implemented in Basic routines grouped under the name CODA and later NEWCODA inMatlab (Aitchison, 1997). After that, several other authors have published extensions to this methodology: Marín-Fernández and others (2000), Barceló-Vidal and others (2001), Pawlowsky-Glahn and Egozcue (2001, 2002) and Egozcue and others (2003). (...)