61 research outputs found
DESIGNING CANCER GROUPS FOR MAXIMUM EFFECTIVENESS
No full textThis article attempts to shed light on some of the problems involved in developing optimum service groups for cancer patients and offers ideas concerning the design, content, leadership and membership of these groups. The article begins with a literature review of current research on issues faced by cancer patients and how these have been handled in support groups and therapy groups across the country. Following this, suggestions are offered to assist those involved in planning for these groups to deal with some of the potential difficulties encountered by many of these groups. Interest in this project grew out of the author’s personal experience with cancer and from the experience of being first a participant, and later a leader, in groups for cancer patients.Publisher’s note: We are now putting all back issues of Groupwork on line. Articles in this issue have been scanned to pdf files as viable original typesetting files no longer exist. Though they may not look it, these files are to some extent searchable. This issue was published nearly 30 years ago. We have stated author professional details as received at time of publication
Multigenerational challenges and the future of graduate medical education
No full textBackground: Demographics are changing on a global scale. In the United States, an aging population continues to work, either by preference or because of insufficient resources to retire. Of even greater importance, a younger generation, referred to as the Millennial Generation, will soon predominate in the workforce and even now accounts for nearly 100% of resident physicians. By the year 2020, there will be 5 generations in the workplace. Methods: This paper defines and details the characteristics of the 5 generations and examines how the vision, attitudes, values, and expectations of the most recent generations will reshape the workforce and graduate medical education. Results: The need for change is imminent to educate the next generation of physicians. Among the changes necessary to adapt to the multigenerational challenges ahead are adopting mobile devices as preferred communication tools; using social networking sites to recruit residents; adding games, simulations, and interactive videos to the curriculum to engage students; breaking down departmental silos and forming learning teams that come from different specialties; developing benchmarks and milestones to measure progress; extending the social learning ecosystem beyond the resident years; embracing diversity as the norm for both practice and learning; and providing both coaching and mentoring. Conclusion: For decades, resident physicians have shown commitment, tenacity, and selflessness while shouldering the dual responsibility of patient care and the pursuit of their own education and skills development. Resident engagement has been shown to drive change in undergraduate medical education and in the learning and performance of their teachers. The latter is evidence of reverse mentoring that will be a major factor for improvement in this digital age. We have only to embrace this opportunity to the benefit of our patients, our learners, and ourselves
Ten years of MON 810 resistance monitoring of field populations of Ostrinia nubilalis in Europe
No full text9 p.-2 fig.-1 tab.From 2005 to 2015, Ostrinia nubilalis were collected in the most important maize-growing areas in Europe where MON 810 was cultivated. The susceptibility of these
O. nubilalis collections to the Cry1Ab protein was determined using overlay bioassays
and compared to that of reference (control) strains. Larvae that died or did not moult
after 7 days were used to calculate a moulting inhibition concentration (MIC). Two
different batches of Cry1Ab protein were used over the course of this study. Between
2005 and 2015, 145 collections of O. nubilalis from 14 areas were analysed. The
Cry1Ab susceptibility of populations from different geographic regions differed only
slightly across years. The greatest variability in the MIC50 for field samples collected
from 2005 to 2011 and tested with batch 1 was 6.6-fold in 2006. For field-collected
O. nubilalis, the difference between MIC50 values of the most susceptible and most
tolerant samples was 13.1-fold for this period. For samples collected in 2012–2015
and tested with batch 2, the greatest variability was 4.1-fold in 2014. A diagnostic
concentration (MIC99) was calculated for batch 1 (48 ng/cm2) using the results from all
the collections in 2005–2012. Bridging experiments indicated that the diagnostic concentration for batch 2 was 28 ng/cm2. From 2006 onwards, no O. nubilalis reached the 2nd larval stage when the diagnostic concentration of either batch of Cry1Ab was
used. Only one insect collected from Romania in 2012 and two insects collected as
reference strain from Spain in 2015 survived exposure to a dosage of 20 ng/cm2, and
none of these larvae survived on MON 810 maize. Our results indicate that there has
