DOOST DARI? : Taidelähtöisten ja toiminnallisten menetelmien käyttö nuorten voimaantumisen, osallisuuden ja sosiaalisten suhteiden tukemisessa.

Toiminnallisen opinnäytetyön tarkoituksena oli kehittää yhteistä taidelähtöistä ryhmätoimintaa eritaustaisten nuorten voimaantumisen, osallisuuden ja sosiaalisten suhteiden tueksi. Järjestimme neljän musiikkityöpajakerran kokonaisuuden, jonka tuotos esitettiin yleisölle. Musiikkityöpajatoiminnan osallistujaryhmään kuului sekä kantasuomalaisia että turvapaikan saaneita pakolaisnuoria. Musiikkityöpajojen ensisijaisena tavoitteena oli koota yhteen nuoria ja tukea heidän vuorovaikutustaan sekä uusien sosiaalisten suhteiden syntyä toiminnallisten harjoitusten ja musiikin avulla. Lisäksi musiikkityöpajatoiminnan tavoitteena oli mahdollistaa nuorille taidelähtöisten ja toiminnallisten menetelmien avulla voimaantumisen ja osallisuuden kokemuksia. Ryhmätoiminnan tavoitteena oli luoda ryhmän sisälle innostava, turvallinen ja kaikkia kunnioittava ilmapiiri, mahdollistaa yhteenkuuluvuuden tunnetta ja uusien verkostojen syntymistä, saada nuoret toimimaan yhteistyössä toistensa kanssa ja löytämään oma musiikillinen rooli ryhmässä. Ryhmätyöskentelyn yhtenä tavoitteena oli tukea pakolaisnuorten kotoutumisprosessia. Aineistonkeruumenetelminä käytimme osallistuvaa havainnointia, kyselylomaketta ja avointa haastattelua. Opinnäytetyön teoreettisessa viitekehyksessä käsittelimme osallistujaryhmään liittyviä asioita, kuten nuoruutta ja maahanmuuttajuutta alaikäisen elämänvaiheena, osallisuuden ja voimaantumisen tukemista taidelähtöisten ja toiminnallisten menetelmien avulla, musiikkia hyvinvoinnin edistäjänä sekä nuorten ryhmätoimintaan ja ohjaukseen liittyviä käsitteitä ja prosesseja. Tulokset viittaavat musiikkityöpajatoiminnan olleen osallistujille merkityksellinen kokemus, joka toi nuorille voimaantumisen ja osallisuuden kokemuksia sekä antoi mahdollisuuden uusien sosiaalisten verkostojen syntymiselle. Tuloksia voi hyödyntää esimerkiksi nuorten taidelähtöisten ja toiminnallisten ryhmien suunnittelussa, toteutuksessa ja arvioimisessa. Tulokset ovat käyttökelpoisia nuoriso ja sosiaalialan työssä ja kouluissa eritaustaisten nuorten kohtaamisen sekä heidän keskinäisen vuorovaikutuksen tukemisessa. Yhteisen mielekkään toiminnan kautta luodaan mahdollisuuksia yhteisöllisyyteen yli kulttuuri- ja kielirajojen.The purpose of this thesis was to develop common arts-based group activities for young people with different backgrounds to empower, include and support social relations. We arranged a series of four music workshops the output of which was performed to an audience. The participants of the music workshops included local youth and refugees with asylum. The primary goal was to gather young people together and support their interaction and develop their social relationships by functional exercises and music. The aim of the music workshops was also to enable young people to experience empowerment and inclusion using arts-based and functional methods. The aim of the group activities was to create an inspiring, safe and respectful atmosphere for all participants of the group, enable social cohesion and networking as well as to allow young people to function and cooperate with each other and find their role in the group. The hidden agenda of the group activities was to support integration of the refugees. We used participant observation, a questionnaire and an open interview as methods of collecting data. In the theoretical framework we processed the concepts related to the participants of the group, supporting involvement and empowerment with arts-based and functional methods and music as a tool for well-being as well as the concepts of group work and guidance. The results of the study indicate that music workshops are meaningful for the participants and brought experiences of empowerment and involvement for the young people and provided an opportunity to create new social networks. The results can be used for example for planning arts-based and functional groups for young people, in youth work or in schools to support the interaction of young people with different backgrounds. Opportunities for communality over cultural and language boundaries can be created through common meaningful activities

Machine Learning of Bone Marrow Histopathology Identifies Genetic and Clinical Determinants in Patients with MDS

Publisher Copyright: ©2021 American Association for Cancer Research.In myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN), bone marrow (BM) histopathology is assessed to identify dysplastic cellular morphology, cellularity, and blast excess. Yet, other morphologic findings may elude the human eye. We used convolutional neural networks to extract morphologic features from 236 MDS, 87 MDS/MPN, and 11 control BM biopsies. These features predicted genetic and cytogenetic aberrations, prognosis, age, and gender in multivariate regression models. Highest prediction accuracy was found for TET2 [area under the receiver operating curve (AUROC) = 0.94] and spliceosome mutations (0.89) and chromosome 7 monosomy (0.89). Mutation prediction probability correlated with variant allele frequency and number of affected genes per pathway, demonstrating the algorithms' ability to identify relevant morphologic patterns. By converting regression models to texture and cellular composition, we reproduced the classical del(5q) MDS morphology consisting of hypolobulated megakaryocytes. In summary, this study highlights the potential of linking deep BM histopathology with genetics and clinical variables. SIGNIFICANCE: Histopathology is elementary in the diagnostics of patients with MDS, but its high-dimensional data are underused. By elucidating the association of morphologic features with clinical variables and molecular genetics, this study highlights the vast potential of convolutional neural networks in understanding MDS pathology and how genetics is reflected in BM morphology.See related commentary by Elemento, p. 195.Peer reviewe

Hemap: An nteractive online resource for characterizing molecular phenotypes across hematologic malignancies

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease contexts for new therapeutic approaches. We analyzed 9,544 transcriptomes from over 30 hematologic malignancies, normal blood cell types and cell lines, and show that the disease types can be stratified in a data-driven manner. We utilized the obtained molecular clustering for discovery of cluster-specific pathway activity, new biomarkers and in silico drug target prioritization through integration with drug target databases. Using known vulnerabilities and available drug screens in benchmarking, we highlight the importance of integrating the molecular phenotype context and drug target expression for in silico prediction of drug responsiveness. Our analysis implicates BCL2 expression level as important indicator of venetoclax responsiveness and provides a rationale for its targeting in specific leukemia subtypes and multiple myeloma, links several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7 and EZH1) with CLL, and supports CDK6 as disease-specific target in AML. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our freely available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies

Hemap : An Interactive Online Resource for Characterizing Molecular Phenotypes across Hematologic Malignancies

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease context for new therapeutic approaches. We analyzed 9,544 transcriptomes from more than 30 hematologic malignancies, normal blood cell types, and cell lines, and showed that disease types could be stratified in a data-driven manner. We then identified cluster-specific pathway activity, new biomarkers, and in silico drug target prioritization through interrogation of drug target databases. Using known vulnerabilities and available drug screens, we highlighted the importance of integrating molecular phenotype with drug target expression for in silico prediction of drug responsiveness. Our analysis implicated BCL2 expression level as an important indicator of venetoclax responsiveness and provided a rationale for its targeting in specific leukemia subtypes and multiple myeloma, linked several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7, and EZH1) with chronic lymphocytic leukemia, and supported CDK6 as a disease-specific target in acute myeloid leukemia. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our publicly available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies.Peer reviewe