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  • 1
    Abstract: BACKGROUND: More than 8.5 million Germans suffer from chronic diseases attributable to smoking. Education Against Tobacco (EAT) is a multinational network of medical students who volunteer for school-based prevention in the classroom setting, amongst other activities. EAT has been implemented in 28 medical schools in Germany and is present in 13 additional countries around the globe. A recent quasi-experimental study showed significant short-term smoking cessation effects on 11-to-15-year-old adolescents. OBJECTIVE: The aim of this study was to provide the first randomized long-term evaluation of the optimized 2014 EAT curriculum involving a photoaging software for its effectiveness in reducing the smoking prevalence among 11-to-15-year-old pupils in German secondary schools. METHODS: A randomized controlled trial was undertaken with 1504 adolescents from 9 German secondary schools, aged 11-15 years in grades 6-8, of which 718 (47.74%) were identifiable for the prospective sample at the 12-month follow-up. The experimental study design included measurements at baseline (t1), 6 months (t2), and 12 months postintervention (t3), via questionnaire. The study groups consisted of 40 randomized classes that received the standardized EAT intervention (two medical student-led interactive modules taking 120 minutes total) and 34 control classes within the same schools (no intervention). The primary endpoint was the difference in smoking prevalence from t1 to t3 in the control group versus the difference from t1 to t3 in the intervention group. The differences in smoking behavior (smoking onset, quitting) between the two groups, as well as gender-specific effects, were studied as secondary outcomes. RESULTS: None of the effects were significant due to a high loss-to-follow-up effect (52.26%, 786/1504). From baseline to the two follow-up time points, the prevalence of smoking increased from 3.1% to 5.2% to 7.2% in the control group and from 3.0% to 5.4% to 5.8% in the intervention group (number needed to treat [NNT]=68). Notable differences were observed between the groups for the female gender (4.2% to 9.5% for control vs 4.0% to 5.2% for intervention; NNT=24 for females vs NNT=207 for males), low educational background (7.3% to 12% for control vs 6.1% to 8.7% for intervention; NNT=30), and migrational background (students who claimed that at least one parent was not born in Germany) at the 12-month follow-up. The intervention appears to prevent smoking onset (NNT=63) but does not appear to initiate quitting. CONCLUSIONS: The intervention appears to prevent smoking, especially in females and students with a low educational background.
    Type of Publication: Journal article published
    PubMed ID: 28588007
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  • 2
    Abstract: BACKGROUND: Around 90% of melanomas are caused by ultraviolet (UV) exposure and are therefore eminently preventable. Unhealthy tanning behavior is mostly initiated in early adolescence, often with the belief that it increases attractiveness; the problems related to skin atrophy and malignant melanoma are too far in the future to fathom. Photoaging desktop programs, in which an image is altered to predict future appearance, have been successful in positively influencing behavior in adiposity or tobacco prevention settings. OBJECTIVE: To develop and test a photoaging app designed for melanoma prevention. METHODS: We harnessed the widespread availability of mobile phones and adolescents' interest in appearance to develop a free mobile app called Sunface. This app has the user take a self-portrait (ie, a selfie), and then photoages the image based on Fitzpatrick skin type and individual UV protection behavior. Afterward, the app explains the visual results and aims at increasing self-competence on skin cancer prevention by providing guideline recommendations on sun protection and the ABCDE rule for melanoma self-detection. The underlying aging algorithms are based on publications showing UV-induced skin damage by outdoor as well as indoor tanning. To get a first impression on how well the app would be received in a young target group, we included a total sample of 25 students in our cross-sectional pilot study with a median age of 22 (range 19-25) years of both sexes (11/25, 44% female; 14/25, 56% male) attending the University of Essen in Germany. RESULTS: The majority of enrolled students stated that they would download the app (22/25, 88%), that the intervention had the potential to motivate them to use sun protection (23/25, 92%) and that they thought such an app could change their perceptions that tanning makes you attractive (19/25, 76%). Only a minority of students disagreed or fully disagreed that they would download such an app (2/25, 8%) or that such an app could change their perceptions on tanning and attractiveness (4/25, 16%). CONCLUSIONS: Based on previous studies and the initial study results presented here, it is reasonable to speculate that the app may induce behavioral change in the target population. Further work is required to implement and examine the effectiveness of app-based photoaging interventions within risk groups from various cultural backgrounds.
