Penggunaan Media Gambar Dalam Meningkatkan Kemampuan Membaca Permulaan Siswa Kelas I SDN Uwedaka Kecamatan Pagimana Kabupaten Banggai

Pokok permasalahan dalam penelitian ini adalah rendahnya tingkat kemampuan membaca permulaan siswa kelas I SDN Uwedaka dalam pembelajaran Bahasa Indonesia. Tujuan Penelitian adalah untuk meningkatkan kemampuan membaca permulaan siswa kelas I SDN Uwedaka Kecamatan Pagimana Kabupaten Banggai. Berdasarkan hasil observasi yang didapatkan masih terdapat beberapa siswa yang sama sekali belum bisa membaca. Pembelajaran membaca permulaan di SDN Uwedaka selama ini hanya menggunakan media pembelajaran yang konvensional yaitu dengan menggunakan papan tulis, pembelajaran yang hanya berpusat pada guru, penggunaan media dalam pembelajaran sebagai alat bantu masih sangat terbatas, hal ini menyebabkan kemampuan membaca permulaan yang masih rendah dan terlihat hampir 65% siswa masih mengalami kesulitan membaca dalam proses belajar mengajar. Metode yang digunakan adalah metode deskriptif kualitatif dan kuantitatif. Data kualitatif didapatkan dari hasil tes dan observasi siswa dan guru. data kuantitatif didapatkan dari hasil tes belajar. Desain penelitian ini mengacu pada desain oleh Kemmis dan Mc Taggart yang terdiri dari empat tahapan, yaitu perencanaan, pelaksanaan tindakan, observasi dan refleksi. Data dikumpulkan melalui penilaian proses dan penilaian hasil setiap akhir tindakan. Penelitian ini dilakukan dalam dua siklus. Pada siklus I diperoleh nilai rata-rata siswa yaitu sebesar 67 dengan ketuntasan belajar klasikal sebesar 40% serta daya serap 66,6%. Pada siklus II, nilai rata-rata meningkat menjadi 83 dengan ketuntasan klasikal sebesar 100% serta daya serap klasikal sebesar 83,3%. Bersarkan hasil penelitian maka dapat disimpulkan bahwa penggunaan media gambar dapat meningkatkan kemampuan membaca permulaan terhadap siswa kelas I SDN Uwedaka Kecamatan Pagimana Kabupaten Banggai

Computed tomography showing partial responses in three different patients at baseline and at 12 months.

<p>Panel A shows ovarian metastases in a 43 years old woman. Panel B shows lung metastases in a 50 years old man. Panel C shows liver metastases and pleural effusion (*) in a 70 years old man. Arrows show the largest diameter of the lesions.</p

Baseline Demographic and Clinical Characteristics of Patients.

<p>Abbreviations: LDH, lactate dehydrogenase; ULN, upper limit of normal; WHO, World Health Organization.</p

Patterns of response to treatment with bevacizumab monotherapy in metastatic malignant melanoma patients.

<p>Panel A shows the best overall response for 32 patients who had undergone at least one tumor assessment measured as the change from baseline in the sum of the largest diameters of each target lesion. Three patients progressed clinically and/or biochemically before first tumor assessment, and are not shown. Negative values indicate tumor shrinkage, and the dashed lines indicate the threshold for a partial response (PR) and progressive disease (PD), respectively. Panel B shows the duration and characteristics of the responses in each patient.</p

Study flow diagram.

<p>Between April 2005 and August 2009, 52 patients with metastatic melanoma were screened. Thirty-five of those patients were eligible according to inclusion criteria and received the study drug.</p

Kaplan Meyer plots of progression free survival (PFS) (A) and overall survival (OS) (B) in 35 metastatic melanoma patients treated with bevacizumab monotherapy.

<p>Early hypertension (EH) was significantly associated with PFS (C) and OS (D).</p

Additional file 2: Table S1. of DNA methylation subgroups in melanoma are associated with proliferative and immunological processes

Centroids of methylation subgroups. (XLS 1550 kb

Additional file 1: Figure S1. of DNA methylation subgroups in melanoma are associated with proliferative and immunological processes

