41 research outputs found

    58166_WaterContent_Soil_JenaExperiment (MainExperiment, 2014)

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    This data set contains soil water content on litter subplots (SPx) with a Ml2x probe during the decomposition experiments. 'plotcode' is plot ID in the Jena Experiment; 'Date' is date of measurement; 'Sample' is replicate number; 'SWC' is soil water content; 'mV' is milli Volt. B3A14 is the plotcode of the common plot

    Familial breast cancer: Genetic counseling over time, including patientsĀ“ expectations and initiators considering the Angelina Jolie effect

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    <div><p>Purpose</p><p>The German Consortium for hereditary breast/ovarian cancer (GC-HBOC) aims for nationwide access to professional, individualized yet structured care for families at high risk. The identification of such families remains key for optimal care. Our study evaluates counseleesā€™ characteristics, referral practices, expectations and motivations in respect to their first genetic consultation. The impact of the Angelina Jolie Effect (AJE) was prospectively assessed.</p><p>Methods</p><p>All counselees could participate through a questionnaire. Groups were built in respect to neoadjuvant chemotherapy (FT) and before/after AJE.</p><p>Results</p><p>The 917 (88.5%) counselees (FT: 8.2%) were on average female (97.3%), with a mean age of 44.6, had children (71.9%), higher education (88%), personal (46.4%) or at least one first-degree relative (74.6%) with BC/OC or known <i>BRCA1</i>/2 mutation (11.8%), were in a relationship (76.1%), and living in a village (40.7%). The AJE is associated with significantly fewer cancelations (p = 0.005), more attendance among men (4.2% vs. 0.8%, p = 0.002), and people with familial <i>BRCA1/2</i> (14.8% vs. 7.5%, p = 0.003). The majority seek information regarding their cancer risk (83%) or relativesā€™ risk (74.8%), HBOC (69.1%), and surveillance programs for themselves (66.6%) or relatives (60.6%).</p><p>Conclusion</p><p>Enhanced media awareness of genetic cancer motivates patients, including other patient groups. A higher number of participants, including more men, are attending GC due to the AJE. In terms of the rising complexity of genetic testing, the analysis of patientsā€™ expectations and initiators for GC suggests that there is an urgent need to develop to participate motivation analysis. The factors revealed as impediments to accessing GC-HBOC guide recommendations to optimize access to genetic counseling. Medical educational programs for primary gynecologists and families at risk might be options to reach more participants.</p></div

    Characteristics of NFT counselees and influence of the ā€œAngelina Jolie (AJ) effectā€ on them (ā€œbefore AJā€ and ā€œafter AJā€ subgroups).

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    <p>Characteristics of NFT counselees and influence of the ā€œAngelina Jolie (AJ) effectā€ on them (ā€œbefore AJā€ and ā€œafter AJā€ subgroups).</p

    Socio-demographic data of the entire study population (NFT and FT).

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    <p>Characteristics of all counselees and differences between the NFT and FT groups.</p

    Expectations of NFT counselees.

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    <p>Counselees quantified different expectations and motivational factors for visiting the Center for HBOC using a scale that ranged from 0 (motivation factor does not apply) to 4 (motivation factor applies completely).</p

    Initiator groups for genetic counseling.

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    <p>Referral by <b>a)</b> medical professionals/physicians and <b>b)</b> Heidelberg University Hospital in the NFT and FT groups and the NFT subgroups ā€œbefore AJā€ and ā€œafter AJā€.</p

    Motivation groups for NFT counselees before and after AJ.

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    <p>Motivation groups for NFT counselees before and after AJ.</p

    Additional file 1: of A direct regulatory link between microRNA-137 and SHANK2: implications for neuropsychiatric disorders

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    Figure S1. Images of primary neuronal cultures preā€ and posttreatment. Figure S2. High conservation of the miRā€137 binding site in the SHANK2ā€3ā€™UTR and of miRā€137 between different species. Figure S3. Relative expression levels of miRā€137 in different human tissues. Figure S4. Uncropped Western blot pictures. Table S1. ASD risk genes which are predicted or validated miRā€137 targets. Table S2. Primers used for cloning, mutagenesis, and screening. Primer sequences are all shown in 5ā€²ā†’3ā€² orientation. Table S3. Origin of total RNA samples used to measure hsaā€miRā€137 relative expression across different tissues (see AdditionalĀ fileĀ 1: Figure S2 for results). Table S4. Experimentally validated miRā€137 targets. Table S5. Gene expression analysis of 69 validated miRā€137 target genes (including SHANK2) in the CommonMind RNA sequencing data. Table S6a. Gene expression analysis of validated targets from five different control microRNAs in the CommonMind RNA sequencing data. Genes labeled in gray withstand correction for multiple testing using the Benjamini-Hochberg method and a FDR of 10%. Table S6b. Comparison of the number of differentially expressed target genes of different microRNAs between SCZ and control individuals in the CommonMind RNASeq data. Table S7. Analysis of the 3ā€²UTR of the differentially expressed miR-137 genes in the DLPFC between SCZ and control individuals for additional putative miR-124 and miR-128 binding sites. (PDF 1417Ā kb
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