    Type of Publication: Journal article published
    PubMed ID: 28747297
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  • 3
    Publication Date: 2016-04-29
    Description: To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Tirosh, Itay -- Izar, Benjamin -- Prakadan, Sanjay M -- Wadsworth, Marc H 2nd -- Treacy, Daniel -- Trombetta, John J -- Rotem, Asaf -- Rodman, Christopher -- Lian, Christine -- Murphy, George -- Fallahi-Sichani, Mohammad -- Dutton-Regester, Ken -- Lin, Jia-Ren -- Cohen, Ofir -- Shah, Parin -- Lu, Diana -- Genshaft, Alex S -- Hughes, Travis K -- Ziegler, Carly G K -- Kazer, Samuel W -- Gaillard, Aleth -- Kolb, Kellie E -- Villani, Alexandra-Chloe -- Johannessen, Cory M -- Andreev, Aleksandr Y -- Van Allen, Eliezer M -- Bertagnolli, Monica -- Sorger, Peter K -- Sullivan, Ryan J -- Flaherty, Keith T -- Frederick, Dennie T -- Jane-Valbuena, Judit -- Yoon, Charles H -- Rozenblatt-Rosen, Orit -- Shalek, Alex K -- Regev, Aviv -- Garraway, Levi A -- 1U24CA180922/CA/NCI NIH HHS/ -- DP2 OD020839/OD/NIH HHS/ -- K99 CA194163/CA/NCI NIH HHS/ -- K99CA194163/CA/NCI NIH HHS/ -- P01CA163222/CA/NCI NIH HHS/ -- P30-CA14051/CA/NCI NIH HHS/ -- P50GM107618/GM/NIGMS NIH HHS/ -- R35CA197737/CA/NCI NIH HHS/ -- U54CA112962/CA/NCI NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2016 Apr 8;352(6282):189-96. doi: 10.1126/science.aad0501.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA. Center for Cancer Precision Medicine, Dana-Farber Cancer Institute, Boston, MA 02215, USA. bizar@partners.org aregev@broadinstitute.org levi_garraway@dfci.harvard.edu. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Institute for Medical Engineering and Science, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA. Department of Chemistry, MIT, Cambridge, MA 02142, USA. Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA 02139, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA. Center for Cancer Precision Medicine, Dana-Farber Cancer Institute, Boston, MA 02215, USA. ; Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. ; Program in Therapeutic Sciences, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA. Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia. ; HMS LINCS Center and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA. ; Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Institute for Medical Engineering and Science, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA. Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA 02139, USA. Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA. ; Department of Surgical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA. Department of Surgical Oncology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. ; Program in Therapeutic Sciences, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA. HMS LINCS Center and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Ludwig Center at Harvard, Boston, MA 02215, USA. ; Division of Medical Oncology, Massachusetts General Hospital Cancer Center, Boston, MA 02114, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Institute for Medical Engineering and Science, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA. Department of Chemistry, MIT, Cambridge, MA 02142, USA. Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA 02139, USA. Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA. Department of Immunology, Massachusetts General Hospital, Boston, MA 02114, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Department of Biology and Koch Institute, MIT, Boston, MA 02142, USA. Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA. bizar@partners.org aregev@broadinstitute.org levi_garraway@dfci.harvard.edu. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. bizar@partners.org aregev@broadinstitute.org levi_garraway@dfci.harvard.edu.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/27124452" target="_blank"〉PubMed〈/a〉
    Keywords: Base Sequence ; Cell Communication ; Cell Cycle ; Drug Resistance, Neoplasm/genetics ; Endothelial Cells/pathology ; Genomics ; Humans ; Immunotherapy ; Lymphocyte Activation ; Melanoma/*genetics/*secondary/therapy ; Microphthalmia-Associated Transcription Factor/metabolism ; Neoplasm Metastasis ; RNA/genetics ; Sequence Analysis, RNA ; Single-Cell Analysis ; Skin Neoplasms/*pathology ; Stromal Cells/pathology ; T-Lymphocytes/immunology/pathology ; Transcriptome ; *Tumor Microenvironment
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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