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

Gene expression of JIMT1 cells grown in Matrigel is closest to xenografts.

<p><b>A</b>. Dendrogram showing hierarchical clustering of genome-wide gene expression data. au = approximately unbiased p-value (%) in red, bp = bootstrap probability value (%) in blue, edge = cluster number in gray. Data shown are the average of two biological RNA replicates. Correlation of the replicates is shown in File S6 B. Venn diagram of ≥2-fold upregulated genes compared to 2D7d shows the number of shared genes in every combination of culture models. A list of common genes for each category is shown in File S4.</p

Drug screening shows differences between the culture models and responses to individual drugs vary greatly.

<p>Cells cultured in 2D, Matrigel (MG4+7d, MG7d), or polyHEMA (PH4+7d, PH7d) were treated with colchicine, methotrexate, helenine or API-2 with the indicated concentrations for 7 days. The cells were treated either directly up on plating for 7 days (2D7d, MG7d, PH7d) or after 4 day pre-growth at 3D (MG4+7d, PH4+7d). CellTiter-Glo (CTG) was used as a cell viability measure; data are an average of three biological replicates. Error bars are STDEV, * indicate statistically (t-test) significant changes compared to the corresponding 2D7d concentration, * < 0.05, ** < 0.01, *** < 0.001.</p

Interferon pathway is activated in polyHEMA cultures.

<p><b>A</b>. The canonical pathway that changed the most in PH4d and in PH7d compared to 2D according to IPA; the interferon pathway with arrows pointing to the top five changing genes in PH4d is shown in Table 2. Genes in red were upregulated in PH4d. Two hundred of the most up- and downregulated genes in PH4d/PH7d compared to the 2D cultures were subjected to IPA analysis. <b>B</b>. The gene expression results were validated by measuring interferon-alpha and beta activity from JIMT1 cells by transfecting them with a Cignal ISRE Reporter dual-luciferase assay kit (Qiagen). The kit measures induction of the STAT1 and STAT2 components of the JAK/STAT-signal transduction pathways as a readout for interferon activity. The cells were grown in 2D, MG, or PH for 3 days before reporter plasmids and transfection reagents were added for 24 hours. *** p-value < 0.001.</p

JIMT1 cells are more sensitive to drugs in Matrigel.

<p><b>A</b>. Average drug response of the JIMT1 cells in different cell culture models. The average responses of the 63 drugs are shown individually for the three highest concentrations (high (0.34-20 µM), medium (0.034-2 µM), and low (0.0034-0.2 µM) and across the concentrations. Response, p-value, and significance (** < 0.01, * < 0.05) compared to 2D are shown above the bars and average across the concentrations is shown above the line. Drug annotations and concentrations used for each drug are shown in File S1. <b>B</b>. Multiple linear regression analysis of individual drug screens comparing general drug effects to 2D. T-value shows the response difference to 2D (33.46 or 26.06). ***< 0.001, **<0.01, *<0.05.</p

JIMT1 cells form mass-shaped structures in 3D.

<p><b>A</b>. Time series of JIMT1 cells grown as either a Matrigel (MG) or polyHEMA (PH) culture. <b>B</b>. Zoom-in representative images of mass-shaped JIMT1 structures in Matrigel and polyHEMA. <b>C</b>. Growth rate comparison of 2D, Matrigel, and polyHEMA cultures. The growth rate was calculated by dividing the CTG (CellTiter-Glo) read by the starting cell number and expressed as % of 2D. Pictures were taken with IncuCyte.</p

Additional file 2: Table S1. of Metabolic clusters of breast cancer in relation to gene- and protein expression subtypes

Antibodies used for reverse phase protein array (RPPA). Table S2. Metabolite integrals for each of the samples included in the study. Table S3. Significantly different expressed genes between the three metabolic clusters. Table S4. Significantly different expressed genes between the metabolic clusters Mc1 and Mc2. Table S5. Significantly different expressed genes between the metabolic clusters Mc1 and Mc3. Table 6. Statistically over-represented annotation terms, according to DAVID, of differently expressed genes between metabolic cluster Mc1 and Mc2. Table S7. Statistically over-represented annotation terms, according to DAVID, of differently expressed genes between metabolic cluster Mc1 and Mc3. Table S8. Gene set enrichment analysis (GSEA) result for gene ontology (GO) gene sets. Metabolic cluster Mc1 was compared with Mc2 and Mc3. Table S9. Gene set enrichment analysis (GSEA) result for gene ontology (GO) gene sets. Metabolic cluster Mc1 was compared with Mc2. Table S10. Gene set enrichment analysis (GSEA) result for gene ontology (GO) gene sets. Metabolic cluster Mc3 was compared with Mc1 and Mc2. Table S11. Integrated pathway analysis result from the comparison of the metabolic clusters Mc1 compared to Mc2. Table S12. Integrated pathway analysis result from the comparison of the metabolic clusters Mc1 compared to Mc3. (XLSX 337 kb

Additional file 10: of Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome

Six proteins differentially expressed between luminal A samples in COCA cluster 1 versus COCA cluster 4. (PDF 771 kb

Additional file 2: of Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome

a Supplementary methods. b Summary of clinicopathological properties of the 425 primary breast tumors in the Oslo2 cohort. (PDF 137 kb