Attending school after treatment for a brain tumor: Experiences of children and key figures

Reintegration into school is a milestone for childhood brain tumor survivors, as well as for their parents, teachers, and healthcare providers. We explored their experiences following the school re-entry by conducting semi-structured interviews. Thematic analysis resulted in four main themes: "school performance," "psychosocial well-being," "support and approach," and "communication and collaboration." Children were pleased to return to school despite confrontation with adverse outcomes. Parents, teachers, and healthcare providers identified current and future concerns and challenges, as well as opportunities for academic and personal development. Their experiences highlight the importance of coordinated and systematic follow-up in close collaboration with healthcare providers

Square root singularity in the viscosity of neutral colloidal suspensions at large frequencies

The asymptotic frequency $\omega$, dependence of the dynamic viscosity of neutral hard sphere colloidal suspensions is shown to be of the form $\eta_0 A(\phi) (\omega \tau_P)^{-1/2}$, where $A(\phi)$ has been determined as a function of the volume fraction $\phi$, for all concentrations in the fluid range, $\eta_0$ is the solvent viscosity and $\tau_P$ the P\'{e}clet time. For a soft potential it is shown that, to leading order steepness, the asymptotic behavior is the same as that for the hard sphere potential and a condition for the cross-over behavior to $1/\omega \tau_P$ is given. Our result for the hard sphere potential generalizes a result of Cichocki and Felderhof obtained at low concentrations and agrees well with the experiments of van der Werff et al, if the usual Stokes-Einstein diffusion coefficient $D_0$ in the Smoluchowski operator is consistently replaced by the short-time self diffusion coefficient $D_s(\phi)$ for non-dilute colloidal suspensions.Comment: 18 pages LaTeX, 1 postscript figur

Thixotropy in macroscopic suspensions of spheres

An experimental study of the viscosity of a macroscopic suspension, i.e. a suspension for which Brownian motion can be neglected, under steady shear is presented. The suspension is prepared with a high packing fraction and is density-matched in a Newtonian carrier fluid. The viscosity of the suspension depends on the shear rate and the time of shearing. It is shown for the first time that a macroscopic suspension shows thixotropic viscosity, i.e. shear-thinning with a long relaxation time as a unique function of shear. The relaxation times show a systematic decrease with increasing shear rate. These relaxation times are larger when decreasing the shear rates, compared to those observed after increasing the shear. The time scales involved are about 10000 times larger than the viscous time scale and about 1000 times smaller than the thermodynamic time scale. The structure of the suspension at the outer cylinder of a viscometer is monitored with a camera, showing the formation of a hexagonal structure. The temporal decrease of the viscosity under shear coincides with the formation of this hexagonal pattern

Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)

Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assisting considerably the traditional ways for unraveling fungal diversity and detection. The raw DNA data in association to environmental descriptors of metabarcoding studies are made available in public sequence read archives. While this is potentially a valuable source of information for the investigation of Fungi across diverse environmental conditions, the annotation used to describe environment is heterogenous. Moreover, a uniform processing pipeline still needs to be applied to the available raw DNA data. Hence, a comprehensive framework to analyses these data in a large context is still lacking. We introduce the MycoDiversity DataBase, a database which includes public fungal metabarcoding data of environmental samples for the study of biodiversity patterns of Fungi. The framework we propose will contribute to our understanding of fungal biodiversity and aims to become a valuable source for large-scale analyses of patterns in space and time, in addition to assisting evolutionary and ecological research on Fungi

Short-term perspectives of parents and teachers on school reintegration of childhood brain tumour survivors

OBJECTIVE: To discover short-term changes in perspectives of parents and teachers of childhood brain tumour survivors on school reintegration, in order to reveal similarities and differences between them over time. METHODS: Semi-structured interviews were conducted with parents and teachers of five children at the start and the end of a 1-year period following the child\u27s school re-entry. RESULTS: Thematic analysis of data resulted in three main themes: \u27the child\u27s performance and wellbeing\u27, \u27the school\u27s attitude and approach\u27 and \u27communication and working together\u27. Parental concerns about child-specific changes and the school\u27s approach to the child could either decrease or increase over time. Teachers remained focused on assessing their pupil\u27s learning potential and finding ways of appropriate support. Their different perspectives on communication and working together became more pronounced. CONCLUSIONS: This study emphasizes the importance of clear communication and collaboration, coordinated follow-up and availability of healthcare professionals during the child\u27s school reintegration

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics