Determinants of the effect of existential behavioral therapy for bereaved partners: a qualitative study.

BACKGROUND: Informal caregivers of palliative patients took part in existential behavioral therapy (EBT), a group intervention comprising mindfulness exercises to reduce psychological distress and improve quality of life. OBJECTIVES: This study examined what the participants perceived as helpful to cope with their loss during the first year of bereavement, particularly with regard to the EBT intervention. DESIGN: Sixteen problem-centered, semi-structured interviews were evaluated with content analysis. RESULTS: Two main categories were found: social support and self-regulation. Social support includes sense of belonging as well as emotional, cognitive, and practical help experienced from others. Mindfulness and acceptance, a clear focus on the positive, and orientation toward the future were helpful strategies of self-regulation; these were also part of the EBT intervention. Mindfulness was understood as permitting emotions and acceptance of one's inner processes, even if they were not pleasant, and was found to be helpful to stop ruminative thinking. CONCLUSIONS: The categories considered as being helpful parallel core elements of EBT and recent grief theories. The intervention was found to be supportive and met the needs of the participants. The interviewees appreciated the continuity of EBT support from palliative care into bereavement.

A qualitative continuous model of cellular auxin and brassinosteroid signaling and their crosstalk.

Motivation: Hormone pathway interactions are crucial in shaping plant development, such as synergism between the auxin and brassinosteroid pathways in cell elongation. Both hormone pathways have been characterized in detail, revealing several feedback loops. The complexity of this network, combined with a shortage of kinetic data, renders its quantitative analysis virtually impossible at present.Results: As a first step towards overcoming these obstacles, we analyzed the network using a Boolean logic approach to build models of auxin and brassinosteroid signaling, and their interaction. To compare these discrete dynamic models across conditions, we transformed them into qualitative continuous systems, which predict network component states more accurately and can accommodate kinetic data as they become available. To this end, we developed an extension for the SQUAD software, allowing semi-quantitative analysis of network states. Contrasting the developmental output depending on cell type-specific modulators enabled us to identify a most parsimonious model, which explains initially paradoxical mutant phenotypes and revealed a novel physiological feature.

Description des objets d'arts [sic] qui composent le cabinet de feu M. le Baron V. Denon... : estampes et ouvrages à figures : [Vente, 12 février 1827 et jours suivants] / par Duchesne Ainé

[Vente. Art. 1827-02-12. Paris]

Description des monuments de Paris / Isaac de Bourges ; introduction et notes par l'abbé Valentin Dufour ; [avant-propos signé : P.-L. Jacob]

Collection : Collection des anciennes descriptions de Paris ; I

Instruments for investigating fitness to drive - needs and expectations in primary care: a qualitative study

Background: Primary care physicians are often requested to assess their patients' fitness to drive. Little is however known on their needs to help them in this task. Aims: The aim of this study is to develop theories on needs, expectations, and barriers for clinical instruments helping physicians assess fitness to drive in primary care. Methods: This qualitative study used semi-structured interviews to investigate needs and expectations for instruments used to assess fitness to drive. From August 2011 to April 2013, we recorded opinions from five experts in traffic medicine, five primary care physicians, and five senior drivers. All interviews were integrally transcribed. Two independent researchers extracted, coded, and stratified categories relying on multi-grounded theory. All participants validated the final scheme. Results: Our theory suggests that for an instruments assessing fitness to drive to be implemented in primary care, it need to contribute to the decisional process. This requires at least five conditions: 1) it needs to reduce the range of uncertainty, 2) it needs to be adapted to local resources and possibilities, 3) it needs to be accepted by patients, 4) choices of tasks need to adaptable to clinical conditions, 5) and interpretation of results need to remain dependant of each patient's context. Discussion and conclusions: Most existing instruments assessing fitness to drive are not designed for primary care settings. Future instruments should also aim to support patient-centred dialogue, help anticipate driving cessation, and offer patients the opportunity to freely take their own decision on driving cessation as often as possible.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Time in e-Learning Research: A Qualitative Review of the Empirical Consideration of Time in Research into e-Learning

Peer-reviewed