- En kvalitativ intervjustudie

De senaste decennierna har antalet flerspråkiga barn ökat i svenska förskolor och idag har vart femte barn ett annat modersmål än svenska. I den här studien undersöks det hur förskollärare integrerar flerspråkighet och kultur i förskoleverksamheten samt vilken betydelse organisatoriska faktorer har i arbetet med flerspråkighet. Datamaterialet består av semistrukturerade intervjuer med sex utbildade förskollärare i sex olika verksamheter i Göteborg. Från analysen urskildes tre övergripande teman: förskollärarens förhållningssätt, medierande verktyg och verkligheten kontra praktiken. Resultatet visar att förskollärarna har en generellt positiv inställning till flerspråkighet och använder en rad verktyg såsom böcker, kroppsliga uttryck, föräldrasamverkan och digitala verktyg i arbetet. Trots förskollärarnas öppenhet och engagemang rörande flerspråkighet utgör en rad organisatoriska faktorer såsom barngruppens storlek, personaltäthet, kompetensutveckling och indragna planeringstider hinder i arbetet med flerspråkighet. För att flerspråkighet ska främjas och lyckas inom förskolan måste personalen ges tid och förutsättningar till kompetensutveckling

Application of Neural Networks for classification of Patau, Edwards, Down, Turner and Klinefelter Syndrome based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics

Abstract Background The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been investigated more extensively over the past few years. The reason for this is that ANNs are good approximates of complex functions, so classification can be performed without the need for explicitly defined input-output model. This engineering tool can be applied for optimization of existing methods for disease/syndrome classification. Cytogenetic and molecular analyses are the most frequent tests used in prenatal diagnostic for the early detection of Turner, Klinefelter, Patau, Edwards and Down syndrome. These procedures can be lengthy, repetitive; and often employ invasive techniques so a robust automated method for classifying and reporting prenatal diagnostics would greatly help the clinicians with their routine work. Methods The database consisted of data collected from 2500 pregnant woman that came to the Institute of Gynecology, Infertility and Perinatology “Mehmedbasic” for routine antenatal care between January 2000 and December 2016. During first trimester all women were subject to screening test where values of maternal serum pregnancy-associated plasma protein A (PAPP-A) and free beta human chorionic gonadotropin (β-hCG) were measured. Also, fetal nuchal translucency thickness and the presence or absence of the nasal bone was observed using ultrasound. Results The architectures of linear feedforward and feedback neural networks were investigated for various training data distributions and number of neurons in hidden layer. Feedback neural network architecture out performed feedforward neural network architecture in predictive ability for all five aneuploidy prenatal syndrome classes. Feedforward neural network with 15 neurons in hidden layer achieved classification sensitivity of 92.00%. Classification sensitivity of feedback (Elman’s) neural network was 99.00%. Average accuracy of feedforward neural network was 89.6% and for feedback was 98.8%. Conclusion The results presented in this paper prove that an expert diagnostic system based on neural networks can be efficiently used for classification of five aneuploidy syndromes, covered with this study, based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics. Developed Expert System proved to be simple, robust, and powerful in properly classifying prenatal aneuploidy syndromes

KANK1-NTRK3 fusions define a subset of BRAF mutation negative renal metanephric adenomas

Background: Metanephric adenoma (MA) is a rare benign renal neoplasm. On occasion, MA can be difficult to differentiate from renal malignancies such as papillary renal cell carcinoma in adults and Wilms̕ tumor in children. Despite recent advancements in tumor genomics, there is limited data available regarding the genetic alterations characteristic of MA. The purpose of this study is to determine the frequency of metanephric adenoma cases exhibiting cytogenetic aberration t (9;15)(p24;q24), and to investigate the association between t (9,15) and BRAF mutation in metanephric adenoma. Methods: This study was conducted on 28 archival formalin fixed paraffin-embedded (FFPE) specimens from patients with pathologically confirmed MA. Tissue blocks were selected for BRAF sequencing and fluorescent in situ hybridization (FISH) analysis for chromosomal rearrangement between KANK1 on chromosome 9 (9p24.3) and NTRK3 on chromosome 15 (15q25.3), which was previously characterized and described in two MA cases. Results: BRAFV600E mutation was identified in 62% of our cases, 9 (38%) cases were BRAFWT, and 4 cases were uninformative. Of the 20 tumors with FISH results, two (10%) were positive for KANK1-NTRK3 fusion. Both cases were BRAFWT suggesting mutual exclusivity of BRAFV600E and KANK1-NTRK3 fusion, the first such observation in the literature. Conclusions: Our data shows that BRAF mutation in MA may not be as frequent as suggested in the literature and KANK-NTRK3 fusions may account for a subset of BRAFWT cases in younger patients. FISH analysis for KANK1-NTRK3 fusion or conventional cytogenetic analysis may be warranted to establish the diagnosis of MA in morphologically and immunohistochemically ambiguous MA cases lacking BRAF mutations