Robustness of methylation subtypes. Principal component analysis to monitor data bias due to technical variables in the Bergen (A) and TCGA (B) cohorts, respectively. The entire set of 473,864 CpGs was used for principal component analysis. The heatmaps indicate the association of a sample annotation to each of the principal components. The strength of association is specified by the log10 p-value of the linear model with the respective principal component as dependent variable and sample annotation as regressor. DNAconc = DNA concentration. Technical variables of TCGA data are termed as defined by the TCGA consortium. TCGA = The Cancer Genome Atlas Consortium. Abbreviations as in Figure 1 of the main manuscript. (C) Sample overlap when using different CpG sets for group discovery in Bergen and TCGA data, respectively. For group discovery we used CpGs with variant methylation between melanoma and melanocytes. CpGs were required to be either methylated or de-methylated in at least 10 tumors for our final subtypes. The CpG set for 10 tumors contained 9,886 melanoma-methylated and 5,236 melanoma-demethylated CpGs. The heatmap displays the overlap of the resulting three consensus clusters at various tumor cutoffs. (D) Heatmap of TCGA sample co-occurrence between unsupervised consensus clusters and methylation subtypes obtained from (supervised) nearest centroid classification. Figure S2. Promoter island consensus clusters. The group discovery CpG set was reduced to CpGs located within 1500 bp upstream of transcription start sites and within a CpG island. In total this analysis includes 947 CpGs, of which 930 are hypermethylated, and 17 are hypomethylated in tumors as compared to melanocytes. Two-group consensus solutions were favorable to three-group solutions in Bergen and TCGA data, respectively. Figure S3. Signature expression across methylation subtypes in TCGA data. (A) ESTIMATE scores and tumor purity. P-value from Kruskal-Wallis test. (B) Mean expression values of gene modules and GO-term ‘cell cycle’. P-value from anova. TCGA tumor data. Figure S4. Aberrant methylation in melanoma compared to colon, lung and breast cancer. (A) Venn diagrams of aberrant methylation on the CpG and gene level. (B) Aberrant methylation in ES-cell chromatin context. Chromatin categories as in ENCODE project. (C) Aberrant methylation in melanocyte chromatin context. Chromatin categories as in Epigenome Roadmap project. Figure S5. Driver gene mutations and methylation subtypes in the TCGA cohort. (A) Number of non-silent mutations per sample across methylation subtypes. (B) Non-silent and hotspot mutations of reported melanoma driver genes across subtypes. Figure S6. Expression of MAPK and PI(3)K pathway genes across methylation subtypes. (A) Expression of MAPK and PI(3)K pathway. fdr = false discovery rate for p-values from anova using Benjamini-Hochberg adjustment. (B) Cross-table of gene expression and methylation subtypes. (PDF 865 kb

Differential Inhibition of <i>Ex-Vivo</i> Tumor Kinase Activity by Vemurafenib in <i>BRAF</i>(V600E) and <i>BRAF</i> Wild-Type Metastatic Malignant Melanoma

<div><p>Background</p><p>Treatment of metastatic malignant melanoma patients harboring <i>BRAF</i>(V600E) has improved drastically after the discovery of the <i>BRAF</i> inhibitor, vemurafenib. However, drug resistance is a recurring problem, and prognoses are still very bad for patients harboring <i>BRAF</i> wild-type. Better markers for targeted therapy are therefore urgently needed.</p><p>Methodology</p><p>In this study, we assessed the individual kinase activity profiles in 26 tumor samples obtained from patients with metastatic malignant melanoma using peptide arrays with 144 kinase substrates. In addition, we studied the overall <i>ex-vivo</i> inhibitory effects of vemurafenib and sunitinib on kinase activity status.</p><p>Results</p><p>Overall kinase activity was significantly higher in lysates from melanoma tumors compared to normal skin tissue. Furthermore, <i>ex-vivo</i> incubation with both vemurafenib and sunitinib caused significant decrease in phosphorylation of kinase substrates, i.e kinase activity. While basal phosphorylation profiles were similar in <i>BRAF</i> wild-type and <i>BRAF</i>(V600E) tumors, analysis with <i>ex-vivo</i> vemurafenib treatment identified a subset of 40 kinase substrates showing stronger inhibition in <i>BRAF</i>(V600E) tumor lysates, distinguishing the <i>BRAF</i> wild-type and <i>BRAF</i>(V600E) tumors. Interestingly, a few <i>BRAF</i> wild-type tumors showed inhibition profiles similar to <i>BRAF</i>(V600E) tumors. The kinase inhibitory effect of vemurafenib was subsequently analyzed in cell lines harboring different <i>BRAF</i> mutational status with various vemurafenib sensitivity <i>in-vitro</i>.</p><p>Conclusions</p><p>Our findings suggest that multiplex kinase substrate array analysis give valuable information about overall tumor kinase activity. Furthermore, intra-assay exposure to kinase inhibiting drugs may provide a useful tool to study mechanisms of resistance, as well as to identify predictive markers.</p></div

Primers used for direct Sanger-sequencing of EGFR-Exon 20

<p>Primers used for direct Sanger-sequencing of EGFR-Exon 20</p