been no significant change in susceptibility to Cry1Ab in European populations of
O. nubilalis over the period 2005–2015.This report presents the results of laboratory-based research and would not have been possible without the kind help of all those who supplied insects: M. Hoenig (Herbolzheim, G), U. Hoffmann(BTL, Keindorf, G), Dr. G. Langenbruch (Darmstadt, G), K.Lindner (Müncheberg, G), A. Schier (Nürtingen, G), D. Proff (Ansbach, G), A.Weissenberger (Wiwersheim, F), A. Mesas and N. Eychenne (Castanet Tolosan, F), I. Rami and N. Daste (Fredon Aquitaine, Villenave d’Ornon,F), K. Koubaïti (Biard, F), Prof. F. Kocourek and V. Falta (Prague, CZ),P. Beres and A. Maslanka (Rzeszow and Warsaw, PL), M. Czepo(Budapest, HU) and Prof. L. Cagan (Nitra, SK), Prof. I. Rosca, I. Sabau(Bucharest, RO), M. Gatti (Repros, Alonte, I) and the laboratory and field technicians of the Spanish group of Plant-Insect Interactions(CIB, CSIC, Madrid, ES). Thanks are also extended to field technicians of Monsanto and Pioneer in Spain and Portugal. Thanks to Monsanto Europe SA for commissioning this study and for providing the Cry1Ab protein.We wish to thank Prof AFG Dixon (UEA Norwich, UK) and Graham Head (Monsanto Company, St Louis, MO, USA) for language
correction.Peer reviewe
Corpos em movimento: um estudo sobre o processo de criação do ator cinematográfico em contexto de formação
No full textDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Filosofia e Ciências Humanas. Programa de Pós-Graduação em Psicologia.Esta dissertação é o resultado de um estudo feito em um curso de atuação para cinema. Com o objetivo geral de investigar o processo de criação do corpo em cena, foram estabelecidos dois objetivos específicos: investigar as mudanças de qualidade no corpo do ator e investigar as diferentes vozes com as quais o ator dialoga neste processo. Para isto, o olhar sobre os movimentos, modos pelos quais o corpo afeta e é afetado, possibilitou uma análise que se fez no diálogo com diferentes perspectivas teóricas, como a teoria psicológica de Vygotsky, a filosofia da linguagem de Bakhtin e a filosofia da vida de Bergson. Reconhecendo as diferenças entre as diversas referências apresentadas neste trabalho foram mobilizados aspectos teóricos que contribuíram com problematizações que emergiram na pesquisa de campo. Numa perspectiva que desnaturaliza a realidade estudada e que não sobrepõe ao real conceitos a priori, o empírico permitiu o olhar sobre as diferenças, singularidades que a vida não cessa de produzir. No contexto estudado ressaltaram-se jogos com os limites entre ficção e realidade que o próprio dispositivo coloca e retira. A análise aponta para diversos modos da criação acontecer, impossibilitando generalizações, inclusive dentro de um mesmo dispositivo artístico. Deste modo, afirmam-se os processos de criação como acontecimentos que se dão no situacional, em eventos que lançam possibilidades e devires
Cell reliability, response size, and odor specificity follow a continuous distribution.
No full text(A) Schematic of 3 response properties that were examined for odors and odor-pairs. Odor reliability refers to the number of trials for which a cell is responsive. Each trial is depicted by a grid square, and black color indicates a response. Cells that respond in more than half the trials were classified as reliable; all other responsive cells were unreliable. Odor response size is the firing rate of the cell in individual trials, as measured by Ca2+ fluorescence. The top line shows a cell with a large response, where the intensity of gray denotes size of response. Odor overlap is the probability that the cell will respond to both odors. The odor overlap here is shown in yellow and decreases for dissimilar odors (bottom) compared to similar odors (top). (B, E) Cumulative frequency histograms showing the distribution of reliabilities for KCs (flies) and PCx cells (mice). Each circle represents the cumulative probability for cells with a reliability value represented on the x-axis. The points are fit by Gamma distributions with shape = 0.64, scale = 0.42 (for B, fly) and shape = 0.64, scale = 0.17 (for E, mice). The significance of the Gamma distribution is that it is a maximum entropy code and optimizes for the most stimuli that can be encoded (see text). (C, F) Cumulative frequency histograms for response sizes in both flies and mice are well fit by Gamma distributions with shape = 0.77, scale = 0.28 (for C, fly) and shape = 0.70, scale = 0.24 (for F, mice). (D, G) Cumulative frequency histograms for the overlap of cells between odor-pairs in both flies and mice, also fit using Gamma distributions with shape = 0.19, scale = 0.60 (for D, fly) and shape = 0.18, scale = 0.35 (for G, mice). Datasets used in these plots for flies (B–D) and mice (E–G) are stored within the Zenodo and Dandi repositories as the main dataset for flies and dataset 164 for mice, respectively. The data underlying the graphs shown in the figure can be found in S2 Data. KC, Kenyon cell; PCx, piriform cortex.</p
A WTA mechanism is needed for generating stochastic codes.
No full text(A, left) Schematic of information transfer in the fly olfactory circuit. Odor information from OSNs is passed from glomeruli to KCs (via PNs) in the MB. KCs synapse with MBONs that influence behavior. The KC→MBON synapses are subject to synaptic plasticity. (A, right) The WTA circuit in MB, where all KCs activate the inhibitory APL neuron that in turn feeds back and inhibits all KCs. (B) A schematic of the linear rate firing model. The PN response to odors is depicted in blue, and their connection matrix with KCs is denoted in red. With a linear rate firing model, we take a product of the odor vector and connection matrix to get the KC response, which is sparsified by the APL neuron inhibitory feedback. (C, D) Examples of how the model was checked against constraints. Model simulations show that injecting noise in (C) PNs or (D) KC-APL synapses produces different ratios of reliable to unreliable cells responding per trial. The straight line in the plots denotes a reliable/unreliable cell ratio of 0.72 observed with experimental MB responses (Fig 1). For both plots, the x-axis denotes the fraction of injected noise. Thus, 1 denotes that noise levels are 100% of signal. (E–G) Distribution of individual parameters that make up the “successful” parameter sets. Here, the 6 parameters were varied over a large range (Methods), and we have plotted individual cumulative distributions to show the dependence of the stochastic code on various parameters. (E) PN noise is uniformly distributed. (F) APL noise is normally distributed with a mean of 0.28. (G) KC noise cumulative distribution, where the initial noise is uniformly distributed. (H) There is a an inverse relationship between APL and KC noise. With increasing KC noise, the amount of APL noise that is required for the stochastic code is reduced. Error bars indicate SEM. See Table B in S1 Text, Fig J in S1 Text, Fig K in S1 Text, Fig G in S1 Text, and Methods for more details. APL, anterior paired lateral; KC, Kenyon cell; MB, mushroom body; MBON, MB output neuron; OSN, olfactory sensory neuron; PN, projection neuron; WTA, winner-take-all.</p
Critical steps during prilling process of molten lipids: main stumbling blocks due to pharmaceutical excipient properties
No full textInternational audiencePrilling by ultrasonic jet break-up is an efficient process to produce perfectly spherical microparticles homogeneous in size. However, the material properties could affect the manufacturability and the final product properties especially with lipid-based excipients which often exhibit complex structural properties. This work presents the characterisation of six lipid-based excipients differing by their melting point and polymorphic behaviour which were used to produce microspheres using a pilot-scale prilling equipment. The experimental results were compared to theoretical calculations, especially the droplet solidification time which is a key-parameter for this process. This work highlighted that monotropic polymorphism of excipients and supercooling effect have a significant impact on process parameters which should be considered with care during formulation design
Pneumocystis jirovecii genotypes and granulomatous pneumocystosis
No full textInternational audienceThis study describes the initial data concerning molecular typing of Pneumocystis jirovecii in a patient having developed granulomatous Pneumocystis pneumonia (PCP). Three types, B(1)a(3), B(1)a(4), B(1)b(2), were identified. All three had been described in reports concerning patients with common diffuse alveolar PCP. The present data show that identical microorganisms can be involved in both granulomatous PCP and diffuse alveolar PCP and that the pathogenesis of the granulomatous response to P. jirovecii may more likely be related to host factors. = Nous présentons les premières données concernant l'identification des génotypes de Pneumocystis jirovecii chez un patient ayant développé une pneumocystose (PPC) granulomateuse. Trois génotypes, B1a3, B1a4, B1b2, ont été identifiés. Ces génotypes sont usuellement retrouvés dans la forme classique alvéolaire de la PPC. Ces résultats montrent que des micro-organismes identiques peuvent être impliqués dans ces deux formes histologiques de la PPC et suggèrent que l'étiologie de la réaction granulomateuse se rapporterait plutôt à des facteurs liés aux patients
Fig A. Odor response sizes in the fly MB and mouse PCx cells increases with reliability.
No full textFig B. Responses in Mouse PCx cells are more variable compared to flies. Fig C. Reliable cells preserve odor-similarity better than unreliable cells. Fig D. Unreliable cells are more likely to respond differently between similar odors compared to reliable cells. Fig E. The probability of overlap cell increases from similar to dissimilar odors. Fig F. Unreliable cells are a composition of cells with different levels of reliabilities. Fig G. Noise in the winner-take-all mechanism produces a stochastic code. Fig H. Sparse coding does not improve discrimination ability for similar odors. Fig I. The effect of the significance levels on discrimination analysis. Fig J. The effect of the significance levels on discrimination analysis. Fig K. Fly circuit model parameter explorations. Table A. Possible contributions by cell x towards discrimination. Table B. The top 40 parameter combinations (out of 44,217) of the single synapse model that produced results most similar to the ones observed in Fig 1C and 1D. Table C. Results of the performance of 3 linear classifiers/decoders on the fly and mouse datasets. Table D. The response characteristics (Fig 1) for all the flies that were examined. Table E. The response characteristics (Fig 1) for all the mice that were examined. (PDF)</p
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